Sensitivity detection method for capacitive flexible touch sensor

Abstract

The invention relates to the technical field of sensor detection, in particular to a method for detecting the sensitivity of a capacitive flexible tactile sensor, which can comprehensively and accurately evaluate the sensitivity of the capacitive flexible tactile sensor under a specific working condition. The method comprises the following steps: acquiring sensor structure design data information and sensor application conditions of a capacitive flexible touch sensor to be detected; performing key parameter pickup on the sensor structure design data information by using a pre-trained structure parameter pickup model to obtain a sensitive performance structure parameter set; the sensitivity performance structure parameter set comprises all structure parameters influencing the sensitivity of the sensor; inputting the sensitivity performance structure parameter set into a sensitivity performance analysis model to obtain a sensor sensitivity performance index in a preset state; considering the application working condition of the sensor, and determining the sensitivity performance requirement of the sensor under the application working condition; and acquiring field environment state information corresponding to the application working condition according to the sensor application working condition.

Description

Technical Field

[0001] The present invention relates to the technical field of sensor detection, and in particular to a sensitivity detection method of a capacitive flexible tactile sensor. Background Art

[0002] Capacitive flexible tactile sensors have shown broad application prospects in many fields such as smart wearable devices, robots, and medical health monitoring due to their unique flexibility and high sensitivity. Such sensors are usually made of one or more layers of flexible materials and can sense tiny deformations of the contact surface and convert them into electrical signals for output. However, the performance of capacitive flexible tactile sensors is affected by many factors, including material selection, structural design, manufacturing process, and use environment.

[0003] Most existing capacitive flexible tactile sensor sensitivity detection methods rely on experimental testing, that is, measuring the sensor's response by applying different forces or pressures to evaluate its sensitivity. Although the existing methods are direct and effective, they have the limitation of being difficult to fully cover all possible application conditions. Since the sensitivity of the sensor is affected by many factors, such as structural design and working environment, the existing detection methods are often difficult to accurately and quickly evaluate the performance of the sensor under specific conditions. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a capacitive flexible tactile sensor sensitivity detection method which can comprehensively and accurately evaluate the sensitivity of the capacitive flexible tactile sensor under specific working conditions.

[0005] In a first aspect, the present invention provides a method for detecting sensitivity of a capacitive flexible tactile sensor, the method comprising:

[0006] Obtaining sensor structure design data information and sensor application conditions of the capacitive flexible tactile sensor to be detected;

[0007] Using a pre-trained structural parameter picking model, key parameters of the sensor structure design data information are picked to obtain a sensitive performance structural parameter set; the sensitive performance structural parameter set includes all structural parameters that affect the sensitivity of the sensor;

[0008] Inputting the sensitivity performance structural parameter set into the sensitivity performance analysis model to obtain the sensor sensitivity performance index under a preset state;

[0009] Considering the sensor application conditions, determining the sensor sensitivity performance requirements under the application conditions;

[0010] According to the sensor application condition, obtaining on-site environmental status information corresponding to the application condition;

[0011] Considering the on-site environmental status information, performing environmental calibration on the sensor sensitivity performance index to obtain a calibrated sensor sensitivity performance index;

[0012] The calibrated sensor sensitivity performance index is compared with the sensor sensitivity performance requirement to determine whether the capacitive flexible tactile sensor to be detected meets the application conditions to be used, and a detection result is generated according to the determination result.

[0013] Further, considering the on-site environmental status information, environmental calibration is performed on the sensor sensitivity performance index to obtain the calibrated sensor sensitivity performance index, including:

[0014] Extracting a sensor material composition vector from the sensor structure design data information;

[0015] Based on the sensor material composition vector, determining an environmental feature set that affects the sensitivity performance of the sensor;

[0016] Traversing the on-site environment status information, extracting the same environment characteristic parameters as those in the environment characteristic set, and forming an on-site environment characteristic parameter set;

[0017] Calculate the difference between the set of on-site environment characteristic parameters and the corresponding characteristic parameters in the preset state to obtain a set of on-site environment parameter deviations;

[0018] Comprehensively calculating the set of on-site environmental parameter deviations to obtain an environmental calibration coefficient;

[0019] The environmental calibration coefficient is multiplied by the sensor sensitivity performance index to obtain the calibrated sensor sensitivity performance index.

[0020] Furthermore, the sensor material composition vector includes a conductive material type and a dielectric material type.

[0021] Furthermore, the sensitive performance structural parameter set includes sensor thickness, electrode spacing, electrode area, relative dielectric constant, vacuum dielectric constant and elastic modulus.

[0022] Furthermore, the core evaluation formula of the sensitivity performance analysis model is:

[0023]

[0024] Among them, C 0 is the initial capacitance value, which means the capacitance value of the sensor before the external force acts; ∈ r is the relative dielectric constant, which indicates the dielectric capacity of the medium inside the sensor relative to the air; 0 is the vacuum dielectric constant, a physical constant, about 8.854×10-12 F / m; A is the electrode area, which indicates the effective area of ​​interaction between the two electrodes; d is the initial electrode spacing, which indicates the initial distance between the two electrodes; C is the new capacitance value after the external force acts, which indicates the capacitance value of the sensor under the external force; Δd ​​is the change in the electrode spacing, which indicates the change in the electrode spacing under the external force; F is the external force applied under the preset state, which indicates the external force acting on the sensor; t is the thickness of the sensor, which indicates the overall thickness of the sensor; E is the elastic modulus, which indicates the ability of the sensor material to resist deformation; SI is the sensor sensitivity performance index.

[0025] Furthermore, the set of on-site environmental characteristic parameters includes on-site temperature, on-site humidity, on-site pressure and on-site electromagnetic interference intensity.

[0026] Furthermore, the field environment parameter deviation set is comprehensively calculated, and the formula is:

[0027] R=w T ·z T (ΔT)+w H ·z H (ΔH)+w P ·z P (ΔP)+w E ·z E (ΔE)

[0028] Where R is the environmental calibration coefficient; ΔT is the temperature deviation; ΔH is the humidity deviation; ΔP is the pressure deviation; ΔE is the electromagnetic interference deviation; w T represents the weight of temperature deviation; w H represents the weight of humidity deviation; w P Indicates the weight of pressure deviation; w E Represents the weight of electromagnetic interference deviation; z T (ΔT) represents the normalized function of temperature deviation; z H (ΔH) represents the normalized function of humidity deviation; z P (ΔP) represents the normalized function of pressure deviation; z E (ΔE) represents the normalized function of the electromagnetic interference deviation.

[0029] On the other hand, the present application also provides a capacitive flexible tactile sensor sensitivity detection system, the system comprising:

[0030] A data acquisition module, used to acquire structural design data information of the capacitive flexible tactile sensor to be detected and sensor application conditions;

[0031] A structural parameter picking module is used to pick up key parameters of sensor structure design data information using a pre-trained structural parameter picking model to obtain a sensitive performance structural parameter set;

[0032] A performance analysis module, used to input a set of sensitive performance structure parameters into a sensitive performance analysis model to obtain a sensor sensitive performance index under a preset state;

[0033] A performance requirement determination module, used to determine the sensor sensitivity performance requirements under the application conditions according to the sensor application conditions;

[0034] An environmental status information acquisition module is used to acquire on-site environmental status information corresponding to the application condition according to the sensor application condition;

[0035] An environmental calibration module is used to perform environmental calibration on the sensor sensitivity performance index by considering the on-site environmental status information to obtain the calibrated sensor sensitivity performance index;

[0036] The performance comparison and judgment module is used to compare the calibrated sensor sensitivity performance index with the sensor sensitivity performance requirement, judge whether the capacitive flexible tactile sensor to be tested meets the application conditions to be used, and generate a test result according to the judgment result;

[0037] The result output module is used to output the results of the performance test, including the judgment of whether the application conditions are met and the specific sensitivity performance index.

[0038] In a third aspect, the present application provides an electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and the computer program, when executed by the processor, implements the steps of any one of the above methods.

[0039] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps in any one of the above-mentioned methods when executed by a processor.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention not only considers the structural design data of the sensor, but also combines the application conditions and the on-site environmental status information to realize a multi-dimensional and comprehensive evaluation of the sensor performance; the pre-trained structural parameter picking model is used to automatically extract the key parameters affecting the sensitivity of the sensor to ensure the comprehensiveness and accuracy of the evaluation; from the acquisition of structural design data to the extraction of key parameters, and then to the analysis and calibration of sensitive performance, the entire process is highly automated, reducing manual intervention and improving detection efficiency; with the assistance of models and algorithms, the evaluation of sensor sensitivity can be completed in a short time, which greatly shortens the evaluation cycle compared with traditional experimental test methods; the pre-trained structural parameter picking model and sensitive performance analysis model are used to ensure the accuracy and reliability of the evaluation results; considering the on-site environmental status information, the sensitive performance index of the sensor is calibrated to eliminate the influence of environmental factors on the evaluation results and improve the accuracy of the evaluation; the present invention can flexibly adjust the evaluation criteria according to the requirements of different application conditions to ensure that the performance of the sensor under specific conditions meets the actual needs; it is suitable for capacitive flexible tactile sensors of different types and structures and has a wide range of applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of the present invention;

[0042] Figure 2 It is a structural diagram of the sensitivity detection system of the capacitive flexible tactile sensor. DETAILED DESCRIPTION

[0043] In the description of the present application, those skilled in the art should know that the present application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, the present application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), a combination of hardware and software. In addition, in some embodiments, the present application can also be implemented in the form of a computer program product in one or more computer-readable storage media, and the computer-readable storage medium contains computer program code.

[0044] The above-mentioned computer-readable storage medium may adopt any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or devices, or any combination of the above. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memories, optical fibers, optical disc read-only memories, optical storage devices, magnetic storage devices, or any combination of the above. In the present application, computer-readable storage media can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device.

[0045] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws.

[0046] The present application describes the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0047] It should be understood that each box in the flowchart and / or block diagram and the combination of boxes in the flowchart and / or block diagram can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine, and these computer-readable program instructions are executed by a computer or other programmable data processing device to produce a device that implements the functions / operations specified by the boxes in the flowchart and / or block diagram.

[0048] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to work in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product including functions / operations specified in the blocks in the flowchart and / or block diagram.

[0049] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process for implementing the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0050] The present application is described below in conjunction with the drawings in the present application.

[0051] Embodiment 1: Figure 1 As shown, a capacitive flexible tactile sensor sensitivity detection method of the present invention specifically includes the following steps:

[0052] Step S1, obtaining sensor structure design data information and sensor application conditions of the capacitive flexible tactile sensor to be detected;

[0053] Step S1 is used to collect and analyze basic information of the sensor to provide necessary input data for subsequent performance evaluation, including sensor structure design data information and sensor application conditions. These two aspects specifically include:

[0054] 1) Sensor structure design data information: Obtain detailed structural design data of the sensor to facilitate extraction of key parameters and performance analysis in subsequent steps; obtain from the sensor design files, such as CAD drawings, 3D model files, bill of materials, etc.; specifically include:

[0055] Geometric parameters: the overall shape of the sensor, such as rectangular, circular, irregular, etc.; the specific dimensions of the sensor, such as length, width, and height; the thickness of each part of the sensor, especially the thickness of the electrode and dielectric layer; the position, shape, and spacing of the electrodes;

[0056] Material parameters: materials used in each layer of the sensor, such as polymers, metals, ceramics, etc.; physical and chemical properties of the materials, such as elastic modulus, Poisson's ratio, relative dielectric constant, vacuum dielectric constant, conductivity, etc.

[0057] 2) Sensor application conditions: Understand the working environment and usage conditions of the sensor in actual applications, so as to determine the performance requirements of the sensor and perform environmental calibration in the subsequent steps; communicate with the end user or application party to understand the specific application scenarios and performance requirements of the sensor; consult the technical documents and standard specifications of the relevant application fields to obtain the typical working conditions of the sensor in specific applications; refer to the actual performance data of similar sensors in the same or similar applications; the working environment specifically includes:

[0058] Physical environment: temperature range, humidity range, pressure range, etc.;

[0059] Mechanical environment: maximum pressure, minimum pressure, pressure change rate, etc. that the sensor can withstand;

[0060] Electrical environment: power supply voltage, operating current, signal transmission distance, etc.;

[0061] Chemical environment: whether there are corrosive media, whether there are special chemical reaction requirements, etc.;

[0062] Biological environment: whether the sensor comes into contact with the human body, whether there are biocompatibility requirements, etc.

[0063] Through the above steps, step S1 provides the necessary basic data for the subsequent sensitivity detection, making the analysis process more accurate and efficient; it not only helps to understand the physical properties of the sensor, but also guides the subsequent model building and calibration work to ensure the accuracy and reliability of the test results.

[0064] Step S2, using a pre-trained structural parameter picking model to pick key parameters of the sensor structure design data information to obtain a sensitive performance structural parameter set; the sensitive performance structural parameter set includes all structural parameters that affect the sensitivity of the sensor;

[0065] Step S2 is used to use the pre-trained structural parameter picking model to accurately extract all key parameters that affect the sensor sensitivity from the sensor structure design data information; in the early stage of the scheme design, the structural parameter picking model needs to be constructed and trained, as follows:

[0066] Step S211: Select a suitable deep learning model architecture according to the characteristics of the sensor structure design data and the requirements of sensitivity analysis; for example, if the data has a spatial structure (such as a geometric shape in a CAD drawing), select a convolutional neural network (CNN); if the data has a time series characteristic, a recurrent neural network (RNN) or a long short-term memory network (LSTM) is more suitable;

[0067] Step S212: Collect a large amount of sensor structure design data, including but not limited to geometric parameters, material parameters, etc.; annotate these data with corresponding sensitive performance parameters, which can be obtained through experimental tests or based on theoretical calculations or simulations; divide the data set into a training set, a validation set, and a test set to ensure the generalization ability of the model and the accuracy of performance evaluation;

[0068] Step S213: using domain knowledge, data preprocessing techniques and feature selection algorithms, extract features that have a significant impact on sensor sensitivity; for example, geometric parameters (shape, size, thickness), material parameters (relative dielectric constant, vacuum dielectric constant, elastic modulus), etc.; standardize, normalize or encode the features to improve the training efficiency and performance of the model;

[0069] Step S214: Use the training set data to train the model and adjust the model parameters to minimize the loss function (such as mean square error, cross entropy, etc.); during the training process, use the validation set for model selection and early stopping strategy to avoid overfitting;

[0070] Step S215: Use the test set to evaluate the performance of the model and calculate key performance indicators (such as accuracy, recall, F1 score, etc.); according to the evaluation results, tune the model, including adjusting the model architecture, increasing the amount of data, improving feature engineering, etc.

[0071] After the structure parameter picking model is built and trained, it is applied to this solution. In the actual application process, the details are as follows:

[0072] Step S221, preprocessing the sensor structure design data obtained in step S1, including data cleaning, format conversion and feature extraction, etc., to ensure that the input data meets the requirements of the pre-training model;

[0073] Step S222, input the preprocessed data into the pre-trained structural parameter picking model; the structural parameter picking model will process the input data and output a set of key parameters; these parameters are features directly related to sensor sensitivity extracted by the model from the input data, including sensor thickness, electrode spacing, electrode area, relative dielectric constant, vacuum dielectric constant, elastic modulus, etc.;

[0074] Step S223: verify the key parameters of the model output to ensure that they are consistent with the known sensor sensitivity performance parameters; if it is found that the parameters output by the model are significantly different from the actual situation, the model can be fine-tuned or retrained;

[0075] Step S224, integrating the verified key parameters into a sensitive performance structure parameter set; the sensitive performance structure parameter set will be used as input for subsequent steps (such as step S3) to analyze the sensitive performance of the sensor.

[0076] Through step S2, using the pre-trained structural parameter picking model, the key parameters affecting the sensitivity of the sensor can be automatically extracted from the structural design data of the sensor to generate a set of sensitive performance structural parameters; not only the efficiency of parameter extraction is improved, but also human errors are reduced; specifically, through model selection, data preparation, feature engineering, model training, parameter extraction and verification optimization and other steps, the accuracy and reliability of the extracted parameters are ensured, providing high-quality input data for subsequent performance analysis and evaluation.

[0077] Step S3, inputting the sensitivity performance structural parameter set into the sensitivity performance analysis model to obtain the sensor sensitivity performance index under a preset state;

[0078] Similar to the application of the structural parameter picking model in step S2, before application, a sensitivity performance analysis model needs to be constructed, the input of which is sensor thickness, electrode spacing, electrode area, relative dielectric constant, vacuum dielectric constant, and elastic modulus; the core evaluation formula of the sensitivity performance analysis model is:

[0079]

[0080] Among them, C 0is the initial capacitance value, which means the capacitance value of the sensor before the external force acts; ∈ r is the relative dielectric constant, which indicates the dielectric capacity of the medium inside the sensor relative to the air; 0 is the vacuum dielectric constant, a physical constant, about 8.854×10 -12 F / m; A is the electrode area, which indicates the effective area of ​​interaction between the two electrodes; d is the initial electrode spacing, which indicates the initial distance between the two electrodes; C is the new capacitance value after the external force acts, which indicates the capacitance value of the sensor under the external force; Δd ​​is the change in the electrode spacing, which indicates the change in the electrode spacing under the external force; F is the external force applied under the preset state, which indicates the external force acting on the sensor; t is the thickness of the sensor, which indicates the overall thickness of the sensor; E is the elastic modulus, which indicates the ability of the sensor material to resist deformation; SI is the sensor sensitivity performance index.

[0081] In this step, not only the basic physical parameters of the capacitor, such as the initial capacitance value, electrode area, and initial electrode spacing, are considered, but also the new capacitance value and the change in electrode spacing under the preset state due to the external force are introduced. Each parameter in the formula has a clear physical meaning, such as relative dielectric constant, vacuum dielectric constant, elastic modulus, etc., which can directly reflect the influence of sensor materials, structures, and external environment on its sensitive performance. Through the above calculations, the sensitive performance of the capacitive flexible tactile sensor can be systematically evaluated, which not only provides a quantitative evaluation of the sensor performance, but also provides a basis for subsequent environmental calibration and performance comparison.

[0082] Step S4, considering the sensor application conditions, determining the sensor sensitivity performance requirements under the application conditions;

[0083] In step S4, the application scenarios of the sensors need to be analyzed, including understanding in which fields the sensors will be used, such as smart wearables, robots, medical health monitoring, etc., and the specific usage methods in the above fields; specifically, communicate with the end user or application party to understand the specific application scenarios and performance requirements of the sensors; for example, if the sensor is used in a smart wearable device, it is necessary to understand the expected usage scenarios of the device, etc.; consult the technical documents and standard specifications of the relevant application fields to obtain the typical working conditions of the sensors in specific applications; for example, consult the standards and literature in the field of medical health monitoring to understand the performance requirements of the sensors in this field; refer to the actual performance data of similar sensors in the same or similar applications; for example, check the performance data of sensors in existing smart wearable devices to understand common performance indicators and thresholds;

[0084] According to the application conditions analyzed above, determine the sensitivity performance requirements of the sensor under specific conditions; define specific sensitivity performance indicators, which reflect the sensitivity of the sensor under specific conditions; that is, the capacitance change rate of the sensor within a certain pressure range; for example, the capacitance change rate of the sensor within the pressure range of 1kPa to 10kPa should be greater than 0.1%.

[0085] By gaining an in-depth understanding of the application scenarios and fields of sensors, we can ensure that performance evaluation is more targeted and that sensors meet the actual needs of specific applications. By defining specific sensitive performance indicators, such as the capacitance change rate, performance evaluation can be more quantitative and objective, making it easier to compare and analyze. By communicating with end users or application parties, we can more accurately understand the performance requirements of sensors and improve the reliability and effectiveness of sensor design. By referring to technical documents and standard specifications in related fields, we can ensure that the performance requirements of sensors meet industry standards, which will help with market access and customer acceptance of products.

[0086] Step S5, according to the sensor application condition, obtaining the field environment status information corresponding to the application condition; the implementation process of step S5 includes the following aspects:

[0087] Clarify the range of field environments that sensors may encounter in actual applications, including physical environment (such as temperature, humidity, pressure, etc.), mechanical environment (such as vibration, shock, etc.), electrical environment (such as electromagnetic interference, power supply stability, etc.), chemical environment (humidity, pH value, gas composition, etc.) and biological environment (biocompatibility when in contact with the human body, skin conductivity, etc.); the combination and changes of these environmental factors will affect the sensitivity of the sensor;

[0088] Use professional measuring tools and equipment to measure and monitor various environmental indicators at the sensor application site in real time; refer to historical data, industry standards, technical documents, etc. to understand the environmental conditions and changing patterns that may be encountered at the sensor application site; ensure that the collected environmental data is as comprehensive as possible, covering all environmental factors that may affect the performance of the sensor, and that the data is accurate and reliable, and can truly reflect the on-site environmental status;

[0089] Taking smart wearable devices as an example, it is necessary to collect data such as skin temperature, humidity, and external pressure of users in different activity states (such as sitting, walking, running, etc.); this helps to evaluate the performance and stability of the sensor when the wearer is active.

[0090] According to the application conditions of the sensor, clarify the range of on-site environments that the sensor may encounter in actual applications, collect environmental data of the sensor at the actual application site, record and organize environmental information, and ensure the comprehensiveness and accuracy of environmental information.

[0091] Step S6: Considering the on-site environmental status information, environmental calibration is performed on the sensor sensitivity performance index to obtain a calibrated sensor sensitivity performance index; the details are as follows:

[0092] Step S61, extracting a sensor material composition vector from the sensor structure design data information; the sensor material composition vector includes a conductive material type and a dielectric material type; understanding the material composition of the sensor is to accurately evaluate the performance changes of these materials under different environmental conditions in subsequent steps; different materials have different sensitivities to environmental factors such as temperature, humidity, and pressure, so material information is the basis for environmental calibration; extracting the type of conductive material from the sensor structure design data, such as copper, silver, carbon nanotubes, etc.; extracting the type of dielectric material from the sensor structure design data, such as polyimide, polyvinyl alcohol, etc.

[0093] Step S62, based on the sensor material composition vector, determine the environmental feature set that affects the sensitivity of the sensor; the properties of the conductive material (such as conductivity, thermal expansion coefficient) will affect the sensitivity of the sensor at different temperatures and humidities; the properties of the electrical material (such as dielectric constant, hygroscopicity) will affect the sensitivity of the sensor at different humidity and pressure; according to the sensor material composition vector, from all possible environmental factors, screen out environmental factors directly related to the sensor material composition, such as temperature, humidity, electromagnetic field strength, etc.; combine the screened environmental factors into an environmental feature set.

[0094] Step S63, traverse the field environment status information, extract the same environment characteristic parameters as those in the environment characteristic set, and form a field environment characteristic parameter set; traverse the field environment status information collected in step S5, extract the same environment characteristic parameters as those in the environment characteristic set, and form a field environment characteristic parameter set; match the environmental data in the actual application with the predetermined environment characteristic set for subsequent difference calculation and calibration; through this step, it can be ensured that the calibration process is based on the real environment data in the actual application; the field environment characteristic parameter set includes field temperature, field humidity, field pressure and field electromagnetic interference intensity.

[0095] Step S64, calculate the difference between the field environment characteristic parameter set and the corresponding characteristic parameters in the preset state to obtain the field environment parameter deviation set; obtain the characteristic parameter values ​​of the sensor in the standard or preset state, which are measured under laboratory conditions; compare each parameter value in the field environment characteristic parameter set with the corresponding parameter value in the preset state to calculate the difference value; by calculating the difference between the actual environmental parameters and the preset state parameters, the degree of influence of the environment on the sensor performance can be quantified; these differences will be used for subsequent comprehensive calculations to obtain the environmental calibration coefficient; the field environment parameter deviation set includes temperature deviation, humidity deviation, pressure deviation and electromagnetic interference deviation.

[0096] Step S65, comprehensively calculate the field environment parameter deviation set to obtain the environmental calibration coefficient; use appropriate mathematical methods (such as weighted average, weighted square sum, etc.) to comprehensively calculate the field environment parameter deviation set; according to the result of the comprehensive calculation, obtain the environmental calibration coefficient, which reflects the influence of the difference between the field environment and the preset state on the sensitivity performance of the sensor; the comprehensive calculation formula for the field environment parameter deviation set is as follows:

[0097] R=w T ·z T (ΔT)+w H ·z H (ΔH)+w P ·z P (ΔP)+w E ·z E (ΔE)

[0098] Where R is the environmental calibration coefficient; ΔT is the temperature deviation; ΔH is the humidity deviation; ΔP is the pressure deviation; ΔE is the electromagnetic interference deviation; w T represents the weight of temperature deviation; w H represents the weight of humidity deviation; w P Indicates the weight of pressure deviation; w E Represents the weight of electromagnetic interference deviation; z T (ΔT) represents the normalized function of temperature deviation; z H (ΔH) represents the normalized function of humidity deviation; z P (ΔP) represents the normalized function of pressure deviation; z E (ΔE) represents the normalized function of the electromagnetic interference deviation.

[0099] Step S66, multiplying the environmental calibration coefficient by the sensor sensitivity performance index to obtain the calibrated sensor sensitivity performance index; multiplying the sensor sensitivity performance index obtained in step S3 by the environmental calibration coefficient calculated in step S65 to obtain the calibrated sensor sensitivity performance index; by multiplying by the environmental calibration coefficient, adjusting the sensor sensitivity performance index so that it can more accurately reflect the performance in the actual application environment; ensuring that the performance evaluation of the sensor under different environmental conditions is more accurate and reliable.

[0100] In this step, by performing environmental calibration on the sensor, the performance of the sensor in the actual application environment can be more accurately reflected, because it takes into account the impact of environmental factors such as temperature, humidity, pressure and electromagnetic interference on the sensor performance; different application environments have different impacts on sensor performance. Through environmental calibration, the performance of the sensor can be customized for a specific field environment to improve its applicability and reliability under specific conditions; the calibration process is based on the actual collected field environmental data, rather than assumptions or averages, which makes the calibration results more reliable and targeted; by calculating the difference between the field environmental parameters and the preset state parameters, and adjusting the sensor sensitivity performance index accordingly, the measurement error caused by environmental factors can be effectively reduced.

[0101] Step S7, comparing the calibrated sensor sensitivity performance index with the sensor sensitivity performance requirement, determining whether the capacitive flexible tactile sensor to be detected meets the application conditions to be used, and generating a detection result according to the determination result;

[0102] Step S7 evaluates whether the sensor meets the requirements of a specific application condition based on the calibrated sensor sensitivity performance index obtained in the previous step and the preset sensor sensitivity performance requirement; the following is a detailed description of step S7:

[0103] In step S6, the sensor sensitivity performance index has been environmentally calibrated according to the on-site environmental status information to obtain the calibrated sensor sensitivity performance index; in step S4, the sensor sensitivity performance requirements are determined according to the application conditions of the sensor; and the calibrated sensor sensitivity performance index is compared with these sensitivity performance requirements;

[0104] According to the comparison results, it is determined whether the capacitive flexible tactile sensor to be tested meets the application conditions to be used; if the sensitivity performance index of the calibrated sensor meets or exceeds the sensitivity performance requirements, the sensor is judged to be qualified, and a corresponding test result is generated, indicating that the sensor can work normally under the specified application conditions; if the sensitivity performance index of the calibrated sensor does not meet the sensitivity performance requirements, the sensor is judged to be unqualified, and a corresponding test result is generated.

[0105] Through step S7, the calibrated sensor sensitivity performance index can be compared with the sensitivity performance requirements of the sensor under specific application conditions to determine whether the sensor meets the needs of actual applications and generate a detailed test report; ensuring that the performance evaluation of the sensor under different environmental conditions is more accurate and reliable; by obtaining the calibrated sensitivity performance index, obtaining the sensitivity performance requirements, performing performance comparison, determining whether the sensor is qualified, and generating test results, a comprehensive evaluation of the sensor performance is achieved.

[0106] Embodiment 2: Figure 2 As shown, a capacitive flexible tactile sensor sensitivity detection method of the present invention specifically includes the following modules;

[0107] The data acquisition module is used to obtain the structural design data information of the capacitive flexible tactile sensor to be tested and the sensor application conditions; this module is responsible for collecting basic information of the sensor and providing necessary input data for subsequent performance evaluation;

[0108] The structural parameter picking module is used to pick key parameters of the sensor structure design data information using the pre-trained structural parameter picking model to obtain a sensitive performance structural parameter set; this module uses intelligent algorithms to identify and extract key structural parameters that affect the sensor sensitivity to ensure the accuracy of the evaluation;

[0109] The performance analysis module is used to input the sensitive performance structural parameter set into the sensitive performance analysis model to obtain the sensor sensitive performance index under a preset state; based on the input structural parameters, the module uses a mathematical model and algorithm to calculate the theoretical sensitive performance of the sensor;

[0110] A performance requirement determination module is used to determine the sensor sensitivity performance requirements under the application conditions according to the sensor application conditions; this module sets the standards and thresholds for performance evaluation according to the expected use and working environment of the sensor;

[0111] The environment status information acquisition module is used to obtain the on-site environment status information corresponding to the application conditions according to the sensor application conditions; this module is responsible for collecting various environmental parameters that may affect the performance of the sensor in the actual working environment;

[0112] The environmental calibration module is used to perform environmental calibration on the sensor sensitivity performance index considering the on-site environmental status information to obtain the calibrated sensor sensitivity performance index; this module improves the practicality and accuracy of the evaluation by adjusting the theoretical performance index to adapt to the actual working environment;

[0113] The performance comparison and judgment module is used to compare the calibrated sensor sensitivity performance index with the sensor sensitivity performance requirements, determine whether the capacitive flexible tactile sensor to be tested meets the application conditions to be used, and generate a test result based on the judgment result; this module is the final decision point of the evaluation process to ensure that the performance of the sensor meets the actual application requirements;

[0114] The result output module is used to output the results of performance testing, including whether the application conditions are met and the specific sensitivity performance index; this module provides users or systems with clear performance evaluation reports to guide subsequent decisions and actions.

[0115] The various variations and specific embodiments of the capacitive flexible tactile sensor sensitivity detection method in the aforementioned embodiment 1 are also applicable to the capacitive flexible tactile sensor sensitivity detection system of the present embodiment. Through the aforementioned detailed description of the capacitive flexible tactile sensor sensitivity detection method, those skilled in the art can clearly understand the implementation method of the capacitive flexible tactile sensor sensitivity detection system of the present embodiment, so for the sake of brevity of the specification, it will not be described in detail here.

[0116] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor. The transceiver, the memory, and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned method for controlling output data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0117] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A capacitive flexible tactile sensor sensitivity detection method, characterized in that: The method comprises: Obtaining sensor structure design data information and sensor application conditions of the capacitive flexible tactile sensor to be detected; Using a pre-trained structural parameter picking model, key parameters of the sensor structure design data information are picked to obtain a sensitive performance structural parameter set; Inputting the sensitivity performance structural parameter set into the sensitivity performance analysis model to obtain the sensor sensitivity performance index under a preset state; Considering the sensor application conditions, determining the sensor sensitivity performance requirements under the application conditions; According to the sensor application condition, obtaining on-site environmental status information corresponding to the application condition; Considering the on-site environmental status information, performing environmental calibration on the sensor sensitivity performance index to obtain a calibrated sensor sensitivity performance index; The calibrated sensor sensitivity performance index is compared with the sensor sensitivity performance requirement to determine whether the capacitive flexible tactile sensor to be detected meets the application conditions to be used, and a detection result is generated according to the determination result.

2. A capacitive flexible tactile sensor sensitivity detection method as claimed in claim 1, characterized in that: Considering the on-site environmental status information, performing environmental calibration on the sensor sensitivity performance index to obtain the calibrated sensor sensitivity performance index includes: Extracting a sensor material composition vector from the sensor structure design data information; Based on the sensor material composition vector, determining an environmental feature set that affects the sensitivity performance of the sensor; Traversing the on-site environment status information, extracting the same environment characteristic parameters as those in the environment characteristic set, and forming an on-site environment characteristic parameter set; Calculate the difference between the set of on-site environment characteristic parameters and the corresponding characteristic parameters in the preset state to obtain a set of on-site environment parameter deviations; Comprehensively calculating the set of on-site environmental parameter deviations to obtain an environmental calibration coefficient; The environmental calibration coefficient is multiplied by the sensor sensitivity performance index to obtain the calibrated sensor sensitivity performance index.

3. A capacitive flexible tactile sensor sensitivity detection method as claimed in claim 2, characterized in that: The sensor material composition vector includes a conductive material type and a dielectric material type.

4. A capacitive flexible tactile sensor sensitivity detection method as claimed in claim 3, characterized in that: The sensitive performance structural parameter set includes sensor thickness, electrode spacing, electrode area, relative dielectric constant, vacuum dielectric constant and elastic modulus.

5. A capacitive flexible tactile sensor sensitivity detection method as claimed in claim 4, characterized in that: The core evaluation formula of the sensitivity performance analysis model is: Where C0 is the initial capacitance value, which means the capacitance value of the sensor before the external force acts; ε r is the relative dielectric constant, which indicates the dielectric capacity of the medium inside the sensor relative to the air; ∈0 is the vacuum dielectric constant, which is a physical constant, approximately 8.854×10 -12 F / m; A is the electrode area, which indicates the effective area of ​​interaction between the two electrodes; d is the initial electrode spacing, which indicates the initial distance between the two electrodes; C is the new capacitance value after the external force acts, which indicates the capacitance value of the sensor under the external force; Δd ​​is the change in the electrode spacing, which indicates the change in the electrode spacing under the external force; F is the external force applied under the preset state, which indicates the external force acting on the sensor; t is the thickness of the sensor, which indicates the overall thickness of the sensor; E is the elastic modulus, which indicates the ability of the sensor material to resist deformation; SI is the sensor sensitivity performance index.

6. A capacitive flexible tactile sensor sensitivity detection method as claimed in claim 2, characterized in that: The set of on-site environmental characteristic parameters includes on-site temperature, on-site humidity, on-site pressure, and on-site electromagnetic interference intensity.

7. A capacitive flexible tactile sensor sensitivity detection method as claimed in claim 6, characterized in that: The field environment parameter deviation set is comprehensively calculated, and the formula is: R=w T ·z T (ΔT)+w H ·z H (ΔH)+w P ·z P (ΔP)+w E ·z E (ΔE) Where R is the environmental calibration coefficient; ΔT is the temperature deviation; ΔH is the humidity deviation; ΔP is the pressure deviation; ΔE is the electromagnetic interference deviation; w T represents the weight of temperature deviation; w H Represents the weight of humidity deviation; w P Indicates the weight of pressure deviation; w E Represents the weight of electromagnetic interference deviation; z T (ΔT) represents the normalized function of temperature deviation; z H (ΔH) represents the normalized function of humidity deviation; z P (ΔP) represents the normalized function of pressure deviation; z E (ΔE) represents the normalized function of the electromagnetic interference deviation.

8. A capacitive flexible tactile sensor sensitivity detection system, characterized in that: The system comprises: A data acquisition module, used to acquire structural design data information of the capacitive flexible tactile sensor to be detected and sensor application conditions; A structural parameter picking module is used to pick up key parameters of sensor structure design data information using a pre-trained structural parameter picking model to obtain a sensitive performance structural parameter set; A performance analysis module, used to input a set of sensitive performance structure parameters into a sensitive performance analysis model to obtain a sensor sensitive performance index under a preset state; A performance requirement determination module, used to determine the sensor sensitivity performance requirements under the application conditions according to the sensor application conditions; An environmental status information acquisition module is used to acquire on-site environmental status information corresponding to the application condition according to the sensor application condition; An environmental calibration module is used to perform environmental calibration on the sensor sensitivity performance index by considering the on-site environmental status information to obtain the calibrated sensor sensitivity performance index; The performance comparison and judgment module is used to compare the calibrated sensor sensitivity performance index with the sensor sensitivity performance requirement, judge whether the capacitive flexible tactile sensor to be tested meets the application conditions to be used, and generate a test result according to the judgment result; The result output module is used to output the results of the performance test, including the judgment of whether the application conditions are met and the specific sensitivity performance index.

9. An electronic device, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, wherein: When the computer program is executed by the processor, the steps in the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 7 are implemented.

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