Performance detection and alarm device for piezoelectric ceramics in high-voltage environment

Abstract

The invention provides a piezoelectric ceramic performance detection alarm device in a high-voltage environment, relates to the technical field of ceramic performance detection, and judges whether a preset high-voltage environment characteristic condition is met or not by obtaining real-time environment monitoring information of piezoelectric ceramic, and if yes, the alarm device is started. The piezoelectric property detection alarm module, the loss characteristic detection alarm module and the mechanical property detection alarm module are activated to carry out detection alarm, so that the technical problems that comprehensive and real-time monitoring on the piezoelectric ceramic property is difficult to realize in a high-voltage environment, and an alarm is timely given out to improve the stability and reliability of the piezoelectric ceramic in case of abnormity are solved; comprehensive real-time monitoring and intelligent warning of the performance of the piezoelectric ceramic in the high-voltage environment are achieved, the use safety and maintenance efficiency of the piezoelectric ceramic under extreme conditions are effectively improved, and reliable technical guarantee is provided for stable application of the piezoelectric ceramic in the high-voltage environment.

Description

Technical Field

[0001] The present invention relates to the technical field of ceramic property detection, and particularly to a performance detection and warning device for piezoelectric ceramics under high-pressure environment. Background Art

[0002] With the progress of technology, piezoelectric ceramics have been widely used in fields such as sensors, transducers, and filters due to their unique piezoelectric effect. Especially in high-pressure environments, the performance stability and reliability of piezoelectric ceramics become key considerations. However, high-pressure environments often have a significant impact on the piezoelectric properties, loss characteristics, and mechanical properties of piezoelectric ceramics, resulting in device failure or performance degradation. Therefore, it is particularly important to develop a technical device that can monitor and warn in real time about the performance changes of piezoelectric ceramics in high-pressure environments.

[0003] Currently, there are various devices on the market for detecting the performance of piezoelectric ceramics, but most of them focus on performance evaluation under normal temperature and pressure, lacking a comprehensive monitoring and warning mechanism for the performance of piezoelectric ceramics in high-pressure environments. Although some high-end devices can simulate high-pressure environments, they often have a single detection parameter, unable to comprehensively evaluate multiple performance indicators of piezoelectric ceramics under extreme conditions, and lacking a real-time warning function, making it difficult to detect and prevent potential performance problems in a timely manner.

[0004] In summary, in the prior art, there are often technical problems that it is difficult to achieve comprehensive and real-time monitoring of the performance of piezoelectric ceramics in high-pressure environments, and to timely issue a warning when performance anomalies are detected, so as to improve the stability and reliability of piezoelectric ceramics in high-pressure applications. Summary of the Invention

[0005] The present application provides a performance detection and warning device for piezoelectric ceramics under high-pressure environment, which is used to solve the technical problems in the prior art that it is difficult to achieve comprehensive and real-time monitoring of the performance of piezoelectric ceramics in high-pressure environments, and to timely issue a warning when performance anomalies are detected, so as to improve the stability and reliability of piezoelectric ceramics in high-pressure applications.

[0006] The present application provides a performance detection and warning device for piezoelectric ceramics under high-pressure environment, and the device includes: A sensing and monitoring module, which is used to obtain real-time environmental monitoring information of a piezoelectric ceramic; a high-voltage environment characteristic judgment module, which is used to judge whether the real-time environmental monitoring information meets a predetermined high-voltage environment characteristic condition; a high-voltage environment characteristic alarm activation module, which is used to activate a piezoelectric performance detection alarm module, a loss characteristic detection alarm module, and a mechanical performance detection alarm module if the real-time environmental monitoring information meets the predetermined high-voltage environment characteristic condition; wherein, the piezoelectric performance detection alarm module performs piezoelectric performance detection and alarm on the piezoelectric ceramic based on embedded multiple piezoelectric performance detection factors and a piezoelectric performance health deviation detection channel; the loss characteristic detection alarm module performs loss characteristic detection and alarm on the piezoelectric ceramic based on embedded dual loss characteristic risk prediction channels; and the mechanical performance detection alarm module performs mechanical performance detection and alarm on the piezoelectric ceramic based on an embedded mechanical performance attenuation evaluation channel.

[0007] It is intended to propose a performance detection and alarm device for a piezoelectric ceramic under a high-voltage environment through this application. By obtaining real-time environmental monitoring information of the piezoelectric ceramic; judging whether the real-time environmental monitoring information meets a predetermined high-voltage environment characteristic condition; if the real-time environmental monitoring information meets the predetermined high-voltage environment characteristic condition, activating a piezoelectric performance detection alarm module, a loss characteristic detection alarm module, and a mechanical performance detection alarm module; wherein, the piezoelectric performance detection alarm module performs piezoelectric performance detection and alarm on the piezoelectric ceramic based on embedded multiple piezoelectric performance detection factors and a piezoelectric performance health deviation detection channel; the loss characteristic detection alarm module performs loss characteristic detection and alarm on the piezoelectric ceramic based on embedded dual loss characteristic risk prediction channels; and the mechanical performance detection alarm module performs mechanical performance detection and alarm on the piezoelectric ceramic based on an embedded mechanical performance attenuation evaluation channel, the technical problem of being difficult to comprehensively and real-time monitor the performance of the piezoelectric ceramic under a high-voltage environment and timely issue an alarm when performance anomalies are detected to improve the stability and reliability of the piezoelectric ceramic in high-voltage applications is solved. The comprehensive real-time monitoring and intelligent alarm of the piezoelectric performance, loss characteristics, and mechanical performance of the piezoelectric ceramic under a high-voltage environment are realized, the use safety and maintenance efficiency of the piezoelectric ceramic under extreme conditions are effectively improved, and reliable technical guarantee is provided for the stable application of the piezoelectric ceramic under a high-voltage environment. Description of the Drawings

[0008] Figure 1 It is a schematic structural diagram of a performance detection and alarm device for a piezoelectric ceramic under a high-voltage environment provided by an embodiment of this application.

[0009] Figure 2 It is a schematic flow diagram of a piezoelectric performance detection alarm module in a performance detection and alarm device for a piezoelectric ceramic under a high-voltage environment provided by an embodiment of this application.

[0010] Explanation of the accompanying drawings: sensor monitoring module 11, high-voltage environment characteristic judgment module 12, high-voltage environment characteristic alarm activation module 13, piezoelectric performance detection alarm module 14, loss characteristic detection alarm module 15, mechanical performance detection alarm module 16. DETAILED DESCRIPTION

[0011] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0012] The embodiment of the present application provides a performance detection and alarm device for piezoelectric ceramics under high voltage environment, such as Figure 1 As shown, the device comprises: The sensor monitoring module 11 is used to obtain real-time environmental monitoring information of the piezoelectric ceramic.

[0013] Piezoelectric ceramics are functional ceramic materials that can convert mechanical energy and electrical energy into each other. They work mainly based on the piezoelectric effect. This material is made by mixing oxides (such as zirconium oxide, lead oxide, titanium oxide, etc.), sintering at high temperature and solid-phase reaction to form polycrystalline, and then subjected to DC high-voltage polarization treatment to give it piezoelectric effect. Piezoelectric ceramics have good mechanical properties and stable piezoelectric properties. They are one of the mainstream materials in the field of functional ceramics. Due to their unique properties, they are widely used in high-tech fields such as electronics, aerospace, and biology, such as piezoelectric sensors, drivers, transducers, and filters. However, the performance of piezoelectric ceramics may change under high-voltage conditions. Through testing, the stability of the material under extreme conditions can be evaluated to ensure its reliability in applications. Therefore, it is very necessary to provide a performance detection and alarm device under high-voltage environments to ensure the safety of piezoelectric ceramics and performance prediction.

[0014] In this embodiment, the sensor monitoring module is mainly used to obtain various physical parameter information of the environment in which the piezoelectric ceramics are located in real time and accurately, and the real-time environment of the piezoelectric ceramics is monitored through the sensor monitoring module to ensure its stable operation and performance optimization. The sensor monitoring module usually includes a temperature sensor, a humidity sensor, a pressure / stress sensor, a vibration sensor, etc. The sensor monitoring module realizes comprehensive monitoring of the real-time environment of the piezoelectric ceramics by integrating a variety of sensors and data acquisition and processing units, which not only helps to discover and solve problems in a timely manner, improve the reliability and stability of the piezoelectric ceramics, but also helps to optimize its working performance and application effects.

[0015] The high-pressure environment characteristic judgment module 12 is used to judge whether the real-time environment monitoring information meets a predetermined high-pressure environment characteristic condition.

[0016] The high-voltage environment feature judgment module is a system component specifically designed to analyze and evaluate real-time environmental monitoring information to determine whether this information meets the predetermined high-voltage environment feature conditions. In fields such as electricity, industry, and scientific research, a high-voltage environment generally refers to an environment with a relatively high voltage level, which may be accompanied by characteristics such as high electric field intensity and high current density. The high-voltage environment feature judgment module receives real-time environmental monitoring data from the sensing and monitoring module, such as voltage, current, electric field intensity, temperature, humidity, etc., and processes and analyzes the collected data. Specifically, preprocessing operations such as filtering and denoising are performed on the original data transmitted by the sensing and monitoring module to improve the accuracy and reliability of the data. At the same time, data format conversion and standardization processing are carried out to ensure the comparability between different sensor data. Furthermore, characteristic parameters related to the high-voltage environment, such as voltage peak value, current density, and electric field intensity distribution, are extracted from the preprocessed data. These characteristic parameters should be able to comprehensively reflect the essential characteristics of the high-voltage environment. Next, a series of high-voltage environment feature conditions are set as judgment criteria, and these conditions may be formulated based on industry standards, safety specifications, or actual application requirements. The analyzed characteristic parameters are compared with the predetermined high-voltage environment feature conditions, and methods such as logical judgment and threshold judgment are used to determine whether the current environment meets the definition of a high-voltage environment, and then corresponding decision-making information is output according to the judgment result, such as issuing an alarm and adjusting the working state of the equipment. It should be noted that due to the complexity and diversity of the high-voltage environment, as well as the specific requirements in different application scenarios, the specific implementation methods of the high-voltage environment feature judgment module may vary. In actual applications, it can be customized and optimized according to specific situations.

[0017] The high-voltage environment feature alarm activation module 13 is used to activate the piezoelectric performance detection alarm module 14, the loss characteristic detection alarm module 15, and the mechanical performance detection alarm module 16 if the real-time environmental monitoring information meets the predetermined high-voltage environment feature conditions.

[0018] Among them, the piezoelectric performance detection alarm module 14 performs piezoelectric performance detection and alarm on the piezoelectric ceramic based on the embedded multi-element piezoelectric performance detection factor and the piezoelectric performance health deviation detection channel.

[0019] The loss characteristic detection alarm module 15 performs loss characteristic detection and alarm on the piezoelectric ceramic based on the embedded loss characteristic risk prediction dual channel.

[0020] The mechanical performance detection alarm module 16 performs mechanical performance detection and alarm on the piezoelectric ceramic based on the embedded mechanical performance attenuation evaluation channel.

[0021] The high-voltage environment characteristic alarm activation module is one of the core control units in the entire detection system. It is responsible for automatically triggering a series of performance detection alarm processes when the real-time environment monitoring information reaches the predetermined high-voltage environment characteristic conditions, so as to start the performance detection, thereby achieving the detection goal of the stability and reliability of piezoelectric ceramics in extreme environments. Specifically, when the sensing and monitoring module continuously collects and transmits the real-time data of the environment where the piezoelectric ceramic is located, the high-voltage environment characteristic judgment module will immediately analyze and compare these data. Once it is confirmed that the current environment meets or exceeds the predetermined high-voltage environment characteristic conditions (such as voltage threshold, upper limit of electric field strength, etc.), the high-voltage environment characteristic alarm activation module will be triggered, and then activate the piezoelectric performance detection alarm module, the loss characteristic detection alarm module, and the mechanical performance detection alarm module. Through the subsequent parallel operation of these three modules, a comprehensive performance evaluation and alarm of the piezoelectric ceramic will be carried out.

[0022] Among them, the piezoelectric performance detection and warning module first loads preset multiple piezoelectric performance detection factors (such as piezoelectric constant, dielectric constant, electromechanical coupling coefficient, etc.), and calibrates the piezoelectric performance health deviation detection channels to complete the initialization settings, that is, preset and calibrate its internal parameters, detection factors and detection channels before the module starts. Furthermore, the module is connected to the sensor network of the piezoelectric ceramic through the interface, and piezoelectric performance data including voltage, current, charge quantity, etc. are collected in real time. These data reflect the working state and performance of the piezoelectric ceramic under different conditions. The collected piezoelectric performance data are preprocessed to remove noise and outliers to ensure the accuracy and consistency of the data. At the same time, necessary format conversion and standardization processing are carried out on the data for subsequent analysis and comparison. Next, the preprocessed data are calculated and analyzed according to the preset multiple piezoelectric performance detection factors, and the piezoelectric performance of the piezoelectric ceramic is evaluated by comparing the standard value and the actual value to see if it meets the requirements. Further, the piezoelectric performance health deviation detection channels are used to continuously monitor the performance parameters of the piezoelectric ceramic, and the abnormal changes of the performance parameters are identified by comparing the current value with the historical value or the standard value. When it is found that the performance parameters deviate from the normal range, the module will further analyze the cause and degree of the deviation. Among them, the piezoelectric performance health deviation detection refers to real-time monitoring of the change trend of the performance parameters of the piezoelectric ceramic through specific detection channels to judge whether there is a health deviation. Finally, the module comprehensively judges the piezoelectric performance of the piezoelectric ceramic based on the results of the multiple piezoelectric performance detection and the piezoelectric performance health deviation detection. When performance anomalies or health deviations are found, the module will output warning information through sound and light alarms, SMS notifications, email reminders, etc. according to the preset warning thresholds and warning strategies (such as immediate warning, delayed warning, hierarchical warning, etc.). At the same time, the module will also record the relevant information of the warning event (such as time, location, reason, etc.) for subsequent analysis and processing. Through the above steps, the piezoelectric performance detection and warning module can achieve real-time and accurate piezoelectric performance monitoring and warning of the piezoelectric ceramic in a high-voltage environment, providing a strong guarantee for the safe operation and performance optimization of the equipment.

[0023] Under high - voltage conditions, the change in the loss characteristics of piezoelectric ceramics may directly affect their working efficiency and lifespan. The loss characteristic detection and warning module realizes the accurate detection and timely warning of the loss characteristics of piezoelectric ceramics through the embedded dual - channel loss characteristic risk prediction. Specifically, the module first loads a preset loss characteristic risk prediction model. This model is trained based on a large amount of historical data and experimental analysis and can accurately predict the loss characteristics of piezoelectric ceramics under different conditions. At the same time, the dual - channel (including the power loss risk prediction channel and the dielectric loss risk prediction channel) is calibrated to ensure the accuracy and consistency of the detection results. After data acquisition and pre - processing of the loss - related data, they are respectively input into the dual - channel for risk prediction. The pre - processed data is input into the power loss risk prediction model. The model calculates the power loss value of the piezoelectric ceramic under the current conditions according to the input parameters and compares it with a preset threshold. If the predicted power loss exceeds the threshold, it is considered that there is a power loss risk and an alarm is ready to be triggered; similarly, the pre - processed data is input into the dielectric loss risk prediction model. The model calculates the dielectric loss value of the piezoelectric ceramic according to the input parameters and compares it with a preset threshold. If the predicted dielectric loss exceeds the threshold, it is considered that there is a dielectric loss risk and an alarm is also ready to be triggered. Finally, after obtaining the prediction results of power loss and dielectric loss, considering the power loss risk and dielectric loss risk comprehensively, the module will conduct a comprehensive risk assessment. If the prediction result of any channel exceeds the threshold, or the comprehensive evaluation result of the two channels reaches or exceeds the preset risk level, the module will judge that there is a loss characteristic risk and is ready to issue an alarm. The loss characteristic detection and warning module can realize the real - time monitoring and risk assessment of the loss characteristics of piezoelectric ceramics under high - voltage conditions and issue an alarm in a timely manner when potential risks are predicted, providing an important reference for the maintenance and servicing of the equipment.

[0024] The mechanical performance detection alarm module is a key component specially designed to monitor the changes in the mechanical properties of piezoelectric ceramics during use. The module continuously and accurately evaluates the mechanical properties of piezoelectric ceramics through the embedded mechanical performance attenuation evaluation channel, and issues an alarm when the performance is detected to be attenuated to a certain extent. Specifically, the module is initialized and the relevant data is collected and preprocessed. Among them, the key parameters of mechanical properties include stress, strain, displacement, vibration frequency, etc. Further, the mechanical performance attenuation evaluation channel uses a specific algorithm or model to conduct an in-depth analysis of the preprocessed data to evaluate whether the mechanical properties of the piezoelectric ceramics are attenuated. The preprocessed data is input into the mechanical performance attenuation evaluation algorithm, which may be based on the principles of material mechanics, machine learning or deep learning technology, and can automatically identify and quantify small changes in mechanical properties. The calculated mechanical performance indicators are compared with the preset baseline values ​​or historical data to determine whether the mechanical properties of the piezoelectric ceramics are attenuated. According to the degree of performance attenuation, its impact on the overall performance and service life of the piezoelectric ceramics is evaluated, and it is determined whether an alarm needs to be issued. If the mechanical performance attenuation assessment channel determines that the mechanical performance of the piezoelectric ceramic has decayed to a certain extent and may have an adverse effect on its normal use, the module will trigger the alarm mechanism to alarm. The mechanical performance detection alarm module can realize real-time monitoring and evaluation of the mechanical performance of piezoelectric ceramics, and issue an alarm in time when performance attenuation is detected, helping users to take timely measures to ensure the normal operation of the equipment and extend its service life.

[0025] Furthermore, if Figure 2 As shown, the piezoelectric performance detection alarm module 14 is also used for: The multivariate piezoelectric performance detection factors include piezoelectric strain coefficient, piezoelectric voltage coefficient and dielectric constant.

[0026] The piezoelectric performance of the piezoelectric ceramic is tested according to the multi-element piezoelectric performance test factor to obtain a piezoelectric performance test result.

[0027] The piezoelectric performance test result of the piezoelectric ceramic under normal environment is obtained by back-testing the piezoelectric performance of the piezoelectric ceramic according to the multi-element piezoelectric performance test factor.

[0028] Deviation identification is performed based on the healthy piezoelectric performance test result and the piezoelectric performance test result to obtain a piezoelectric performance healthy deviation identification result.

[0029] The piezoelectric performance healthy deviation identification result is input into the piezoelectric performance healthy deviation detection channel to obtain a piezoelectric performance healthy deviation detection coefficient.

[0030] The piezoelectric performance health deviation detection coefficient is input into the piezoelectric performance deviation classification warning component in the piezoelectric performance detection alarm module to obtain a piezoelectric performance alarm signal.

[0031] Specifically, the multi - piezoelectric performance detection factors include piezoelectric strain coefficient, piezoelectric voltage coefficient, and dielectric constant. Among them, the piezoelectric strain coefficient is a physical quantity that measures the ability of a piezoelectric material to generate electric charges when subjected to an external force, and it reflects the degree of change in the internal charge distribution of the material when it is subjected to mechanical stress. The magnitude of the piezoelectric strain coefficient directly determines the application effect of piezoelectric ceramics in fields such as sensors and transducers. A larger piezoelectric strain coefficient means that the material can generate a more significant charge change when subjected to a smaller stress, thereby improving the sensitivity and response speed of the sensor. The piezoelectric voltage coefficient is a physical quantity that describes the relationship between the voltage generated by a piezoelectric material and the pressure applied under a given pressure, and it reflects the ability of the material to convert mechanical energy into electrical energy. The piezoelectric voltage coefficient is a key indicator for evaluating the power generation performance of piezoelectric ceramics. In applications such as energy harvesting and vibration sensing, a higher piezoelectric voltage coefficient means higher energy conversion efficiency and a larger output voltage, thus meeting the requirements of specific applications. And the dielectric constant is a physical quantity that describes the ability of a material to store electric charges in an electric field, and it reflects the response degree of the material to the electric field, that is, the degree of rearrangement and polarization of the internal charges of the material under the action of the electric field. The dielectric constant plays an important role in the capacitance, insulation, and interaction with other electronic components of piezoelectric ceramics. A higher dielectric constant means that the material has better charge storage ability in an electric field, which is crucial for improving the performance of piezoelectric ceramics in electronic devices such as capacitors and filters. By real - time monitoring and evaluating these multi - piezoelectric performance detection factors, the piezoelectric performance state of piezoelectric ceramics can be comprehensively and accurately understood. Once it is found that the performance deviates from the normal range, the module will immediately issue an alarm signal to remind the user to pay attention and take corresponding measures to ensure the normal operation of the device and extend its service life.

[0032] The module collects data reflecting the piezoelectric performance of the piezoelectric ceramics in real - time through sensors connected to the piezoelectric ceramics. These data include voltage, current, displacement, etc. under specific conditions (such as applying a certain pressure or electric field), and are used to calculate the piezoelectric strain coefficient, piezoelectric voltage coefficient, and dielectric constant. According to the real - time collected data and the definitions of the multi - piezoelectric performance detection factors, the piezoelectric performance detection results of the current piezoelectric ceramics are calculated, and these results directly reflect the piezoelectric performance of the piezoelectric ceramics in the current state. In order to obtain the health performance benchmark of the piezoelectric ceramics, the module also conducts a retrospective piezoelectric performance detection under normal environmental conditions, which is usually achieved by referring to historical data or conducting tests under standard conditions to obtain the piezoelectric performance parameters of the piezoelectric ceramics in a healthy state. The healthy piezoelectric performance detection results refer to the piezoelectric performance exhibited by the piezoelectric ceramics under ideal or standard conditions, and serve as a benchmark for subsequent performance deviation identification.

[0033] Next, compare the current piezoelectric performance detection results with the healthy piezoelectric performance detection results, and identify whether the piezoelectric performance of the piezoelectric ceramic has deviated through methods such as statistical analysis or model prediction. Input the piezoelectric performance health deviation identification result into the piezoelectric performance health deviation detection channel, which uses a specific algorithm or model to quantitatively evaluate the deviation degree and calculate the piezoelectric performance health deviation detection coefficient. The piezoelectric performance health deviation detection coefficient is a quantitative index used to represent the degree of deviation of the piezoelectric performance of the piezoelectric ceramic from the healthy state. Furthermore, input the piezoelectric performance health deviation detection coefficient into the piezoelectric performance deviation grading and warning component in the piezoelectric performance detection warning module. This component grades the deviation degree according to the preset threshold and grading standard and generates a corresponding warning signal.

[0034] Through the above process, the piezoelectric performance detection warning module can achieve comprehensive monitoring and evaluation of the piezoelectric performance of the piezoelectric ceramic, and issue a warning in a timely manner when a performance deviation is detected, providing strong support for the maintenance and upkeep of the equipment.

[0035] Furthermore, performing a normal environment piezoelectric performance detection backtracking on the piezoelectric ceramic according to the multiple piezoelectric performance detection factors to obtain the healthy piezoelectric performance detection results further includes: Based on the piezoelectric ceramic, establish a backtracking target entity, where the backtracking target entity includes the piezoelectric ceramic and multiple piezoelectric ceramics of the same model corresponding to the piezoelectric ceramic. Collect piezoelectric performance detection sample areas in the normal environment for the backtracking target entity according to the multiple piezoelectric performance detection factors to obtain multiple piezoelectric performance detection characteristic sample areas.

[0036] Calculate the central value based on the multiple piezoelectric performance detection characteristic sample areas to generate the healthy piezoelectric performance detection results.

[0037] Further, clarify the backtracking target entity, that is, the piezoelectric ceramic to be detected (target piezoelectric ceramic). To more accurately evaluate its performance state, a series of piezoelectric ceramics of the same model need to be introduced as references. These piezoelectric ceramics of the same model will jointly form the overall backtracking target entity. The purpose of doing this is to eliminate individual differences through comparative analysis and more accurately reflect the performance of the target piezoelectric ceramic among its peers. Specifically, the backtracking target entity refers to the main object of this performance detection backtracking and its reference object set, including the target piezoelectric ceramic and multiple piezoelectric ceramics of the same model. For example, assume the target piezoelectric ceramic is the 100th product of a certain model. Products numbered from 95th to 105th of this model can be selected as references to jointly form the backtracking target entity.

[0038] Next, according to the previously defined multi - piezoelectric performance detection factors (piezoelectric strain coefficient, piezoelectric voltage coefficient, dielectric constant), piezoelectric performance detection is carried out on each piezoelectric ceramic in the backtracking target object under normal environment. This step aims to collect enough performance data to form multiple piezoelectric performance detection feature sample areas. Each sample area contains a series of performance data points related to a specific detection factor. The feature sample area refers to the set of performance data collected based on a certain detection factor, and these data can reflect the performance characteristics of the piezoelectric ceramic under this factor.

[0039] After completing the sample collection, the central value is calculated for the feature sample area corresponding to each detection factor. The central value refers to a statistic that can represent the overall average level or central tendency in a set of data. It can be the average value, median or other statistics, and the specific choice depends on the distribution characteristics of the data and the analysis requirements. By calculating the central value, a reference value that can represent the average performance level of this type of piezoelectric ceramic under a certain detection factor can be obtained. Subsequently, the corresponding detection value of the target piezoelectric ceramic is compared with this reference value to evaluate its healthy piezoelectric performance state.

[0040] For example, assume that the calculated average value of the piezoelectric strain coefficient of piezoelectric ceramics of the same type is X and the median is Y. Compare the piezoelectric strain coefficient value of the target piezoelectric ceramic with X and Y. If it is found that its value does not deviate much and is within the acceptable range, it is judged that its piezoelectric strain performance is healthy; otherwise, it is regarded as abnormal performance and further inspection or maintenance is required. The same method also applies to the evaluation of the piezoelectric voltage coefficient and dielectric constant. Finally, based on the evaluation results of all detection factors, the healthy piezoelectric performance detection result of the target piezoelectric ceramic is obtained.

[0041] Furthermore, the loss characteristic detection and alarm module 15 is also used for: The loss characteristic risk prediction dual - channel includes a power loss risk prediction channel and a dielectric loss risk prediction channel.

[0042] Perform power loss detection on the piezoelectric ceramic to obtain a power loss detection result.

[0043] Perform dielectric loss detection on the piezoelectric ceramic to obtain a dielectric loss detection result.

[0044] The loss characteristic detection and alarm module includes a power loss alarm component and a dielectric loss alarm component.

[0045] Based on the power loss alarm component, generate a power loss alarm signal according to the power loss detection result and the power loss risk prediction channel.

[0046] Based on the dielectric loss warning component, a dielectric loss warning signal is generated according to the dielectric loss detection result and the dielectric loss risk prediction channel.

[0047] Exemplarily, the dual-channel loss characteristic risk prediction embedded in the loss characteristic detection and warning module includes two independent prediction channels, namely the power loss risk prediction channel and the dielectric loss risk prediction channel, which are used to detect in real time and conduct risk assessments for power loss and dielectric loss respectively, so as to warn of possible loss problems. The power loss risk prediction channel is specifically used to predict the energy loss risk generated by the piezoelectric ceramic due to power conversion during use; the dielectric loss risk prediction channel focuses on the energy loss risk generated by the piezoelectric ceramic due to the internal polarization phenomenon of the medium under the action of an electric field.

[0048] First, the module conducts power loss detection on the piezoelectric ceramic. This process usually involves placing the piezoelectric ceramic in a specific test environment, applying a certain external force or electric field, measuring the difference in energy input and output during its conversion process, and thus calculating the power loss amount. For example, using a precision power measurement instrument, applying an alternating force with a certain frequency and amplitude to the piezoelectric ceramic under standard test conditions, recording its generated electrical energy output, and comparing it with the theoretical value to obtain the actual power loss value. Then, dielectric loss detection is carried out. This step mainly focuses on the performance of the piezoelectric ceramic under the action of an electric field, and evaluates its dielectric loss characteristics by measuring the change of its capacitance value with frequency and the energy loss under different electric field strengths. For example, using a dielectric constant tester to measure the capacitance value of the piezoelectric ceramic at different frequencies and electric field strengths, and calculating the dielectric loss factor based on the measurement results as the result of dielectric loss detection.

[0049] The loss characteristic detection and warning module also includes two warning components, namely the power loss warning component and the dielectric loss warning component. These two components respectively judge whether there is a potential loss risk according to the detection results and risk prediction models of their respective channels and issue warnings. The power loss warning component compares the power loss detection result with the preset threshold or the model prediction value in the power loss risk prediction channel. If the detection result exceeds the normal range or reaches the preset warning condition, a power loss warning signal is generated; similarly, the dielectric loss warning component also compares its detection result with the standard in the dielectric loss risk prediction channel. If there is an abnormality, a dielectric loss warning signal is generated.

[0050] Through the above process, the loss characteristic detection and warning module can achieve comprehensive monitoring and timely warning of the power loss and dielectric loss characteristics of the piezoelectric ceramic, providing strong support for the stable operation and maintenance of the equipment.

[0051] Furthermore, based on the power loss warning component, generating a power loss warning signal according to the power loss detection result and the power loss risk prediction channel further includes: The power loss risk prediction channel includes multiple power loss risk prediction models.

[0052] Input the power loss detection result into the multiple power loss risk prediction models to obtain multiple power loss risk prediction coefficients.

[0053] Perform confidence calculation according to the multiple power loss risk prediction coefficients to obtain a confidence power loss risk prediction coefficient.

[0054] Judge whether the confidence power loss risk prediction coefficient is greater than or equal to a predetermined power loss risk prediction coefficient.

[0055] If the confidence power loss risk prediction coefficient is greater than or equal to the predetermined power loss risk prediction coefficient, input the confidence power loss risk prediction coefficient into the power loss warning component to obtain the power loss warning signal.

[0056] Optionally, the power loss risk prediction channel is a module integrating multiple power loss risk prediction models, which is used to evaluate the power loss risk of piezoelectric ceramics under specific working conditions. The power loss risk prediction model is a mathematical model established based on historical data, physical principles or machine learning algorithms, and can predict the power loss risk of piezoelectric ceramics under different conditions. After obtaining the power loss detection result of the piezoelectric ceramics, this result is used as input data and transmitted to each prediction model in the power loss risk prediction channel. For example, if the detection result shows that the power loss rate of the current piezoelectric ceramic under specific working conditions is 3%, this value will be directly input into all relevant power loss risk prediction models. Each power loss risk prediction model independently calculates the corresponding power loss risk prediction coefficient according to the input power loss detection result, and these coefficients represent the risk assessment of the model for the current power loss situation. For example, assume that there are three prediction models, which respectively output risk prediction coefficients of 0.8 (high risk), 0.5 (medium risk) and 0.2 (low risk), and these coefficients reflect the risk assessment results of different models for the current power loss risk.

[0057] Furthermore, in order to obtain a more reliable and accurate prediction result of power loss risk, it is necessary to calculate the confidence of the outputs of multiple prediction models. This step usually involves weighted average, voting mechanism or more complex fusion algorithms to integrate multiple prediction results. For example, the weighted average method can be adopted. Different weights (such as 0.4, 0.3, 0.3) are assigned according to the accuracy and reliability of each model, and then the weighted average is calculated. The confidence power loss risk prediction coefficient is obtained as 0.53, which represents the final assessment of the current power loss risk after considering multiple models. The confidence power loss risk prediction coefficient is compared with the predetermined power loss risk prediction coefficient (i.e., the alarm threshold) to determine whether the current power loss risk has reached the level that requires an alarm. When the confidence power loss risk prediction coefficient is greater than or equal to the predetermined power loss risk prediction coefficient, the coefficient is input into the power loss alarm component, and the component generates a corresponding power loss alarm signal according to the preset rules and logic.

[0058] Through the above steps, the power loss alarm component can accurately judge the power loss risk level of the piezoelectric ceramic based on the comprehensive evaluation results of multiple power loss risk prediction models, and generate an alarm signal when necessary to ensure the stable operation of the equipment and the timeliness of maintenance.

[0059] Furthermore, based on the dielectric loss alarm component, generating a dielectric loss alarm signal according to the dielectric loss detection result and the dielectric loss risk prediction channel further includes: The dielectric loss risk prediction channel includes multiple dielectric loss risk prediction models.

[0060] Input the dielectric loss detection result into the multiple dielectric loss risk prediction models to obtain multiple dielectric loss risk prediction coefficients.

[0061] Perform confidence calculation according to the multiple dielectric loss risk prediction coefficients to obtain a confidence dielectric loss risk prediction coefficient.

[0062] Judge whether the confidence dielectric loss risk prediction coefficient is greater than or equal to the predetermined dielectric loss risk prediction coefficient.

[0063] If the confidence dielectric loss risk prediction coefficient is greater than or equal to the predetermined dielectric loss risk prediction coefficient, input the confidence dielectric loss risk prediction coefficient into the dielectric loss alarm component to obtain the dielectric loss alarm signal.

[0064] Furthermore, a channel containing multiple dielectric loss risk prediction models is constructed. These models are trained through machine learning or statistical methods based on historical data, device characteristics, and environmental factors, aiming to accurately predict the dielectric loss risk of the device in a future period. Among them, each model may focus on different prediction dimensions or adopt different algorithm strategies to improve the comprehensiveness and accuracy of the prediction. Next, the dielectric loss detection results obtained in real time are used as input data and fed into these prediction models. The dielectric loss detection results are usually collected by dedicated detection devices or sensors, reflecting the loss of dielectric performance of the device in the current operating state and serving as an important basis for evaluating the health status of the device. After that, each dielectric loss risk prediction model independently calculates a dielectric loss risk prediction coefficient based on the input detection results. This coefficient is a quantitative indicator used to represent the likelihood or degree of the device experiencing dielectric loss risk in a future period. Different models may obtain different prediction coefficients due to algorithm differences.

[0065] Similarly, in order to obtain a more reliable and comprehensive prediction result, confidence calculations are performed on the dielectric loss risk prediction coefficients output by multiple models. Subsequently, the calculated confidence dielectric loss risk prediction coefficient is compared with a predetermined dielectric loss risk prediction coefficient (i.e., the risk threshold). This risk threshold is set based on the safety standards of the device, historical experience, or expert opinions and is used to determine whether the current predicted risk level has reached the degree that requires an alarm to be issued. If the confidence dielectric loss risk prediction coefficient is greater than or equal to the predetermined risk threshold, it indicates that the dielectric loss risk of the device has reached a level that requires attention or measures to be taken. At this time, the confidence dielectric loss risk prediction coefficient is used as input and fed into the dielectric loss alarm component. The alarm component generates and issues a dielectric loss alarm signal according to the received information in accordance with certain rules (such as alarm level, alarm content, etc.).

[0066] Furthermore, the mechanical property detection alarm module 16 is also used for: Conducting mechanical property detection on the piezoelectric ceramic to establish a mechanical property attenuation matrix.

[0067] Inputting the mechanical property attenuation matrix into the mechanical property attenuation evaluation channel to obtain a mechanical property attenuation evaluation coefficient.

[0068] Judging whether the mechanical property attenuation evaluation coefficient is greater than or equal to the mechanical property attenuation evaluation threshold.

[0069] If the mechanical property attenuation evaluation coefficient is greater than or equal to the mechanical property attenuation evaluation threshold, activate the mechanical property alarm component within the mechanical property detection alarm module to generate a mechanical property alarm signal.

[0070] Optionally, first conduct a comprehensive mechanical property test on the piezoelectric ceramic material. This process includes measuring key indicators such as the elastic modulus, fracture toughness, and fatigue strength of the material, which can reflect the behavioral characteristics of the material under mechanical stress. Based on the data obtained from the test, establish a mechanical property attenuation matrix using a mathematical model or algorithm. This matrix is a multi-dimensional data structure used to quantitatively describe the attenuation of the mechanical properties of the piezoelectric ceramic material under specific conditions (such as time, temperature, stress, etc.). Subsequently, input the established mechanical property attenuation matrix into the embedded mechanical property attenuation evaluation channel. This channel consists of a series of predefined algorithms, rules, or machine learning models, aiming to comprehensively analyze and predict the future mechanical property performance of the piezoelectric ceramic material based on the input attenuation matrix. After processing by the channel, output a mechanical property attenuation evaluation coefficient. Next, compare the calculated mechanical property attenuation evaluation coefficient with a preset mechanical property attenuation evaluation threshold. The preset threshold is set according to factors such as the safety standard, design life, and usage environment of the material, and is used to determine whether the mechanical property attenuation of the current material has reached a level that requires attention. If the mechanical property attenuation evaluation coefficient is greater than or equal to the mechanical property attenuation evaluation threshold, it indicates that the mechanical properties of the piezoelectric ceramic material have decayed to a stage where measures need to be taken. At this time, the mechanical property warning component in the mechanical property detection warning module is activated, and this component generates and emits a mechanical property warning signal according to the preset warning rules (such as warning level, warning content, warning method, etc.).

[0071] Through the above steps, the mechanical property detection warning module can effectively monitor the mechanical property attenuation of the piezoelectric ceramic material and issue a warning in a timely manner when necessary, reminding relevant personnel to take measures to ensure the safe and stable operation of the equipment.

[0072] Furthermore, according to the mechanical property test of the piezoelectric ceramic to establish a mechanical property attenuation matrix, it further includes: Conduct a mechanical property test on the piezoelectric ceramic to obtain the mechanical property test results.

[0073] Retrieve the factory mechanical property test data of the piezoelectric ceramic.

[0074] Conduct standardization processing based on the mechanical property test results and the factory mechanical property test data to generate a mechanical property test matrix and a factory mechanical property test matrix.

[0075] Conduct attenuation analysis on the mechanical property test matrix according to the factory mechanical property test matrix to generate the mechanical property attenuation matrix.

[0076] Specifically, first, a comprehensive mechanical property test is conducted on the target piezoelectric ceramic sample. This process refers to measuring various mechanical property indexes of the material using professional testing equipment and methods, such as elastic modulus, fracture toughness, hardness, fatigue strength, etc. These indexes can directly reflect the physical behavior characteristics of the material under the action of force. Then, the mechanical property test data of the material at the time of leaving the factory are retrieved from the piezoelectric ceramic manufacturer or relevant archives. These data are obtained after the material is manufactured and undergoes strict tests, representing the mechanical property benchmark of the material in its brand-new state. The current mechanical property test results and the mechanical property test data at the time of leaving the factory are standardized to eliminate the influence of different test conditions (such as temperature, humidity, instrument precision, etc.) on the data, enabling the two sets of data to be compared under the same standard. Furthermore, a mechanical property test matrix and a mechanical property test matrix at the time of leaving the factory are generated based on these data. Among them, the mechanical property test matrix refers to organizing the current measured mechanical property indexes into a matrix form, where each row represents a property index and each column represents the data under different test conditions. Similarly, the mechanical property indexes of the factory test are also organized into a matrix form. Furthermore, using the mechanical property test matrix at the time of leaving the factory as a benchmark, an attenuation analysis is performed on the mechanical property test matrix. This step aims to identify the attenuation of the mechanical properties of the piezoelectric ceramic during use by comparing the two sets of data. That is, by calculating the attenuation percentage or difference of each mechanical property index relative to the factory value, a new matrix, namely the mechanical property attenuation matrix, is formed. This matrix intuitively shows which property indexes of the material have attenuated and the degree of attenuation.

[0077] Through the above steps, not only a comprehensive test of the mechanical properties of the piezoelectric ceramic is completed, but also a mechanical property attenuation matrix is successfully established, providing an important basis for subsequent performance evaluation, life prediction, and maintenance decision-making.

[0078] Through the technical solution of the above embodiment, a performance detection and warning device for piezoelectric ceramics in a high-pressure environment provided by the present application solves the technical problem in the prior art that it is difficult to comprehensively and real-time monitor the performance of piezoelectric ceramics in a high-pressure environment and issue an alarm in a timely manner when performance anomalies are detected, so as to improve the stability and reliability of piezoelectric ceramics in high-pressure applications. It realizes the comprehensive real-time monitoring and intelligent warning of the piezoelectric performance, loss characteristics, and mechanical properties of piezoelectric ceramics in a high-pressure environment, effectively improving the use safety and maintenance efficiency of piezoelectric ceramics under extreme conditions, and providing a reliable technical guarantee for the stable application of piezoelectric ceramics in a high-pressure environment.

[0079] The above specific embodiments do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the protection scope of this application. In some cases, the actions or steps recited in this application can be executed in a sequence different from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A performance detection and alarm device for piezoelectric ceramics under high-voltage environment, characterized in that: The device comprises: A sensor monitoring module, which is used to obtain real-time environmental monitoring information of piezoelectric ceramics; A high-pressure environment characteristic judgment module, the high-pressure environment characteristic judgment module is used to judge whether the real-time environment monitoring information meets a predetermined high-pressure environment characteristic condition; A high-voltage environment characteristic alarm activation module, the high-voltage environment characteristic alarm activation module is used to activate the piezoelectric performance detection alarm module, the loss characteristic detection alarm module and the mechanical performance detection alarm module if the real-time environmental monitoring information meets the predetermined high-voltage environment characteristic condition; Wherein, the piezoelectric performance detection alarm module performs piezoelectric performance detection alarm on the piezoelectric ceramic based on the embedded multivariate piezoelectric performance detection factor and the piezoelectric performance health deviation detection channel; The loss characteristic detection and alarm module performs loss characteristic detection and alarm on the piezoelectric ceramic based on the embedded loss characteristic risk prediction dual channel; The mechanical property detection alarm module performs mechanical property detection alarm on the piezoelectric ceramic based on the embedded mechanical property attenuation evaluation channel.

2. A performance detection and alarm device for piezoelectric ceramics under high-voltage environment as claimed in claim 1, characterized in that: The piezoelectric performance detection alarm module is used for: The multivariate piezoelectric performance detection factors include piezoelectric strain coefficient, piezoelectric voltage coefficient and dielectric constant; Performing a piezoelectric performance test on the piezoelectric ceramic according to the multi-element piezoelectric performance test factor to obtain a piezoelectric performance test result; Performing a normal environment piezoelectric performance test back to the piezoelectric ceramic according to the multivariate piezoelectric performance test factor to obtain a healthy piezoelectric performance test result; Perform deviation identification based on the healthy piezoelectric performance test result and the piezoelectric performance test result to obtain a piezoelectric performance healthy deviation identification result; Inputting the piezoelectric performance healthy deviation identification result into the piezoelectric performance healthy deviation detection channel to obtain a piezoelectric performance healthy deviation detection coefficient; The piezoelectric performance health deviation detection coefficient is input into the piezoelectric performance deviation classification warning component in the piezoelectric performance detection alarm module to obtain a piezoelectric performance alarm signal.

3. A performance detection and alarm device for piezoelectric ceramics under high-voltage environment as claimed in claim 2, characterized in that: The piezoelectric performance detection alarm module is used for: According to the piezoelectric ceramic, a backtracking target entity is established, wherein the backtracking target entity includes the piezoelectric ceramic and a plurality of piezoelectric ceramics of the same model corresponding to the piezoelectric ceramic; According to the multivariate piezoelectric performance detection factor, a normal environment piezoelectric performance detection sample is collected for the traceability target subject to obtain a plurality of piezoelectric performance detection characteristic sample areas; The healthy piezoelectric performance detection result is generated by performing concentrated value calculation based on the multiple piezoelectric performance detection feature sample areas.

4. The performance detection and warning device for piezoelectric ceramics under high-voltage environment as claimed in claim 1, characterized in that: The loss characteristic detection alarm module is used for: The loss characteristic risk prediction dual channels include a power loss risk prediction channel and a dielectric loss risk prediction channel; Performing power loss detection according to the piezoelectric ceramic to obtain a power loss detection result; Performing dielectric loss detection on the piezoelectric ceramic to obtain a dielectric loss detection result; The loss characteristic detection alarm module includes a power loss alarm component and a dielectric loss alarm component; Based on the power loss alarm component, generating a power loss alarm signal according to the power loss detection result and the power loss risk prediction channel; Based on the dielectric loss alarm component, a dielectric loss alarm signal is generated according to the dielectric loss detection result and the dielectric loss risk prediction channel.

5. A performance detection and alarm device for piezoelectric ceramics under high-voltage environment as claimed in claim 4, characterized in that: The loss characteristic detection alarm module is used for: The power loss risk prediction channel includes a plurality of power loss risk prediction models; Inputting the power loss detection result into the multiple power loss risk prediction models to obtain multiple power loss risk prediction coefficients; Performing confidence calculation according to the multiple power loss risk prediction coefficients to obtain a confidence power loss risk prediction coefficient; Determining whether the confidence power loss risk prediction coefficient is greater than / equal to a predetermined power loss risk prediction coefficient; If the confident power loss risk prediction coefficient is greater than / equal to the predetermined power loss risk prediction coefficient, the confident power loss risk prediction coefficient is input into the power loss alarm component to obtain the power loss alarm signal.

6. A performance detection and warning device for piezoelectric ceramics under high-voltage environment as claimed in claim 4, characterized in that: The loss characteristic detection alarm module is used for: The dielectric loss risk prediction channel includes a plurality of dielectric loss risk prediction models; Inputting the dielectric loss detection result into the multiple dielectric loss risk prediction models to obtain multiple dielectric loss risk prediction coefficients; Performing confidence calculation according to the multiple dielectric loss risk prediction coefficients to obtain a confident dielectric loss risk prediction coefficient; Determining whether the confident dielectric loss risk prediction coefficient is greater than / equal to a predetermined dielectric loss risk prediction coefficient; If the confident dielectric loss risk prediction coefficient is greater than / equal to the predetermined dielectric loss risk prediction coefficient, the confident dielectric loss risk prediction coefficient is input into the dielectric loss alarm component to obtain the dielectric loss alarm signal.

7. The performance detection and warning device for piezoelectric ceramics under high-voltage environment as claimed in claim 1, characterized in that: The mechanical performance detection alarm module is used for: Conducting mechanical property testing on the piezoelectric ceramics to establish a mechanical property attenuation matrix; Inputting the mechanical property attenuation matrix into the mechanical property attenuation evaluation channel to obtain a mechanical property attenuation evaluation coefficient; Determining whether the mechanical property attenuation assessment coefficient is greater than / equal to a mechanical property attenuation assessment threshold; If the mechanical property attenuation assessment coefficient is greater than / equal to the mechanical property attenuation assessment threshold, the mechanical property alarm component in the mechanical property detection alarm module is activated to generate a mechanical property alarm signal.

8. A performance detection and warning device for piezoelectric ceramics under high-voltage environment as claimed in claim 7, characterized in that: The mechanical performance detection alarm module is used for: Performing mechanical property testing on the piezoelectric ceramic to obtain mechanical property testing results; Retrieving factory mechanical performance test data of the piezoelectric ceramic; Performing standardization processing on the mechanical property test results and the factory mechanical property test data to generate a mechanical property test matrix and a factory mechanical property test matrix; The mechanical property attenuation matrix is ​​generated by performing attenuation analysis on the mechanical property detection matrix according to the factory mechanical property detection matrix.

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