Disclosure of Invention
According to the application, the operation abnormality assessment result, the belt operation abnormality assessment result and the mineral transportation condition data are imported into a belt conveyor life prediction strategy to predict the life of the belt conveyor, the belt conveyor driving operation data and the belt operation data in the operation process are comprehensively analyzed, the implicit abnormal characteristics about the life of the belt conveyor in the data are analyzed, and further the damage speed of the abnormal characteristics and the mineral transportation to the life of the belt conveyor is comprehensively assessed, so that the life of the belt conveyor is accurately predicted, and the accuracy of the life prediction of the belt conveyor is improved.
In order to achieve the above purpose, the application provides the following technical scheme that in a first aspect, the application provides a horizontal belt conveyor operation monitoring method based on data analysis, which comprises the following specific steps:
s1, acquiring driving operation data and belt operation data of a horizontal belt conveyor in the operation process, and acquiring mineral transportation condition data in the operation process;
S2, importing the driving operation data of the horizontal belt conveyor into a driving operation abnormality evaluation model to evaluate driving operation abnormality;
S3, importing the acquired belt running data into a belt abnormality assessment model to carry out belt running abnormality assessment;
S4, importing the operation abnormality assessment result, the belt operation abnormality assessment result and the transported mineral condition data into a belt conveyor life prediction strategy to predict the life of the belt conveyor;
S5, carrying out life comparison early warning according to the obtained life estimation result of the belt conveyor.
As a preferable technical scheme of the horizontal belt conveyor operation monitoring method based on data analysis, the method for acquiring the driving operation data and the belt operation data of the horizontal belt conveyor in the operation process comprises the following specific contents of the condition data of transported minerals in the operation process:
S11, acquiring surface crack data of a horizontal belt and sliding data of two sides of the running horizontal belt in the running process of the horizontal belt through an image acquisition terminal arranged below the horizontal belt, wherein the surface crack data comprise crack length and crack width data, and the sliding data of the two sides of the running are edge displacement data relative to a normal belt track when each point on the edge of the belt passes through the position right above the image acquisition terminal in the running process;
S12, acquiring driving equipment operation data through a driving equipment data acquisition terminal, wherein the driving equipment operation data comprise driving equipment temperature, driving equipment rotating speed, driving equipment vibration frequency and amplitude data;
s13, acquiring real-time transportation mineral mass data and simultaneously acquiring transportation plan data.
As a preferable technical scheme of the horizontal belt conveyor operation monitoring method based on data analysis, the method for guiding the horizontal belt conveyor driving operation data into a driving operation abnormality assessment model to carry out driving operation abnormality assessment comprises the following specific steps:
S21, testing the driving equipment at intervals of a set period to obtain driving equipment temperature, driving equipment rotating speed, driving equipment vibration frequency and amplitude data in the running process of the driving equipment, wherein the testing duration is preferably the duration of two weeks of horizontal belt rotation;
S22, importing the obtained driving equipment temperature, driving equipment rotating speed, driving equipment vibration frequency and amplitude data into a driving equipment abnormal value calculation formula to calculate the driving equipment abnormal value, wherein the driving equipment abnormal value calculation formula is as follows: Wherein Tc is the test time duration, dt is the time integral, tt is the temperature at the time t of the test, tmc is the median value of the temperature safety range of the driving device, tm is the maximum value minus the minimum value of the temperature safety range of the driving device, since the temperature changes along with the operation process during the operation of the driving device, vt is the rotation speed data at the time t of the test, vm is the rotation speed data to be output, vt-Vm is the difference of the evaluation rotation speeds, m is the vibration times of the driving device during the test at the time t, rit is the ith vibration amplitude of the driving device during the test at the time t, rm is the maximum value of the vibration safety range,In order for the vibration anomaly to be a duty cycle,Is the abnormal duty cycle of the rotating speed,For the abnormal temperature duty ratio, the vibration, temperature and rotating speed abnormality of the driving equipment are comprehensively analyzed in the formula;
S23, acquiring the calculated abnormal value of the driving equipment, and substituting the abnormal value into a driving equipment abnormal change speed calculation formula to calculate the abnormal change speed of the driving equipment, wherein the driving equipment abnormal change speed calculation formula is as follows: Wherein Xc is the abnormal change speed of the driving device, xt is the abnormal value of the driving device calculated in the current test period, X (t-1) is the abnormal value of the driving device calculated in the last test period, mt is the mass of the transported mineral between the last test period and the last test period, M is a set safety value of the mass of the transported mineral, namely the maximum mass of the mineral which can be placed on the conveyor belt;
in the step, the vibration, the temperature and the rotating speed of the driving equipment are tested, and then the vibration, the temperature and the rotating speed of the driving equipment are subjected to comprehensive abnormal analysis to obtain the abnormal change speed, so that the abnormal change trend of the driving equipment is further predicted.
As a preferable technical scheme of the horizontal belt conveyor operation monitoring method based on data analysis, the method for guiding the acquired belt operation data into a belt abnormality evaluation model to evaluate the belt operation abnormality comprises the following specific steps:
S31, acquiring horizontal belt surface crack data and horizontal belt running two-side sliding data of a test period;
S32, acquiring horizontal belt surface crack data of a test period, and importing the data into a crack abnormal value calculation formula to calculate a crack abnormal value, wherein the crack abnormal value calculation formula is as follows: wherein M is the number of cracks, sj is the length of the jth crack, zj is the width of the jth crack, sc is a surface crack length safety value, and zc is a surface crack width safety value;
S33, acquiring sliding data on two sides of the horizontal belt running, and importing the sliding data into a sliding displacement abnormal value calculation formula to calculate a sliding displacement abnormal value, wherein the sliding displacement abnormal value calculation formula is as follows: Wherein J is the transmission displacement of the horizontal belt in the test period, xc is the edge displacement data relative to the normal belt track when the c-th point on the edge of the horizontal belt passes over the image acquisition terminal, xm is the width of the horizontal belt, and dc is the point integration on the edge of the horizontal belt;
S34, acquiring the calculated crack abnormal value and sliding displacement abnormal value, importing the obtained crack abnormal value and sliding displacement abnormal value into a belt running abnormal value calculation formula, and calculating the belt running abnormal value, wherein the belt running abnormal value calculation formula is as follows: Wherein, the method comprises the steps of, wherein,Is the fracture anomaly value duty ratio coefficient.
As a preferable technical scheme of the horizontal belt conveyor operation monitoring method based on data analysis, the method for guiding the operation abnormality assessment result, the belt operation abnormality assessment result and the transportation mineral condition data into a belt conveyor life prediction strategy to perform belt conveyor life prediction comprises the following specific contents:
S41, acquiring the calculated abnormal value of the belt running, and introducing the abnormal value of the belt running into a belt abnormal change speed calculation formula to calculate the abnormal change speed of the belt, wherein the abnormal change speed calculation formula of the belt is as follows: spt is the abnormal value of the belt running calculated in the current test period, and Sp (t-1) is the abnormal value of the belt running calculated in the last test period;
S42, obtaining the calculated abnormal belt running value, the abnormal driving equipment change speed and the abnormal belt change speed, substituting the abnormal driving equipment change speed and the abnormal belt change speed into a life predicted value calculation formula to calculate a life predicted value, wherein the life predicted value calculation formula is as follows: wherein Xr is a set abnormal threshold, vr is the mineral transportation speed of the lower stage of the horizontal belt conveyor, namely how much mass of mineral needs to be transported in the average time of the lower stage,To drive the abnormal duty cycle.
As a preferable technical scheme of the horizontal belt conveyor operation monitoring method based on data analysis, the life comparison early warning according to the obtained belt conveyor life estimation result comprises the following specific contents:
Comparing the calculated life predicted value with a set belt life threshold value, if the life predicted value is larger than or equal to the set belt life threshold value, not carrying out belt life early warning, if the life predicted value is smaller than the set belt life threshold value, carrying out belt life early warning, wherein the belt life early warning is required to be carried out in advance because the horizontal belt conveyor is usually operated continuously, the belt life threshold value is flexibly set according to the requirement, and if the maintenance preparation period is 1 hour, the belt life threshold value can be set to be 1.5 hours-2 hours.
The application provides a horizontal belt conveyor operation monitoring system based on data analysis, which is realized based on the horizontal belt conveyor operation monitoring method based on the data analysis, and specifically comprises a data acquisition module, a driving operation abnormality evaluation module, a belt conveyor service life estimation module and a comparison early warning module;
The data acquisition module is used for acquiring horizontal belt conveyor driving operation data and belt operation data in the operation process and acquiring mineral transportation condition data in the operation process;
the driving operation abnormality evaluation module is used for importing driving operation data of the horizontal belt conveyor into a driving operation abnormality evaluation model to perform driving operation abnormality evaluation;
the belt running abnormality evaluation module is used for guiding the acquired belt running data into a belt abnormality evaluation model to perform belt running abnormality evaluation;
the belt conveyor life estimating module is used for guiding the abnormal operation estimating result, the abnormal belt operation estimating result and the mineral transportation condition data into a belt conveyor life estimating strategy to estimate the service life of the belt conveyor;
The comparison and early warning module is used for carrying out life comparison and early warning according to the obtained life estimated result of the belt conveyor;
The belt conveyor life prediction system comprises a belt conveyor life prediction module, a driving operation abnormality assessment module, a belt conveyor life prediction module and a comparison early warning module.
In a third aspect, the application provides an electronic device comprising a processor and a memory, wherein the memory stores a computer program for the processor to call;
the processor executes the horizontal belt conveyor operation monitoring method based on data analysis by calling the computer program stored in the memory.
In a fourth aspect, the present application provides a computer readable storage medium storing instructions that, when executed on a computer, cause the computer to perform a horizontal belt conveyor operation monitoring method based on data analysis as described above.
Compared with the prior art, the method has the beneficial effects that firstly, the horizontal belt conveyor driving operation data and the belt operation data in the operation process are obtained, meanwhile, the transportation mineral condition data in the operation process are obtained, then the horizontal belt conveyor driving operation data are imported into the driving operation abnormality evaluation model for driving operation abnormality evaluation, the obtained belt operation data are imported into the belt abnormality evaluation model for belt operation abnormality evaluation, finally, the operation abnormality evaluation result, the belt operation abnormality evaluation result and the transportation mineral condition data are imported into the belt conveyor life prediction strategy for belt conveyor life prediction, through comprehensive analysis of the belt conveyor driving operation data and the belt operation data in the operation process, the implicit abnormal characteristics of the belt conveyor life are analyzed, and further, the damage speed of the belt conveyor life is estimated comprehensively by the transportation of the abnormal characteristics and minerals, so that the belt conveyor life is estimated accurately, and the accuracy of the belt conveyor life is improved.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. The following description of at least one exemplary embodiment is merely exemplary in nature and is in no way intended to limit the application, its application, or uses.
Example 1. In order to solve the technical problems in the background art, the application provides a preferable embodiment, as shown in fig. 1-3, of a horizontal belt conveyor operation monitoring method based on data analysis, which comprises the following specific steps:
s1, acquiring driving operation data and belt operation data of a horizontal belt conveyor in the operation process, and acquiring mineral transportation condition data in the operation process;
In this embodiment, the specific contents of the driving operation data and the belt operation data of the horizontal belt conveyor in the operation process and the condition data of the transported minerals in the operation process are:
S11, as shown in FIG. 6, acquiring horizontal belt surface crack data and horizontal belt running two-side sliding data in the running process of the horizontal belt conveyor through an image acquisition terminal arranged below the horizontal belt conveyor, wherein the surface crack data comprise crack length and crack width data, and the running two-side sliding data are edge displacement data relative to a normal belt track when each point on the edge of the belt passes over the image acquisition terminal in the running process;
It should be noted that, the specific steps for acquiring the data of the length and width of the slit on the belt of the belt conveyor may be as follows, as shown in fig. 5,
S111, image acquisition, namely firstly, capturing an image of the surface of a belt through an image acquisition terminal (such as a high-definition camera) arranged below the belt conveyor, so as to ensure that the camera can clearly capture details of the surface of the belt, including possible cracks;
s112, image processing, namely transmitting the acquired image to a computer, and processing the acquired image by using image processing software, wherein the image processing software can perform operations such as enhancement, filtering, denoising and the like on the image so as to improve the image quality and make cracks more obvious;
S113, identifying cracks on the belt by using algorithms such as image segmentation, edge detection and the like in image processing software, wherein the algorithms can separate the cracks from the belt background according to the characteristics of colors, brightness, textures and the like of pixels;
S114, measuring the cracks, namely measuring the length and the width of the identified cracks by using a measuring tool in image processing software, wherein the length can be obtained by arranging mark points at two ends of the cracks and then measuring the distance between the mark points;
S12, acquiring driving equipment operation data through a driving equipment data acquisition terminal, wherein the driving equipment operation data comprise driving equipment temperature, driving equipment rotating speed, driving equipment vibration frequency and amplitude data;
s13, acquiring real-time transportation mineral mass data and simultaneously acquiring transportation plan data;
S2, importing the driving operation data of the horizontal belt conveyor into a driving operation abnormality evaluation model to evaluate driving operation abnormality;
In this embodiment, the driving operation abnormality evaluation performed by importing the driving operation data of the horizontal belt conveyor into the driving operation abnormality evaluation model includes the following specific steps:
S21, testing the driving equipment at intervals of a set period to obtain driving equipment temperature, driving equipment rotating speed, driving equipment vibration frequency and amplitude data in the running process of the driving equipment, wherein the testing duration is preferably the duration of two weeks of horizontal belt rotation;
S22, importing the obtained driving equipment temperature, driving equipment rotating speed, driving equipment vibration frequency and amplitude data into a driving equipment abnormal value calculation formula to calculate the driving equipment abnormal value, wherein the driving equipment abnormal value calculation formula is as follows: Wherein Tc is the test time duration, dt is the time integral, tt is the temperature at the time t of the test, tmc is the median value of the temperature safety range of the driving device, tm is the maximum value minus the minimum value of the temperature safety range of the driving device, since the temperature changes along with the operation process during the operation of the driving device, vt is the rotation speed data at the time t of the test, vm is the rotation speed data to be output, vt-Vm is the difference of the evaluation rotation speeds, m is the vibration times of the driving device during the test at the time t, rit is the ith vibration amplitude of the driving device during the test at the time t, rm is the maximum value of the vibration safety range,In order for the vibration anomaly to be a duty cycle,Is the abnormal duty cycle of the rotating speed,For the abnormal temperature duty ratio, the vibration, temperature and rotating speed abnormality of the driving equipment are comprehensively analyzed in the formula;
S23, acquiring the calculated abnormal value of the driving equipment, and substituting the abnormal value into a driving equipment abnormal change speed calculation formula to calculate the abnormal change speed of the driving equipment, wherein the driving equipment abnormal change speed calculation formula is as follows: Wherein Xc is the abnormal change speed of the driving device, xt is the abnormal value of the driving device calculated in the current test period, X (t-1) is the abnormal value of the driving device calculated in the last test period, mt is the mass of the transported mineral between the last test period and the last test period, M is a set safety value of the mass of the transported mineral, namely the maximum mass of the mineral which can be placed on the conveyor belt;
In the step, the vibration, the temperature and the rotating speed of the driving equipment are tested, and then the vibration, the temperature and the rotating speed of the driving equipment are comprehensively and abnormally analyzed to obtain the abnormal change speed, so that the abnormal change trend of the driving equipment is further predicted;
S3, importing the acquired belt running data into a belt abnormality assessment model to carry out belt running abnormality assessment;
In this embodiment, the step of introducing the acquired belt running data into the belt abnormality evaluation model to perform the belt running abnormality evaluation includes the following specific steps:
S31, acquiring horizontal belt surface crack data and horizontal belt running two-side sliding data of a test period;
S32, acquiring horizontal belt surface crack data of a test period, and importing the data into a crack abnormal value calculation formula to calculate a crack abnormal value, wherein the crack abnormal value calculation formula is as follows: Wherein M is the number of cracks, sj is the length of the jth crack, zj is the width of the jth crack, sc is the surface crack length safety value, zc is the surface crack width safety value, crack analysis helps to prevent potential safety risks, and when a belt is cracked, the strength and durability of the belt are greatly reduced, which may lead to unexpected breakage of the belt during operation of the equipment. The broken belt can not only cause equipment to stop, but also possibly cause chain reaction to damage other components and even possibly cause safety accidents, so that belt cracks can be found and processed in time, potential risks can be effectively avoided, and crack analysis is helpful for optimizing maintenance and management of equipment. The service condition of the belt can be known through analysis of the belt cracks, and the residual service life of the belt can be predicted, so that a more scientific and reasonable maintenance plan can be formulated;
S33, acquiring sliding data on two sides of the horizontal belt running, and importing the sliding data into a sliding displacement abnormal value calculation formula to calculate a sliding displacement abnormal value, wherein the sliding displacement abnormal value calculation formula is as follows: Wherein J is the transmission displacement of the horizontal belt in the test period, xc is the edge displacement data relative to the normal belt track when the c-th point on the edge of the horizontal belt passes right above the image acquisition terminal, xm is the width of the horizontal belt, dc is the point integration on the edge of the horizontal belt, and the sliding displacement is analyzed for analyzing whether the horizontal belt has derailment risk or not;
S34, acquiring the calculated crack abnormal value and sliding displacement abnormal value, importing the obtained crack abnormal value and sliding displacement abnormal value into a belt running abnormal value calculation formula, and calculating the belt running abnormal value, wherein the belt running abnormal value calculation formula is as follows: Wherein, the method comprises the steps of, wherein,The ratio coefficient of the abnormal value of the crack;
S4, importing the operation abnormality assessment result, the belt operation abnormality assessment result and the transported mineral condition data into a belt conveyor life prediction strategy to predict the life of the belt conveyor;
In this embodiment, the method for estimating the life of the belt conveyor by introducing the operation abnormality estimation result, the belt operation abnormality estimation result and the transportation mineral condition data into the belt conveyor life estimation strategy includes the following specific contents:
S41, acquiring the calculated abnormal value of the belt running, and introducing the abnormal value of the belt running into a belt abnormal change speed calculation formula to calculate the abnormal change speed of the belt, wherein the abnormal change speed calculation formula of the belt is as follows: spt is the abnormal value of the belt running calculated in the current test period, and Sp (t-1) is the abnormal value of the belt running calculated in the last test period;
S42, obtaining the calculated abnormal belt running value, the abnormal driving equipment change speed and the abnormal belt change speed, substituting the abnormal driving equipment change speed and the abnormal belt change speed into a life predicted value calculation formula to calculate a life predicted value, wherein the life predicted value calculation formula is as follows: wherein Xr is a set abnormal threshold, vr is the mineral transportation speed of the lower stage of the horizontal belt conveyor, namely how much mass of mineral needs to be transported in the average time of the lower stage,The driving anomaly duty ratio coefficient;
S5, carrying out life comparison early warning according to the obtained life estimation result of the belt conveyor;
In this embodiment, performing life comparison and early warning according to the obtained estimated life result of the belt conveyor includes the following specific contents:
Comparing the calculated life predicted value with a set belt life threshold value, if the life predicted value is larger than or equal to the set belt life threshold value, not carrying out belt life early warning, if the life predicted value is smaller than the set belt life threshold value, carrying out belt life early warning, wherein the belt life early warning is required to be carried out in advance because the horizontal belt conveyor is usually operated continuously, the belt life threshold value is flexibly set according to the requirement, and if the maintenance preparation period is 1 hour, the belt life threshold value can be set to be 1.5 hours-2 hours.
The vibration abnormal duty ratio, the rotating speed abnormal duty ratio, the temperature abnormal duty ratio, the crack abnormal value duty ratio coefficient, the driving abnormal duty ratio coefficient and the set abnormal threshold value are preferably obtained by obtaining the driving operation data of the horizontal belt conveyor in the 500 groups of operation processes, the belt operation data and the transportation mineral condition data in the operation processes, substituting the driving operation data and the transportation mineral condition data into a life pre-estimated value calculation formula to calculate the life pre-estimated value, and importing the calculated life pre-estimated value and the actual service life of the horizontal belt conveyor into fitting software to output the vibration abnormal duty ratio, the rotating speed abnormal duty ratio, the temperature abnormal duty ratio, the crack abnormal value duty ratio coefficient, the driving abnormal duty ratio coefficient and the set abnormal threshold value which meet the maximum life judgment accuracy.
Compared with the prior art, the method has the advantages that the operation abnormality assessment result, the belt operation abnormality assessment result and the mineral transportation condition data are imported into a belt conveyor life prediction strategy to predict the life of the belt conveyor, the belt conveyor driving operation data and the belt operation data in the operation process are comprehensively analyzed, the implicit abnormal characteristics about the life of the belt conveyor in the data are analyzed, the damage speed of the abnormal characteristics and the mineral transportation to the life of the belt conveyor is comprehensively assessed, the life of the belt conveyor is accurately predicted, and the accuracy of the life prediction of the belt conveyor is improved.
Example 2. As shown in fig. 4, the horizontal belt conveyor operation monitoring system based on data analysis is implemented based on the above horizontal belt conveyor operation monitoring method based on data analysis, and specifically includes a data acquisition module, a driving operation anomaly evaluation module, a belt conveyor life prediction module, and a comparison and early warning module, where the data acquisition module is configured to acquire driving operation data and belt operation data of the horizontal belt conveyor in the operation process, and simultaneously acquire transport mineral condition data in the operation process, the driving operation anomaly evaluation module is configured to introduce the driving operation data of the horizontal belt conveyor into the driving operation anomaly evaluation model for driving operation anomaly evaluation, the belt operation anomaly evaluation module is configured to introduce the acquired belt operation data into the belt anomaly evaluation model for belt operation anomaly evaluation, and the belt conveyor life prediction module is configured to introduce the operation anomaly evaluation result, the belt operation anomaly evaluation result, and the transport mineral condition data into a belt conveyor life policy for life comparison and early warning according to the obtained belt conveyor life prediction result, and further includes a control module configured to control the data acquisition module, the driving operation anomaly evaluation module, the belt operation anomaly evaluation module, and the comparison and early warning module.
The system can execute the method in any of the foregoing embodiments and achieve the same or similar technical effects, and will not be described herein.
Example 3. The embodiment provides an electronic device, which comprises a processor, and optionally an internal bus, a network interface and a memory at a hardware level. The memory may include a memory such as a high-speed Random access memory (Random-AccessMemory, RAM), and may further include a nonvolatile memory (non-volatilememory), such as at least 1 disk memory, etc. Of course, the electronic device may also include hardware required for other services.
The processor, network interface, and memory may be interconnected by an internal bus, which may be an ISA (IndustryStandardArchitecture ) bus, a PCI (PeripheralComponentInterconnect, peripheral component interconnect standard) bus, or EISA (ExtendedIndustryStandardArchitecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc.
The electronic device can generate larger difference due to different configurations or performances, and can comprise one or more processors and one or more memories, wherein at least one computer program is stored in the memories, and the computer program is loaded and executed by the processors to realize the horizontal belt conveyor operation monitoring method based on data analysis provided by the method embodiment. The electronic device can also include other components for implementing the functions of the device, for example, the electronic device can also have wired or wireless network interfaces, input-output interfaces, and the like, for inputting and outputting data. The present embodiment is not described herein.
Example 4. The present embodiment proposes a computer-readable storage medium having stored thereon an erasable computer program;
When the computer program runs on the computer equipment, the computer equipment is caused to execute the horizontal belt conveyor running monitoring method based on the data analysis.
For example, the computer readable storage medium can be read-only memory, random-access memory, read-only optical disks, magnetic tape, floppy disk, optical data storage device, etc.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions in accordance with embodiments of the present application are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by way of wired or/and wireless networks from one website site, computer, server, or data center to another. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices, such as servers, data centers, etc. that contain one or more collections of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
The above description is only illustrative of the preferred embodiments of the present application and of the principles of the technology employed. It will be appreciated by persons skilled in the art that the scope of the application is not limited to the specific combinations of the features described above, but also covers other embodiments which may be formed by any combination of the features described above or their equivalents without departing from the spirit of the application. Such as the above-mentioned features and the technical features having similar functions (but not limited to) applied for in the present application are replaced with each other.