A calibration and repair management system and management method for optical detection equipment

Abstract

The present invention discloses a calibration and repair management system for optical detection equipment and a management method thereof, and specifically relates to the technical field of optical detection equipment calibration, comprising the following steps: firstly, determining whether a current measurement error exceeds a standard through a standard test, and if so, calculating an environmental variation coefficient; then obtaining the current measurement error, the environmental variation coefficient and the number of calibrations, performing fuzzy reasoning, selecting an appropriate calibration strategy and executing calibration; if the measurement error still exceeds the standard after calibration, repairing the relevant optical elements or control components; and looping the above steps until the measurement error meets a preset standard; the present invention can dynamically adjust the calibration strategy, adapt to different environmental change conditions, reduce the need for frequent recalibration, ensure the measurement accuracy of the optical detection equipment under different environmental conditions, and can not only comprehensively correct the measurement error of the equipment in stable and dynamic environments, but also ensure the high accuracy and reliability of the equipment in long-term use through a cyclic calibration mechanism.

Description

Technical Field

[0001] The present invention relates to the technical field of optical detection equipment calibration, and more specifically, to a calibration and repair management system and a management method thereof for optical detection equipment. Background Art

[0002] Optical inspection equipment has been widely used in industries such as industry, medicine, and scientific research. Its core task is to precisely measure the target object through optical components to obtain high-precision data. However, the measurement accuracy of optical inspection equipment is affected by many factors, such as the state of the optical components of the equipment itself, changes in environmental conditions, and the service life of the equipment. These factors will lead to the accumulation of measurement errors, thus affecting the final measurement results.

[0003] Traditional single calibration methods often fail to take into account the various working states of equipment in complex application scenarios. Especially in the fields of industrial automation and intelligent manufacturing, equipment often operates in a changing environment, requiring calibration methods to intelligently optimize the calibration process and achieve high-precision measurement of equipment under various conditions of use. Therefore, a calibration and repair management system for optical detection equipment and its management method are proposed. Summary of the invention

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A calibration and repair management method for an optical detection device comprises the following steps:

[0006] Step 1: Use standard test procedures to perform performance tests on the optical inspection equipment to determine whether the current measurement error exceeds the preset standard. If the current measurement error is within the allowable range, continue to use the equipment. If it exceeds the preset standard, quantify the degree of influence of the environment on the optical inspection equipment by calculating the environmental variation coefficient to obtain the environmental variation coefficient;

[0007] Step 2: Obtain the current measurement error, environmental variation coefficient, and calibration times of the optical detection device, perform fuzzy reasoning, and decide to execute a corresponding preset calibration strategy according to the result of the fuzzy reasoning;

[0008] Step 3: Calibrate the optical detection equipment based on the calibration strategy obtained by fuzzy reasoning;

[0009] Step 4: After each calibration, if the current measurement error after the execution of the calibration strategy still exceeds the preset standard, the optical element or control component corresponding to the calibration strategy is repaired;

[0010] Step 5: loop through steps 2, 3 and 4 until the current measurement error of the optical detection device meets the preset standard.

[0011] In a preferred embodiment, the logic for obtaining the current measurement error is:

[0012] Measure the performance of optical inspection equipment according to standard test procedures and obtain actual output measurements of the equipment , make multiple measurements and record multiple measurement values , and obtain the measurement time series X: , , …, , n is the total number of measured data, obtain the standard reference value for comparison For each measurement, the deviation between it and the standard reference value is calculated, which is called the single measurement error. , ; i represents the i-th measurement;

[0013] Then, based on all the single measurement errors Calculate the average measurement error , and the standard deviation of the measurement error , the current measurement error refers to the average measurement error and the standard deviation of the measurement error Summarize the resulting error combinations.

[0014] In a preferred embodiment, determining whether the current measurement error exceeds a preset standard refers to:

[0015] An allowable measurement error range is set for the optical detection device in advance, which is recorded as the error tolerance. Another allowable error discrete threshold is also set. The current measurement error, that is, the average measurement error in the error combination, is The standard deviation of the measurement error is compared with the error tolerance. Compared with the error discrete threshold, if the average measurement error is satisfied The standard deviation of the measurement error falls within the error tolerance If the average measurement error is not greater than the discrete error threshold, the current measurement error does not exceed the preset standard; if the average measurement error is not satisfied The standard deviation of the measurement error falls within the error tolerance If it is not greater than the error discrete threshold, the current measurement error exceeds the preset standard.

[0016] In a preferred embodiment, the logic for obtaining the environmental variation coefficient is:

[0017] Select multiple preset environmental parameters, collect the change data of the preset multiple environmental parameters in real time, obtain the curves of the preset multiple environmental parameters changing with time, standardize the change range of all parameters to the [0,1] interval, calculate the change rate of each standardized environmental parameter, set a fixed time sampling interval Δt, and use the difference formula to approximate the derivative to obtain the change rate of the environmental parameter. The formula is expressed as:

[0018] ; represents the standardized value of the i-th environmental parameter corresponding to time t, represents the change rate of the i-th environmental parameter. Each environmental parameter is assigned a weight wi and the sum of all weights wi is 1. The weighted sum of the change rates of all environmental parameters is obtained to obtain the comprehensive environmental change coefficient. The calculation formula is: ; n is the number of environmental parameters, Represents the environmental variation coefficient corresponding to the test time t.

[0019] In a preferred embodiment, the preset calibration strategy refers to three calibration strategies: static calibration, dynamic calibration, and joint calibration, and one of them corresponds to the result of fuzzy reasoning when executed.

[0020] In a preferred embodiment, the logic of fuzzy reasoning is: obtain the average measurement error, standard deviation of the measurement error, environmental variation coefficient, and number of calibration times in the current measurement error of the optical detection device as input variables, use the type of calibration strategy as the output variable, fuzzify the input variables, convert the values ​​of the input variables into fuzzy sets, fuzzify the output variables, convert the output variables into fuzzy sets, formulate fuzzy rules, describe the calibration requirements under different data type combinations, reason with the fuzzified input variables through fuzzy rules, and determine the type of calibration strategy suitable for the optical detection device.

[0021] In a preferred embodiment, static calibration refers to:

[0022] Establish a static error model and use a linear model to express it:

[0023] ; is the error term, a and b are both model parameters, and the data pair refers to the use of the optical detection equipment to be calibrated to measure multiple data points that are the same as the reference standard. The data obtained at each data point is expressed as , i represents the i-th measurement data point, and the objective function is defined as the residual sum of squares. The goal is to minimize the difference between the actual measurement value and the model prediction value, find the optimal parameters a and b that minimize the residual sum of squares, and then adjust the output of the optical detection equipment according to the obtained optimal parameters a and b.

[0024] In a preferred embodiment, dynamic calibration refers to:

[0025] Select and set an initial filter structure, such as a mean filter or a weighted moving average filter. The initial parameters are set based on prior knowledge of the device. Then define an error function for evaluating the filter performance, such as the mean square error (MSE). The error function represents the deviation between the filter output and the target value. The real-time measurement data is input and processed through the initial filter to obtain the filtered output. Then, the error between the current filter output and the actual measurement value is calculated, which is the value of the error function.

[0026] The filter parameters are adjusted using the LMS algorithm to minimize the error function. The parameter update formula is:

[0027] ; are the filter parameters, is the learning rate, is the average measurement error in the current measurement error, The input signal is the adjusted filter that gradually adapts to the dynamic changes of the optical detection equipment, making its output closer to the actual measurement value. When the filter parameters gradually converge and the error function value tends to be stable, the calibration is considered to be completed and the optical detection equipment has achieved the best measurement accuracy under the current dynamic conditions.

[0028] In a preferred embodiment, joint calibration refers to:

[0029] Based on static calibration and dynamic calibration, a joint objective function is defined, which is expressed as:

[0030] ; J represents the value of the joint objective function, , are all preset weight factors. represents the value of the objective function in static calibration, Represents the value of the error function in dynamic calibration;

[0031] Generate an initial parameter population. Each individual in the population represents a set of corresponding calibration parameters. A set of corresponding calibration parameters includes a static calibration parameter combination and a dynamic calibration parameter group. Set the population size N. For each individual in the population, calculate its fitness value. The goal is to minimize J, that is, to find the parameter combination that minimizes the static and dynamic calibration errors. The fitness function F is defined as: ; C is a non-negative constant to prevent the denominator from being zero, and the fitness F of each parameter combination is calculated;

[0032] Selection operation: Use the roulette wheel selection method to select offspring as new parents;

[0033] Crossover operation: randomly exchange data in chromosomes of different parents;

[0034] Mutation operation: randomly select data of different offspring chromosomes for adjustment;

[0035] Iteration and termination condition: Iterate until the preset termination condition is met, and after the genetic algorithm iteration is completed, the individual with the highest fitness is selected as the final joint calibration parameter combination.

[0036] In a preferred embodiment, a calibration and repair management system for optical detection equipment includes:

[0037] A performance test module is used to perform a performance test on the optical inspection equipment using a standard test procedure to determine whether the current measurement error exceeds a preset standard;

[0038] An environmental impact analysis module is used to quantify the degree of environmental impact on the optical detection equipment by calculating the environmental variation coefficient when the current measurement error exceeds the preset standard to obtain the environmental variation coefficient;

[0039] An inference module, used to perform fuzzy inference according to the current measurement error, environmental variation coefficient, and the number of calibrations of the optical detection device, and to decide to execute a corresponding preset calibration strategy according to the result of the fuzzy inference;

[0040] A calibration execution module, used for calibrating the optical detection device based on a calibration strategy obtained by fuzzy reasoning;

[0041] The inspection module is used to inspect whether the current measurement error after the execution of the calibration strategy still exceeds the preset standard after each calibration. If it still exceeds the preset standard, the optical elements or control components corresponding to the calibration strategy are repaired, and the calibration is performed cyclically until the current measurement error of the optical detection equipment meets the preset standard.

[0042] Technical effects and advantages of the present invention:

[0043] The present invention can significantly improve the measurement accuracy of optical detection equipment under different environmental conditions by combining static calibration and dynamic calibration. Static calibration handles the systematic errors of the equipment in a stable environment, while dynamic calibration can deal with the measurement errors caused by environmental changes in real time. This combined calibration method ensures that the equipment can output high-precision measurement results regardless of whether it is in a static or dynamic environment.

[0044] Through the quantitative analysis of the environmental variation coefficient, the present invention can dynamically adjust the calibration strategy to adapt to different environmental variation conditions. This method improves the adaptability of the device to complex and changing environments, enables the device to maintain stable measurement accuracy during long-term use, and reduces the need for frequent recalibration.

[0045] By applying fuzzy reasoning technology, the present invention can automatically select the most appropriate calibration strategy according to the current state of the equipment and environmental conditions. Through fuzzy processing and rule reasoning of input variables, the system can intelligently judge the calibration requirements and execute the optimal calibration strategy, thus improving the efficiency and accuracy of calibration management.

[0046] The inspection module checks the measurement error after each calibration to ensure that the calibration effect of the equipment meets the preset standard. If the error still exceeds the standard, the system will automatically trigger the repair of the optical element or control component. This cyclic calibration and repair mechanism reduces the failure rate of the equipment, extends the service life of the equipment, and thus reduces maintenance costs. Through the application of genetic algorithms, the present invention can effectively avoid falling into the situation of local optimal solutions during the calibration parameter optimization process. Genetic algorithms maintain the diversity of the population through selection, crossover and mutation operations, explore a wider parameter space, and finally find the globally optimal calibration parameter combination. This enables the device to maintain optimal measurement performance under various operating environments.

[0047] The calibration and repair management method of the present invention can not only comprehensively correct the measurement errors of the equipment in stable and dynamic environments, but also ensure the high accuracy and reliability of the equipment in long-term use through a cyclic calibration and repair mechanism. The implementation of joint calibration enables the equipment to maintain consistent high-quality measurement performance under laboratory conditions and in practical applications. The present invention can still maintain high decision-making accuracy and stability in complex and changeable detection environments, and is suitable for the optimization of optical detection equipment in various industrial scenarios, with broader application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0049] Figure 1 This is a schematic diagram of a calibration and repair management method for an optical detection device in the present invention.

[0050] Figure 2 The schematic diagram is a calibration and repair management system for an optical detection device in the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] Reference Figure 1 - Figure 2 The following examples are obtained:

[0053] Embodiment 1: A calibration and repair management method for an optical detection device comprises the following steps:

[0054] Step 1: Use standard test procedures to perform performance tests on the optical inspection equipment to determine whether the current measurement error exceeds the preset standard. If the current measurement error is within the allowable range, continue to use the equipment. If it exceeds the preset standard, quantify the degree of influence of the environment on the optical inspection equipment by calculating the environmental variation coefficient to obtain the environmental variation coefficient;

[0055] Step 2: Obtain the current measurement error, environmental variation coefficient, and calibration times of the optical detection device, perform fuzzy reasoning, and decide to execute a corresponding preset calibration strategy according to the result of the fuzzy reasoning;

[0056] Step 3: Calibrate the optical detection equipment based on the calibration strategy obtained by fuzzy reasoning;

[0057] Step 4: After each calibration, if the current measurement error after the execution of the calibration strategy still exceeds the preset standard, the optical element or control component corresponding to the calibration strategy is repaired;

[0058] Step 5: loop through steps 2, 3 and 4 until the current measurement error of the optical detection device meets the preset standard.

[0059] The current measurement error acquisition logic is:

[0060] Measure the performance of optical inspection equipment according to standard test procedures and obtain actual output measurements of the equipment , make multiple measurements and record multiple measurement values , and obtain the measurement time series X: , , …, , n is the total number of measured data, obtain the standard reference value for comparison For each measurement, the deviation between it and the standard reference value is calculated, which is called the single measurement error. , ; i represents the i-th measurement;

[0061] Then, based on all the single measurement errors Calculate the average measurement error , and the standard deviation of the measurement error , the current measurement error refers to the average measurement error and the standard deviation of the measurement error Summarize the resulting error combinations.

[0062] Determining whether the current measurement error exceeds the preset standard refers to:

[0063] An allowable measurement error range is set for the optical detection device in advance, which is recorded as the error tolerance. Another allowable error discrete threshold is also set. The current measurement error, that is, the average measurement error in the error combination, is The standard deviation of the measurement error is compared with the error tolerance. Compared with the error discrete threshold, if the average measurement error is satisfied The standard deviation of the measurement error falls within the error tolerance If the average measurement error is not greater than the discrete error threshold, the current measurement error does not exceed the preset standard; if the average measurement error is not satisfied The standard deviation of the measurement error falls within the error tolerance If it is not greater than the error discrete threshold, the current measurement error exceeds the preset standard.

[0064] The logic for obtaining the environmental variation coefficient is:

[0065] Select multiple preset environmental parameters, collect the change data of the preset multiple environmental parameters in real time, obtain the curves of the preset multiple environmental parameters changing with time, standardize the change range of all parameters to the [0,1] interval, and calculate the change rate of each standardized environmental parameter (i.e., the time derivative): ; Environmental parameters The rate of change at time t describes the speed at which the environmental parameters change over time. If a fixed time sampling interval Δt is further set, the rate of change of the environmental parameters is obtained by approximating the derivative using the differential formula. The formula is expressed as:

[0066] ; represents the standardized value of the i-th environmental parameter corresponding to time t, represents the change rate of the i-th environmental parameter. Each environmental parameter is assigned a weight wi and the sum of all weights wi is 1. The weighted sum of the change rates of all environmental parameters is obtained to obtain the comprehensive environmental change coefficient. The calculation formula is: ; n is the number of environmental parameters, Represents the environmental variation coefficient corresponding to the test time t.

[0067] The preset calibration strategies refer to three calibration strategies: static calibration, dynamic calibration, and joint calibration, and one of them corresponds to the result of fuzzy reasoning when executed.

[0068] The logic of fuzzy reasoning is: obtain the average measurement error, standard deviation of measurement error, environmental variation coefficient, and number of calibration times in the current measurement error of the optical detection equipment as input variables, take the type of calibration strategy as the output variable, fuzzify the input variables, convert the values ​​of the input variables into fuzzy sets, fuzzify the output variables, convert the output variables into fuzzy sets, formulate fuzzy rules, describe the calibration requirements under different data type combinations, reason with the fuzzified input variables through fuzzy rules, and determine the type of calibration strategy suitable for the optical detection equipment.

[0069] Obtain the four key input variables of the optical inspection equipment: Average measurement error, which is the average deviation value of the equipment in multiple measurements. Standard deviation of measurement error, which measures the degree of fluctuation of the equipment measurement error and reflects the stability of the measurement results. Environmental variation coefficient, which quantifies the dynamic changes in the equipment working environment, such as the comprehensive change range of multiple preset environmental factors such as temperature and humidity. Number of calibrations, which records the number of calibrations that have been performed on the equipment, reflects the current status of the equipment and possible aging.

[0070] The calibration strategy type is the output variable that needs to be determined in the end, including three different strategies: static calibration, dynamic calibration or joint calibration. The average measurement error will be fuzzified into three ranges: low, medium and high. For example, a measurement error below 0.1 is low, between 0.1 and 0.5 is medium, and more than 0.5 is high. The standard deviation of the measurement error is fuzzified into three ranges: stable, medium fluctuation, and large fluctuation. A small standard deviation means that the measurement result is stable, and a large standard deviation means that the measurement result fluctuates greatly. The environmental variation coefficient is fuzzified into three ranges: small, medium and large. Small changes mean that the environment is basically stable, and large changes mean that the environment changes frequently and with large amplitudes. The number of calibrations is fuzzified into three ranges: few, moderate and many. Few means that the equipment is new or has just been calibrated, and many means that the equipment has been used for a long time or has been calibrated many times. The calibration strategy type is fuzzified into three ranges: static calibration, dynamic calibration and joint calibration.

[0071] Based on experience or expert knowledge, develop a set of rules that describe the calibration strategy to be selected for different combinations of input variables. For example: If the average measurement error is high, the standard deviation of the measurement error fluctuates greatly, the environmental variation coefficient is large, and the number of calibrations is high, then joint calibration should be selected. If the average measurement error is moderate, the standard deviation of the measurement error fluctuates moderately, the environmental variation coefficient is moderate, and the number of calibrations is moderate, then dynamic calibration should be selected. If the average measurement error is low, the standard deviation of the measurement error is stable, the environmental variation coefficient is small, and the number of calibrations is low, then static calibration should be selected.

[0072] Substitute the fuzzification results of the input variables into the fuzzy rules, and derive the calibration strategy suitable for the current optical detection equipment through fuzzy reasoning. For example: if the average measurement error of the current equipment is 0.3, the standard deviation is 0.15, the environmental variation coefficient is 0.2, and the number of calibrations is 2, the following fuzzy results can be derived: the average measurement error is medium, the standard deviation of the measurement error is medium fluctuation, the environmental variation coefficient is medium, and the number of calibrations is moderate. According to the above fuzzy rules, such a combination usually corresponds to a dynamic calibration strategy. Therefore, the equipment should perform dynamic calibration in this environment.

[0073] Static calibration refers to:

[0074] Select reference standard: determine the standard reference value used for calibration, which usually comes from a certified calibration standard or high-precision equipment. Actual measurement: use the optical inspection equipment to be calibrated, measure multiple data points that are the same as the reference standard, and record the actual measurement values. Collect data pairs: obtain a set (or multiple sets) of data pairs , where i represents the i-th data point.

[0075] Establish a static error model and use a linear model to express it:

[0076] ; is the error term, a and b are both model parameters, and the data pair refers to the use of the optical detection equipment to be calibrated to measure multiple data points that are the same as the reference standard. The data obtained at each data point is expressed as , i represents the i-th measurement data point, and the objective function is defined as the residual sum of squares. The goal is to minimize the difference between the actual measurement value and the model prediction value, find the optimal parameters a and b that minimize the residual sum of squares, and then adjust the output of the optical detection equipment according to the obtained optimal parameters a and b. The objective function is expressed as:

[0077] ; Here represents the data obtained from the i-th measurement data point, N is the total number of samples measured, Represents the objective function, through the objective function Derivative a and b respectively, and set the derivative to zero, to find the optimal parameters a and b that minimize the residual sum of squares. Adjust the output of the device based on the obtained optimal parameters a and b. For example, calibrate the actual measured value of the device: ; Represents the corrected output. Static calibration through the least squares method can effectively fit the measurement error of the equipment and obtain the calibration parameters, thereby adjusting the measurement output of the equipment, reducing the error and improving the measurement accuracy.

[0078] An adaptive filter is an algorithm that adjusts filter parameters in real time and is suitable for situations where environmental conditions change or system characteristics are uncertain. The following are the specific steps in the dynamic calibration of an adaptive filter:

[0079] Select initial filter: Select and set an initial filter structure, such as a mean filter or a weighted moving average filter. The initial parameters can be set based on prior knowledge of the device.

[0080] Define an error function: Define an error function such as mean square error (MSE) for evaluating filter performance, which represents the deviation between the filter output and the target value.

[0081] Real-time measurement data input: Input real-time measurement data and process it through the initial filter to obtain filtered output.

[0082] Error calculation: Calculate the error between the current filter output and the actual measured value, that is, the value of the error function.

[0083] Adjust filter parameters: Use an adaptive algorithm (such as LMS algorithm, gradient descent method) to adjust the filter parameters to minimize the error function. In the present invention, the LMS algorithm is used to adjust the filter parameters to minimize the error function. The parameter update formula is:

[0084] ; are the filter parameters, is the learning rate, is the average measurement error in the current measurement error, The input signal is the adjusted filter that gradually adapts to the dynamic changes of the optical detection equipment, making its output closer to the actual measurement value. Error evaluation and parameter adjustment are continuously performed to make the filter dynamically adapt to environmental changes, thereby maintaining high-precision measurement of the equipment during the dynamic calibration process. When the filter parameters gradually converge and the error function value tends to be stable, the calibration is considered to be completed and the optical detection equipment has achieved the best measurement accuracy under the current dynamic conditions. The adaptive filter adapts to environmental changes by continuously adjusting the filter parameters. Under dynamic conditions, it can effectively reduce measurement errors and improve the measurement accuracy of optical detection equipment.

[0085] Joint calibration refers to:

[0086] On the basis of static calibration and dynamic calibration, a joint objective function is defined to combine the results of static calibration and dynamic calibration and comprehensively consider the measurement accuracy under different environmental conditions. The joint objective function is expressed as:

[0087] ; J represents the value of the joint objective function, , are all preset weight factors. represents the value of the objective function in static calibration, Represents the value of the error function in dynamic calibration;

[0088] Generate an initial parameter population. Each individual in the population represents a set of corresponding calibration parameters. A set of corresponding calibration parameters includes a static calibration parameter combination and a dynamic calibration parameter group. Set the population size N. Usually, a reasonable range is selected to ensure the diversity of the parameter space. For each individual in the population, calculate its fitness value. The goal is to minimize J, that is, to find the parameter combination that minimizes the static and dynamic calibration errors. The fitness function F is defined as: ; C is a non-negative constant to prevent the denominator from being zero, and the fitness F of each parameter combination is calculated;

[0089] Selection operation: Use the roulette wheel selection method to select offspring as new parents, select individuals with high fitness from the current population for crossover and reproduction, and form a new next generation population;

[0090] Crossover operation: randomly exchange data in chromosomes of different parents;

[0091] Mutation operation: Randomly select the data of different offspring chromosomes for adjustment; as the genetic algorithm iterates, the individuals in the population may gradually tend to be similar, which will cause the algorithm to fall into the local optimal solution and cannot be further optimized. Through mutation, some parameter values ​​of individuals are randomly changed to keep a certain diversity in the population and avoid premature convergence to a suboptimal solution. In each generation of the population, a certain proportion of individuals are selected and their parameters are randomly adjusted. This adjustment may be small (such as adding or subtracting a tiny random number) or large (such as replacing with a completely new random value), depending on the design of the mutation operation. The mutation rate determines how many individuals will mutate in each generation. Usually the mutation rate is set low (such as 1% to 5%) to avoid excessive randomness from destroying existing good solutions, but at the same time ensure a sufficient mutation rate to continuously explore new possible solutions. Genetic algorithms simulate the natural evolution process through selection, crossover and mutation. The introduction of mutation can break the current local optimal state and provide the algorithm with an opportunity to jump out of the local optimal state and find the global optimal solution.

[0092] Iteration and termination conditions: Iterate until the preset termination conditions are met, and after the genetic algorithm iteration is completed, select the individual with the highest fitness as the final joint calibration parameter combination, and apply these optimal parameters to the calibration of the optical detection equipment to achieve the final joint calibration. The genetic algorithm is used to find the optimal parameter combination to minimize the measurement error of the equipment and ensure that it can maintain high accuracy under various conditions.

[0093] Although static calibration and dynamic calibration are aimed at different environmental conditions (static and dynamic), they are independent of each other in the calibration process. Static calibration adjusts the basic output of the device to eliminate systematic deviations, while dynamic calibration further corrects the measured values ​​in real time based on this. Therefore, there is no conflict or disharmony between the static calibration parameter group (a, b) and the dynamic calibration parameter group w. The genetic algorithm jointly optimizes these two sets of parameters to ensure that the device can obtain the best measurement accuracy under different environmental conditions. Static calibration and dynamic calibration complement each other through the joint calibration process to ensure that the device can output high-precision measurement results under various operating environments.

[0094] Static calibration deals with the systematic errors of the device under stable conditions, while dynamic calibration deals with the real-time errors of the device in a dynamic environment. This joint calibration method can fully correct the measurement errors of the device and adapt to different environmental conditions. Through joint calibration with genetic algorithms, both static and dynamic calibration parameters are optimized, so that the device can maintain high measurement accuracy under both static and dynamic conditions. Genetic algorithms help to find the globally optimal combination of calibration parameters to minimize measurement errors. The jointly calibrated device is better able to cope with environmental changes, and the device can output accurate measurement results both in the stable environment of the laboratory and in the dynamic environment of actual applications. Due to the global search capability of the genetic algorithm, the joint calibration parameters are optimized under a wider range of conditions, so the device can maintain stable measurement accuracy in long-term use and reduce the possibility of frequent recalibration.

[0095] Embodiment 2: A calibration and repair management system for an optical inspection device, comprising:

[0096] A performance test module is used to perform a performance test on the optical inspection equipment using a standard test procedure to determine whether the current measurement error exceeds a preset standard;

[0097] An environmental impact analysis module is used to quantify the degree of environmental impact on the optical detection equipment by calculating the environmental variation coefficient when the current measurement error exceeds the preset standard to obtain the environmental variation coefficient;

[0098] An inference module, used to perform fuzzy inference according to the current measurement error, environmental variation coefficient, and the number of calibrations of the optical detection device, and to decide to execute a corresponding preset calibration strategy according to the result of the fuzzy inference;

[0099] A calibration execution module, used for calibrating the optical detection device based on a calibration strategy obtained by fuzzy reasoning;

[0100] The inspection module is used to inspect whether the current measurement error after the execution of the calibration strategy still exceeds the preset standard after each calibration. If it still exceeds the preset standard, the optical elements or control components corresponding to the calibration strategy are repaired, and the calibration is performed cyclically until the current measurement error of the optical detection equipment meets the preset standard.

[0101] Restoration refers to the inspection, maintenance, repair or replacement of optical components or control parts in optical inspection equipment that may cause measurement errors in order to restore their normal function and accuracy. The purpose of restoration is to ensure that the equipment can achieve the expected measurement accuracy after calibration and reduce or eliminate errors.

[0102] Specifically, repair includes the following situations: Inspection and maintenance: Perform a detailed inspection of the equipment to identify components that cause errors, such as optical lenses, reflectors, photoelectric sensors, etc. Inspection may involve cleaning the surface of optical components, tightening loose parts, or adjusting the optical path.

[0103] Repair: Restoring damaged or aged optical or control components. For example, patching a scratched lens, replacing a damaged cable, fixing a fault on an electronic control board.

[0104] Replacement: When some parts are seriously damaged and cannot be repaired, they are directly replaced with new parts. Common replacement parts include optical lenses, reflectors, light sources, sensors, etc.

[0105] Realignment: Realignment of an optical system to ensure that the beam path is accurate, the focus is correct, or the electronic control system is responding properly.

[0106] The goal of repair is to ensure that each component of the equipment is restored to the performance state required by the design, so that the measurement error of the calibrated equipment meets the preset standard. Recalibration after repair: Recalibration is required after the repair is completed to verify whether the correction repair is effective. The calibration is repeated until the current measurement error of the optical inspection equipment meets the preset standard to ensure that the measurement accuracy of the equipment meets the standard.

[0107] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0108] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0109] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0110] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0111] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A calibration and repair management method for optical detection equipment, characterized in that: The following steps are involved: Step 1: Use standard test procedures to perform performance tests on the optical inspection equipment to determine whether the current measurement error exceeds the preset standard. If the current measurement error is within the allowable range, continue to use the equipment. If it exceeds the preset standard, quantify the degree of influence of the environment on the optical inspection equipment by calculating the environmental variation coefficient to obtain the environmental variation coefficient. Step 2: Obtain the current measurement error, environmental variation coefficient, and calibration times of the optical detection device, perform fuzzy reasoning, and decide to execute a corresponding preset calibration strategy according to the result of the fuzzy reasoning; Step 3: Calibrate the optical detection equipment based on the calibration strategy obtained by fuzzy reasoning; Step 4: After each calibration, if the current measurement error after the execution of the calibration strategy still exceeds the preset standard, the optical element or control component corresponding to the calibration strategy is repaired; Step 5, looping through steps 2, 3 and 4 until the current measurement error of the optical detection device meets the preset standard; The logic for obtaining the environmental variation coefficient is: Select multiple preset environmental parameters, collect the change data of the preset multiple environmental parameters in real time, obtain the curves of the preset multiple environmental parameters changing with time, standardize the change range of all parameters to the [0,1] interval, calculate the change rate of each standardized environmental parameter, set a fixed time sampling interval Δt, and use the difference formula to approximate the derivative to obtain the change rate of the environmental parameter. The formula is expressed as: ; represents the standardized value of the i-th environmental parameter corresponding to time t, represents the change rate of the i-th environmental parameter, assigns a weight wi to each environmental parameter and the sum of all weights wi is 1, and the weighted sum of the change rates of all environmental parameters is obtained to obtain the comprehensive environmental change coefficient. The calculation formula is: ; n is the number of environmental parameters, Indicates the environmental variation coefficient corresponding to the test time t; The preset calibration strategies refer to three calibration strategies: static calibration, dynamic calibration, and joint calibration, and one of them corresponds to the result of fuzzy reasoning when executed; The logic of fuzzy reasoning is: obtain the average measurement error, standard deviation of measurement error, environmental variation coefficient, and calibration times of the current measurement error of the optical detection device as input variables, use the type of calibration strategy as output variable, perform fuzzy processing on the input variables, convert the value of the input variables into fuzzy sets, perform fuzzy processing on the output variables, convert the output variables into fuzzy sets, formulate fuzzy rules, describe the calibration requirements under different data type combinations, and use fuzzy rules to reason the fuzzified input variables to determine the type of calibration strategy suitable for the optical detection device; Static calibration refers to: Establish a static error model and use a linear model to express it: ; is the error term, a and b are both model parameters, and the data pair refers to the use of the optical detection equipment to be calibrated to measure multiple data points that are the same as the reference standard. The data obtained at each data point is expressed as , i represents the i-th measurement data point, and the objective function is defined as the residual sum of squares. The goal is to minimize the difference between the actual measurement value and the model prediction value, find the optimal parameters a and b that minimize the residual sum of squares, and then adjust the output of the optical detection equipment according to the obtained optimal parameters a and b; Dynamic calibration refers to: Select and set an initial filter structure. The initial parameters are set based on the prior knowledge of the device. Then define an error function for evaluating the filter performance. The error function represents the deviation between the filter output and the target value. Input the real-time measurement data and process it through the initial filter to obtain the filtered output. Then calculate the error between the current filter output and the actual measurement value, which is the value of the error function. The filter parameters are adjusted using the LMS algorithm to minimize the error function. The parameter update formula is: ; are the filter parameters, is the learning rate, is the average measurement error in the current measurement error, The input signal is the adjusted filter that gradually adapts to the dynamic changes of the optical detection equipment, making its output closer to the actual measurement value. When the filter parameters gradually converge and the error function value tends to be stable, it is considered that the calibration is completed and the optical detection equipment has achieved the best measurement accuracy under the current dynamic conditions. Joint calibration refers to: Based on static calibration and dynamic calibration, a joint objective function is defined, which is expressed as: ; J represents the value of the joint objective function, , are all preset weight factors. represents the value of the objective function in static calibration, Represents the value of the error function in dynamic calibration; Generate an initial parameter population. Each individual in the population represents a set of corresponding calibration parameters. A set of corresponding calibration parameters includes a static calibration parameter combination and a dynamic calibration parameter group. Set the population size N. For each individual in the population, calculate its fitness value. The goal is to minimize J, that is, to find the parameter combination that minimizes the static and dynamic calibration errors. The fitness function F is defined as: ; C is a non-negative constant to prevent the denominator from being zero, and the fitness F of each parameter combination is calculated; Selection operation: Use the roulette wheel selection method to select offspring as new parents; Crossover operation: randomly exchange data in chromosomes of different parents; Mutation operation: randomly select data of different offspring chromosomes for adjustment; Iteration and termination condition: Iterate until the preset termination condition is met, and after the genetic algorithm iteration is completed, the individual with the highest fitness is selected as the final joint calibration parameter combination.

2. The calibration and repair management method of an optical detection device according to claim 1, characterized in that: The current measurement error acquisition logic is: Measure the performance of optical inspection equipment according to standard test procedures and obtain actual output measurements of the equipment , make multiple measurements and record multiple measurement values , and obtain the measurement time series X: , , …, , n is the total number of measured data, obtain the standard reference value for comparison For each measurement, the deviation between it and the standard reference value is calculated, which is called the single measurement error. , ; i represents the i-th measurement; Then, based on all the single measurement errors Calculate the average measurement error , and the standard deviation of the measurement error , the current measurement error refers to the average measurement error and the standard deviation of the measurement error Summarize the resulting error combinations.

3. The calibration and repair management method of an optical detection device according to claim 2, characterized in that: Determining whether the current measurement error exceeds the preset standard refers to: An allowable measurement error range is set for the optical detection device in advance, which is recorded as the error tolerance. Another allowable error discrete threshold is also set. The current measurement error, that is, the average measurement error in the error combination, is The standard deviation of the measurement error is compared with the error tolerance. Compared with the error discrete threshold, if the average measurement error is satisfied The standard deviation of the measurement error falls within the error tolerance If the average measurement error is not greater than the discrete error threshold, the current measurement error does not exceed the preset standard; if the average measurement error is not satisfied The standard deviation of the measurement error falls within the error tolerance If it is not greater than the error discrete threshold, the current measurement error exceeds the preset standard.

4. A calibration and repair management system for optical detection equipment, according to any one of claims 1 to 3, characterized in that: include: A performance test module is used to perform a performance test on the optical inspection equipment using a standard test procedure to determine whether the current measurement error exceeds a preset standard; An environmental impact analysis module is used to quantify the degree of environmental impact on the optical detection equipment by calculating the environmental variation coefficient when the current measurement error exceeds the preset standard to obtain the environmental variation coefficient; An inference module, used to perform fuzzy inference according to the current measurement error, environmental variation coefficient, and the number of calibrations of the optical detection device, and to decide to execute a corresponding preset calibration strategy according to the result of the fuzzy inference; A calibration execution module, used for calibrating the optical detection device based on a calibration strategy obtained by fuzzy reasoning; The inspection module is used to inspect whether the current measurement error after the execution of the calibration strategy still exceeds the preset standard after each calibration. If it still exceeds the preset standard, the optical elements or control components corresponding to the calibration strategy are repaired, and the calibration is performed cyclically until the current measurement error of the optical detection equipment meets the preset standard.

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