A piezoelectric material testing method based on artificial intelligence

Abstract

The application discloses a piezoelectric material testing method based on artificial intelligence, relates to the technical field of artificial intelligence piezoelectric material testing, and comprises the following steps: creating an integrated testing platform, completing integrated testing environment of piezoelectric materials, and decomposing the integrated testing platform; simulating and regulating piezoelectric materials under the decomposed integrated testing platform; identifying variables affecting the piezoelectric materials by using the integrated testing platform; and completing piezoelectric material testing based on artificial intelligence. The application realizes accurate regulation and real-time monitoring of key environmental parameters such as temperature, humidity and pressure, not only reduces manual operation, but also captures the dynamic response characteristics of materials under different environments, so that the performance of the materials can be more accurately evaluated. In addition, the application effectively taps the application potential of new materials, meets the strict requirements of modern industry on high precision, high efficiency and multi-functionality, and greatly promotes the application and development of piezoelectric material testing.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence piezoelectric material testing, in particular to a piezoelectric material testing method based on artificial intelligence. BACKGROUND

[0002] With the rapid development of technology and the progress of society, the demand for material science, especially new functional materials, is increasing in modern society. Piezoelectric materials, as a unique material that can convert mechanical energy into electrical energy and vice versa, have a wide range of applications in sensors, transducers, medical devices, and energy harvesting.

[0003] Currently, the existing piezoelectric material testing methods face multiple challenges in practical applications. Traditional testing methods usually require a lot of manual intervention, which not only increases labor costs but also may lead to inconsistent test results due to operational differences. In addition, traditional evaluation methods often provide limited performance data under certain conditions, making it difficult to fully reflect the real behavior of materials in various complex environments or working conditions. This method limits the full exploitation of the potential of new materials, especially in modern application scenarios that require high precision and diversity. However, in the face of growing technical requirements and the increasing complexity of application scenarios, traditional piezoelectric material testing methods have been unable to meet the demands of modern industry for precision, efficiency, and multi-functionality. SUMMARY

[0004] In view of the problems existing in the current piezoelectric material testing method based on artificial intelligence, the present application is proposed.

[0005] Therefore, to overcome the defects of the existing piezoelectric material testing method, such as multiple manual interventions, limited test conditions leading to inconsistent results, and the inability to fully reflect the real behavior of materials, the present application adopts a combination of integrated testing platforms and intelligent condition simulation control units to automatically and accurately evaluate the performance of piezoelectric materials under various complex environmental conditions.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] In a first aspect, the embodiment of the present application provides a piezoelectric material testing method based on artificial intelligence, which comprises: creating an integrated testing platform by using a piezoelectric material sample for manual testing, completing an integrated testing environment of the piezoelectric material, and decomposing the integrated testing platform; introducing an intelligent condition simulation control unit into the integrated testing platform, collecting environmental parameters in the integrated testing platform under different environmental conditions, and simulating and regulating the piezoelectric material under the decomposed integrated testing platform; based on the piezoelectric material, dynamically collecting piezoelectric material test data, identifying variables affecting the piezoelectric material by using the integrated testing platform, and completing piezoelectric material testing based on artificial intelligence.

[0008] As a preferred scheme of the piezoelectric material testing method based on artificial intelligence, the piezoelectric material sample comprises characteristics and sizes of the piezoelectric material sample, the characteristics refer to the type of the piezoelectric material sample, the integrated testing platform is created by the type and size of the piezoelectric material sample, and the creating of the integrated testing platform comprises automatically adjusting the internal configuration of the piezoelectric material according to the type and size of the piezoelectric material sample.

[0009] As a preferred scheme of the piezoelectric material testing method based on artificial intelligence, the integrated testing environment comprises extracting environmental parameters on the integrated testing platform, the decomposing of the integrated testing platform comprises establishing a type-independent component and a size-independent component of the piezoelectric material sample, the extracting of the environmental parameters on the integrated testing platform comprises establishing a sensor array and a dynamic environment simulation cabin of the sensor array on the integrated testing platform.

[0010] The establishing of the sensor array comprises integrating the sensor array on the integrated testing platform, and the dynamic environment simulation cabin of the sensor array comprises designing an independent cabin under the condition of simulating environmental parameters, and extracting environmental parameters according to the integrated sensor array.

[0011] As a preferred scheme of the piezoelectric material testing method based on artificial intelligence, the introducing of the intelligent condition simulation control unit comprises deploying a sensor network on the integrated sensor array, integrating an environmental data recorder on the sensor network, collecting and storing environmental parameter data from the sensor network.

[0012] Based on the stored environmental parameter data, the internal environmental conditions of the dynamic environment simulation cabin are adjusted according to the established dynamic environment simulation cabin.

[0013] The adjusting of the internal environmental conditions of the dynamic environment simulation cabin comprises establishing an automatic regulation mechanism, and the establishing of the automatic regulation mechanism comprises a response system and a remote control interface.

[0014] The response system includes automatically adjusting the internal environmental conditions of the environmental cabin according to the environmental parameter data of the sensor network;

[0015] Based on detecting the temperature fluctuation range, the response system starts the heating or cooling device to recover;

[0016] Based on detecting the humidity fluctuation range, the response system starts the humidification or dehumidification device to recover;

[0017] Based on detecting the pressure fluctuation range, the response system starts the air flow control system to recover.

[0018] As a preferred scheme of the piezoelectric material test method based on artificial intelligence, wherein: the dynamic collection of piezoelectric material test data includes mapping the environmental state report to the sensor network deployed on the upper part of the sensor array, establishing a mapping relationship between the environmental state report and the piezoelectric material test data, and completing the piezoelectric material test based on the mapping conditions of the environmental state report and the piezoelectric material test data.

[0019] The environmental parameters in the integrated test platform include collecting environmental parameters in the integrated test platform according to the temperature fluctuation range, the humidity fluctuation range and the pressure fluctuation range;

[0020] The temperature fluctuation range includes installing temperature sensors on the integrated test platform, capturing temperature fluctuation changes, using temperature data synchronous collection technology to synchronously collect the temperature captured by all temperature sensors to the temperature central database of the integrated test platform, and marking the time stamp of the temperature captured by each temperature sensor;

[0021] The humidity fluctuation range includes integrating humidity sensing modules on the integrated test platform, capturing humidity fluctuation changes, configuring a data stream processor to receive information from each humidity sensing module, preprocessing the information of the humidity sensing module, the preprocessing including preliminary filtering and formatting of the information of the humidity sensing module, and transmitting the formatted information of the humidity sensing module to the humidity central repository of the integrated test platform;

[0022] The pressure fluctuation range includes secondarily deploying a pressure sensor array on the integrated sensor array, the pressure sensor array including an array of resolution pressure sensors, capturing dynamic pressure changes of the static pressure of the internal and peripheral areas of the test platform, recording signals simultaneously captured by all pressure sensors, and transmitting to the integrated test platform. The wet pressure central repository.

[0023] As a preferred scheme of the piezoelectric material test method based on artificial intelligence, the piezoelectric material under the decomposed integrated test platform is simulated and controlled, including integrating the collected environmental parameters in the integrated test platform by using an environmental parameter integration unit.

[0024] The environmental parameter integration unit includes an environmental parameter integration unit responsible for integrating all environmental parameters from a temperature central database, a humidity central repository and a pressure central repository, synchronously processing different types of environmental parameters, and generating an environmental state report.

[0025] The environmental state report is transmitted to the environmental control strategy environment, and different environmental parameters collected in the integrated test platform are used to simultaneously manage the environmental variables of different environmental parameters by using a variable cooperative control system.

[0026] The variable cooperative control system includes upper layer simulation control and lower layer simulation control, the upper layer simulation control includes a control strategy responsible for formulating the environmental variables of different environmental parameters, and the lower layer simulation control includes an operation instruction for executing the environmental variables of different environmental parameters.

[0027] As a preferred scheme of the piezoelectric material test method based on artificial intelligence, the piezoelectric material test data is dynamically collected, including mapping the environmental state report to the sensor network deployed on the upper part of the sensor array, establishing a mapping relationship between the environmental state report and the piezoelectric material test data, and completing the piezoelectric material test based on the mapping conditions of the environmental state report and the piezoelectric material test data.

[0028] In a second aspect, the embodiments of the present application provide a piezoelectric material test system based on artificial intelligence, which includes: a creation integrated test platform module, which uses a piezoelectric material sample for artificial testing to create an integrated test platform, completes the integrated test environment of the piezoelectric material, and decomposes the integrated test platform; a simulation control module, which introduces an intelligent condition simulation control unit in the integrated test platform, collects environmental parameters in the integrated test platform under different environmental conditions, and simulates and controls the piezoelectric material under the decomposed integrated test platform; and a piezoelectric material test module, which simulates and controls the piezoelectric material, dynamically collects piezoelectric material test data, uses the integrated test platform to identify variables affecting the piezoelectric material, and completes the piezoelectric material test based on artificial intelligence.

[0029] In a third aspect, the embodiments of the present application provide a computer device, including a memory and a processor, the memory stores a computer program, wherein the processor executes the computer program to realize any step of the piezoelectric material test method based on artificial intelligence.

[0030] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, which stores a computer program, wherein the computer program is executed by a processor to implement any step of the piezoelectric material testing method based on artificial intelligence.

[0031] The present application has the following beneficial effects: the present application creates an integrated testing platform with automatic adjustment function, and introduces an intelligent control unit that can simulate various actual use conditions, so that the present application realizes accurate regulation and real-time monitoring of key environmental parameters such as temperature, humidity and pressure, and not only reduces manual operation, but also captures the dynamic response characteristics of materials under different environments, so as to more accurately evaluate their performance, in addition, by establishing a mapping relationship between the environmental state report and the piezoelectric material testing data, the present application effectively taps the application potential of new materials, meets the strict requirements of modern industry for high precision, high efficiency and multi-functionality, and greatly promotes the application and development of piezoelectric material testing. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained without creative labor based on these drawings. Among them:

[0033] Figure 1 It is a flowchart of a piezoelectric material testing method based on artificial intelligence.

[0034] Figure 2 It is a system schematic diagram of a piezoelectric material testing method based on artificial intelligence. DETAILED DESCRIPTION

[0035] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0036] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the connotation of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0037] Secondly, the "one embodiment" or "embodiment" referred to herein is intended to represent a specific feature, structure, characteristic, or combination of features and characteristics described herein that can be included in at least one implementation of the present application. The appearance of the phrase "in one embodiment" in various places in the specification is not intended to be construed as an indication that each of the features, structures, or characteristics, so described is required in all implementations or that actual implementations only include features, structures, or characteristics so described.

[0038] The present application is described in detail below with reference to the accompanying drawings. In describing the embodiments of the present application, the cross-sectional view of the device structure is partially enlarged without the general scale for the convenience of explanation, and the schematic view is only an example, which should not limit the scope of protection of the present application. In addition, the three-dimensional spatial dimensions of length, width and depth should be included in actual production.

[0039] Meanwhile, in the description of the present application, it should be noted that the terms "upper, lower, inner and outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first, second or third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0040] Unless otherwise specifically defined and limited in the present application, the terms "mounting, connecting, connecting" should be broadly understood, for example: it can be fixedly connected, detachably connected or integrally connected; it can also be mechanically connected, electrically connected or directly connected; it can also be indirectly connected through an intermediate medium; it can also be the communication between two elements inside. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0041] Embodiment 1

[0042] Reference Figure 1 and Figure 2 The first embodiment of the present application provides a piezoelectric material testing method based on artificial intelligence, which comprises:

[0043] S1: using a piezoelectric material sample for artificial testing, creating an integrated testing platform, completing the integrated testing environment of the piezoelectric material, and decomposing the integrated testing platform.

[0044] Among them, the piezoelectric material sample includes the characteristics and size of the piezoelectric material sample, the characteristics refer to the type of the piezoelectric material sample, and the integrated testing platform is created by the type and size of the piezoelectric material sample. The integrated testing platform includes automatically adjusting the internal configuration of the piezoelectric material according to the type and size of the piezoelectric material sample.

[0045] S1.1: The integrated test environment includes extracting environmental parameters on the integrated test platform, decomposing the integrated test platform includes establishing type-independent components and size-independent components of piezoelectric material samples; extracting environmental parameters on the integrated test platform includes establishing a sensor array on the integrated test platform and establishing a dynamic environment simulation cabin of the sensor array.

[0046] Establishing a sensor array includes integrating the sensor array on the integrated test platform, and establishing a dynamic environment simulation cabin of the sensor array includes designing independent cabins under simulated environmental parameter conditions, and extracting environmental parameters according to the integrated sensor array.

[0047] S2: Introducing an intelligent condition simulation control unit in the integrated test platform, and simulating and regulating the piezoelectric material under the decomposed integrated test platform by collecting environmental parameters in the integrated test platform under different environmental conditions.

[0048] Among them, introducing an intelligent condition simulation control unit includes deploying a sensor network on the integrated sensor array, integrating an environmental data recorder on the sensor network, collecting and storing environmental parameter data from the sensor network.

[0049] Based on the stored environmental parameter data, the internal environmental conditions of the dynamic environment simulation cabin are adjusted according to the established dynamic environment simulation cabin.

[0050] Adjusting the internal environmental conditions of the dynamic environment simulation cabin includes establishing an automatic control mechanism, which includes a response system and a remote control interface.

[0051] The response system includes automatically adjusting the internal environmental conditions of the environmental cabin according to the environmental parameter data of the sensor network.

[0052] Based on detecting the temperature fluctuation range, the response system starts the heating or cooling device to recover.

[0053] Based on detecting the humidity fluctuation range, the response system starts the humidifying or dehumidifying device to recover.

[0054] Based on detecting the pressure fluctuation range, the response system starts the air flow control system to recover.

[0055] Further, the internal environmental conditions can be adjusted during the test process, and the environmental cabin is equipped with automatic adjustment devices such as heating or cooling elements, humidifying or dehumidifying devices, and air flow control systems, which are accurately controlled according to preset conditions or real-time feedback.

[0056] S2.1 Collecting environmental parameters in the integrated test platform includes collecting environmental parameters in the integrated test platform according to the temperature fluctuation range, the humidity fluctuation range, and the pressure fluctuation range.

[0057] Temperature fluctuation range includes installing temperature sensors on the integrated test platform, capturing temperature fluctuation changes, using temperature data synchronous acquisition technology, synchronously collecting all temperature sensors captured temperature to the temperature central database of the integrated test platform, and marking the time stamp of each temperature sensor captured temperature.

[0058] A series of high-sensitivity temperature sensors are installed at key positions on the integrated test platform. These sensors use advanced thermosensitive materials that can produce significant electrical signal changes under small temperature differences, thus achieving precise capture of temperature fluctuations.

[0059] A distributed sensor network is designed to ensure that temperature changes throughout the test area are fully covered. The position of each sensor is optimized based on heat conduction paths and potential hotspots to maximize the ability to capture temperature fluctuations.

[0060] A multi-channel high-speed data acquisition device is used, which can handle data streams from multiple temperature sensors simultaneously. This device has low latency and high precision, ensuring real-time and accurate data from all sensors.

[0061] A high-precision synchronous clock system is introduced to provide a unified time reference for all temperature sensors. This ensures accurate time synchronization even when multiple sensors are working in parallel, avoiding data deviation due to time errors.

[0062] An intelligent data transmission module is developed to efficiently transmit data captured by each temperature sensor to the central database. This module has automatic error correction capabilities, which can detect and repair errors that may occur during data transmission, ensuring that data arrives at the destination intact.

[0063] A redundant storage mechanism is implemented in the central database, where data is not only stored in a primary database but also copied to a backup database. This improves data security and reliability, preventing data loss due to hardware failures and other reasons.

[0064] Whenever a temperature sensor captures a new temperature data point, the system automatically generates a precise time stamp and embeds it directly into the corresponding temperature data record. This process is completed by an internal time stamp generator, ensuring that each data point has a unique and accurate time identifier.

[0065] A dedicated time series management system is established to manage and query temperature data with timestamps. This system allows researchers to retrieve and analyze data in chronological order, facilitating the tracking of temperature trends and the identification of abnormal fluctuations.

[0066] The humidity fluctuation range includes integrating humidity sensing modules on the integrated test platform, capturing humidity fluctuation changes, configuring data stream processors to receive information from various humidity sensing modules, preprocessing humidity sensing module information, preprocessing including preliminary filtering and formatting humidity sensing module information, and transmitting formatted humidity sensing module information to the humidity central repository of the integrated test platform.

[0067] A series of high-precision humidity sensing modules are installed at key locations on the integrated test platform. These modules use advanced capacitive or resistive humidity sensors that can provide accurate readings over a wide humidity range and have fast response characteristics.

[0068] According to the air flow pattern and potential humidity gradient in the test space, an intelligent layout is designed to arrange humidity sensing modules, which ensures that the humidity changes in the entire test area, including local humidity differences, can be fully monitored.

[0069] A multi-channel data stream processor is developed to receive data from multiple humidity sensing modules simultaneously. The processor supports high-speed data input and has adaptive adjustment functions that can dynamically adjust receiving parameters according to the output characteristics of different humidity sensing modules.

[0070] A real-time data synchronization mechanism is implemented in the data stream processor to ensure that data from all humidity sensing modules is accurately received with minimal delay. This mechanism uses hardware-level clock synchronization technology to ensure data consistency and time accuracy.

[0071] Intelligent filters are customized for each humidity sensing module. These filters can identify and remove noise signals such as electromagnetic interference or fluctuations caused by other non-humidity factors. By analyzing historical data patterns, the filter can automatically adjust its parameters to achieve the best noise reduction effect.

[0072] A standardized format converter is introduced to convert data received from various humidity sensing modules into a standard format. This format not only facilitates subsequent data processing and storage, but also improves system compatibility, allowing humidity sensing modules of different brands and models to seamlessly collaborate.

[0073] An efficient point-to-point data transmission protocol is used to safely and quickly transmit preprocessed humidity data to the humidity central repository. This protocol supports breakpoint resume and data compression functions, reducing network bandwidth usage and improving transmission efficiency.

[0074] A distributed humidity central repository is constructed, composed of multiple physical storage nodes, each responsible for storing humidity data for a specific time period or a specific region. This architecture improves the system's scalability and fault tolerance, ensuring that even if a single node fails, the overall data integrity is not affected.

[0075] The pressure fluctuation range includes a secondary deployment of a pressure sensor array on the integrated sensor array, which includes an array of high-resolution pressure sensors. The static pressure in the test platform and the surrounding area captures dynamic pressure changes, records signals captured simultaneously from all pressure sensors, and transmits them to the integrated test platform's humidity pressure central repository.

[0076] A modular design strategy is adopted, adding a dedicated pressure sensor array to the existing sensor array. Each module contains multiple high-resolution pressure sensors and supports hot-swapping, making installation and maintenance more convenient.

[0077] Based on the pressure distribution characteristics of the test platform's internal and peripheral areas, an intelligent layout is designed to arrange the pressure sensor array. Through simulation and actual measurement, the best position is determined to ensure comprehensive coverage and accurate capture of pressure changes in different areas.

[0078] Pressure sensors with nanoscale sensitive elements are used. These sensors can produce significant electrical signal changes under very small pressure changes, enabling accurate capture of small pressure fluctuations.

[0079] Each pressure sensor is equipped with a built-in self-calibration mechanism that can automatically adjust the sensor's sensitivity and offset regularly, ensuring long-term stability and accuracy.

[0080] A dynamic monitoring system is developed that can not only capture static pressure but also track rapidly changing dynamic pressure in real time. By setting different sampling frequencies and trigger conditions, the system can adapt to various application scenarios for pressure monitoring.

[0081] Multi-dimensional data fusion technology is used to combine temperature, humidity, and other environmental parameters for comprehensive analysis of pressure data, providing a more accurate reflection of real-world pressure changes.

[0082] A high-performance synchronous acquisition unit is configured to capture signals from all pressure sensors simultaneously. This unit supports multi-channel high-speed sampling, ensuring accurate data recording even in rapidly changing pressure conditions.

[0083] Each captured data point is assigned an accurate timestamp, which is embedded directly into the corresponding pressure data record. This ensures the temporal order and traceability of the data, facilitating subsequent analysis and processing.

[0084] An efficient peer-to-peer data transmission protocol is adopted to securely and quickly transmit the pre-processed pressure data to the central pressure repository. This protocol supports functions such as resuming from a breakpoint and data compression, reducing network bandwidth occupation and improving transmission efficiency.

[0085] A distributed central pressure repository is constructed, composed of multiple physical storage nodes, each responsible for storing pressure data of a specific time period or a specific region. This architecture improves the system's scalability and fault tolerance, ensuring that even a single node failure will not affect the overall data integrity.

[0086] S2.2: Simulate and control the piezoelectric material under the decomposed integrated test platform, including integrating the collected environmental parameters in the integrated test platform using the environmental parameter integration unit.

[0087] The environmental parameter integration unit is responsible for integrating all environmental parameters from the temperature central database, humidity central repository and pressure central repository, synchronously processing different types of environmental parameters, and generating an environmental status report.

[0088] The environmental status report is transmitted to the environmental control strategy environment, and different environmental parameters collected in the integrated test platform are used to manage different environmental variables using a variable cooperative control system.

[0089] The variable cooperative control system includes upper-level simulation control and lower-level simulation control. The upper-level simulation control includes formulating the overall control strategy for different environmental variables, and the lower-level simulation control includes executing the operation instructions for different environmental variables.

[0090] Further, an environmental parameter integration unit is established on the integrated test platform, which is responsible for real-time integration of all environmental parameters from the temperature central database, humidity central repository and pressure central repository. This unit supports multi-source data fusion and can synchronously process different types of environmental parameters such as temperature, humidity and pressure, and generate a unified environmental status report.

[0091] A variable cooperative control system is developed to manage the interaction between multiple environmental variables such as temperature, humidity and pressure. This system adopts a hierarchical control structure, with the upper layer responsible for formulating the overall control strategy and the lower layer executing specific operation instructions to ensure coordination between variables.

[0092] S3: Simulate and control based on piezoelectric materials, dynamically collect piezoelectric material test data, identify variables affecting piezoelectric materials using the integrated test platform, and complete piezoelectric material testing based on artificial intelligence.

[0093] The dynamic collection of piezoelectric material test data comprises mapping environmental state reports to a sensor network deployed on the sensor array, establishing a mapping relationship between the environmental state reports and the piezoelectric material, and completing the piezoelectric material test based on the mapping condition of the environmental state reports and the piezoelectric material test data.

[0094] In a preferred embodiment, a piezoelectric material test system based on artificial intelligence comprises:

[0095] S310: An integrated test platform module is created, which uses a piezoelectric material sample for artificial testing to create an integrated test platform, complete an integrated test environment for the piezoelectric material, and decompose the integrated test platform.

[0096] S320: An analog control module is introduced into the integrated test platform, which introduces an intelligent condition simulation control unit into the integrated test platform, collects environmental parameters in the integrated test platform under different environmental conditions, and performs analog control on the piezoelectric material under the decomposed integrated test platform.

[0097] S330: A piezoelectric material test module based on the piezoelectric material performs analog control, dynamically collects piezoelectric material test data, uses the integrated test platform to identify variables affecting the piezoelectric material, and completes the piezoelectric material test based on artificial intelligence.

[0098] The above-mentioned unit modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory in the computer device in software form, so as to call and execute the operations of the above-mentioned modules by the processor.

[0099] The computer device can be a terminal, and the computer device comprises a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device comprises a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be achieved through WIFI, operator network, NFC (near field communication) or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device. It can also be an external keyboard, touchpad or mouse, etc.

[0100] In summary, the present application creates an integrated test platform with automatic adjustment function, and introduces an intelligent control unit that can simulate various actual use conditions. The present application realizes precise regulation and real-time monitoring of key environmental parameters such as temperature, humidity and pressure. The present application not only reduces manual operation, but also captures the dynamic response characteristics of materials under different environments, thereby more accurately evaluating their performance. In addition, by establishing a mapping relationship between environmental state reports and piezoelectric material test data, the present application effectively taps the application potential of new materials, meets the strict requirements of modern industry for high precision, high efficiency and multi-functionality, and greatly promotes the application and development of piezoelectric material testing.

[0101] Embodiment 2

[0102] With reference to Figure 1 and Figure 2 As a second embodiment of the present application, the embodiment provides a piezoelectric material testing method based on artificial intelligence. In order to verify the beneficial effects of the present application, scientific demonstration is carried out through simulation experiments.

[0103] The temperature fluctuation range includes installing temperature sensors on the integrated test platform to capture temperature fluctuation changes. Temperature data synchronous acquisition technology is used to synchronously collect the temperatures captured by all temperature sensors into the temperature central database of the integrated test platform. The temperatures captured by each temperature sensor are marked with a time stamp.

[0104] Preferably, temperature sensors are installed on the integrated test platform to capture temperature fluctuation changes. These sensors can accurately monitor the temperature range from -40°C to 150°C, ensuring coverage of most actual application environments that piezoelectric materials may encounter. Temperature data synchronous acquisition technology is used to synchronously collect the data of all temperature sensors into the temperature central database of the integrated test platform in real time. The sampling frequency can reach 100 times per second to ensure high resolution and accuracy of the data. The data captured by each temperature sensor is marked with a time stamp accurate to milliseconds, so that the time sequence of temperature changes can be accurately tracked during subsequent analysis.

[0105] The selection of the temperature range from -40°C to 150°C, the sampling frequency of 100 times per second and the time stamp marking accurate to milliseconds is mainly based on the following considerations:

[0106] First, the temperature range of -40°C to 150°C is chosen to cover the working environment that most piezoelectric materials may encounter in practical applications, for example, in extreme weather conditions or industrial application scenarios, materials may experience changes from extremely low temperature to high temperature, -40°C is close to the lowest natural temperature on Earth, and 150°C is enough to cover many high-temperature working environments, such as sensors near car engines, etc. This range ensures that the test results can reflect the true performance of the material under a wide range of conditions.

[0107] Second, the sampling frequency is set to 100 times per second, which is to capture rapid changes in temperature fluctuations, especially when piezoelectric materials are used in dynamic response application scenarios, such as vibration energy harvesters or high-precision sensors. Higher sampling frequency can more accurately record the trend of temperature changes and avoid missing any critical transient changes, thus providing more detailed data support.

[0108] Finally, the timestamp is accurate to the millisecond level, which is crucial for tracking the time sequence of temperature changes, especially when analyzing the rate of temperature change or identifying temperature fluctuation patterns within a specific time period. Accurate timestamps enable researchers to conduct more detailed time-dependent analysis. Compared to second-level or other rougher time markers, millisecond-level timestamps provide higher time resolution, which helps improve the accuracy and reliability of data analysis.

[0109] The humidity fluctuation range includes integrating humidity sensing modules on the integrated test platform to capture humidity fluctuation changes, configuring data stream processors to receive information from various humidity sensing modules, and preprocessing humidity sensing module information, which includes preliminary filtering and formatting of humidity sensing module information. The formatted humidity sensing module information is transmitted to the humidity central repository of the integrated test platform.

[0110] Preferably, humidity sensing modules are integrated on the integrated test platform to capture humidity fluctuation changes. These modules can provide accurate readings in a relative humidity range of 0% to 95% RH in a non-condensing state, suitable for simulating various climate conditions in application scenarios. Configure data stream processors to receive information from various humidity sensing modules and perform preliminary filtering and formatting of these information to remove noise signals and ensure data consistency. The processed humidity data is sent to the humidity central repository of the integrated test platform through an efficient transmission protocol, with a data update frequency of once per second, ensuring real-time and data integrity.

[0111] The relative humidity range of 0% to 95% RH in a non-condensing state and the data update frequency of once per second are chosen based on the following key factors:

[0112] Firstly, the relative humidity range of 0% to 95% RH is chosen to cover the environmental conditions that most piezoelectric materials may encounter in practical applications. 0% RH represents a completely dry environment, while 95% RH is close to a high humidity state but does not reach the condensation point. This range covers a variety of climate conditions from arid regions to tropical rainforests. This range not only simulates extreme humidity changes in nature, but also reflects common humidity fluctuations in industry and daily life. In addition, avoiding reaching 100% RH can prevent condensation from affecting the accuracy of the sensor and the performance of the material, ensuring the authenticity and reliability of the test data.

[0113] Secondly, the data update frequency is set to once per second, which is to balance the data volume and processing efficiency while ensuring real-time data. For most humidity-related application scenarios, an update frequency of once per second is sufficient to capture the trend of humidity changes and respond to rapidly changing environmental conditions in a timely manner. For example, in humidity-sensitive electronic devices or medical devices that require precise humidity control, this frequency is sufficient to meet monitoring needs. Higher update frequencies may provide more detailed data, but they also increase the pressure on data processing and storage. Therefore, once per second is an ideal choice that balances real-time performance and system load.

[0114] Finally, by configuring the data stream processor to perform preliminary filtering and formatting on the received humidity data, noise signals can be effectively removed and data consistency can be ensured, which is crucial for subsequent data analysis. Clean and consistent data helps accurately identify the impact of humidity changes on the performance of piezoelectric materials. The application of efficient transmission protocols further ensures seamless data from collection to storage, improving the overall reliability and data integrity of the system.

[0115] In summary, the selection of a humidity range of 0% to 95% RH and a data update frequency of once per second is based on the comprehensive consideration of the wide coverage of actual application environments, the requirement of data real-time performance and the processing capacity of the system. Compared with other possible value ranges, this setting can achieve the best balance between data quality and system efficiency, thereby providing strong support for the performance evaluation of piezoelectric materials under different humidity conditions.

[0116] The pressure fluctuation range includes a secondary deployment of a pressure sensor array on the integrated sensor array, which includes an array of resolution pressure sensors. The static pressure in the test platform and the surrounding area captures dynamic pressure changes, records signals captured by all pressure sensors simultaneously, and transmits them to the central humidity and pressure storage of the integrated test platform.

[0117] Preferably, a pressure sensor array is deployed on the integrated sensor array, which consists of multiple high-resolution pressure sensors capable of detecting a pressure range from 0.1 kPa to 200 kPa, meeting the monitoring needs of static and dynamic pressure changes in different application scenarios. The sensor array not only captures the static pressure inside and around the test platform, but also records the rapidly changing dynamic pressure with a sampling rate of up to 1000 times per second to ensure the capture of subtle pressure fluctuations. All captured pressure signals are recorded synchronously and transmitted to the integrated test platform's wet pressure central repository through a safe and efficient transmission pipeline, ensuring data integrity and timeliness. This design enables the system to accurately evaluate the performance of piezoelectric materials under complex and variable pressure conditions.

[0118] The selection of a pressure range from 0.1 kPa to 200 kPa and a sampling rate of 1000 times per second is mainly based on the comprehensive consideration of the actual needs of piezoelectric materials in various application scenarios, data accuracy and system performance:

[0119] First, the selection of the pressure range from 0.1 kPa to 200 kPa is to cover a wide range of static and dynamic pressure change scenarios. 0.1 kPa is close to the level of micro air flow or light touch pressure, while 200 kPa is sufficient to cover higher pressure conditions that may be encountered in most industrial applications and daily environments, such as certain types of sensors, transducers and medical devices, etc. This range not only simulates gentle pressure environments such as touch screens or biomechanics monitoring, but also handles high-pressure application scenarios such as hydraulic systems or certain industrial process control. By covering such a wide range, it can ensure that the test results are applicable to the performance evaluation of piezoelectric materials under various use conditions.

[0120] Second, the sampling rate is set to 1000 times per second, which is to capture the rapidly changing dynamic pressure fluctuations. This is crucial for accurately evaluating the response of piezoelectric materials under transient conditions. High sampling rate enables the system to record subtle pressure changes, which is particularly critical for applications that require high precision and fast response, such as vibration energy harvesting, acoustic sensing, etc. Compared to low sampling frequency, a sampling rate of 1000 times per second can provide more detailed dynamic characteristic information, avoiding missing any important transient changes, thereby providing more comprehensive data support for subsequent analysis.

[0121] In addition, the captured pressure signals are processed using a synchronous recording and efficient transmission pipeline, ensuring data integrity and timeliness. This design allows data from all sensors to be recorded simultaneously and transmitted to the central repository with minimal delay, reducing the risk of data loss and improving system reliability. This is particularly important for real-time monitoring and immediate feedback applications, as it ensures accurate and reliable test data even under complex and variable pressure conditions.

[0122] In summary, the selection of a pressure range of 0.1 kPa to 200 kPa and a sampling rate of 1000 times per second is based on the actual needs of the widely used environment of piezoelectric materials, the requirement for accurate capture of dynamic characteristics, and the comprehensive consideration of system data processing capacity. Compared with other possible numerical ranges, this setting can cover a wide range of application scenarios while ensuring high-resolution data and efficient system operation, thereby providing strong support for the performance evaluation of piezoelectric materials under various pressure conditions. This balance meets the needs of practical applications while taking into account the feasibility and economy of technical implementation.

[0123] It should be noted that the above examples are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and they should be included in the scope of the claims of the present application.

Claims

1. A method for testing piezoelectric materials based on artificial intelligence, characterized in that: include, An integrated testing platform was created using piezoelectric material samples tested manually, and an integrated testing environment for piezoelectric materials was established. The integrated testing platform was then disassembled. An intelligent condition simulation control unit is introduced into the integrated test platform. By collecting environmental parameters in the integrated test platform under different environmental conditions, the piezoelectric material under the decomposed integrated test platform is simulated and controlled. Based on the simulation and control of piezoelectric materials, test data of piezoelectric materials are dynamically collected, and the variables affecting piezoelectric materials are identified using an integrated testing platform to complete the testing of piezoelectric materials based on artificial intelligence. The intelligent condition simulation control unit includes deploying a sensor network on an integrated sensor array, integrating an environmental data logger on the sensor network, and collecting and storing environmental parameter data from the sensor network. Based on the stored environmental parameter data, the internal environmental conditions of the dynamic environment simulation chamber are adjusted according to the established dynamic environment simulation chamber. The adjustment of the internal environmental conditions of the dynamic environment simulation chamber includes the establishment of an automated control mechanism, which consists of a response system and a remote control interface. The response system includes automatically adjusting the internal environmental conditions of the environmental chamber based on environmental parameter data from the sensor network; Based on the detected temperature fluctuation range, the response system activates heating or cooling devices to restore normal operation. Based on the detected humidity fluctuation range, the response system activates humidification or dehumidification devices to restore humidity levels. Based on the detected pressure fluctuation range, the response system activates the airflow control system to restore normal operation.

2. The artificial intelligence-based piezoelectric material testing method as described in claim 1, characterized in that: The piezoelectric material sample includes the characteristics and dimensions of the piezoelectric material sample. The characteristics refer to the type of piezoelectric material sample. An integrated testing platform is created based on the type and dimensions of the piezoelectric material sample. The creation of the integrated testing platform includes automatically adjusting the internal configuration of the piezoelectric material according to the type and dimensions of the piezoelectric material sample.

3. The artificial intelligence-based piezoelectric material testing method as described in claim 2, characterized in that: The integrated testing environment includes extracting environmental parameters on an integrated testing platform; the decomposition of the integrated testing platform includes establishing type-independent components and size-independent components for the piezoelectric material sample; the extraction of environmental parameters on the integrated testing platform includes establishing a sensor array and a dynamic environment simulation chamber for the sensor array on the integrated testing platform. The establishment of the sensor array includes integrating the sensor array on an integrated test platform. The dynamic environment simulation chamber for establishing the sensor array includes designing independent chambers under simulated environmental parameter conditions and extracting environmental parameters based on the integrated sensor array.

4. The artificial intelligence-based piezoelectric material testing method as described in claim 3, characterized in that: The environmental parameters collected in the integrated testing platform include those based on temperature fluctuation range, humidity fluctuation range, and pressure fluctuation range. The temperature fluctuation range includes installing temperature sensors on the integrated test platform to capture temperature fluctuation changes, using temperature data synchronous acquisition technology to synchronously collect the temperatures captured by all temperature sensors into the temperature central database of the integrated test platform, and marking the temperatures captured by each temperature sensor with a timestamp. The humidity fluctuation range includes integrating a humidity sensing module on the integrated test platform to capture humidity fluctuation changes, configuring a data stream processor to receive information from each humidity sensing module, preprocessing the information from the humidity sensing modules, the preprocessing including preliminary filtering and formatting of the information from the humidity sensing modules, and transmitting the formatted information from the humidity sensing modules to the humidity central storage of the integrated test platform. The pressure fluctuation range includes a secondary deployment of a pressure sensing array on an integrated sensor array. The pressure sensing array consists of an array of high-resolution pressure sensors. The static pressure inside and around the test platform captures dynamic pressure changes, records and captures signals output by all pressure sensors, and transmits them to the central wet pressure storage of the integrated test platform.

5. The artificial intelligence-based piezoelectric material testing method as described in claim 4, characterized in that: The simulation and control of the piezoelectric material under the decomposed integrated test platform includes using an environmental parameter integration unit to integrate the collected environmental parameters in the integrated test platform; The environmental parameter integration unit is responsible for integrating all environmental parameters from the central temperature database, central humidity database, and central pressure database, processing different types of environmental parameters synchronously, and generating an environmental status report. The environmental status report is transmitted to the environmental control strategy environment. By collecting different environmental parameters in the integrated testing platform, the variable collaborative control system is used to manage environmental variables of different environmental parameters at the same time. The variable collaborative control system includes upper-level simulation control and lower-level simulation control. The upper-level simulation control includes formulating control strategies for environmental variables with different overall environmental parameters, and the lower-level simulation control includes executing operation instructions for environmental variables with different environmental parameters.

6. The artificial intelligence-based piezoelectric material testing method as described in claim 5, characterized in that: The dynamic collection of piezoelectric material test data includes mapping environmental status reports to a sensor network deployed on a sensor array, establishing a mapping relationship between environmental status reports and piezoelectric material test data, and completing piezoelectric material testing based on the mapping conditions between environmental status reports and piezoelectric material test data.

7. An artificial intelligence-based piezoelectric material testing system, based on the artificial intelligence-based piezoelectric material testing method according to any one of claims 1 to 6, characterized in that: include, An integrated testing platform module is created, which utilizes manually tested piezoelectric material samples to create an integrated testing platform, completes the integrated testing environment for piezoelectric materials, and decomposes the integrated testing platform; The simulation control module introduces an intelligent condition simulation control unit into the integrated test platform. By collecting environmental parameters in the integrated test platform under different environmental conditions, it simulates and controls the piezoelectric material under the decomposed integrated test platform. The piezoelectric material testing module simulates and controls piezoelectric materials, dynamically collects piezoelectric material test data, uses an integrated testing platform to identify variables affecting piezoelectric materials, and completes artificial intelligence-based piezoelectric material testing.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the artificial intelligence-based piezoelectric material testing method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the artificial intelligence-based piezoelectric material testing method according to any one of claims 1 to 6.

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