Disclosure of Invention
The application mainly aims to provide a wafer defect detection method and device, and aims to solve the problem that the defect accuracy of the existing single acoustic wave detection is insufficient.
In order to achieve the above object, the present application provides a wafer defect detection method, which includes:
transmitting an ultrasonic signal and a surface wave signal to a wafer to be detected based on detection parameters of the wafer to be detected, and collecting a reflected signal of the ultrasonic signal and a propagation signal of the surface wave signal;
Extracting reflection characteristics of the reflection signals and propagation characteristics of the propagation signals, and identifying first defect information of the wafer to be detected based on the reflection characteristics and the propagation characteristics;
fusing the reflection characteristic and the propagation characteristic to obtain a characteristic parameter of the wafer to be detected, and identifying second defect information of the wafer to be detected based on the characteristic parameter;
and identifying target defect information of the wafer to be tested based on the first defect information and the second defect information.
In an embodiment, the step of fusing the reflection characteristic and the propagation characteristic to obtain the characteristic parameter of the wafer to be measured includes:
Matching the reflection characteristic and the propagation characteristic based on a first sampling point of the reflection signal and a second sampling point of the propagation signal to obtain first fusion data;
Correcting the first fused data based on the first timestamp of the reflected signal and the second timestamp of the propagated signal to obtain second fused data;
calculating the similarity of the reflection characteristic and the propagation characteristic, and checking the second fusion data based on the similarity;
And screening out the characteristic parameters of the wafer to be tested from the second fusion data according to the verification result.
In an embodiment, a reflection parameter of the reflection characteristic and a propagation parameter of the propagation characteristic are selected, and a corresponding feature vector and a reference feature vector are constructed based on the reflection parameter and the propagation parameter;
based on the feature vector and the reference feature vector, calculating a corresponding column vector, and transposing the column vector to obtain a corresponding row vector;
calculating a corresponding covariance matrix based on the reflection parameter and the propagation parameter, and calculating an inverse of the covariance matrix;
And substituting the inverse of the column vector, the row vector and the covariance matrix into a Markov distance formula to calculate the similarity of the reflection characteristic and the propagation characteristic.
In an embodiment, the step of identifying the first defect information of the wafer to be tested based on the reflection characteristic and the propagation characteristic includes:
the reflection characteristics include reflection intensity and transmission time, and the propagation characteristics include attenuation characteristics and phase variation;
Positioning internal defect information of the wafer to be detected based on reflection intensities of the reflection signals at different positions of the wafer to be detected and transmission time of the reflection signals at different positions;
Positioning surface defect information of the wafer to be detected based on attenuation characteristics and phase changes of the propagation signal on the surface of the wafer to be detected;
and generating first defect information of the wafer to be tested according to the internal defect information and the surface defect information.
In an embodiment, before the step of transmitting the ultrasonic signal and the surface wave signal to the wafer to be measured based on the inspection parameters of the wafer to be measured, the method further includes:
acquiring wafer information of the wafer to be tested, wherein the wafer information comprises a wafer type and historical defect information corresponding to the wafer type;
And determining detection parameters of the wafer to be detected based on the wafer information, wherein the detection parameters comprise probe parameters, detection environment parameters and acoustic frequency parameters.
In an embodiment, the step of transmitting an ultrasonic signal and a surface wave signal to the wafer to be tested based on the inspection parameters of the wafer to be tested, and collecting a reflected signal of the ultrasonic signal and a propagation signal of the surface wave signal includes:
Determining a corresponding emission mode based on detection parameters of the wafer to be detected, wherein the emission mode comprises an emission interval;
And based on the emission mode, sequentially emitting ultrasonic signals and surface wave signals to the wafer to be detected, and based on the emission interval, respectively collecting reflected signals of the ultrasonic signals and propagation signals of the surface wave signals.
In one embodiment, the step of extracting the reflection characteristic of the reflection signal and the propagation characteristic of the propagation signal comprises:
respectively acquiring a first transmitting time of the ultrasonic signal and a second transmitting time of the surface wave signal;
according to the first emission time and the second emission time, carrying out data preprocessing on the reflected signal and the propagation signal, wherein the data preprocessing comprises noise filtering, signal enhancement and standardization;
and extracting the reflection characteristics of the reflection signals and the propagation characteristics of the propagation signals after data preprocessing.
In addition, to achieve the above object, the present application also proposes a wafer defect detecting apparatus, including:
the detection module is used for transmitting ultrasonic signals and surface wave signals to the wafer to be detected based on detection parameters of the wafer to be detected, and collecting reflected signals of the ultrasonic signals and propagation signals of the surface wave signals;
The data processing module is used for extracting the reflection characteristic of the reflection signal and the propagation characteristic of the propagation signal and identifying the first defect information of the wafer to be detected based on the reflection characteristic and the propagation characteristic;
The data processing module is further used for fusing the reflection characteristic and the propagation characteristic to obtain a characteristic parameter of the wafer to be detected, and identifying second defect information of the wafer to be detected based on the characteristic parameter;
The data processing module is further configured to identify target defect information of the wafer to be tested based on the first defect information and the second defect information.
In an embodiment, the apparatus further comprises:
The pre-scanning lens is used for acquiring wafer information of the wafer to be detected, wherein the wafer information comprises a wafer type and historical defect information corresponding to the wafer type;
the pre-scanning lens is further used for determining detection parameters of the wafer to be detected based on the wafer information, wherein the detection parameters comprise probe parameters, detection environment parameters and acoustic frequency parameters.
In addition, in order to achieve the above object, the present application also proposes a wafer defect detection system comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program being configured to implement the steps of the wafer defect detection method as described above.
In addition, in order to achieve the above object, the present application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the steps of the wafer defect detection method as described above.
Furthermore, to achieve the above object, the present application provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the wafer defect detection method as described above.
One or more technical schemes provided by the application have at least the following technical effects:
The method comprises the steps of transmitting ultrasonic signals and surface wave signals to a wafer to be detected based on detection parameters of the wafer to be detected, collecting reflection signals of the ultrasonic signals and propagation signals of the surface wave signals, extracting reflection characteristics of the reflection signals and propagation characteristics of the propagation signals, identifying first defect information of the wafer to be detected based on the reflection characteristics and the propagation characteristics, fusing the reflection characteristics and the propagation characteristics to obtain characteristic parameters of the wafer to be detected, identifying second defect information of the wafer to be detected based on the characteristic parameters, and identifying target defect information of the wafer to be detected based on the first defect information and the second defect information. In addition, the feedback signals of the two acoustic waves are fused, so that fusion verification is carried out between the defects, a defect result with higher recognition accuracy is obtained, and better defect recognition effect is obtained through comparison of two front and rear defect recognition.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the technical solution of the present application and are not intended to limit the present application.
For a better understanding of the technical solution of the present application, the following detailed description will be given with reference to the drawings and the specific embodiments.
The embodiment of the application aims to provide a better wafer defect detection method, which aims to improve the accuracy of wafer defect detection, and mainly adopts the technical scheme that a surface wave technology is added on the basis of the existing single ultrasonic detection, the defects in a wafer are detected by utilizing the reflection and transmission characteristics of ultrasonic waves, the defects on the surface of the wafer are detected by utilizing the propagation characteristics of surface waves, so that the detection is more comprehensive, meanwhile, in order to further improve the detection accuracy, the ultrasonic waves and the surface waves are fused, so that the defect is positioned more accurately and reliably, and finally, the front and rear analysis is carried out by combining the defect results of the front and rear two times, so that the comprehensiveness and the accuracy of the detection are considered.
In the present embodiment, a wafer defect detection apparatus is described as an execution body. It should be noted that, referring to fig. 1, the wafer defect detecting apparatus of the present embodiment includes a pre-scanning lens (not shown) for scanning wafer information of a wafer to be detected, including size information of the wafer, type of the wafer, and the like, and selecting a suitable probe, detection environment, and sound frequency, and the like, according to the scanned information, a wafer carrying platform 1 for carrying the wafer to be detected, a mechanical arm 2 for precisely moving the wafer to be detected to different detection positions, a probe 3 for transmitting ultrasonic waves and surface waves, in particular, the probe may be a composite probe, that is, a combination of an ultrasonic probe and a surface wave probe, so as to enable one probe to emit two kinds of waves, a signal processor (not shown) including a signal generator and a signal receiver for transmitting acoustic signals and collecting feedback of the acoustic signals, a probe and a signal processor forming a detection module, a data processing module 4 for performing data analysis according to the feedback signals, thereby identifying defects of the wafer to be detected, a display module (not shown) for displaying detection results including positions and types of the defects, and the like.
Specifically, when a wafer (wafer to be detected) needs to be detected, the wafer defect detection equipment scans and judges wafer information of the current wafer to be detected, such as 8 inches, an unprocessed wafer and the like, generally causes historical defect problems such as cracks, selects a proper probe, such as an ultrasonic probe and a surface wave composite probe, according to the wafer information, selects a detection environment, such as a water or oil environment, selects an acoustic wave frequency, such as 5MHz, then controls a mechanical arm to position the wafer to be detected to a wafer carrying platform, then controls a signal generator on the probe to emit ultrasonic waves and surface waves, impacts the wafer to be detected on the wafer carrying platform, receives reflected waves and propagation waves which are fed back through a signal receiver, transmits the reflected waves and the propagation waves to a data processing module, and analyzes and identifies the reflected waves and the propagation waves by the data processing module, so that preliminary defect information, namely first defect information, is fused by the data after fusion, analysis and identification are carried out according to the fused data, so that more accurate defect information, namely second defect information and second defect information, which is more accurate and more complete and balanced defect information are obtained after the first defect information and the second defect information are analyzed.
The technical scheme of the application will be described in detail below.
Referring to fig. 2, fig. 2 is a schematic flow chart of an embodiment of a wafer defect detection method according to the present application.
In this embodiment, the wafer defect detection method includes steps S10 to S40:
Step S10, based on detection parameters of a wafer to be detected, transmitting ultrasonic signals and surface wave signals to the wafer to be detected, and collecting reflection signals of the ultrasonic signals and propagation signals of the surface wave signals;
In order to solve the problem that the prior art has a certain effect when single ultrasonic waves are adopted to detect the wafer defects, but still has a certain misjudgment rate, and particularly aims at the surface defects of the wafer, such as tiny scratches, particle pollution and the like, the surface waves are introduced during detection, so that the problem that the defect detection is incomplete is solved.
Specifically, when the wafer defect detection system detects a wafer to be detected, corresponding ultrasonic signals and surface wave signals are emitted according to detection parameters of the wafer to be detected, then the emitted signals of the ultrasonic signals and the propagation signals of the surface waves are collected according to propagation behavior characteristics of the acoustic waves, and the two signals are used as the basis of subsequent data analysis.
It will be appreciated that the wafer to be tested is a sample of wafers to be tested, typically a sample of a batch of wafers, and that ultrasonic waves are sound waves having a frequency above the upper limit of human hearing (typically above 20 kHz) and are propagated in solids, liquids and gases. It should be noted that by transmitting ultrasonic waves into the wafer interior, receiving and analyzing the reflected signals, defects in the wafer interior can be detected. If there are defects, such as cracks, bubbles or inclusions, within the wafer, the ultrasonic waves will reflect or scatter at these defects, thereby creating different signal characteristics. Surface waves are ultrasonic waves propagating along the surface of a wafer, and by transmitting surface waves to the surface of the wafer, surface defects can be detected. Surface waves are very sensitive to surface imperfections and can detect microscopic scratches, particle contamination, etc. Therefore, the ultrasonic wave and the surface wave can be complemented, so that a more comprehensive reflected signal of the ultrasonic wave and a propagation signal of the surface wave are acquired.
An exemplary implementation scenario is assuming a 12 inch silicon wafer as the wafer to be tested, and the types of defects that may exist include cracks, voids, and surface scratches. The wafer defect detection apparatus selects an ultrasonic probe having a frequency of 10MHz and a surface wave probe having a frequency of 5 MHz. The equipment controls the probe to uniformly move on the surface of the wafer, transmits ultrasonic signals and surface wave signals, and respectively collects reflected signals and propagation signals.
In a possible implementation manner, before the step of transmitting the ultrasonic signal and the surface wave signal to the wafer to be tested based on the detection parameter of the wafer to be tested, the method further includes:
Step a, obtaining wafer information of the wafer to be tested, wherein the wafer information comprises a wafer type and historical defect information corresponding to the wafer type;
that is, in another embodiment, in order to obtain a more suitable detection result, the wafer defect detection apparatus is configured to first obtain wafer information of a wafer to be detected, so as to select a suitable parameter to detect the wafer to be detected, where the wafer information includes a wafer size, a wafer type, and historical defect information corresponding to the wafer type.
It should be noted that, different wafers are manufactured by different production processes, the quality qualification standards are slightly different, the defect information of the historic occurrence is different, and in order to ensure efficient and matching detection, the wafer to be detected is subjected to front-end judgment.
And b, determining detection parameters of the wafer to be detected based on the wafer information, wherein the detection parameters comprise probe parameters, detection environment parameters and acoustic frequency parameters.
After the wafer information of the wafer to be tested is obtained, a proper probe parameter, an environment detection parameter and a sound wave frequency parameter can be selected, then a proper probe is selected according to the probe parameter, in one embodiment, the probe is a multifunctional integrated probe, not only an ultrasonic probe, but also a surface wave probe, and also a combined probe of the ultrasonic probe and the surface wave probe, the environment detection parameter, namely the transmission environment of sound waves, can be air, of course, water or oil can be adopted to ensure the continuity of the sound wave transmission, the sound wave frequency parameter, namely the frequency of the sound waves, can be used for counting the past historical defects when the method is implemented, and the frequency required by different wafers is analyzed, for example, the ultrasonic wave required by a 12-inch wafer is 10MHz, the surface wave is 5MHz, and the like. These parameters are collectively referred to as detection parameters, and provide standard basis for subsequent detection.
In particular, when the probe is a composite probe, that is, the probe can emit both ultrasonic signals and surface wave signals. Then, when the ultrasonic signal and the surface wave signal are transmitted to the wafer to be tested, the simultaneous transmission and the interval transmission can be selected.
It will be appreciated that. If simultaneous transmission is chosen, it is necessary to separate the reflected signal of the subsequently acquired ultrasonic signal from the propagating signal of the surface wave signal, or else there is a mutual interference of the two waves, resulting in a slightly insufficient final detection accuracy, and therefore, in one embodiment, a spaced transmission is preferred.
Specifically, the step of transmitting an ultrasonic signal and a surface wave signal to the wafer to be tested based on the detection parameters of the wafer to be tested, and collecting a reflected signal of the ultrasonic signal and a propagation signal of the surface wave signal includes:
Determining a corresponding emission mode based on detection parameters of the wafer to be detected, wherein the emission mode comprises an emission interval;
And based on the emission mode, sequentially emitting ultrasonic signals and surface wave signals to the wafer to be detected, and based on the emission interval, respectively collecting reflected signals of the ultrasonic signals and propagation signals of the surface wave signals.
That is, in order to avoid the mutual interference of the two acoustic waves, an emission interval may be set, and an ultrasonic signal or a surface wave signal is emitted first, and then a surface wave signal or an ultrasonic signal is emitted, so that a cleaner reflected signal and a propagation signal may be collected, respectively.
In practice, if an excessively long transmission interval is set, the whole detection duration is prolonged, but the transmission interval is too short, and echo interference may exist in the sound wave transmitted for the first time, so that it is necessary to set an appropriate transmission interval to balance the detection duration and the detection accuracy. In practice, empirical methods, such as full-scale accurate inspection for 2 inch wafers 1mm thick, with an emission interval of 0.4ms, etc., may be used. Of course, a better transmission interval can be obtained by adopting a machine simulation learning mode.
Step S20, extracting reflection characteristics of the reflection signals and propagation characteristics of the propagation signals, and identifying first defect information of the wafer to be detected based on the reflection characteristics and the propagation characteristics;
In this step, the wafer defect detection apparatus performs preprocessing on the collected reflected signal and the propagation signal to extract the reflection characteristic and the propagation characteristic. The reflection characteristics include reflection intensity, transmission time, frequency response, etc. for describing reflection characteristics of the ultrasonic wave, and the propagation characteristics include propagation speed, attenuation characteristics, phase change, etc. for describing propagation characteristics of the surface wave. Then, the apparatus identifies first defect information of the wafer to be tested based on the feature parameters.
Specifically, the step of identifying the first defect information of the wafer to be tested based on the reflection characteristic and the propagation characteristic includes:
Step c, positioning internal defect information of the wafer to be detected based on reflection intensities of the reflection signals at different positions of the wafer to be detected and transmission time of the reflection signals at different positions;
Step d, positioning surface defect information of the wafer to be detected based on attenuation characteristics and phase changes of the propagation signal on the surface of the wafer to be detected;
And e, generating first defect information of the wafer to be tested by the internal defect information and the surface defect information.
It should be noted that the reflection intensity of the reflection characteristic refers to measuring the reflection intensity of the ultrasonic signal at different positions to reflect the size and shape of the defect, the projection time refers to recording the time from the transmission to the reception of the ultrasonic signal for calculating the depth of the defect, and the frequency response refers to analyzing the frequency component of the ultrasonic signal to identify defects of different types and properties. The propagation speed of the propagation signal refers to the propagation speed of the surface wave signal on the surface of the wafer to reflect the physical property and the surface state of the wafer to be measured, the attenuation characteristic refers to the attenuation condition of the surface wave signal, the existence and the degree of the surface defect are identified, and the phase change refers to the phase change of the surface wave signal, which is measured and used for accurately positioning the position of the defect.
Therefore, it can be understood that the internal defect information of the wafer to be measured can be positioned by ultrasonic waves, the surface defect information of the wafer to be measured can be positioned by surface waves, and the two can be combined to obtain the comprehensive defect information of the wafer to be measured.
An exemplary implementation scenario is to assume that the reflection characteristics of the acquired ultrasound signal are:
Reflection intensity of 100
Transmission time 10. Mu.s
Frequency response [100,200,300]
The propagation characteristics of the collected surface wave signal are assumed to be:
Propagation speed of 5000m/s
Attenuation characteristics of 0.5dB/cm
Phase change of pi/4 rad
The wafer defect detection equipment preliminarily recognizes that a crack exists on the surface of the wafer according to the characteristic parameters, and the crack is positioned at (x, y) = (10 mm ).
In a possible embodiment, the step of extracting the reflection characteristic of the reflection signal and the propagation characteristic of the propagation signal comprises:
respectively acquiring a first transmitting time of the ultrasonic signal and a second transmitting time of the surface wave signal;
according to the first emission time and the second emission time, carrying out data preprocessing on the reflected signal and the propagation signal, wherein the data preprocessing comprises noise filtering, signal enhancement and standardization;
and extracting the reflection characteristics of the reflection signals and the propagation characteristics of the propagation signals after data preprocessing.
That is, when the reflection characteristic of the reflected signal and the propagation characteristic of the propagation signal are extracted, the signals are preprocessed, in order to further avoid mutual interference of the two acoustic waves, the first emission time of the ultrasonic signal and the second emission time of the surface wave signal are acquired, and the processing is staggered according to the interval between the first emission time and the second emission time, so that the distinction of the two acoustic waves is increased.
It will be appreciated that the purpose of data preprocessing is to remove noise from the signal and improve signal quality. And enhancing weak signals to ensure the reliability and accuracy of the signals. And performing normalization processing to enable signals from different sources to have comparability.
In the specific implementation, a digital filter (such as a low-pass filter and a band-pass filter) can be used for removing noise in the signals, wherein the low-pass filter can remove high-frequency noise;
The signal amplification technology can be used for enhancing the weak signal, so that the reliability and the accuracy of the signal are ensured, for example, the gain is adjusted, the gain is dynamically adjusted according to the signal intensity, and the signal is ensured not to be distorted;
the signals from different sources can be standardized to be comparable, so that subsequent feature extraction and matching are facilitated, such as minimum-maximum normalization, which is to scale the signal value to the [0,1] interval, Z-score normalization, which is to convert the signal value into a standard normal distribution with the mean value of 0 and the standard deviation of 1, and the like.
An exemplary implementation scenario is (code implementation example):
Step S30, fusing the reflection characteristic and the propagation characteristic to obtain a characteristic parameter of the wafer to be detected, and identifying second defect information of the wafer to be detected based on the characteristic parameter;
In the step, the wafer defect detection equipment fuses the reflection characteristic representing the internal defect of the wafer to be detected and the propagation characteristic representing the surface defect of the wafer to be detected, so that the characteristic parameters reflecting the defect of the wafer to be detected more accurately can be obtained. This is because there is a lack of detection of a single acoustic signal, whether it is an ultrasonic signal or a surface wave signal, and for such defects that span defects, i.e., are both internal defects and surface defects, there are two feedback from using an ultrasonic signal plus a surface wave signal, there is a suspicion that a repeatedly defined defect, such as a defect that a surface crack extends into the interior, there is a defect mark in the reflection characteristic, and there is a defect mark in the propagation characteristic, but the two marks may not be accurate, such as a surface wave identifying it as a pit, an ultrasonic wave identifying it as a void, or the like. Therefore, data fusion is required to complement defect information on the one hand and correct error defect information on the other hand.
Specifically, the step of fusing the reflection characteristic and the propagation characteristic to obtain the characteristic parameter of the wafer to be tested includes:
f, matching the reflection characteristic and the propagation characteristic based on a first sampling point of the reflection signal and a second sampling point of the propagation signal to obtain first fusion data;
In one embodiment, the preliminary fusion may be accomplished from a spatial dimension, and in particular, may be aligned by a coordinate system, such as matching the reflection and propagation characteristics under the same spatial coordinate system. This means that each sample point of the ultrasonic signal and the surface wave signal needs to have a corresponding coordinate position. For example, if the ultrasonic probe acquires a reflected intensity value at location (x, y), the surface wave probe also acquires a propagation velocity value at the same location (x, y). If the sampling points of the two probes do not completely coincide, the data can be aligned to the same grid by a spatial interpolation method (such as linear interpolation or spline interpolation), so as to obtain first fusion data.
Step g, correcting the first fusion data based on the first time stamp of the reflected signal and the second time stamp of the propagation signal to obtain second fusion data;
Further data fusion can then be completed from the time dimension. In particular, in order to ensure that the acquisition times of the ultrasonic signal and the surface wave signal are identical. This can be achieved by adding a time stamp during the data acquisition process. For example, each signal acquisition point has a time stamp that ensures that the sampled data of the two signals at the same point in time can be correlated. Therefore, the first fusion data can be corrected according to the first time stamp of the reflected signal and the second time stamp of the propagation signal, and the problem that the acquisition points are not identical due to inconsistent acquisition time is avoided. Of course, if the collection of the reflected signal and the propagation signal is delayed in time, such as before and after collection, the time deviation can be corrected by a time delay compensation technology, so that the consistency of the data is ensured.
Step h, calculating the similarity of the reflection characteristic and the propagation characteristic, and checking the second fusion data based on the similarity;
And then, comparing the extracted reflection characteristic with the propagation characteristic by using a similarity measurement method (such as a mahalanobis distance, cosine similarity and the like) to identify defect information at the same position. For example, the similarity of the reflection intensity and the propagation speed may be calculated, and if the similarity is high, the position is considered to have a defect. Otherwise, there may be an identification error, thereby completing the verification of the second fusion data.
Further, in a possible embodiment, the step of calculating the similarity of the reflection characteristic and the propagation characteristic includes:
step h1, selecting reflection parameters of the reflection characteristics and propagation parameters of the propagation characteristics, and determining similarity formulas corresponding to the reflection parameters and the propagation parameters;
And h2, substituting the reflection parameter and the propagation parameter into the similarity formula to obtain the similarity.
That is, the calculation of the similarity may be performed in various manners, and the reflection parameter and the propagation parameter may be performed in different manners.
In a specific implementation, because there may be a correlation between different characteristic parameters, for example, there may be some correlation between the reflection intensity and the propagation speed, which affects the accuracy of the similarity measurement, for example, some types of defects may affect the reflection intensity and the propagation speed at the same time, so that the two parameters may change in some areas at the same time, and if a conventional distance measurement method (such as euclidean distance) is used, the correlation may cause distortion of the result of the similarity measurement. For example, the common variation of two characteristic parameters may be excessively amplified or reduced, thereby affecting the final similarity determination.
In one possible embodiment, therefore, a distance measurement method is proposed that considers the correlation between variables, specifically by measuring the correlation between different features through a covariance matrix, so as to eliminate the correlation interference between the features.
Specifically, a reflection parameter of the reflection characteristic and a propagation parameter of the propagation characteristic are selected, and a corresponding feature vector and a reference feature vector are constructed based on the reflection parameter and the propagation parameter;
based on the feature vector and the reference feature vector, calculating a corresponding column vector, and transposing the column vector to obtain a corresponding row vector;
calculating a corresponding covariance matrix based on the reflection parameter and the propagation parameter, and calculating an inverse of the covariance matrix;
And substituting the inverse of the column vector, the row vector and the covariance matrix into a Markov distance formula to calculate the similarity of the reflection characteristic and the propagation characteristic.
For easy understanding, the reflection parameter is taken as reflection intensity, and the propagation parameter is taken as propagation speed for example to describe in detail:
assume that at the position (10 mm ), the reflection intensity is 100 and the propagation speed is 5000m/s.
First, constructing a feature vector:
Wherein the feature vector x includes the reflected intensity and propagation velocity;
second, constructing a reference feature vector:
Let the mean values of the reflection intensity and propagation velocity be μ Reflection intensity＝50,μ Propagation velocity =4500, respectively, to construct a reference eigenvector μ
Third, calculating covariance matrix:
assuming a covariance matrix of known reflection intensity and propagation velocity:
Where δ11 is the variance of the reflected intensity, δ22 is the variance of the propagation velocity, δ12 and δ21 are the covariances of the reflected intensity and the propagation velocity, assuming specific values:
and fourthly, substituting the parameters into a Markov distance formula:
First calculate
Then the inverse S of the covariance matrix is calculated-1
Wherein, the det (S) =δ11δ22-δ12δ21 =25×10000-100×100=250000-10000=240000
Therefore:
thus:
if the similarity exceeds a certain threshold, such as 10, the location is considered defective.
In the above calculation, (x- μ) is a column vector, and represents the difference between the obtained feature vector and the reference feature vector;
(x- μ)T is a transpose of (x- μ) converting the column vectors to row vectors;
S-1 is the inverse of the covariance matrix.
The method can eliminate the correlation interference between the reflection intensity and the propagation speed, so that the similarity measurement is more accurate. Specifically, through the inverse matrix of the covariance matrix, the correlation between the features is adjusted, so that the accuracy and reliability of defect detection are improved.
In addition, other parameters and formulas may be selected for calculation, such as calculating the similarity of transmission time and attenuation characteristics. For example, a cosine similarity formula may be used:
Where A and B are vectors of transmission time and attenuation characteristics, respectively.
For example, to calculate the similarity of frequency response and phase change. For example, a correlation coefficient formula may be used:
where Ai and Bi are the values of the frequency response and the phase change, respectively,AndAre their average values, etc.
If the similarity exceeds a certain threshold, the location is considered defective.
And i, screening out the characteristic parameters of the wafer to be tested from the second fusion data according to the verification result.
In this step, according to the similarity calculation of each sampling point or sampling point, reliability identification is performed on each sampling point or sampling point, and for the sampling points or sampling points with similarity higher than the threshold value, the characteristic parameters of the wafer to be tested are screened out, and the characteristic parameters can further represent defect information of the wafer to be tested, namely, the reliability of the defect information corresponding to the characteristic parameters is higher, and the defects are preferentially considered.
An exemplary implementation scenario is:
Suppose we have collected the following data at location (x, y):
ultrasonic signal:
Reflection intensity of 100
Transmission time 10. Mu.s
Frequency response [100,200,300]
Surface wave signal:
Propagation speed of 5000m/s
Attenuation characteristics of 0.5dB/cm
Phase change of pi/4 rad
Spatial matching:
The data collected at the same position (x, y) of the ultrasonic signal and the surface wave signal can be correspondingly ensured.
Time synchronization:
It is ensured that the sampled data of the ultrasonic signal and the surface wave signal at the same point in time can be correlated. For example, if the ultrasonic signal acquires data at t=0s, the surface wave signal also acquires data at t=0s.
Feature contrast:
The reflected intensity 100 is compared with a propagation speed of 5000m/s to determine if a defect exists at the location.
The similarity of the reflection intensity and the propagation speed is calculated, and if the similarity is high, the position is considered to have a defect.
In addition, other characteristic parameters (such as transmission time, frequency response, attenuation characteristic and phase change) can be comprehensively considered, so that the type and severity of the defect can be further confirmed.
Similarity calculation example description:
Assume that at the position (10 mm ), the reflection intensity is 100 and the propagation speed is 5000m/s. The wafer defect detection equipment matches the two characteristic parameters under the same space coordinate system, and ensures the consistency of the acquisition time through a time synchronization technology. And then a similarity measurement method (such as a mahalanobis distance) is used for calculating the similarity of the two characteristic parameters:
assuming μ Reflection intensity＝50,μ Propagation velocity =4500, which are the average of the reflection intensity and propagation speed under normal conditions, respectively, then:
if the set threshold is 10, the similarity exceeds the threshold, and the wafer defect detection apparatus considers that the position has a defect.
Step S40, identifying target defect information of the wafer to be tested based on the first defect information and the second defect information.
In this embodiment, the first defect information includes internal defect information and surface defect information of the wafer to be tested, that is, the first defect information provides more comprehensive defect information, and the second defect information includes the most definite (high-similarity) defect information, that is, provides more accurate defect information, so that the two pieces of defect information are combined to obtain target defect information of the wafer to be tested, and the target defect information considers both the comprehensiveness and the authenticity of the defect, so that the defect of the wafer to be tested can be more characterized.
Finally, the wafer defect detection device synthesizes the first defect information (the crack position which is preliminarily identified) and the second defect information (the crack position which is confirmed through feature parameter fusion) to generate a detailed defect detection report.
An exemplary implementation scenario is:
defect location (10 mm )
Type of defect, crack
Defect size 20 μm
Defect depth 5 μm
Defect distribution local
The embodiment provides a wafer defect detection method, which not only obtains internal defect information of a wafer to be detected, but also obtains surface defect information of the wafer to be detected by using a sound wave combination mode of ultrasonic signals and surface wave signals when the wafer to be detected is detected, so that the defect is more comprehensively identified, and simultaneously, fusion treatment is carried out on reflection characteristics corresponding to the ultrasonic signals and propagation characteristics corresponding to the surface waves, and more accurate defect information is identified by obtaining characteristic parameters which can more represent the defect of the wafer to be detected, and finally, the front identification and the rear identification are combined, so that the final detection result is comprehensive and reliable, and the accuracy of wafer defect detection is improved.
It should be noted that the foregoing examples are only for understanding the present application, and are not meant to limit the method for detecting wafer defects of the present application, and more forms of simple transformation based on the technical concept are all within the scope of the present application.
The present application also provides a wafer defect detection apparatus, referring to fig. 3, including:
The detection module 20 is configured to transmit an ultrasonic signal and a surface wave signal to a wafer to be detected based on a detection parameter of the wafer to be detected, and collect a reflected signal of the ultrasonic signal and a propagation signal of the surface wave signal;
a data processing module 30, configured to extract a reflection characteristic of the reflected signal and a propagation characteristic of the propagation signal, and identify first defect information of the wafer to be tested based on the reflection characteristic and the propagation characteristic;
The data processing module is further used for fusing the reflection characteristic and the propagation characteristic to obtain a characteristic parameter of the wafer to be detected, and identifying second defect information of the wafer to be detected based on the characteristic parameter;
The data processing module is further configured to identify target defect information of the wafer to be tested based on the first defect information and the second defect information.
In addition, the wafer defect detection apparatus further includes:
a pre-scanning lens 10, configured to obtain wafer information of the wafer to be tested, where the wafer information includes a wafer type and historical defect information corresponding to the wafer type;
the pre-scanning lens is further used for determining detection parameters of the wafer to be detected based on the wafer information, wherein the detection parameters comprise probe parameters, detection environment parameters and acoustic frequency parameters.
And a display module 40 for displaying the target defect information.
The wafer defect detection equipment provided by the application can solve the technical problem of insufficient single acoustic wave detection precision by adopting the wafer defect detection method in the embodiment. Compared with the prior art, the beneficial effects of the wafer defect detection device provided by the application are the same as those of the wafer defect detection method provided by the embodiment, and other technical features of the wafer defect detection device are the same as those disclosed by the method of the embodiment, so that the description is omitted herein.
The application provides a wafer defect detection system which comprises at least one processor and a memory in communication connection with the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the wafer defect detection method in the embodiment.
Referring now to FIG. 4, a schematic diagram of a hardware architecture suitable for use in implementing a wafer defect detection system according to an embodiment of the present application is shown. The wafer defect detection system in the embodiments of the present application may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (Personal DigitalAssistant: personal digital assistants), PADs (Portable Application Description: tablet computers), PMPs (Portable MEDIA PLAYER: portable multimedia players), vehicle terminals (e.g., car navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The wafer defect inspection system shown in fig. 4 is only an example and should not be construed as limiting the functionality and scope of use of embodiments of the present application.
As shown in fig. 4, the wafer defect detection system may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.) that may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access Memory (RAM: random Access Memory) 1004. In the RAM1004, various programs and data required for the operation of the wafer defect detection system are also stored. The processing device 1001, the ROM1002, and the RAM1004 are connected to each other by a bus 1005. An input/output (I/O) interface 1006 is also connected to the bus. In general, a system including an input device 1007 such as a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc., an output device 1008 including a Liquid crystal display (LCD: liquid CRYSTAL DISPLAY), a speaker, a vibrator, etc., a storage device 1003 including a magnetic tape, a hard disk, etc., and a communication device 1009 may be connected to the I/O interface 1006. The communication means 1009 may allow the wafer defect detection system to communicate with other devices wirelessly or by wire to exchange data.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through a communication device, or installed from the storage device 1003, or installed from the ROM 1002. The above-described functions defined in the method of the disclosed embodiment of the application are performed when the computer program is executed by the processing device 1001.
The wafer defect detection system provided by the application adopts the wafer defect detection method in the embodiment, and can solve the technical problem of insufficient single acoustic wave detection precision. Compared with the prior art, the wafer defect detection system provided by the application has the same beneficial effects as the wafer defect detection method provided by the embodiment, and other technical features in the wafer defect detection system are the same as those disclosed by the method of the previous embodiment, and are not repeated herein.
It is to be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the description of the above embodiments, particular features, structures, materials, or characteristics may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
The present application provides a computer readable storage medium having computer readable program instructions (i.e., a computer program) stored thereon for performing the wafer defect detection method of the above-described embodiments.
The computer readable storage medium provided by the present application may be, for example, a USB flash disk, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system or device, or a combination of any of the foregoing. More specific examples of a computer-readable storage medium may include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access Memory (RAM: random Access Memory), a Read-Only Memory (ROM: read Only Memory), an erasable programmable Read-Only Memory (EPROM: erasable Programmable Read Only Memory or flash Memory), an optical fiber, a portable compact disc Read-Only Memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this embodiment, the computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to electrical wiring, fiber optic cable, RF (Radio Frequency) and the like, or any suitable combination of the foregoing.
The computer readable storage medium may be included in the wafer defect inspection system or may exist alone without being incorporated into the wafer defect inspection system.
The computer readable storage medium carries one or more programs that, when executed by the wafer defect inspection system, cause the wafer defect inspection system to perform the steps of the wafer defect inspection method.
Computer program code for carrying out operations of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of remote computers, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN: localArea Network) or a wide area network (WAN: wide Area Network), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules involved in the embodiments of the present application may be implemented in software or in hardware. Wherein the name of the module does not constitute a limitation of the unit itself in some cases.
The readable storage medium provided by the application is a computer readable storage medium, and the computer readable storage medium stores computer readable program instructions (namely computer program) for executing the wafer defect detection method, so that the technical problem of insufficient single sound wave detection precision can be solved. Compared with the prior art, the beneficial effects of the computer readable storage medium provided by the application are the same as those of the wafer defect detection method provided by the above embodiment, and are not described in detail herein.
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of a wafer defect detection method as described above.
The computer program product provided by the application can solve the technical problem of insufficient single sound wave detection precision. Compared with the prior art, the beneficial effects of the computer program product provided by the application are the same as those of the wafer defect detection method provided by the above embodiment, and are not described herein.
The foregoing description is only a partial embodiment of the present application, and is not intended to limit the scope of the present application, and all the equivalent structural changes made by the description and the accompanying drawings under the technical concept of the present application, or the direct/indirect application in other related technical fields are included in the scope of the present application.