Motor self-adaptive adjusting method and device for electric toothbrushTechnical Field
The invention relates to the technical field of electric toothbrushes, in particular to a motor self-adaptive adjusting method and device of an electric toothbrush.
Background
Electric toothbrushes are a common oral care implement that are simple to operate and have a significant oral cleaning effect and have begun to be widely used by people. The electric toothbrush is characterized in that the brush head generates high-frequency vibration through the rapid rotation or vibration of the motor core, and the cleaning of the inside of the tooth cavity is realized by utilizing vibration or the generated vibration of the brush head relative to the tooth cavity. However, the phenomenon that the motor working mode of the existing electric toothbrush is single and basically the same as that of the electric toothbrush on the current market is difficult to generate personalized motor working modes and tooth brushing modes for different users according to different users, and the motor working modes are difficult to adaptively adjust in the working process.
The existing electric toothbrush has the following defects:
in the patent document CN112526875A, mainly through the disclosed motor self-adaptive adjusting device, the motor is self-adaptively adjusted before leaving the factory to obtain the optimal working frequency point of the motor, and the problems of how to generate a personalized motor working mode for a user and dynamically adjust the motor operation parameters in real time in the use process of the electric toothbrush are not considered;
in patent document CN117243717a, the working mode of the motor is mainly selected by the pressure applied to the brush head during brushing, and the problem that the brush head working mode is not matched with the user requirement due to long-term fixation of the parameter range corresponding to the working mode is not considered;
in patent document CN112515801B, the vibration force output by the motor is mainly adjusted by the pressing time, and the problem of how to adaptively adjust the operation parameters of the motor according to the brushing route and brushing time is not considered;
In patent document CN110840605A, the user selects the brushing mode and the motor operation mode mainly by pressing a key, and the problem of how to predict and recommend the brushing mode and the motor operation mode and dynamically update the prediction model is not considered.
Disclosure of Invention
The invention aims to provide a motor self-adaptive adjusting method and device of an electric toothbrush, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the invention provides a motor self-adaptive adjusting method of an electric toothbrush, comprising the following steps:
S1, collecting user tooth brushing historical data and motor operation parameters corresponding to the historical tooth brushing data, and introducing a self-adaptive learning algorithm based on the historical data and the motor operation parameters to generate a user tooth brushing preference model and a corresponding motor operation mode;
S2, predicting the operation mode of the motor when the electric toothbrush is to be used at the present time according to the tooth brushing preference model, and optimizing the operation parameter range of the motor corresponding to the operation mode of the motor when the electric toothbrush is to be used at the present time according to the tooth oral cavity state acquired before the use of the electric toothbrush at the present time;
s3, collecting real-time tooth brushing data in the using process of the electric toothbrush, and calculating corresponding real-time motor operation parameters according to the real-time tooth brushing data;
S4, comparing the real-time motor operation parameters with the motor operation parameter ranges corresponding to the operation modes of the motor to be used at the time to obtain comparison results, feeding back the comparison results, adjusting PWM signals of the motor, and adjusting the real-time motor operation parameters;
the step S3 is also to analyze the tooth brushing actions according to the real-time tooth brushing data;
And S4, adjusting the running parameters of the motor in real time according to the PWM signal of the motor for adjusting the tooth brushing action, and adjusting the tooth brushing action for prompting.
Preferably, in the step S1, the user brushing history data includes a brushing head swinging amplitude, a brushing head posture, a brushing pressure, a brushing duration and a brushing time point during brushing, the motor operation parameters corresponding to the brushing history data include a motor rotation speed, an output power and a motor output vibration amplitude, a user brushing preference model is constructed based on a learning algorithm, different brushing modes are generated according to the brushing preference model, the brushing modes correspond to the motor operation modes, and an initial parameter range of the motor operation parameters is set in the motor operation modes.
Preferably, the adaptive learning algorithm comprises an online random forest and/or deep learning algorithm based on incremental learning.
Preferably, the predicting the operation mode of the motor when the electric toothbrush is to be used in S2 specifically includes:
s21, recommending a plurality of groups of brushing modes corresponding to the brushing time point according to the brushing time point, and predicting the brushing mode and motor operation parameters corresponding to the brushing mode according to the recent brushing preference model:
S22, collecting tooth oral cavity state data of a user before the electric toothbrush is used, wherein the tooth oral cavity state data comprise tooth surface states and gum states, and generating a tooth oral cavity model diagram according to the tooth oral cavity state data;
S22, fine-tuning the predicted initial parameter range of the motor operation parameter corresponding to the tooth brushing mode according to the tooth oral cavity state data, and setting the actual parameter range of the motor operation parameter corresponding to the tooth brushing mode and the standard brush head residence time in the tooth brushing process.
Preferably, the step S3 specifically includes:
s31, cleaning the tooth and the oral cavity according to the tooth brushing mode predicted in the S2;
S32, acquiring real-time tooth brushing data through a sensor module in the cleaning process, wherein the real-time tooth brushing data comprise tooth brushing area I, tooth brushing pressure data P, tooth brushing sound wave data S and tooth brushing actions, and the tooth brushing actions comprise tooth brushing head inclination angle data theta, tooth brushing head acceleration data A, tooth brushing head moving state and tooth brushing head residence time;
Wherein the method comprises the steps ofAnd (2) andIs the surface of the tooth and is provided with a plurality of teeth,Is the gingival area;
S33, calculating real-time motor operation parameters according to the real-time tooth brushing data, wherein a calculation formula of the real-time motor rotating speed n is as follows: wherein、、、The weight of brushing pressure data P, brushing sound wave data S, brushing head inclination angle data theta and brushing head acceleration data A in a real-time motor rotating speed calculation formula are respectively calculated;
The calculation formula of the output power w of the real-time motor is as follows: wherein、、、The weight of brushing pressure data P, brushing sound wave data S, brushing head inclination angle data theta and brushing head acceleration data A in a real-time motor output power calculation formula are respectively calculated;
Real-time motor output vibration amplitudeThe calculation formula of (2) is as follows: wherein、、、The weight of the brush head acceleration data A in the real-time motor output vibration amplitude calculation formula is respectively calculated for the brush tooth pressure data P, the brush tooth sound wave data S, the brush head inclination angle data theta.
Preferably, the S4 specifically includes:
s41, comparing the real-time motor operation parameters calculated in the S3 with the actual parameter ranges of the motor operation parameters corresponding to the tooth brushing mode, and obtaining a comparison result;
S42, when the comparison result is that the calculated real-time motor operation parameter exceeds the actual parameter range of the motor operation parameter, PWM signals of the motor are adjusted, and the real-time motor operation parameter of the motor is dynamically adjusted.
Preferably, the step S2 further includes generating a dental model diagram of the tooth surface according to the tooth surface state data, wherein the dental model diagram is used for displaying a region to be brushed, a tooth gap distribution state and a tartar distribution state, and dividing the region to be brushed into a key cleaning region and a general cleaning region according to the tartar distribution state;
And S3, analyzing brushing actions according to the real-time brushing data, wherein the method specifically comprises the steps of determining the position of a brush head and generating a brush head moving path diagram according to the brush head acceleration data A and the brush head moving state data, inputting the brush head moving path diagram into a tooth oral cavity model diagram, analyzing whether the brush head moving path diagram covers a complete area to be brushed, automatically increasing real-time operation parameters of a motor according to the position of the brush head and the distribution state of the area to be brushed, analyzing whether the corresponding brush head residence time in different actual data to be brushed accords with the predicted standard brush head residence time in the current brushing mode according to the brush head moving state data and the brush head residence time, adjusting PWM signals of the motor when the actual brush head residence time in the same area exceeds the standard brush head residence time, controlling the motor to stop running, dynamically adjusting the running state of the motor, and carrying out feedback prompt on a user when the actual brush head residence time in the same area is lower than the standard brush head residence time.
Preferably, the real-time tooth brushing data further comprises self temperature data in the motor operation process and battery power data for power supply of the motor in the battery operation process, and the real-time operation parameters of the motor are dynamically adjusted according to the self temperature data in the motor operation process and the battery power data for power supply of the motor in the battery operation process.
The motor self-adaptive adjusting device of the electric toothbrush comprises a motor module, a motor control module and a motor control module, wherein the motor module is used for driving a brush head of the electric toothbrush to realize the current brushing mode;
the sensor module is used for acquiring historical brushing data and real-time brushing data of a user;
The learning module is used for generating a user brushing preference model and a corresponding motor operation mode according to the user brushing historical data and motor operation parameters corresponding to the historical brushing data, and optimizing a motor operation parameter range corresponding to the motor operation mode when the user brushing preference model is to be used;
the control module is used for predicting a tooth brushing mode according to the tooth brushing preference model, generating a tooth oral model diagram, calculating real-time motor operation parameters according to real-time tooth brushing data, and dynamically adjusting motor real-time camera operation parameters according to the calculated real-time motor operation parameters;
and the feedback module is used for carrying out feedback prompt on the user.
Preferably, the sensor module comprises a miniature camera and/or an infrared sensor, a pressure sensor, an angular velocity sensor, a gyroscope and a sound wave sensor which are arranged in the brush head, and a timer, a temperature sensor and a current sensor which are arranged in the handle.
Compared with the prior art, the invention has the beneficial effects that:
1. According to the invention, the function of predicting the current brushing mode and the initial range of the corresponding motor operation parameters according to the brushing preference model is realized by collecting historical data to generate the brushing preference model, the current brushing action is performed according to the recommended brushing mode, the personalized brushing mode for the user is generated, various real-time brushing data are obtained in the current brushing process, the real-time motor operation parameters under the multi-factor condition are calculated according to the data, the real-time motor operation parameters and the motor operation parameter range are compared and analyzed, the real-time operation parameters of the current motor are dynamically adjusted according to the analysis result, and the brush head is driven to perform the brushing action according to the adjusted motor operation parameters, so that the phenomenon that the predicted cleaning effect is difficult to realize or the phenomenon that teeth or gums are damaged due to excessive cleaning is avoided.
2. According to the invention, the tooth oral cavity state data is collected before the tooth brushing action, the tooth surface state and the gum state are judged, and the initial parameter range of motor operation corresponding to the tooth brushing mode is adjusted according to the tooth oral cavity state data, so that the cleaning effect of the electric toothbrush is improved to a certain extent.
3. According to the tooth and mouth model image generating method, the tooth and mouth model image is generated according to the tooth and mouth state data, the area to be brushed is divided into multiple areas, the actual parameter ranges of the motor operation parameters of the corresponding areas are set for the different areas, the motor operation parameters corresponding to the tooth brushing modes are further adjusted, the cleaning requirements of different parts are met, and excessive cleaning of weak parts of the mouth is avoided.
4. According to the invention, by generating the brush head moving path diagram, comparing the brush head moving path diagram with the tooth oral cavity model diagram, analyzing whether the brush head moving path diagram covers a complete area to be brushed, analyzing whether all areas in the oral cavity are cleaned, analyzing whether the brushing action accords with a predicted brushing mode by combining the brush head moving path diagram, the standard brush head residence time and the actual brush head residence time, adjusting output parameters of the motor according to an analysis result, realizing the purpose of self-adaptive adjustment of the motor, and being beneficial to improving the normalization and the effectiveness of the brushing action.
5. According to the invention, the learning module is arranged, and the tooth brushing historical data and the motor operation parameters acquired in the tooth brushing process are input into the existing tooth brushing preference model again according to the tooth brushing data and the motor operation parameters acquired in the tooth brushing process, so that the tooth brushing preference model is dynamically adjusted, and the accuracy of the tooth brushing preference model and the instantaneity of the motor operation parameters are improved.
Drawings
FIG. 1 is a flow chart of the overall method of the present invention;
Fig. 2 is a flow chart of S3 and S4 of the present invention.
Detailed Description
The following description of the embodiments of the present invention 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 invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be noted that the terms "provided," "connected," and the like should be construed broadly, unless otherwise explicitly specified and defined, and that the specific meaning of the terms in the present invention may be understood by those of ordinary skill in the art in light of the specific circumstances.
Referring to fig. 1, the motor self-adaptive adjustment method of the electric toothbrush comprises the steps of collecting user brushing history data and motor operation parameters corresponding to the historical brushing data, introducing a self-adaptive learning algorithm based on the historical data and the motor operation parameters, generating a user brushing preference model and a corresponding motor operation mode, wherein the user brushing history data comprises a brushing head swinging amplitude, a brushing head posture, brushing pressure, brushing duration and brushing time point during brushing, the brushing history can be obtained through a sensor module arranged in the brushing head and the brush handle, or the electric toothbrush is in wireless connection with a mobile phone APP, the historical data is set through the mobile phone APP, the motor operation parameters corresponding to the brushing history data comprise a motor rotating speed, an output power and a motor output vibration amplitude, constructing a user preference model based on a learning algorithm, generating different brushing preference models according to the brushing preference model, and setting an initial parameter range of the motor operation parameters in the motor operation mode corresponding to the motor operation mode.
Further, a personalized brushing preference model for the user is generated according to the user brushing history data and the motor operation parameters corresponding to the history brushing data, for example, a morning brushing preference model and an evening brushing preference model are generated according to brushing time points, a plurality of different brushing modes exist in different brushing preference models, the diversity of the brushing modes is improved, the initial parameter range of the different motor operation modes and the motor operation parameters corresponding to the different brushing modes is convenient for improving the brushing effect and the comfort, the user brushing preference model is generated through the self-adaptive learning algorithm, the brushing history data and the motor operation parameters acquired in the process are input into the existing brushing preference model again after each brushing action is finished, and the brushing preference model is dynamically adjusted, so that the accuracy of the brushing preference model is improved.
Referring to fig. 1, an embodiment of the invention provides a motor adaptive adjustment method of an electric toothbrush, which comprises predicting an operation mode of a motor when the electric toothbrush is to be used according to a brushing preference model, and optimizing a motor operation parameter range corresponding to the operation mode of the motor when the electric toothbrush is to be used according to a tooth oral state obtained before the electric toothbrush is used;
Recommending a plurality of groups of brushing modes corresponding to the brushing time point according to the brushing time point, and predicting the brushing mode and motor operation parameters corresponding to the brushing mode according to the recent brushing preference model, wherein the predicted motor operation parameters corresponding to the brushing mode are in an initial parameter range:
collecting tooth oral cavity state data of a user before the electric toothbrush is used, wherein the tooth oral cavity state data comprise tooth surface states and gum states, a tooth oral cavity model diagram is generated according to the tooth oral cavity state data, and the tooth oral cavity state data are obtained through a micro camera and/or an infrared sensor in a sensor module;
And fine-tuning the predicted initial parameter range of the motor operation parameter corresponding to the tooth brushing mode according to the tooth oral cavity state data, and setting the actual parameter range of the motor operation parameter corresponding to the tooth brushing mode and the standard brush head residence time in the tooth brushing process.
Further, the initial parameter ranges of the current brushing mode and the motor operation parameters are predicted and recommended from a plurality of groups of brushing modes through the brushing preference model, and the accuracy and the instantaneity of the prediction of the current brushing mode are improved as the brushing preference model is dynamically adjusted according to the brushing history data and the corresponding history motor operation parameters;
Before the tooth brushing action is performed by adopting the predicted tooth brushing mode, collecting the tooth oral cavity state data, analyzing the tartar state of the tooth surface and/or analyzing whether residual dirt residues exist on the tooth surface and in the tooth gaps and/or the current state of the gingiva, adjusting the initial parameter range of the motor operation parameters corresponding to the predicted tooth brushing mode according to the currently collected tooth oral cavity state data, for example, increasing the initial parameters in the initial parameter range of the motor operation parameters when the tartar state of the tooth surface deepens and/or residues in the tooth and the tooth gaps are more, and reducing the two end values in the initial parameter range of the motor operation parameters when the gingiva is damaged, and improving the cleaning effect of the electric toothbrush to a certain extent by fine adjusting the initial parameter range of the motor operation parameters.
Referring to fig. 1 and 2, the invention provides an embodiment of a motor self-adaptive adjustment method of an electric toothbrush, which comprises collecting real-time brushing data during the use of the electric toothbrush, and calculating corresponding real-time motor operation parameters according to the real-time brushing data;
specifically, the method comprises cleaning teeth and oral cavity according to predicted brushing mode;
acquiring real-time tooth brushing data through a sensor module in the cleaning process, wherein the real-time tooth brushing data comprise tooth brushing area I, tooth brushing pressure data P, tooth brushing sound wave data S and tooth brushing actions, and the tooth brushing actions comprise tooth brushing head inclination angle data theta, tooth brushing head acceleration data A, tooth brushing head moving state and tooth brushing head residence time;
Wherein the method comprises the steps ofAnd (2) andIs the surface of the tooth and is provided with a plurality of teeth,The actual parameter ranges of the motor operation parameters corresponding to different tooth brushing areas are different for the gum areas;
Calculating real-time motor operation parameters according to the real-time tooth brushing data, wherein a calculation formula of the real-time motor rotating speed n is as follows: wherein、、
、The weight of brushing pressure data P, brushing sound wave data S, brushing head inclination angle data theta and brushing head acceleration data A in a real-time motor rotating speed calculation formula are respectively calculated;
The calculation formula of the output power w of the real-time motor is as follows: wherein、、、The weight of brushing pressure data P, brushing sound wave data S, brushing head inclination angle data theta and brushing head acceleration data A in a real-time motor output power calculation formula are respectively calculated;
Real-time motor output vibration amplitudeThe calculation formula of (2) is as follows: wherein、、、The weight of the brush head acceleration data A in the real-time motor output vibration amplitude calculation formula is respectively calculated for the brush tooth pressure data P, the brush tooth sound wave data S, the brush head inclination angle data theta.
Further, through the sensor module, including pressure sensor, angular velocity sensor, gyroscope and sonic sensor, acquire real-time data of brushing teeth, calculate real-time motor operating parameter jointly through multiple data, be favorable to improving the accuracy that motor real-time operating parameter calculated, and then improve the accuracy of actual parameter scope contrast analysis result among motor real-time parameter and the motor operating parameter, be convenient for carry out the self-adaptation to the real-time operating parameter under the current state of toothbrush according to the analysis result.
Referring to fig. 1 and 2, the invention provides an embodiment of a motor self-adaptive adjustment method of an electric toothbrush, which comprises the steps of comparing a real-time motor operation parameter with a motor operation parameter range corresponding to an operation mode of a motor to be used at this time to obtain a comparison result, feeding back according to the comparison result, adjusting a PWM signal of the motor, and adjusting the real-time motor operation parameter;
Comparing the calculated real-time motor operation parameters with the actual parameter ranges of the motor operation parameters corresponding to the tooth brushing mode, and obtaining a comparison result;
and when the comparison result is that the calculated real-time motor operation parameter exceeds the actual parameter range of the motor operation parameter, adjusting the PWM signal of the motor, and dynamically adjusting the real-time motor operation parameter of the motor.
Further, a comparison result is obtained by comparing the real-time motor operation parameters with the actual parameter ranges, the real-time motor operation parameters in the current state are adjusted according to the comparison result, and the brush head is driven to brush teeth according to the adjusted motor operation parameters, so that the phenomenon that the predicted cleaning effect is difficult to realize or teeth or gum is damaged due to excessive cleaning is avoided.
Referring to fig. 1 and 2, in a method for adaptively adjusting a motor of an electric toothbrush, a tooth-oral model diagram is specifically included in the tooth-oral model diagram, wherein the tooth-oral model diagram is used for generating a tooth-oral model diagram related to a tooth surface according to tooth surface state data, and is used for displaying a region to be brushed, a tooth gap distribution state and a tartar distribution state, dividing the region to be brushed into a key cleaning region and a general cleaning region according to the tartar distribution state, and the actual parameter ranges of the motor corresponding to the different regions are different;
The method comprises the steps of determining the position of a brush head and generating a brush head moving path diagram according to brush head acceleration data A and brush head moving state data, inputting the brush head moving path diagram into a tooth oral cavity model diagram, analyzing whether the brush head moving path diagram covers a complete area to be brushed, automatically increasing real-time operation parameters of a motor according to the position of the brush head and the distribution state of the area to be brushed, analyzing whether the brush head residence time in corresponding actual data in different areas to be brushed accords with the predicted standard brush head residence time set in the current brushing mode according to the brush head moving state data and the brush head residence time, adjusting PWM signals of the motor when the actual brush head residence time in the same area exceeds the standard brush head residence time, controlling the motor to stop running, dynamically adjusting the running state of the motor, and carrying out feedback prompt on a user when the actual brush head residence time in the same area is lower than the standard brush head residence time.
Further, generating a tooth oral model graph according to tooth oral state data, dividing a to-be-brushed area into multiple areas, setting actual parameter ranges of motor operation parameters of corresponding areas according to different areas, for example, improving two end values of the actual parameter ranges at teeth and tooth gaps, reducing two end values of the actual parameter ranges corresponding to gum areas, further adjusting the motor operation parameters corresponding to tooth brushing modes, ensuring that the cleaning requirements of different parts are met, and avoiding excessive cleaning of weak parts of the oral cavity;
Judging whether all areas in the oral cavity are cleaned by analyzing whether the brush head moving path diagram covers a complete area to be brushed, and prompting the brushing action through a feedback module, such as a sound prompting device and a light prompting device when uncleaned parts exist in the area to be brushed, prompting that the area to be cleaned still exists in the oral cavity, and keeping the running state of a motor;
The method comprises the steps of comparing and analyzing the residence time of a brush head in each group of areas in the tooth brushing process, prompting a user through voice when the residence time of the brush head in actual data is smaller than the residence time of a standard brush head in the corresponding same group of areas, stopping outputting by a motor when the brush head moves to another area, prompting the user to move the brush head to an area with the residence time which does not reach the standard, continuing to clean the tooth oral cavity of the area, prompting the user to move the brush head when the residence time of the brush head in the actual data reaches the residence time of the standard brush head in the corresponding same group of areas, adjusting PWM signals of the motor, controlling the motor to stop operating, controlling the motor to resume operating when the brush head reaches the new area through the movement of the brush head position detected by an acceleration sensor and a gyroscope, and enabling the motor to operate according to the motor operating parameters corresponding to a predicted tooth brushing mode, ensuring that the tooth oral cavity is not a cleaning area when the electric toothbrush performs tooth brushing action, and avoiding the phenomenon of incomplete cleaning or excessive cleaning.
Referring to fig. 1 and 2, in an embodiment of the present invention, a motor adaptive adjustment method for an electric toothbrush is provided, where real-time brushing data further includes self temperature data during motor operation and battery power data for power supply of a motor during battery operation, and real-time motor operation parameters are dynamically adjusted according to self temperature data during motor operation and battery power data for power supply of the motor during battery operation.
Further, after the current motor real-time operation parameters are dynamically adjusted according to the calculated real-time motor operation parameters, the motor driving brush head operates according to the adjusted motor operation parameters, in the motor operation process, the motor operation temperature is detected through the sensor module, namely the temperature sensor, when the motor operation temperature is too high, the motor operation parameters are reduced, the motor driving brush head comprises motor output power and motor output rotating speed, the battery power for driving the motor is detected through the current sensor, when the battery power is low, the motor output power and the motor output rotating speed are reduced in a self-adaptive mode, so that the battery power supply duration is prolonged, the operation duration of the motor in a brushing area is prolonged, and the stay duration of the brush head is further prolonged, so that the brushing effect is ensured.
The method comprises the steps of firstly collecting user tooth brushing historical data and motor operation parameters corresponding to the historical tooth brushing data, introducing a self-adaptive learning algorithm based on the historical data and the motor operation parameters, generating a user tooth brushing preference model and a corresponding motor operation mode, secondly predicting the operation mode of a motor when the electric toothbrush is to be used according to the tooth brushing preference model, optimizing a threshold value corresponding to the operation mode of the motor when the electric toothbrush is to be used according to the tooth oral cavity state acquired before the electric toothbrush is used, then collecting real-time tooth brushing data in the use process of the electric toothbrush, calculating the corresponding real-time motor operation parameters according to the real-time tooth brushing data, comparing the real-time motor operation parameters with the threshold value corresponding to the operation mode of the motor when the electric toothbrush is to be used to obtain a comparison result, feeding back according to the comparison result, adjusting PWM signals of the motor, and adjusting the real-time motor operation parameters.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.