CN115508658B - Method and device for automatic polarization analysis of piezoelectric ceramics - Google Patents
Method and device for automatic polarization analysis of piezoelectric ceramics Download PDFInfo
- Publication number
- CN115508658B CN115508658B CN202211451653.2A CN202211451653A CN115508658B CN 115508658 B CN115508658 B CN 115508658B CN 202211451653 A CN202211451653 A CN 202211451653A CN 115508658 B CN115508658 B CN 115508658B
- Authority
- CN
- China
- Prior art keywords
- polarization
- preset
- parameter
- ultrasonic frequency
- sample
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Investigating Or Analyzing Materials By The Use Of Ultrasonic Waves (AREA)
Abstract
The invention discloses a method and a device for automatic polarization analysis of piezoelectric ceramics, which relate to the field of data processing, wherein the method comprises the following steps: testing the target piezoelectric ceramic by adopting a preset alternating voltage to obtain test frequency information; judging whether the test frequency information conforms to the preset ultrasonic frequency; if so, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain performance parameters of the target piezoelectric ceramics; obtaining polarization parameter adjustment amplitude information according to the performance parameters; obtaining a preset polarization parameter; and adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters. The technical problem of poor polarization effect for piezoelectric ceramics in the prior art is solved. The technical effects of improving the polarization effect of the piezoelectric ceramic and the like are achieved.
Description
Technical Field
The invention relates to the field of data processing, in particular to a method and a device for automatic polarization analysis of piezoelectric ceramics.
Background
Piezoelectric ceramics are widely applied to the fields of electronics, aerospace and the like with excellent piezoelectric performance. Along with the wide application of piezoelectric ceramics, people put higher level requirements on the piezoelectric performance of the piezoelectric ceramics, and the piezoelectric ceramics have the piezoelectric performance after polarization. How to polarize piezoelectric ceramics with high quality so as to make piezoelectric ceramics have more excellent piezoelectric performance is receiving wide attention.
In the prior art, the polarization analysis accuracy of the piezoelectric ceramics is insufficient, the comprehensiveness is not high, and the polarization effect of the piezoelectric ceramics is poor.
Disclosure of Invention
The application provides a method and a device for automatic polarization analysis of piezoelectric ceramics. The polarization analysis method solves the technical problems that in the prior art, the polarization analysis accuracy for piezoelectric ceramics is not enough, the comprehensiveness is not high, and the polarization effect of the piezoelectric ceramics is not good.
In view of the above problems, the present application provides a method and an apparatus for automatic polarization analysis of piezoelectric ceramics.
In a first aspect, the present application provides a method for automatic polarization analysis of piezoelectric ceramics, wherein the method is applied to an apparatus for automatic polarization analysis of piezoelectric ceramics, and the method includes: acquiring a preset alternating voltage and a preset ultrasonic frequency; testing the target piezoelectric ceramic by adopting a preset alternating voltage, and acquiring the ultrasonic frequency of the target piezoelectric ceramic under the preset alternating voltage to obtain test frequency information; judging whether the test frequency information conforms to the preset ultrasonic frequency; if so, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain performance parameters of the target piezoelectric ceramics; obtaining polarization parameter adjustment amplitude information according to the performance parameters, wherein the polarization parameter adjustment amplitude information comprises polarization time adjustment amplitude information and polarization temperature adjustment amplitude information; obtaining preset polarization parameters, wherein the preset polarization parameters comprise a preset polarization time parameter and a preset polarization temperature parameter; and adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters.
In a second aspect, the present application further provides an apparatus for automatic polarization analysis of piezoelectric ceramics, wherein the apparatus comprises: the ultrasonic diagnosis device comprises an information acquisition module, a data acquisition module and a control module, wherein the information acquisition module is used for acquiring a preset alternating voltage and a preset ultrasonic frequency; the test module is used for testing the target piezoelectric ceramic by adopting a preset alternating voltage, and acquiring the ultrasonic frequency of the target piezoelectric ceramic under the preset alternating voltage to obtain test frequency information; the frequency judging module is used for judging whether the test frequency information conforms to the preset ultrasonic frequency; a judgment result execution module, configured to continue to use the target piezoelectric ceramic if the judgment result execution module is yes, and analyze and obtain the performance parameter of the target piezoelectric ceramic if the judgment result execution module is not yes; an adjustment amplitude information obtaining module, configured to obtain polarization parameter adjustment amplitude information according to the performance parameter, where the polarization parameter adjustment amplitude information includes polarization time adjustment amplitude information and polarization temperature adjustment amplitude information; the device comprises a preset polarization parameter obtaining module, a polarization parameter obtaining module and a polarization parameter judging module, wherein the preset polarization parameter obtaining module is used for obtaining a preset polarization parameter, and the preset polarization parameter comprises a preset polarization time parameter and a preset polarization temperature parameter; and the polarization module is used for adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
testing the target piezoelectric ceramic by preset alternating voltage to obtain test frequency information; judging whether the test frequency information conforms to the preset ultrasonic frequency; if so, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain the performance parameters of the target piezoelectric ceramics; obtaining polarization parameter adjustment amplitude information according to the performance parameters; and adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain the optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters. The polarization analysis accuracy and comprehensiveness of the piezoelectric ceramics are improved, the polarization effect of the piezoelectric ceramics is improved, and the technical effects of the intelligence and the automation degree of the polarization of the piezoelectric ceramics are improved.
Drawings
FIG. 1 is a schematic flow chart of a method for automatic polarization analysis of piezoelectric ceramics according to the present application;
FIG. 2 is a schematic flow chart illustrating the process of obtaining polarization parameter adjustment amplitude information in an automatic polarization analysis method for piezoelectric ceramics according to the present application;
fig. 3 is a schematic structural diagram of an apparatus for automatic polarization analysis of piezoelectric ceramics according to the present application.
Description of reference numerals: the device comprises an information acquisition module 11, a test module 12, a frequency judgment module 13, a judgment result execution module 14, an adjustment amplitude information acquisition module 15, a preset polarization parameter acquisition module 16 and a polarization module 17.
Detailed Description
The application provides a method and a device for automatic polarization analysis of piezoelectric ceramics. The technical problems that in the prior art, the polarization analysis accuracy of piezoelectric ceramics is not enough, the comprehensiveness is not high, and the polarization effect of the piezoelectric ceramics is not good are solved. The polarization analysis accuracy and comprehensiveness of the piezoelectric ceramics are improved, the polarization effect of the piezoelectric ceramics is improved, and the technical effects of the intelligence and the automation degree of the polarization of the piezoelectric ceramics are improved.
Example one
Referring to fig. 1, the present application provides a method for automatic polarization analysis of piezoelectric ceramics, wherein the method is applied to an apparatus for automatic polarization analysis of piezoelectric ceramics, and the method specifically includes the following steps:
step S100: acquiring a preset alternating voltage and a preset ultrasonic frequency;
step S200: testing the target piezoelectric ceramic by adopting a preset alternating voltage, and acquiring the ultrasonic frequency of the target piezoelectric ceramic under the preset alternating voltage to obtain test frequency information;
specifically, a preset alternating voltage and a preset ultrasonic frequency are determined, the target piezoelectric ceramic is tested according to the preset alternating voltage, the ultrasonic frequency of the target piezoelectric ceramic under the preset alternating voltage is collected, and test frequency information is obtained. The preset alternating voltage and the preset ultrasonic frequency comprise self-adaptive setting determination alternating voltage and ultrasonic frequency. Exemplarily, the ultrasonic frequency with the largest number of times of use in the historical time of the ultrasonic instrument where the target piezoelectric ceramic is located is used as the preset ultrasonic frequency, and the alternating voltage applied to the target piezoelectric ceramic corresponding to the preset ultrasonic frequency is used as the preset alternating voltage. The target piezoelectric ceramics comprise any piezoelectric ceramics which are subjected to intelligent polarization analysis by using the piezoelectric ceramics automatic polarization analysis device. The test frequency information includes an ultrasonic frequency of the target piezoelectric ceramic at a preset alternating voltage in practice. The technical effects that the target piezoelectric ceramic is tested through the preset alternating voltage, the test frequency information is obtained, and a foundation is laid for the subsequent performance parameter analysis of the target piezoelectric ceramic are achieved.
Step S300: judging whether the test frequency information conforms to the preset ultrasonic frequency;
further, step S300 of the present application further includes:
step S310: the preset alternating voltage is adopted to test the standard target piezoelectric ceramics for multiple times, and test frequency information of a plurality of samples is obtained;
step S320: obtaining compensation parameters according to the test frequency information of the samples and the preset ultrasonic frequency;
step S330: compensating the preset ultrasonic frequency by adopting the compensation parameters to obtain a preset ultrasonic frequency range;
step S340: and judging whether the test frequency information falls into the preset ultrasonic frequency range.
Specifically, a standard target piezoelectric ceramic is tested for multiple times according to a preset alternating voltage, and test frequency information of multiple samples is obtained. Further, frequency statistics is carried out on the multiple sample testing frequency information, sample testing frequency information corresponding to each same sample testing frequency in the multiple sample testing frequency information is determined, the multiple sample testing frequency information is obtained, median selection is carried out on the multiple sample testing frequency information, median sample testing frequency information is determined, and the multiple sample testing frequency information which is not smaller than the median sample testing frequency information is set to be the multiple sample testing frequency information. And matching the test frequency information of the plurality of samples according to the high-frequency information of the test frequency of the plurality of samples to obtain the test frequency information of the plurality of high-frequency samples. And calculating the difference value between the test frequency information of the high-frequency samples and the preset ultrasonic frequency to obtain a compensation parameter. And further, compensating and summing the preset ultrasonic frequency according to the compensation parameters to obtain a preset ultrasonic frequency range. And judging whether the test frequency information falls into a preset ultrasonic frequency range. The plurality of sample test frequency information comprise a plurality of test frequency information of the standard target piezoelectric ceramics, which are obtained by testing the standard target piezoelectric ceramics for a plurality of times according to preset alternating voltage. The standard target piezoelectric ceramics include piezoelectric ceramics of the same type as the target piezoelectric ceramics which have just been shipped. The compensation parameters comprise a plurality of difference information between a plurality of high-frequency sample test frequency information and a preset ultrasonic frequency in a plurality of sample test frequency information. The preset ultrasonic frequency range includes a plurality of summation calculation results between the compensation parameter and the preset ultrasonic frequency. The technical effects that the preset ultrasonic frequency is compensated through the compensation parameters, the preset ultrasonic frequency range is obtained, whether the test frequency information falls into the preset ultrasonic frequency range or not is judged, and the accuracy of polarization analysis on the piezoelectric ceramic is improved are achieved.
Step S400: if yes, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain performance parameters of the target piezoelectric ceramics;
further, step S400 of the present application further includes:
step S410: calculating to obtain an ultrasonic frequency difference value according to the preset ultrasonic frequency and the test frequency information;
specifically, when it is determined whether the test frequency information falls within the preset ultrasonic frequency range, if the test frequency information falls within the preset ultrasonic frequency range, the use of the target piezoelectric ceramic is continued. And if the test frequency information does not fall into the preset ultrasonic frequency range, performing difference calculation based on the preset ultrasonic frequency and the test frequency information to obtain an ultrasonic frequency difference. Wherein the ultrasonic frequency difference includes difference information between a preset ultrasonic frequency and test frequency information. The technical effects that when the test frequency information does not fall into the preset ultrasonic frequency range, the difference value calculation is carried out on the preset ultrasonic frequency and the test frequency information to obtain the ultrasonic frequency difference value, and data support is provided for the subsequent performance parameter analysis of the target piezoelectric ceramic are achieved.
Step S420: constructing a performance parameter analysis model;
further, step S420 of the present application further includes:
step S421: testing a plurality of target piezoelectric ceramics in different using states by adopting the preset alternating voltage, and calculating by combining the preset ultrasonic frequency to obtain a plurality of sample ultrasonic frequency difference values;
step S422: performing piezoelectric ceramic performance evaluation according to the ultrasonic frequency difference values of the samples to obtain a plurality of sample performance parameters;
step S423: randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values as a first division threshold value, and constructing a primary division node of the performance parameter analysis model;
step S424: randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values again to serve as a second division threshold value, and constructing a secondary division node of the performance parameter analysis model;
step S425: continuously constructing multi-level division nodes of the performance parameter analysis model;
step S426: obtaining a plurality of final division results according to the multistage division nodes;
step S427: and marking the final division results by adopting the sample performance parameters to obtain the constructed performance parameter analysis model.
Step S430: and inputting the ultrasonic frequency difference value into the performance parameter analysis model to obtain the performance parameter.
Specifically, a plurality of target piezoelectric ceramics in different use states are tested according to preset alternating voltage to obtain a plurality of ultrasonic frequency test result information, and difference calculation is performed by combining preset ultrasonic frequency to obtain a plurality of sample ultrasonic frequency differences. And further, performing performance evaluation on a plurality of target piezoelectric ceramics in different using states based on a plurality of sample ultrasonic frequency difference values to obtain a plurality of sample performance parameters. The ultrasonic frequency test result information comprises a plurality of pieces of test frequency information corresponding to a plurality of target piezoelectric ceramics in different use states, which are tested according to preset alternating voltage. The plurality of sample ultrasonic frequency difference values include a plurality of difference value information between a plurality of ultrasonic frequency test result information and a preset ultrasonic frequency. The plurality of target piezoelectric ceramics for different usage states includes a plurality of target piezoelectric ceramics for different usage years. The plurality of sample performance parameters include piezoelectric properties corresponding to a plurality of target piezoelectric ceramics in different use states. The larger the ultrasonic frequency difference of the sample is, the poorer the corresponding piezoelectric performance is.
Further, randomly selecting the ultrasonic frequency difference values of the multiple samples to obtain a first division threshold value, and setting the first division threshold value as a primary division node of the performance parameter analysis model. And randomly selecting the ultrasonic frequency difference values of the multiple samples again to obtain a second division threshold value, and setting the second division threshold value as a secondary division node of the performance parameter analysis model. And by parity of reasoning, randomly selecting and setting division nodes of the ultrasonic frequency difference values of the samples, so that multistage division nodes of the performance parameter analysis model are constructed, and a plurality of final division results are obtained. And marking the final division results according to the performance parameters of the samples to obtain a constructed performance parameter analysis model. And then, the ultrasonic frequency difference value is used as input information and is input into the performance parameter analysis model to obtain performance parameters. The first division threshold is any sample ultrasonic frequency difference value in a plurality of sample ultrasonic frequency difference values. The primary partition node includes a first partition threshold. The second division threshold includes any sample ultrasonic frequency difference value different from the first division threshold within the plurality of sample ultrasonic frequency difference values. The secondary partition node includes a second partition threshold. The multi-level division nodes comprise a plurality of division nodes such as first-level division nodes and second-level division nodes. The final division results comprise a first division threshold value, a second division threshold value and other division threshold values. The performance parameter analysis model comprises a plurality of sample performance parameters, a plurality of final division results and a corresponding relation between the plurality of sample performance parameters and the plurality of final division results. The performance parameters comprise piezoelectric performance corresponding to the ultrasonic frequency difference. The technical effects of performing performance analysis on the target piezoelectric ceramic through the performance parameter analysis model, obtaining reliable performance parameters, and improving the comprehensiveness of polarization analysis of the piezoelectric ceramic so as to improve the accuracy of polarization of the target piezoelectric ceramic are achieved.
Step S500: obtaining polarization parameter adjustment amplitude information according to the performance parameters, wherein the polarization parameter adjustment amplitude information comprises polarization time adjustment amplitude information and polarization temperature adjustment amplitude information;
further, as shown in fig. 2, step S500 of the present application further includes:
step S510: obtaining a plurality of sample polarization parameter adjustment amplitude information;
step S520: constructing a mapping relation between the polarization parameter adjustment amplitude information of the multiple samples and the performance parameters of the multiple samples;
step S530: and inputting the performance parameters into the mapping relation for traversing to obtain the polarization parameter adjustment amplitude information.
Specifically, historical polarization parameter adjustment amplitude information is acquired based on a plurality of sample performance parameters, the adjustment amplitude information of the plurality of sample polarization parameters is obtained, and a mapping relation is obtained by analyzing a corresponding relation in combination with the plurality of sample performance parameters. And further, inputting the performance parameters into a mapping relation to perform traversal matching analysis to obtain polarization parameter adjustment amplitude information. The polarization parameter adjustment amplitude information of the multiple samples comprises multiple historical polarization parameter adjustment amplitude information corresponding to the multiple sample performance parameters, wherein the worse the performance of the target piezoelectric ceramic corresponding to the sample performance parameters is, the larger the corresponding historical plan parameter adjustment amplitude information is, so that the polarization parameter adjustment optimization is rapidly performed, the proper polarization parameter is obtained, the piezoelectric ceramic is polarized, otherwise, the smaller the corresponding historical plan parameter adjustment amplitude information is, the polarization parameter adjustment optimization is accurately performed with a small amplitude, the proper polarization parameter is obtained, and the piezoelectric ceramic is polarized. The plurality of pieces of historical polarization parameter adjustment amplitude information include a plurality of pieces of historical polarization time adjustment amplitude information and a plurality of pieces of historical polarization temperature adjustment amplitude information, which are used for performing polarization parameter adjustment on a plurality of pieces of target piezoelectric ceramics in different use states. For example, the plurality of historical polarization temperature adjustment magnitude information includes a polarization temperature adjustment degree of 4 degrees celsius. The mapping relationship includes a correspondence between the plurality of sample polarization parameter adjustment amplitude information and the plurality of sample performance parameters. The polarization parameter adjustment amplitude information includes polarization time adjustment amplitude information and polarization temperature adjustment amplitude information of the target piezoelectric ceramics corresponding to the performance parameters for polarization parameter adjustment. The technical effects that the performance parameters are subjected to matching analysis through the mapping relation, the polarization parameter adjustment amplitude information with high adaptation degree is obtained, and the subsequent accuracy of adjusting and optimizing the preset polarization parameters is improved are achieved.
Step S600: obtaining preset polarization parameters, wherein the preset polarization parameters comprise a preset polarization time parameter and a preset polarization temperature parameter;
step S700: and adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters.
Further, step S700 of the present application further includes:
step S710: taking the preset polarization parameter as a first polarization parameter and a current optimization result to obtain a first polarization score of the first polarization parameter;
further, step S710 of the present application further includes:
step S711: obtaining a plurality of sample polarization parameters;
step S712: polarizing a plurality of piezoelectric ceramics which are the same as the target piezoelectric ceramics by adopting the plurality of sample polarization parameters to obtain a plurality of sample piezoelectric ceramics;
step S713: testing the sample piezoelectric ceramics to obtain test frequency information of the samples;
step S714: calculating to obtain a plurality of sample polarization scores according to the plurality of sample testing frequency information and the preset ultrasonic frequency;
step S715: constructing a polarization score analysis model based on the BP neural network;
step S716: performing data identification on the plurality of sample polarization parameters and the plurality of sample polarization scores to obtain a constructed data set;
step S717: performing iterative supervision training and verification on the polarization score analysis model by adopting the constructed data set until the accuracy of the polarization score analysis model meets the preset requirement, and obtaining the constructed polarization score analysis model;
step S718: and inputting the first polarization parameter into the polarization score analysis model to obtain the first polarization score.
Specifically, the preset polarization parameter is set as the first polarization parameter, and the first polarization parameter is used as the current optimization result, that is, the first polarization parameter is used as the current optimal polarization parameter. The preset polarization parameters comprise a preset polarization time parameter and a preset polarization temperature parameter. The preset polarization time parameter comprises a preset and determined polarization time length parameter. The preset polarization temperature parameter comprises a preset and determined polarization temperature parameter. The preset polarization time parameter and the preset polarization temperature parameter can be determined through big data query self-adaptive setting. The first polarization parameter is a preset polarization parameter.
Further, a plurality of piezoelectric ceramics with the same target piezoelectric ceramics are polarized according to a plurality of sample polarization parameters, and a plurality of sample piezoelectric ceramics are obtained. And testing the piezoelectric ceramics of the multiple samples according to the preset alternating voltage to obtain the testing frequency information of the multiple samples. And performing scoring calculation based on the test frequency information of the samples and the preset ultrasonic frequency to obtain a plurality of sample polarization scores. Wherein each sample polarization parameter of the plurality of sample polarization parameters comprises a sample polarization time parameter and a sample polarization temperature parameter. The plurality of sample polarization parameters may be obtained by large data acquisition. The plurality of sample piezoelectric ceramics include a plurality of piezoelectric ceramics that are the same as the target piezoelectric ceramics after polarization by a plurality of sample polarization parameters. The plurality of sample test frequency information includes a plurality of ultrasonic frequencies of the plurality of sample piezoelectric ceramics under a preset alternating voltage. The plurality of sample polarization scores may be used to characterize the polarization effect of a plurality of sample polarization parameters. The smaller the difference between the sample testing frequency information and the preset ultrasonic frequency is, the higher the polarization effect of the sample polarization parameter corresponding to the sample testing frequency information is, and the higher the sample polarization score corresponding to the sample testing frequency information is.
And further, carrying out data division and identification on the plurality of sample polarization parameters and the plurality of sample polarization scores to obtain a constructed data set. The constructed data set comprises a sample polarization parameter training set, a sample polarization scoring training set, a sample polarization parameter testing set and a sample polarization scoring testing set. And then, based on the BP neural network, carrying out iterative supervision training on the sample polarization parameter training set to obtain a polarization score analysis model. And when the accuracy of the polarization score analysis model meets the preset requirement, namely the similarity between the output information corresponding to the sample polarization parameter training set and the sample polarization score training set meets the preset requirement, finishing the iterative supervision training. And then, inputting the sample polarization parameter test set as input information into the polarization score analysis model, and verifying the polarization score analysis model. And when the accuracy of the polarization scoring analysis model meets the preset requirement, namely the similarity between the output information corresponding to the sample polarization parameter test set and the sample polarization scoring test set meets the preset requirement, obtaining the sample polarization scoring test set with the accuracy meeting the preset requirement. And then, the first polarization parameter is used as input information and is input into the polarization score analysis model to obtain a first polarization score. Wherein the BP neural network is a multi-layer feedforward neural network trained according to an error back propagation algorithm. The BP neural network comprises an input layer, a plurality of layers of neurons and an output layer. The accuracy rate comprises the similarity degree between the output information corresponding to the sample polarization parameter training set and the sample polarization scoring training set, and the similarity degree between the output information corresponding to the sample polarization parameter testing set and the sample polarization scoring testing set. The preset requirements comprise a preset accuracy threshold value, and can be determined according to the accuracy requirement self-adaptive setting of the polarization score analysis model. The polarization scoring analysis model is an intelligent polarization scoring model which has accuracy meeting preset requirements and meets the BP neural network. The first polarization score may be used to characterize the polarization effect of the first polarization parameter. The higher the first polarization score, the better the polarization effect of the first polarization parameter. The technical effects that the polarization scoring analysis model with accuracy meeting preset requirements, high precision and good generalization performance is obtained by performing iterative supervision training and verification on the constructed data set, the first polarization parameter is accurately and efficiently evaluated through the polarization scoring analysis model, the reliable first polarization score is obtained, the polarization analysis accuracy of the piezoelectric ceramic is improved, and the adaptability and the accuracy of polarization on the target piezoelectric ceramic are improved are achieved.
Step S720: obtaining a plurality of polarization parameter adjusting modes according to the polarization parameter adjusting amplitude information;
step S730: adjusting the first polarization parameter by adopting a plurality of polarization parameter adjusting modes to construct and obtain a first neighborhood, wherein the first neighborhood comprises a plurality of adjusted polarization parameters;
step S740: obtaining a plurality of adjusted polarization scores for the plurality of adjusted polarization parameters;
step S750: obtaining a maximum value in the plurality of adjusted polarization scores as a second adjusted polarization score, obtaining a corresponding second polarization parameter as a current optimization result, and adding a polarization parameter adjusting mode for adjusting the obtained second polarization parameter into a tabu table;
step S760: continuing to construct a second neighborhood of the second polarization parameter, continuing optimizing iteration, and deleting the polarization parameter adjusting mode for adjusting the second polarization parameter from the taboo table after the iteration times reach a preset taboo iteration time;
step S770: and when the optimization iteration reaches the preset iteration times, outputting the final current optimization result to obtain the optimal polarization parameter.
Specifically, a plurality of polarization parameter adjustment modes are determined based on the polarization parameter adjustment amplitude information. The plurality of polarization parameter adjustment modes comprise a plurality of specific polarization time adjustment parameters and a plurality of specific polarization temperature adjustment parameters. For example, the polarization parameter adjustment amplitude information includes a degree of polarization temperature adjustment of 3 degrees celsius. Then, the plurality of polarization parameter adjustment manners include increasing the polarization temperature by 1 degree celsius, decreasing by 2 degrees celsius, increasing by 2 degrees celsius, and the like.
Further, a plurality of polarization parameter adjustment modes are randomly selected from the plurality of polarization parameter adjustment modes to adjust the first polarization parameter, and a first neighborhood is obtained. The first neighbourhood comprises a plurality of adjusted polarisation parameters. The plurality of polarization parameter adjustment methods include adjusting a first polarization parameter according to a plurality of polarization parameter adjustment methods to obtain a plurality of adjusted polarization parameters. Then, the plurality of adjusted polarization parameters are used as input information and input into a polarization score analysis model to obtain a plurality of adjusted polarization scores. And screening the maximum values of the plurality of adjusted polarization scores to obtain a second adjusted polarization score, and matching the plurality of adjusted polarization parameters according to the second adjusted polarization score to obtain a second polarization parameter. And setting the second polarization parameter as the current optimization result, namely taking the second polarization parameter as the current optimal polarization parameter. And adding a polarization parameter adjusting mode corresponding to the second polarization parameter to the tabu table, and performing subsequent neighborhood construction and optimization iteration without using the polarization parameter adjusting mode in the tabu table. Furthermore, a second neighborhood is constructed based on the first neighborhood and the tabu table, and the second neighborhood and the first neighborhood are obtained in the same manner, and are not repeated herein for the simplicity of the specification. And then, optimizing iteration is carried out based on the second neighborhood, when the iteration times reach the preset taboo iteration times, the polarization parameter adjusting mode for adjusting to obtain the second polarization parameter is deleted from the taboo table, after the iteration times reach the preset iteration times, the final current optimizing result is output to obtain the optimal polarization parameter, and the target piezoelectric ceramic is polarized according to the optimal polarization parameter. Wherein the second adjusted polarization score comprises a maximum of a plurality of adjusted polarization scores. The second polarization parameter includes an adjusted polarization parameter corresponding to the second adjusted polarization score among the plurality of adjusted polarization parameters. The tabu table comprises a polarization parameter adjusting mode corresponding to the second polarization parameter. The preset iteration times comprise a preset determined optimizing iteration time threshold value. The optimal polarization parameter comprises a current optimization result when the iteration number reaches a preset iteration number. The optimization iteration of the preset iteration times is carried out on the first polarization parameter according to a plurality of polarization parameter adjusting modes, the optimal polarization parameter with high precision and strong adaptability is obtained, and the technical effect of improving the accuracy of polarization of the target piezoelectric ceramic is achieved.
In summary, the method for automatic polarization analysis of piezoelectric ceramics provided by the present application has the following technical effects:
1. testing the target piezoelectric ceramic by preset alternating voltage to obtain test frequency information; judging whether the test frequency information conforms to the preset ultrasonic frequency; if so, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain the performance parameters of the target piezoelectric ceramics; obtaining polarization parameter adjustment amplitude information according to the performance parameters; and adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain the optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters. The polarization analysis accuracy and comprehensiveness of the piezoelectric ceramics are improved, the polarization effect of the piezoelectric ceramics is improved, and the technical effects of the intelligent and automatic polarization degree of the piezoelectric ceramics are improved.
2. And performing performance analysis on the target piezoelectric ceramic through the performance parameter analysis model to obtain reliable performance parameters, and improving the comprehensiveness of polarization analysis of the piezoelectric ceramic, so that the accuracy of polarization of the target piezoelectric ceramic is improved.
3. Iterative supervision training and verification are carried out on the constructed data set, a polarization scoring analysis model with accuracy meeting preset requirements and good high-precision generalization performance is obtained, the first polarization parameter is accurately and efficiently evaluated through the polarization scoring analysis model, a reliable first polarization score is obtained, polarization analysis accuracy of the piezoelectric ceramic is improved, and adaptability and accuracy of polarization of the target piezoelectric ceramic are improved.
Example two
Based on the method for piezoelectric ceramic automatic polarization analysis in the foregoing embodiment, the same inventive concept is also provided, and the present invention further provides an apparatus for piezoelectric ceramic automatic polarization analysis, referring to fig. 3, the apparatus includes:
the ultrasonic diagnosis device comprises an information acquisition module 11, wherein the information acquisition module 11 is used for acquiring a preset alternating voltage and a preset ultrasonic frequency;
the test module 12 is configured to test the target piezoelectric ceramic by using a preset alternating voltage, and acquire an ultrasonic frequency of the target piezoelectric ceramic under the preset alternating voltage to obtain test frequency information;
the frequency judging module 13 is configured to judge whether the test frequency information all conforms to the preset ultrasonic frequency;
a judgment result execution module 14, where the judgment result execution module 14 is configured to continue to use the target piezoelectric ceramic if the judgment result is positive, and analyze to obtain a performance parameter of the target piezoelectric ceramic if the judgment result is negative;
an adjustment amplitude information obtaining module 15, where the adjustment amplitude information obtaining module 15 is configured to obtain polarization parameter adjustment amplitude information according to the performance parameter, where the polarization parameter adjustment amplitude information includes polarization time adjustment amplitude information and polarization temperature adjustment amplitude information;
a preset polarization parameter obtaining module 16, where the preset polarization parameter obtaining module 16 is configured to obtain a preset polarization parameter, where the preset polarization parameter includes a preset polarization time parameter and a preset polarization temperature parameter;
and the polarization module 17 is configured to adjust and optimize the preset polarization parameter by using the polarization parameter adjustment amplitude information to obtain an optimal polarization parameter, and polarize the target piezoelectric ceramic by using the optimal polarization parameter.
Further, the apparatus further comprises:
the sample test frequency information acquisition module is used for carrying out multiple tests on the standard target piezoelectric ceramic by adopting the preset alternating voltage to acquire a plurality of sample test frequency information;
a compensation parameter obtaining module, configured to obtain a compensation parameter according to the multiple sample test frequency information and the preset ultrasonic frequency;
the preset ultrasonic frequency range obtaining module is used for compensating the preset ultrasonic frequency by adopting the compensation parameters to obtain a preset ultrasonic frequency range;
and the frequency range judging module is used for judging whether the test frequency information falls into the preset ultrasonic frequency range.
Further, the apparatus further comprises:
the ultrasonic frequency difference value calculating module is used for calculating to obtain an ultrasonic frequency difference value according to the preset ultrasonic frequency and the test frequency information;
a model construction module for constructing a performance parameter analysis model;
and the performance parameter obtaining module is used for inputting the ultrasonic frequency difference value into the performance parameter analysis model to obtain the performance parameters.
Further, the apparatus further comprises:
the system comprises a plurality of sample ultrasonic frequency difference obtaining modules, a plurality of sample ultrasonic frequency difference obtaining module and a plurality of ultrasonic frequency difference obtaining module, wherein the sample ultrasonic frequency difference obtaining modules are used for testing a plurality of target piezoelectric ceramics in different using states by adopting the preset alternating voltage and obtaining a plurality of sample ultrasonic frequency differences by combining the preset ultrasonic frequency calculation;
the system comprises a plurality of sample performance parameter obtaining modules, a plurality of sampling module and a plurality of sampling module, wherein the sample performance parameter obtaining modules are used for evaluating the performance of the piezoelectric ceramics according to the ultrasonic frequency difference values of the samples to obtain a plurality of sample performance parameters;
the primary division node construction module is used for randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values as a first division threshold value and constructing a primary division node of the performance parameter analysis model;
the secondary division node construction module is used for randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values again to serve as a second division threshold value, and constructing a secondary division node of the performance parameter analysis model;
the multi-level division node construction module is used for continuously constructing the multi-level division nodes of the performance parameter analysis model;
a plurality of final division result obtaining modules, configured to obtain a plurality of final division results according to the multi-level division node;
and the marking module is used for marking the final division results by adopting the sample performance parameters to obtain the constructed performance parameter analysis model.
Further, the apparatus further comprises:
the device comprises a sample adjustment amplitude information acquisition module, a data processing module and a data processing module, wherein the sample adjustment amplitude information acquisition module is used for acquiring a plurality of pieces of sample polarization parameter adjustment amplitude information;
the mapping relation construction module is used for constructing the mapping relation between the polarization parameter adjustment amplitude information of the multiple samples and the performance parameters of the multiple samples;
and the polarization parameter adjustment amplitude information determining module is used for inputting the performance parameters into the mapping relation for traversal to obtain the polarization parameter adjustment amplitude information.
Further, the apparatus further comprises:
the first polarization score acquisition module is used for taking the preset polarization parameter as a first polarization parameter and taking the preset polarization parameter as a current optimization result to acquire a first polarization score of the first polarization parameter;
the polarization parameter adjustment mode determining modules are used for obtaining a plurality of polarization parameter adjustment modes according to the polarization parameter adjustment amplitude information;
the first neighborhood construction module is used for adjusting the first polarization parameter by adopting a plurality of polarization parameter adjustment modes to construct and obtain a first neighborhood, and the first neighborhood comprises a plurality of adjustment polarization parameters;
a plurality of adjusted polarization score acquisition modules for acquiring a plurality of adjusted polarization scores for the plurality of adjusted polarization parameters;
a second polarization parameter determining module, configured to obtain a maximum value of the multiple adjusted polarization scores, use the maximum value as a second adjusted polarization score, obtain a corresponding second polarization parameter, use the second polarization parameter as a current optimization result, and add a polarization parameter adjustment mode for adjusting the obtained second polarization parameter into a taboo table;
the optimizing iteration module is used for continuously constructing a second neighborhood of the second polarization parameter, continuously optimizing iteration, and deleting the polarization parameter adjusting mode for adjusting the second polarization parameter from the tabu table after the iteration times reach the preset tabu iteration times;
and the optimal polarization parameter determining module is used for outputting a final current optimization result after the optimization iteration reaches a preset iteration number, so as to obtain the optimal polarization parameter.
Further, the apparatus further comprises:
a plurality of sample polarization parameter determination modules for obtaining a plurality of sample polarization parameters;
a plurality of sample piezoelectric ceramic obtaining modules, configured to polarize a plurality of piezoelectric ceramics that are the same as the target piezoelectric ceramic using the plurality of sample polarization parameters, to obtain a plurality of sample piezoelectric ceramics;
the system comprises a plurality of sample testing frequency information obtaining modules, a plurality of sampling frequency information obtaining module and a plurality of sampling frequency information acquiring module, wherein the plurality of sample testing frequency information obtaining modules are used for testing a plurality of sample piezoelectric ceramics to obtain a plurality of sample testing frequency information;
the sample polarization score obtaining modules are used for calculating and obtaining a plurality of sample polarization scores according to the sample testing frequency information and the preset ultrasonic frequency;
the polarization score analysis model building module is used for building a polarization score analysis model based on a BP neural network;
a constructed data set obtaining module, configured to perform data identification on the plurality of sample polarization parameters and the plurality of sample polarization scores to obtain a constructed data set;
the execution module is used for carrying out iterative supervision training and verification on the polarization score analysis model by adopting the constructed data set until the accuracy of the polarization score analysis model meets the preset requirement, and obtaining the constructed polarization score analysis model;
a first polarization score determining module, configured to input the first polarization parameter into the polarization score analysis model, and obtain the first polarization score.
The application provides a method for piezoelectric ceramic automatic polarization analysis, wherein the method is applied to a piezoelectric ceramic automatic polarization analysis device, and the method comprises the following steps: testing the target piezoelectric ceramic by preset alternating voltage to obtain test frequency information; judging whether the test frequency information conforms to the preset ultrasonic frequency; if so, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain the performance parameters of the target piezoelectric ceramics; obtaining polarization parameter adjustment amplitude information according to the performance parameters; and adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain the optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters. The technical problems that in the prior art, the polarization analysis accuracy of piezoelectric ceramics is not enough, the comprehensiveness is not high, and the polarization effect of the piezoelectric ceramics is not good are solved. The polarization analysis accuracy and comprehensiveness of the piezoelectric ceramics are improved, the polarization effect of the piezoelectric ceramics is improved, and the technical effects of the intelligence and the automation degree of the polarization of the piezoelectric ceramics are improved.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The specification and drawings are merely illustrative of the present application, and it is intended that the present invention cover modifications and variations of this invention provided they come within the scope of the invention and their equivalents.
Claims (6)
1. A method for automated polarization analysis of piezoelectric ceramics, the method comprising:
acquiring a preset alternating voltage and a preset ultrasonic frequency;
testing the target piezoelectric ceramic by adopting a preset alternating voltage, and acquiring the ultrasonic frequency of the target piezoelectric ceramic under the preset alternating voltage to obtain test frequency information;
judging whether the test frequency information conforms to the preset ultrasonic frequency;
if so, continuing to use the target piezoelectric ceramics, and if not, analyzing to obtain performance parameters of the target piezoelectric ceramics;
obtaining polarization parameter adjustment amplitude information according to the performance parameters, wherein the polarization parameter adjustment amplitude information comprises polarization time adjustment amplitude information and polarization temperature adjustment amplitude information;
obtaining preset polarization parameters, wherein the preset polarization parameters comprise a preset polarization time parameter and a preset polarization temperature parameter;
adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters;
analyzing and obtaining the performance parameters of the target piezoelectric ceramic, wherein the performance parameters comprise:
calculating to obtain an ultrasonic frequency difference value according to the preset ultrasonic frequency and the test frequency information;
constructing a performance parameter analysis model;
inputting the ultrasonic frequency difference into the performance parameter analysis model to obtain the performance parameters;
constructing a performance parameter analysis model, comprising:
testing a plurality of target piezoelectric ceramics in different using states by adopting the preset alternating voltage, and calculating by combining the preset ultrasonic frequency to obtain a plurality of sample ultrasonic frequency difference values;
performing piezoelectric ceramic performance evaluation according to the ultrasonic frequency difference values of the samples to obtain a plurality of sample performance parameters;
randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values as a first division threshold value, and constructing a primary division node of the performance parameter analysis model;
randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values again to serve as a second division threshold value, and constructing a secondary division node of the performance parameter analysis model;
continuously constructing multi-level division nodes of the performance parameter analysis model;
obtaining a plurality of final division results according to the multistage division nodes;
and marking the final division results by adopting the sample performance parameters to obtain the constructed performance parameter analysis model.
2. The method of claim 1, wherein determining whether the test frequency information conforms to the predetermined ultrasonic frequency comprises:
adopting the preset alternating voltage to test the standard target piezoelectric ceramic for multiple times to obtain test frequency information of multiple samples;
obtaining compensation parameters according to the test frequency information of the samples and the preset ultrasonic frequency;
compensating the preset ultrasonic frequency by adopting the compensation parameters to obtain a preset ultrasonic frequency range;
and judging whether the test frequency information falls into the preset ultrasonic frequency range.
3. The method of claim 1, wherein obtaining polarization parameter adjustment magnitude information based on the performance parameter comprises:
obtaining a plurality of sample polarization parameter adjustment amplitude information;
constructing a mapping relation between the polarization parameter adjustment amplitude information of the multiple samples and the performance parameters of the multiple samples;
and inputting the performance parameters into the mapping relation for traversing to obtain the polarization parameter adjustment amplitude information.
4. The method of claim 1, wherein adjusting and optimizing the preset polarization parameter using the polarization parameter adjustment magnitude information comprises:
taking the preset polarization parameter as a first polarization parameter and a current optimization result to obtain a first polarization score of the first polarization parameter;
obtaining a plurality of polarization parameter adjusting modes according to the polarization parameter adjusting amplitude information;
adjusting the first polarization parameter by adopting a plurality of polarization parameter adjusting modes to construct and obtain a first neighborhood, wherein the first neighborhood comprises a plurality of adjusted polarization parameters;
obtaining a plurality of adjusted polarization scores for the plurality of adjusted polarization parameters;
obtaining a maximum value in the plurality of adjusted polarization scores as a second adjusted polarization score, obtaining a corresponding second polarization parameter as a current optimization result, and adding a polarization parameter adjusting mode for adjusting the obtained second polarization parameter into a tabu table;
continuing to construct a second neighborhood of the second polarization parameter, continuing optimization iteration, and deleting the polarization parameter adjusting mode for adjusting the second polarization parameter from the tabu table after the iteration number reaches a preset tabu iteration number;
and when the optimization iteration reaches the preset iteration times, outputting the final current optimization result to obtain the optimal polarization parameter.
5. The method of claim 4, wherein obtaining a first polarization score for the first polarization parameter comprises:
obtaining a plurality of sample polarization parameters;
polarizing a plurality of piezoelectric ceramics which are the same as the target piezoelectric ceramics by adopting the plurality of sample polarization parameters to obtain a plurality of sample piezoelectric ceramics;
testing the sample piezoelectric ceramics to obtain test frequency information of the samples;
calculating to obtain a plurality of sample polarization scores according to the plurality of sample testing frequency information and the preset ultrasonic frequency;
constructing a polarization score analysis model based on the BP neural network;
performing data identification on the plurality of sample polarization parameters and the plurality of sample polarization scores to obtain a constructed data set;
performing iterative supervision training and verification on the polarization score analysis model by adopting the constructed data set until the accuracy of the polarization score analysis model meets the preset requirement, and obtaining the constructed polarization score analysis model;
and inputting the first polarization parameter into the polarization score analysis model to obtain the first polarization score.
6. An apparatus for automated polarization analysis of piezoelectric ceramics, the apparatus comprising:
the ultrasonic transducer comprises an information acquisition module, a data acquisition module and a data processing module, wherein the information acquisition module is used for acquiring a preset alternating voltage and a preset ultrasonic frequency;
the test module is used for testing the target piezoelectric ceramics by adopting a preset alternating voltage, and acquiring the ultrasonic frequency of the target piezoelectric ceramics under the preset alternating voltage to obtain test frequency information;
the frequency judging module is used for judging whether the test frequency information conforms to the preset ultrasonic frequency;
the judgment result execution module is used for continuing using the target piezoelectric ceramics if the judgment result execution module is used, and analyzing and obtaining the performance parameters of the target piezoelectric ceramics if the judgment result execution module is not used;
an adjustment amplitude information obtaining module, configured to obtain polarization parameter adjustment amplitude information according to the performance parameter, where the polarization parameter adjustment amplitude information includes polarization time adjustment amplitude information and polarization temperature adjustment amplitude information;
the device comprises a preset polarization parameter obtaining module, a polarization parameter obtaining module and a polarization parameter judging module, wherein the preset polarization parameter obtaining module is used for obtaining a preset polarization parameter, and the preset polarization parameter comprises a preset polarization time parameter and a preset polarization temperature parameter;
the polarization module is used for adjusting and optimizing the preset polarization parameters by adopting the polarization parameter adjustment amplitude information to obtain optimal polarization parameters, and polarizing the target piezoelectric ceramics by adopting the optimal polarization parameters;
wherein, the module for analyzing and obtaining the performance parameters of the target piezoelectric ceramics comprises:
the ultrasonic frequency difference value calculating module is used for calculating to obtain an ultrasonic frequency difference value according to the preset ultrasonic frequency and the test frequency information;
a model construction module for constructing a performance parameter analysis model;
a performance parameter obtaining module, configured to input the ultrasonic frequency difference into the performance parameter analysis model to obtain the performance parameter;
wherein the model building module comprises:
the system comprises a plurality of sample ultrasonic frequency difference obtaining modules, a plurality of sample ultrasonic frequency difference obtaining module and a plurality of ultrasonic frequency difference obtaining module, wherein the sample ultrasonic frequency difference obtaining modules are used for testing a plurality of target piezoelectric ceramics in different using states by adopting the preset alternating voltage and obtaining a plurality of sample ultrasonic frequency differences by combining the preset ultrasonic frequency calculation;
the system comprises a plurality of sample performance parameter obtaining modules, a plurality of sampling module and a plurality of sampling module, wherein the sample performance parameter obtaining modules are used for evaluating the performance of the piezoelectric ceramics according to the ultrasonic frequency difference values of the samples to obtain a plurality of sample performance parameters;
the primary division node construction module is used for randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values as a first division threshold value and constructing a primary division node of the performance parameter analysis model;
the secondary division node construction module is used for randomly selecting a sample ultrasonic frequency difference value from the plurality of sample ultrasonic frequency difference values again to serve as a second division threshold value, and constructing a secondary division node of the performance parameter analysis model;
the multi-level division node construction module is used for continuously constructing the multi-level division nodes of the performance parameter analysis model;
a plurality of final division result obtaining modules, configured to obtain a plurality of final division results according to the multi-level division node;
and the marking module is used for marking the final division results by adopting the sample performance parameters to obtain the constructed performance parameter analysis model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211451653.2A CN115508658B (en) | 2022-11-21 | 2022-11-21 | Method and device for automatic polarization analysis of piezoelectric ceramics |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211451653.2A CN115508658B (en) | 2022-11-21 | 2022-11-21 | Method and device for automatic polarization analysis of piezoelectric ceramics |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115508658A CN115508658A (en) | 2022-12-23 |
| CN115508658B true CN115508658B (en) | 2023-03-14 |
Family
ID=84513729
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211451653.2A Active CN115508658B (en) | 2022-11-21 | 2022-11-21 | Method and device for automatic polarization analysis of piezoelectric ceramics |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115508658B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06315196A (en) * | 1993-04-28 | 1994-11-08 | Sumitomo Metal Ind Ltd | Characteristic control method for piezoelectric body |
| JPH09102722A (en) * | 1995-10-05 | 1997-04-15 | Murata Mfg Co Ltd | Polarization control method of piezoelectric resonator and device therefor |
| JP2001127356A (en) * | 1999-08-13 | 2001-05-11 | Murata Mfg Co Ltd | Polarization processing method of piezoelectric material |
| CN1362748A (en) * | 2000-12-26 | 2002-08-07 | 株式会社村田制作所 | Piezoelectric element polarization method |
| JP2002319720A (en) * | 2001-04-20 | 2002-10-31 | Murata Mfg Co Ltd | Method for controlling temperature characteristic of piezoelectric ceramic |
| US6521166B1 (en) * | 1999-08-13 | 2003-02-18 | Murata Manufacturing Co., Ltd. | Method of polarization-treating piezoelectric body |
| CN104391185A (en) * | 2014-11-27 | 2015-03-04 | 上海电机学院 | Piezoelectric ceramic parameter consistency online monitoring device |
| CN105655479A (en) * | 2015-12-30 | 2016-06-08 | 中国科学院上海硅酸盐研究所 | Polarization aging treatment method for obtaining large strain effect in piezoceramics |
-
2022
- 2022-11-21 CN CN202211451653.2A patent/CN115508658B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH06315196A (en) * | 1993-04-28 | 1994-11-08 | Sumitomo Metal Ind Ltd | Characteristic control method for piezoelectric body |
| JPH09102722A (en) * | 1995-10-05 | 1997-04-15 | Murata Mfg Co Ltd | Polarization control method of piezoelectric resonator and device therefor |
| JP2001127356A (en) * | 1999-08-13 | 2001-05-11 | Murata Mfg Co Ltd | Polarization processing method of piezoelectric material |
| US6521166B1 (en) * | 1999-08-13 | 2003-02-18 | Murata Manufacturing Co., Ltd. | Method of polarization-treating piezoelectric body |
| CN1362748A (en) * | 2000-12-26 | 2002-08-07 | 株式会社村田制作所 | Piezoelectric element polarization method |
| JP2002319720A (en) * | 2001-04-20 | 2002-10-31 | Murata Mfg Co Ltd | Method for controlling temperature characteristic of piezoelectric ceramic |
| CN104391185A (en) * | 2014-11-27 | 2015-03-04 | 上海电机学院 | Piezoelectric ceramic parameter consistency online monitoring device |
| CN105655479A (en) * | 2015-12-30 | 2016-06-08 | 中国科学院上海硅酸盐研究所 | Polarization aging treatment method for obtaining large strain effect in piezoceramics |
Non-Patent Citations (1)
| Title |
|---|
| (1-x)NBT-xBaTiO_3系陶瓷材料制备过程中极化条件的研究;余靖华;《陶瓷》;20070425(第04期);第25、26、35页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115508658A (en) | 2022-12-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11855265B2 (en) | Acoustic signal based analysis of batteries | |
| KR20200014129A (en) | Diagnosis method of electric transformer using Deep Learning | |
| CN114692677B (en) | Welding defect identification method based on multi-target feature selection | |
| CN110208702B (en) | Neural network-based lithium battery ultrasonic information characteristic extraction method | |
| CN114331238B (en) | Intelligent model algorithm optimization method, system, storage medium and computer equipment | |
| Jordovic-Pavlovic et al. | Computationally intelligent description of a photoacoustic detector | |
| CN115508658B (en) | Method and device for automatic polarization analysis of piezoelectric ceramics | |
| CN118395126A (en) | Fault diagnosis method, system and storage medium for equipment rotation state analysis | |
| CN117041847B (en) | Adaptive microphone matching method and system for hearing aid | |
| CN118041255A (en) | Signal noise reduction method and system for double-channel adjustable analog signal amplifier | |
| CN111678991B (en) | Method for nondestructive testing damage identification of concrete structure | |
| JP2022003451A (en) | Optimal solution acquisition program, optimal solution acquisition method, and information processing device | |
| CN111859241A (en) | Unsupervised sound source orientation method based on sound transfer function learning | |
| CN109063928B (en) | Transformer oil density prediction model modeling method and device | |
| Tavares et al. | Automated damage localization for lightweight plates | |
| CN113128158A (en) | Coupling coefficient identification method of wireless power transmission system | |
| CN118553344B (en) | Weak magnetic signal identification method and system for ferromagnetic material | |
| CN116851942B (en) | New energy power battery aluminum shell explosion-proof valve hole processing method and system | |
| CN118396167A (en) | Collaborative operation method and system for multi-type sweeping equipment | |
| CN118574068B (en) | Intelligent loudspeaker detection method and system | |
| Deng et al. | Intelligent Representation of Wireless Network States: A Multi-Layer Correlation Approach | |
| CN116668909A (en) | Audio conversion and tuning method for moving-coil microphone | |
| CN118746617A (en) | Piano soundboard sound vibration and point vibration characteristic test system | |
| CN118193961A (en) | Hydrophone signal receiving optimization method and system based on filtering algorithm | |
| CN118784104A (en) | Radio frequency power supply signal synchronous detection method based on real-time spectrum analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |