A push button switch life detection method, detection device and medium

Abstract

The present invention discloses a method, a detection device and a medium for detecting the life of a button switch. By real-time collection of button usage parameters and physical response signals, signal decoupling technology is used to separate the instantaneous pressing force and the accumulated fatigue damage, and composite damage indicators are calculated based on nonlinear rules. The life prediction module dynamically selects an exponential decay model or a power-law decay model in combination with the total damage amount, and outputs the remaining life assessment result. The device has a built-in calibration unit, which periodically applies standard pressure and collects response signals, and uses a recursive optimization algorithm to dynamically adjust the model sensitivity coefficient and fatigue parameters to ensure long-term stability of the prediction accuracy. The present invention realizes closed-loop control of the entire process from data collection, damage feature extraction to intelligent prediction, significantly improving the accuracy and real-time performance of button life assessment, and effectively reducing the risk of equipment downtime and maintenance costs caused by button failure.

Description

Technical Field

[0001] The present invention relates to the technical field of life detection, and in particular to a method, a detection device and a medium for detecting the life of a push button switch. Background Art

[0002] As a commonly used electromechanical component, push button switches are often affected by various environmental stresses such as mechanical, thermal, electrical, and humidity during use. To ensure product reliability, their reliability needs to be evaluated during device selection and product design.

[0003] Currently, switch lifespan assessment is primarily based on failure statistics. This involves counting failed push button switches and determining their service life, which in turn serves as a reference for assessing the lifespan of similar push button switches.

[0004] Although the failure statistics-based method can determine the life of a push button switch and use it as a reference to determine the life of push button switches of the same type, it cannot accurately reflect the failure changes of the push button switch under the influence of various environmental stresses, resulting in poor accuracy in the life assessment of the push button switch. Summary of the Invention

[0005] (1) Technical issues to be resolved

[0006] To solve the above problems, the present invention proposes a button switch life detection method, detection device and medium, aiming to solve the problem in the prior art that the failure changes of the button switch under the influence of various environmental stresses cannot be accurately reflected.

[0007] (2) Technical solution

[0008] A method for detecting the life of a button switch of the present invention comprises:

[0009] Acquire usage parameter data of the button to be detected, wherein the usage parameter data includes pressing force, pressing frequency and environmental parameters;

[0010] Acquiring historical usage data and a real-time physical response signal of the button to be detected, and generating a damage signature based on the historical usage data and the real-time physical response signal, wherein the real-time physical response signal is obtained by mapping the material properties of the button to be detected;

[0011] The usage parameter data and damage characteristics are input into a life prediction model, and a remaining life evaluation result of the button to be tested is output.

[0012] In the present invention, a real-time physical response signal of the button to be detected is collected each time it is pressed, and the real-time physical response signal includes a resistance value change and an ambient temperature;

[0013] Based on the real-time physical response signal, the instantaneous pressing force is decoupled and the fatigue damage amount is accumulated. A composite damage index is calculated according to a preset rule. The composite damage indexes of all pressing events are accumulated to generate a total damage amount to characterize the degradation degree of the button to be detected.

[0014] In the present invention, the preset rules include:

[0015] Obtaining a resistance value of the button to be detected each time it is pressed, and obtaining a resistance baseline value based on the resistance value;

[0016] Comparing the resistance change with a historical baseline value to calculate a resistance increment, wherein the historical baseline value is obtained by recording the resistance baseline value of each press;

[0017] Based on the resistance increment and the pressing force, the instantaneous load and the historical damage effect are fused through a nonlinear function to generate the composite damage index.

[0018] In the present invention, the construction of the life prediction model includes:

[0019] According to the relationship between the total damage amount and the preset critical value, an exponential decay model or a power law decay model is selected to calculate the remaining life;

[0020] When the total damage amount is less than or equal to the critical value, an exponential decay model is adopted;

[0021] When the total damage amount is greater than the critical value, the power law decay model is switched to match the physical characteristics of the accelerated degradation stage.

[0022] The present invention also includes:

[0023] Real-time physical response signals under standard pressure are periodically collected, and the parameters of the life prediction model are dynamically calibrated through a recursive optimization algorithm to compensate for model drift caused by material aging or environmental interference.

[0024] In the present invention, the recursive optimization algorithm includes:

[0025] Adjusting the pressing force sensitivity coefficient and the fatigue accumulation rate constant based on the deviation between the measured signal and the theoretical signal under standard pressure;

[0026] The parameter weights are updated through the covariance matrix to ensure the convergence and stability of the calibration process.

[0027] In the present invention, the environmental parameters include temperature and humidity, and the method further includes:

[0028] An environmental compensation term is introduced into the composite damage feature data to eliminate the interference of temperature and humidity changes on the physical response signal.

[0029] Another push button switch life detection device of the present invention implements the push button switch life detection method described in any one of the above technical solutions, and the push button switch life detection device includes:

[0030] a data acquisition unit configured to acquire usage parameter data and physical response signals of the button in real time;

[0031] a feature extraction unit configured to generate composite damage feature data based on the physical response signal;

[0032] a life prediction unit configured to input the usage parameter data and the composite damage feature data into a life prediction model and output a remaining life assessment result;

[0033] A calibration unit is configured to adjust the coefficients of the life prediction model through periodic parameter optimization.

[0034] In the present invention, the feature extraction unit includes:

[0035] a signal decoupling module configured to separate the pressing force and the accumulated fatigue damage from the physical response signal;

[0036] a damage calculation module configured to calculate a composite damage index of a single compression based on a preset nonlinear rule and accumulate the calculated damage index to generate a total damage amount;

[0037] The life prediction unit includes:

[0038] a model switching module configured to select an exponential decay model or a power law decay model according to a relationship between the total damage amount and a preset critical value;

[0039] a dynamic prediction module configured to output a remaining life assessment result based on a selected model;

[0040] The calibration unit is configured to:

[0041] Applying standard pressure and collecting corresponding physical response signals, and updating the sensitivity coefficient and fatigue parameters of the life prediction model through a recursive optimization algorithm.

[0042] Another computer-readable storage medium of the present invention stores a computer program thereon, characterized in that when the program is executed by a processor, the button switch life detection method described in any one of the above technical solutions is implemented.

[0043] (3) Beneficial effects

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] (1) In the present invention, the composite damage characteristics and the dual-model (exponential / power-law decay) dynamic switching mechanism are used to accurately match the degradation laws of buttons at different damage stages and reduce the error of a single model. The standard pressure signal is periodically collected and the model parameters are optimized to effectively compensate for material performance drift and environmental interference, thereby ensuring long-term detection reliability.

[0046] (2) The present invention separates the pressing force and fatigue damage from the physical response signal, avoiding the destructive testing of the switch by traditional methods, reducing the detection cost, automatically completing signal decoupling, damage calculation, model selection and life output, reducing manual intervention and improving detection efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 This is a schematic diagram in Example 1;

[0049] Figure 2 Schematic diagram of the curve of resistance value changing with pressing force;

[0050] Figure 3 Schematic diagram of the curve of resistance value changing with the number of presses;

[0051] Figure 4 Schematic diagram of the curve change of the segmented life prediction model. DETAILED DESCRIPTION

[0052] Example

[0053] like Figure 1-Figure 4 The method for detecting the life of a button switch comprises the following steps:

[0054] S100: Acquire usage parameter data of a button to be detected, where the usage parameter data includes pressing force, pressing frequency, and environmental parameters.

[0055] Carbon nanotube / polymer composite material is used as the piezoresistive material of the button contact, and its resistance value changes linearly with the pressing force, satisfying the relationship ,in Indicates the acquisition resistance value, is the initial resistance value, is the pressure sensitivity coefficient, is the temperature coefficient, Indicates the The ambient temperature when the first press is pressed, The reference temperature is calibrated to 25°C. Carbon nanotube / polymer composites are novel nanocomposites with carbon nanotubes (CNTs) as the reinforcement phase and a polymer as the matrix. Their core properties and value lie in the complementary performance of carbon nanotubes and polymers through nanoscale structural integration, resulting in materials with excellent mechanical, electrical, thermal, and functional properties.

[0056] S200. Obtain historical usage data and a real-time physical response signal of the button to be detected, and generate a damage signature based on the historical usage data and the real-time physical response signal, wherein the real-time physical response signal is obtained by mapping the material characteristics of the button to be detected.

[0057] The resistance change is converted into a voltage signal through an embedded Wheatstone bridge circuit, which is then input into an analog-to-digital converter (ADC) after amplification and filtering to acquire the resistance value at a sampling rate of 1 kHz. The pressing force directly affects the mechanical load strength of a single press and is an indicator of composite damage. A greater pressing force will accelerate material fatigue and lead to faster life decay.

[0058] The ambient temperature is converted into a voltage signal through the integrated micro NTC thermistor through a voltage divider circuit, and then converted into a temperature value after being collected by the ADC. The linear change of resistivity of carbon nanotube / polymer composites with pressure has been widely verified (such as the literature ACS Appl. Mater. Interfaces 2015, 7, 5484), but the hysteresis effect and nonlinear response of the material must be considered in practical applications. This type of error can be partially compensated. The expression of the corrected acquisition resistance value is: ,in represents the fatigue rate constant, which characterizes the damage rate of the material due to the increase in the number of pressing times. is the cumulative number of presses, Indicates the crack growth index, which describes the acceleration effect of damage as the number of presses increases. Can directly decouple the pressing force and cumulative damage , no external force sensors are required.

[0059] A real-time physical response signal is collected each time the button to be tested is pressed. The real-time physical response signal includes a change in resistance value and ambient temperature. The real-time physical response signal refers to a real-time measurable signal of a change in physical quantity generated by a smart material (such as a carbon nanotube / polymer composite material) during the use of the button, and is used to characterize the instantaneous load and cumulative damage state of the button.

[0060] Based on the real-time physical response signal, the instantaneous pressing force is decoupled to accumulate fatigue damage, and the electric shock resistance value of the button to be tested is obtained each time it is pressed. Before the button is used for the first time, the initial resistance value of the smart material is calibrated experimentally under no load and standard environment (such as 25℃, 50%RH). For example, a high-precision multimeter is used to measure the resistance of the carbon nanotube / polymer composite contact, and the average value of multiple measurements is taken as .

[0061] After each press, record the current resistance value , and use it as the baseline value for the next press, that is, , for example, Measured after pressing , then The baseline value of the compression is .

[0062] The historical baseline value is the accumulation of the resistance baseline value, which is calculated by calculating the difference between the current resistance and the historical baseline. , which directly reflects the material damage caused by a single press, that is, the resistance increase.

[0063] Combined pressure , through nonlinear functions, such as logarithmic functions, power functions, exponential functions, etc., the present disclosure mainly generates composite damage indicators through logarithmic functions: , accumulate all composite damage indices Get the total damage , as the core output of lifespan prediction, e.g. After pressing , indicating the overall degradation of the button. Exceeding the critical value When the crack propagation rate reaches 0.000, the model switches to a power-law decay, reflecting the nonlinear failure during the accelerated crack propagation phase. The continuous updating of the baseline value forms a closed-loop feedback loop, reflecting changes in the material state in real time. For example, if the material resistance continues to rise due to fatigue, the baseline value will be adjusted synchronously, avoiding the cumulative error caused by the fixed baseline.

[0064] S300: Input the usage parameter data and damage characteristics into a life prediction model, and output a remaining life evaluation result of the button to be tested.

[0065] Preset damage threshold ,like The life prediction model disclosed in this paper includes exponential decay and power law decay, where exponential decay simulates the uniform fatigue of the material in the early stage, and the damage rate is independent of the current life; power law decay reflects the acceleration effect of crack extension in the late stage, which conforms to the law of fracture mechanics. The specific expression is: initial stage ,in is the remaining life, Indicates the rated life, is the initial attenuation coefficient; in the later stage ,in Indicates the maximum allowable damage. is the late power law index. In this disclosure, , , for example when hour The model parameters are dynamically calibrated by recursive least squares (RLS) to suppress drift. After a certain number of presses, a standard pressure is applied. , measuring resistance And calculate the theoretical value If the actual measurement , and the theoretical value ,deviation Trigger parameter update. Update the parameter vector using the RLS algorithm :

[0066] , where the observation vector , observed values , the covariance matrix Initialized to For example, after the fifth calibration you might get , the covariance matrix norm decreases by 15%, indicating that the parameters converge.

[0067] The model output was optimized through experimental verification, and the 100 button sample test showed the correlation coefficient between the predicted life and the actual life , the 95% confidence interval is After environmental interference is suppressed, the impact of temperature and humidity is greatly reduced. This model achieves high-precision lifespan assessment through a closed loop of "signal-damage-prediction-calibration."

[0068] Example

[0069] A device for detecting the life of a button switch, the core of which is the integration of four functional modules: data acquisition, feature analysis, life prediction, and model calibration. By combining multi-dimensional parameter monitoring with intelligent algorithms, it can achieve an accurate assessment of the remaining service life of the button switch. The device first continuously obtains the real-time usage parameters of the button switch during operation through the data acquisition unit, including operating status data such as voltage, current, and operating frequency, and at the same time collects physical response signals such as mechanical vibration, sound, and contact resistance. These raw data are transmitted to the feature extraction unit, which has a built-in signal decoupling module that can separate the dynamic characteristic parameters reflecting the change in pressing force and the damage characteristic parameters characterizing the accumulation of material fatigue from the mixed signal. Furthermore, the damage calculation module performs a quantitative damage assessment on each pressing operation according to the preset nonlinear damage evolution law, and continuously accumulates the total damage index.

[0070] The life prediction unit utilizes a dual-model collaborative mechanism, comprising a model switching module and a dynamic prediction module. Based on the comparison of the total damage volume with a preset critical threshold, the system automatically selects either an exponential decay model or a power-law decay model for life prediction. When damage is in its early stages, the exponential model, which accurately describes early performance degradation, is used; as the lifespan approaches its end, the power-law model, which better reflects late-stage failure characteristics, is switched to. The dynamic prediction module, based on the selected model and combined with real-time parameter data, outputs a dynamically updated remaining life assessment result.

[0071] To ensure prediction accuracy, the device is also equipped with a self-calibration unit. This unit periodically applies a standard pressure load, synchronously collects the corresponding standardized physical response signals, and uses a recursive optimization algorithm to iteratively correct the sensitivity coefficients and fatigue characteristic parameters in the life prediction model. This periodic model parameter optimization mechanism effectively compensates for prediction deviations caused by material property drift and changes in environmental factors, enabling the device to maintain high prediction accuracy over the long term. The entire detection process achieves complete closed-loop control, from raw signal acquisition, damage feature extraction, intelligent model prediction, to adaptive calibration, significantly improving the reliability and prediction accuracy of push button switch life detection.

[0072] Example

[0073] An embodiment of the present invention provides a computer-readable storage medium.

[0074] The computer-readable storage medium provided in the embodiment of the present invention stores a computer program, and when the computer program is executed by a processor, the steps of any one of the above-mentioned methods for detecting the life of a push button switch can be implemented.

[0075] The computer-readable storage medium may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., which can store program codes.

[0076] For an introduction to the computer-readable storage medium provided in an embodiment of the present invention, please refer to the above method embodiment, and the present invention will not elaborate on it here.

[0077] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0078] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0079] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein may be implemented directly using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0080] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the concept and scope of the present invention. Any modifications and improvements made to the technical solution of the present invention by a person of ordinary skill in the art without departing from the design concept of the present invention shall fall within the scope of protection of the present invention. The technical content for which protection is sought in the present invention is fully set forth in the claims.

Claims

1. A method for detecting the life of a button switch, characterized in that: include: Acquire usage parameter data of the button to be detected, wherein the usage parameter data includes pressing force, pressing frequency and environmental parameters; Acquiring historical usage data and a real-time physical response signal of the button to be detected, and generating a damage signature based on the historical usage data and the real-time physical response signal, wherein the real-time physical response signal is obtained by mapping the material properties of the button to be detected; Inputting the usage parameter data and damage characteristics into a life prediction model, and outputting a remaining life assessment result of the button to be tested; Collecting a real-time physical response signal of the button to be detected each time it is pressed, wherein the real-time physical response signal includes a resistance value change and an ambient temperature; Decoupling the instantaneous pressing force based on the real-time physical response signal to accumulate fatigue damage, calculating a composite damage index using a preset rule, and accumulating the composite damage indexes of all pressing events to generate a total damage amount to characterize the degradation degree of the button to be detected; Obtaining a resistance value of the button to be detected each time it is pressed, and obtaining a resistance baseline value based on the resistance value; Comparing the resistance change with a historical baseline value to calculate a resistance increment, wherein the historical baseline value is obtained by recording the resistance baseline value of each press; Based on the resistance increment and the pressing force, the composite damage index is generated by fusing the instantaneous load and the historical damage effect through a nonlinear function; According to the relationship between the total damage amount and the preset critical value, an exponential decay model or a power law decay model is selected to calculate the remaining life; When the total damage amount is less than or equal to the critical value, an exponential decay model is adopted; When the total damage amount is greater than the critical value, the power law decay model is switched to match the physical characteristics of the accelerated degradation stage.

2. The method for detecting the life of a push button switch according to claim 1, wherein: Also includes: Real-time physical response signals under standard pressure are periodically collected, and the parameters of the life prediction model are dynamically calibrated through a recursive optimization algorithm to compensate for model drift caused by material aging or environmental interference.

3. The method for detecting the life of a push button switch according to claim 2, wherein: The recursive optimization algorithm includes: Adjusting the sensitivity coefficient of the pressing force and the fatigue accumulation rate constant based on the deviation between the measured signal and the theoretical signal under the standard pressure; The parameter weights are updated through the covariance matrix to ensure the convergence and stability of the calibration process.

4. The method for detecting the life of a push button switch according to claim 3, wherein: The environmental parameters include temperature and humidity, and the method further includes: An environmental compensation term is introduced into the damage characteristics to eliminate the interference of temperature and humidity changes on the physical response signal.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the push button switch life detection method according to any one of claims 1 to 4 is implemented.

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