31 results about "Statistical error" patented technology

This invention discloses an accelerated safety assessment method and system for low-altitude navigation systems based on alternating cross-entropy and importance sampling, relating to the fields of computer simulation and safety assessment technology. The method includes: constructing a probabilistic risk assessment model and initializing a proposal distribution; entering an alternating iterative loop: first, performing importance sampling assessment, calculating accident rate estimates and statistical errors; if the error does not meet accuracy requirements, initiating cross-entropy optimization, updating the proposal distribution parameters using simulation data; the new distribution is fed back to the next round of assessment. This loop continues until the results converge, and an assessment report is output. This invention, through a closed-loop feedback mechanism of alternating assessment and optimization, enables the sampling distribution to adaptively approximate the optimal distribution, intelligently focusing simulation resources on high-risk scenarios, solving the computational efficiency bottleneck of assessing extremely low probability events, achieving an order-of-magnitude improvement in assessment efficiency, and possessing high adaptability and engineering practical value.

The present invention discloses a method and device for statistically calculating the biological migration flux of insect radar, belonging to the technical field of insect radar, which solves the problem of statistical error caused by the deviation of the position of insect movement from the beam normal line, and helps to improve the accuracy of statistical calculation of insect migration flux. The technical solution of the present invention is as follows: In the vertical measurement mode, a statistical method model for insect migration flux is established, and the statistical unit (k,n) is defined; the actual distance that all insects pass through the beam is obtained; an estimation model of the radar beam and the position where the migrating insects pass through the beam is established, and the deviation parameter is obtained based on the longest distance that the target passes through the beam and the actual distance that the target passes through the beam; the statistical method is used to estimate the insect migration flux, and the flux statistical results of different altitude layers are obtained. According to the expression of the migration flux in the fixed beam mode of vertical measurement and the flux statistical results of different altitude layers, the expression of the migration flux in the fixed beam mode of any direction and the flux statistical results of different altitude layers are obtained.

The application provides a frequency standard measurement method, device, computer equipment and storage medium, the method comprises: frequency source output measurement signal is carried out frequency division processing, obtains low frequency pulse signal; using high-precision time interval counter to low frequency pulse signal is carried out delay measurement and time interval counting, and is output in the form of time stamp; by setting a sliding window, using sliding average algorithm to time stamp is carried out sliding average filtering processing, all time stamps are carried out sliding difference to obtain time difference, time difference is grouped according to order and is taken average in group to obtain average time difference; by increasing the length of the sliding window, the number of samples is increased to reduce the statistical error; using average time difference, calculate frequency measurement value, relative frequency deviation and allan variance. The method of the application increases the sliding window, and the frequency measurement result obtained by the algorithm of grouping and averaging the time difference has higher measurement precision and stability.

The invention discloses an intelligent top pipe splitting method based on a BIM technology. The method comprises the following steps that 1, a first Revit self-adaptive pipe joint family is manufactured; 2, generating an overall model of the pipeline according to a projection path of the pipeline by using the first Revit self-adaptive pipe joint family; 3, by means of Dynamo software, the splitting fixed length and the splitting distance of the pipeline are preset, segmentation is conducted, and multiple segments of segmented curves are obtained; 4, processing all the segmentation curves through Boolean operation by utilizing Dynamo software to obtain corresponding segmentation curves segmented into accurate lengths; 5, by utilizing Dynamo software, generating all pipe joints after the pipeline is segmented through the segmentation curve; 6, according to a preset corner threshold value of the adjacent pipe joints, the corner between the adjacent pipe joints is calculated; and 7, exporting a detailed list of all the pipe joints. According to the method, design and machining can be quickly joined, the material statistical error is reduced, and the design and machining efficiency is improved.

The application discloses a kind of based on statistical error analysis's gate group timing flow abnormal diagnosis method, comprising the following steps, S1, flow data pre-processing based on filtering method;S2, flow error distribution analysis;S3, based on k up / down Reasonable flow error range determination of σ rule;S4, over gate flow coefficient relationship curve fitting;S5, theoretical gate station flow calculation;S6, abnormal flow data diagnosis and correction.The advantage is: the method can make full use of the specific monitoring error distribution characteristics and monitoring variable mapping relationship of different gate stations, reduce the missed detection or false detection rate.Through introducing the real error distribution of flow monitoring data in the abnormal data diagnosis model, the specific monitoring error range of specific project is determined, and the reliability of flow abnormal diagnosis process is improved.

The invention discloses a converter blanking automatic statistical system based on intouch configuration software development, relates to the technical field of steelmaking process analysis, and is used for automatically collecting and counting converter blanking weight data and generating a report so as to improve the accuracy and analysis efficiency of steelmaking process data. The display module is used for selecting bin blanking types and displaying statistical results; the data acquisition and storage module is used for acquiring the weighing data of the stock bin through a PLC (Programmable Logic Controller); the data processing and association module adopts an enumeration comparison method to merge the weights of similar materials; and the dynamic report generation module dynamically generates a header and updates the statistical table. According to the method, under the condition that the blanking types of the stock bin are changed, automatic statistics of the blanking types, weight and other data can be achieved through simple operation, the data are displayed on an operation picture in a table form, the problems that in the prior art, manual statistics errors are large, and table updating efficiency is low are solved, and powerful support is provided for data analysis of the steelmaking process.

The invention is suitable for the technical field of charging piles, and provides a charging pile availability determination method and a charging pile monitoring system. The method comprises the steps of obtaining target state data and target fault data of a target charging pile based on an identifier of the target charging pile and a target time interval; state data correction is performed according to an acquisition result of the target state data and the target time interval, and an online time interval of the target charging pile is determined according to a correction result; de-duplicating the obtained target fault data, and obtaining a fault time interval of the target charging pile according to a de-duplicating result; and determining the availability rate of the target charging pile based on the online time interval and the fault time interval. According to the method, statistical errors of the online time interval and the fault time interval can be reduced, the availability rate of the charging pile can be accurately obtained, the state of the charging pile can be timely and accurately mastered subsequently, the charging pile is reasonably used and maintained, meanwhile, the determination process of the availability rate of the charging pile is simplified, the calculation amount is reduced, and the efficiency is improved.

The invention discloses a robust sub-sampling method based on an influence function. The method comprises the following steps: constructing a model and a robust sub-sampling problem; based on a robust iteration sub-sampling algorithm, data points which are close to a clean subset as much as possible are screened out from a data set through step-by-step iteration, it is ensured that after finite iteration, sub-sampling data are from unpolluted samples, and the optimal statistical error boundary of parameter estimation is obtained; calculating a gradient by using a robust sub-sampling method in each iteration based on a robust small-batch stochastic gradient descent algorithm, and updating parameters based on the gradient; the sub-sampling method provided by the invention realizes an approximately optimal error rate and provides a strong robustness guarantee.

The invention provides a frequency scale measurement method and device, computer equipment and a storage medium, and the method comprises the steps: carrying out the frequency division processing of a measurement signal outputted by a frequency source, and obtaining a low-frequency pulse signal; carrying out delay measurement and time interval counting on the low-frequency pulse signal by using a high-precision time interval counter, and outputting the low-frequency pulse signal in a timestamp form; the method comprises the following steps of: setting a sliding window, carrying out sliding average filtering processing on timestamps by utilizing a sliding average algorithm, carrying out sliding action difference on all the timestamps to obtain time differences, grouping the time differences in sequence, and averaging in groups to obtain average time differences; the number of measured samples is increased by increasing the length of the sliding window, so that statistical errors are reduced; a frequency measurement value, a relative frequency deviation and an Arron variance are calculated using the average time difference. According to the method provided by the invention, the sliding window is increased, and the frequency measurement result is obtained by using the algorithm of grouping and averaging the time difference, so that the method has higher measurement precision and stability.

The utility model discloses an organoid culture pore plate convenient to count and position, which belongs to the technical field of cell culture and comprises a culture pore plate, a plurality of pore grooves are arranged on the culture pore plate, scale marks are arranged at the bottoms of the pore grooves, and the scale marks comprise a plurality of transverse lines and a plurality of longitudinal lines which are uniformly distributed outwards by taking the circle centers of the pore grooves as centers. According to the utility model, orientation coordinates in the pore plate are arranged, so that the dynamic growth process of the organoid can be conveniently positioned and observed, regular counting of each organoid in each pore is facilitated, the budding number is calculated, and the accuracy of statistical analysis is improved; by setting the grids, the organoid can be located in a grid with a fixed area, so that the area can be conveniently calculated without being limited by different shooting machines or software, the efficiency of experimental data analysis is improved, and calculation or statistical errors are reduced; the same type of organs are continuously observed through scale line positioning, the efficiency of organoid culture experiment operation and data analysis and the data reliability are improved, and the device has very high practicability and wide application prospects.

The invention relates to the technical field of internet information, can be applied to the fields of financial advertisement putting, user behavior analysis and the like, and provides a page component exposure information automatic capturing method and device, a medium and equipment. When rolling stops or the rolling speed is lower than a threshold value, the current position of each assembly in the window is calculated according to the rolling distance and direction; for the component element, marking the component element as an exposure state when the component element enters the visible range for the first time, and recording an entry timestamp; if the video is marked and is still in the visible range, updating the staying duration; if the user leaves the visual range, recording a leaving timestamp and calculating a single-time stay duration; the staying duration is accumulated as the total staying duration during multiple times of entering and exiting, and when the total duration exceeds the preset minimum effective duration, the data are marked as effective exposure data, and the effective exposure data are encrypted in batches through a buffer queue and then reported to a server. By automatically capturing and analyzing the component exposure information, manual statistical errors can be reduced, and the data accuracy is improved.

The disclosure includes a computer-implemented method (100) for determining a 3D body joint position (20) of an object (70) comprising the following steps: - generating (102) a first 2D body joint position (12) for at least one body joint point (10) of the object (70) based on a body joint position data set (30) which contains at least one image from a plurality of camera perspectives; - Manually annotating (104) a second 2D body joint position (14) based on the body joint position data set (30) to determine an error deviation of the second 2D body joint position (14) from the generated first 2D body joint position (12); - determining (106) an error model (50) by estimating a statistical error value indicating a deviation (55) of the first 2D body joint position (12) from the second 2D body joint position data (14); - Determining (108) the 3D body joint position (20) for the at least one body joint point (10) on the basis of the first 2D body joint position (12) and the determined error model (50) by applying a statistical method.

The invention belongs to the field of radio detection, particularly relates to a signal and data processing method for a multi-base incoherent scatter radar, and aims to solve the problem of failure of a conventional signal and data processing method for the multi-base incoherent scatter radar. The method comprises the following steps: dividing a detection distance range of a multi-base incoherent scatter radar beam into a plurality of detection distance doors, and calculating a signal autocorrelation function of each detection distance door; after time correction is carried out on the signal of the receiving station, an observation system equation constant is determined based on antenna gains of the transmitting station and the receiving station and the detection co-body height in combination with radar transmitting power; fitting the signal autocorrelation function according to the spectrum fuzzy function and the plasma scattering theory power spectrum function in combination with the observation system equation constant and the statistical error of the signal autocorrelation function, and performing inversion to obtain the ionosphere parameter of each detection range gate. The method is applied to a multi-base incoherent scattering radar, and an effective ionosphere multi-parameter result is obtained.

The application relates to a dynamic frequency and voltage adjustment method, device, equipment, storage medium and program product. The method comprises the following steps: determining the value of the utilization time length under the upper and lower limits of the utilization time length of a video decoder according to the current decoding information of the video decoder; the upper and lower limit conditions comprise a frame loss limit condition and a statistical error condition of the video decoder; and the dynamic frequency and voltage adjustment strategy parameters of the video decoder are determined according to the value of the utilization time length, and the dynamic frequency and voltage adjustment strategy parameters are used for dynamically adjusting the frequency and voltage of the video decoder. The method can more accurately dynamically adjust the frequency and voltage of the video decoder.

The invention relates to the technical field of grape nondestructive testing, in particular to a grape yield and quality evaluation method and system based on image recognition, and the method comprises the steps of image data set acquisition and processing, model training and verification, model recognition and report output. Correcting the plane grain number in the image into an actual grain number through a linear regression model; the maturity of a single fruit grain is accurately identified through expert labeling; a variable coefficient is calculated through the coordinates of the fruit grains and the occupied pixel area and is used for judging the fruit grain uniformity of the grape bunch; the evaluation system is used for realizing the method, and seamless connection of the whole process from original image input to report generation is realized. According to the method, the problem that the existing actual grain number statistical error is large is solved, and meanwhile quantitative evaluation on the maturity and the uniformity is achieved; an algorithm model used by the evaluation system is simple in form, few in parameter, efficient in calculation and suitable for being deployed on lightweight computing equipment, and the requirements for practicability, robustness and generalizability of the method are met.

The invention discloses a vehicle operation condition prediction method, device and equipment, a medium and a product. The method comprises the following steps: acquiring sensor data and spatial positioning data of a vehicle, and constructing a space-time sequence tensor based on the sensor data and the spatial positioning data; inputting the space-time sequence tensor into a target prediction model to obtain a prediction output result; the prediction output result comprises an operation state identification result, a transportation task starting point and a transportation task ending point; and determining the running state of the vehicle according to the running state recognition result, and determining the transportation times of the vehicle according to the transportation task starting point and the transportation task ending point. According to the technical scheme of the invention, the method can solve the problems that the operation state of the mine card is difficult to recognize, the statistical error of the number of times is large, and the data is discontinuous due to the lack of GPS signals in the mine transportation operation, achieves the recognition of the operation state of the mine card, and automatically calculates the number of times of transportation every day.

This invention relates to a method, system, and computer program product for performance evaluation of diffractive optical elements based on measured morphology and simulation analysis. It pertains to the field of diffractive optical element design, testing, and performance evaluation technology, addressing the problem of existing technologies lacking effective analysis methods and evaluation models for diffractive optical elements. The method includes the following steps: Step S1, for a reflective phase mask, constructing a corresponding etching depth distribution based on the designed phase distribution; Step S2, based on the designed phase distribution, constructing a corresponding etching depth distribution and establishing a statistical error model; Step S3, measuring the actually processed diffractive optical element to obtain its surface three-dimensional morphology data and obtaining the actual processing error distribution; Step S4, based on the statistical error model described in Step S2 and the actual processing error distribution described in Step S3, constructing a light field propagation model; Step S5, based on the light field propagation model, performing performance analysis on the diffractive optical element.

The invention belongs to the technical field of impact toughness evaluation, and particularly relates to a low alloy steel impact energy intelligent prediction method based on transfer learning, which comprises the following steps: step 1, selecting an impact energy prediction position of a material, step 2, shooting a microstructure optical microscope image of a target position, and carrying out an impact toughness test. The method comprises the following steps of: 1, acquiring image data and impact energy data, 3, sorting the image data and the impact energy data, and dividing training and testing data sets, 4, building a transfer learning model, and completing model parameter adjustment and optimization selection, and 5, inputting an optical microscope image at any position, and realizing impact energy prediction. According to the low alloy steel impact energy intelligent prediction method based on transfer learning, the impact energy value prediction result can be obtained only by shooting the light microscope image of the concerned position and inputting the light microscope image as the prediction model, the manpower time cost and possible statistical errors caused by manual statistics of microstructure parameters are avoided, and intelligent impact energy prediction is achieved.

The application belongs to the field of radio detection, and particularly relates to a signal and data processing method of a multi-base incoherent scatter radar, and aims to solve the problem that the conventional signal and data processing method is invalid for the multi-base incoherent scatter radar. The application comprises: dividing the detection distance range of the multi-base incoherent scatter radar beam into multiple detection distance gates, and calculating the signal autocorrelation functions of the detection distance gates; after time correction of the signals at the receiving station, determining the observation system equation constant based on the antenna gains of the transmitting station and the receiving station, the detection common height, and the radar transmitting power; fitting the signal autocorrelation functions according to the spectral ambiguity function, the plasma scattering theory power spectrum function, the observation system equation constant and the statistical error of the signal autocorrelation functions, and inversely obtaining the ionospheric parameters of the detection distance gates. The application is applied to the multi-base incoherent scatter radar, and effective ionospheric multi-parameter results are obtained.

We provide a pronunciation learning support system that improves the efficiency, acceptability, and continuity of pronunciation learning by acoustically quantitatively evaluating learners' pronunciation errors, visually presenting their directionality and magnitude, and individually optimizing teaching materials based on error history. [Solution] This invention processes speech on a phoneme-by-phoneme basis, extracts formants F1 and F2 from each phoneme, and performs error evaluation based on Z-scores and normalized distance Z_norm. Error information is visually displayed as points, vectors, and ellipses in F1F2 space, intuitively presenting the statistical error structure to the learner. Error information is recorded as a history and analyzed over time, and error trends are classified using clustering processing. The teaching material presentation means calculates presentation priority based on scoring based on the amount of error and frequency of recurrence, and is equipped with a mechanism for gradually controlling the difficulty of the teaching material according to the recurrence rate and improvement trend.

The invention belongs to the technical field of industrial automation control, and particularly relates to a textile processing progress monitoring method and system, and the method comprises the steps: collecting the original operation linear speed data of textile equipment, and carrying out the preprocessing of the data, and obtaining an operation speed time sequence; carrying out scale permutation entropy analysis and phase space reconstruction to obtain an operation microscopic disorder degree and a phase space trajectory deviation degree; calculating an effective man-hour correction coefficient based on the operation microcosmic disorder degree and the phase space trajectory deviation degree; and correcting the instantaneous measurement speed by using the effective man-hour correction coefficient to obtain the residual processing time of the textile equipment, uploading the residual processing time to a management system, and comparing the operation microcosmic disorder degree with a preset disorder degree threshold to carry out abnormal early warning. According to the method, the man-hour statistical error caused by micro shutdown or low-speed creep of equipment is reduced, and the accuracy of textile processing progress prediction is improved.

The invention provides a real-time classroom behavior detection method based on edge information and a decoupling shared detection head. On one hand, an efficient edge information convolution module is provided to extract edge information of classroom body behaviors, the performance of model detection is better improved, a global-to-local Transform module is added to enhance the feature extraction capability, and then context anchor attention is utilized to make up for the deficiency of global information perception when only dependence on local multi-scale convolution is performed, so that the accuracy of model detection is improved. And on the other hand, a decoupling sharing detection head with light weight and efficiency merging is adopted, all convolution layers share the same weight, and each corresponding normalization layer carries out independent calculation, so that numerical value normalization among different level features is ensured, cross contamination of statistical errors of batch normalization layers is also avoided, and the detection accuracy is improved. And meanwhile, additional group normalization calculation overhead is not introduced. According to the technical scheme, the requirements of high real-time performance and easy deployment are met, and an innovative method is provided for solving the problem.

The invention relates to the technical field of health monitoring, in particular to a health monitoring method based on millimeter wave radar and infrared imaging, a computer and a storage medium, and the method comprises the steps: building a tracking algorithm when a plurality of targets coincide, and enabling each target to obtain a plurality of associated confidence values, each target in the first set selects a target whose association confidence value is most close to 1 as a tracking target; according to the method, the moving targets in the time period before coincidence and the time period after coincidence are selected for tracking, so that statistical errors caused by target confusion due to wrong patient identification by millimeter-wave radar and infrared imaging after movement coincidence of patients are avoided; the tracking algorithm is established, and the Euclidean norm is utilized, so that the vector when the target moves can be included, and the accuracy of target tracking is further improved; through the adjustable variance parameter, as the speed change probability is relatively large, the respiration change probability is lower or is described to have hysteresis, and the tracking accuracy can be improved.

The application discloses a kind of based on circuit board's wiring length determination method, it is related to circuit board technical field.According to the current layer of circuit board, the coordinate corresponding to the auxiliary area of the target device connected with the starting point of the current wiring when the current wiring reaches is determined to the wiring length of the current layer, considering the actual coordinates of the vicinity of the target device reached by the starting point of the current wiring, avoid the problem of statistical error caused by artificial statistics to determine the wiring length of the corresponding target device.In the case of via, the starting point of the corresponding wiring of the next layer needs to be tracked by the via tracking, to avoid the omission of artificial statistics.In the case of pin, the fact that the corresponding pin device includes two pins in the conventional artificial statistical process will ignore the statistical error caused by the wiring length between the pins.Considering the wiring length determination of the wiring length mapping relationship between the inner layer and the outer layer of the circuit board, the calculation accuracy of the wiring length is improved.

An in-place state monitoring device for cutter management of a deep hole drilling and boring machine is characterized by comprising a base, a groove is formed in the base, a gap is formed between the side wall of the groove and the side wall of the base, a step groove and more than two spring guide columns are arranged at the bottom of the groove, and a travel switch is installed in the step groove. The two opposite side walls of the groove are each provided with a sliding groove, the two sliding grooves are opposite in position, and rectangular grooves are formed in the positions, opposite to the sliding grooves, of the side walls of the base. According to the in-place state monitoring device disclosed by the utility model, the mode that paper sheets are adopted for manual receiving and returning in the past is changed, manual real-time receiving and real-time statistics are realized, it is ensured that the device is placed at a designated position during returning, and the problem of low efficiency caused by tedious receiving procedures and statistical errors is solved.

The invention discloses an improved large-vortex simulation vortex generation method, belongs to the technical field of turbulence simulation, and solves the problems of insufficient vortex randomness control, significant inlet turbulence statistical error and large computing resource consumption in the existing synthetic vortex method. The method comprises the following steps: generating randomly distributed synthetic vortexes at an inlet based on target turbulence characteristics, processing a velocity field by using a dynamic normalization factor to meet a statistic requirement, and finally determining the number of vortexes according to a specific ratio and enabling the vortexes to be randomly distributed. According to the improved large-vortex simulation vortex generation method, traditional limitation is broken through, vortexes can be placed at will, statistical accuracy is improved, small-scale turbulence coverage is optimized, calculation efficiency is improved by 1-2 orders of magnitude, cost is reduced, the method can be achieved based on OpenFOAM software, the method is suitable for various scenes, and powerful support is provided for multiple fields.

The application discloses a kind of quick calculation methods of rain radar partition rainfall data, it is related to meteorological technical field.The method is by constructing multistage basic rule grid system and stratified lossless compression weight matrix, complex geometric operation is converted into static look-up table;In real-time calculation stage, analysis radar data dynamic parameter, based on rainfall gradient threshold triggers adaptive grid refinement, uses coarse grid and nearest neighbor interpolation to gentle area of rainfall, uses fine grid and high-precision interpolation to dramatic change area and boundary area;Finally, through stratified compression weight, realizes the quick accumulation of partition statistics, outputs each partition surface average rainfall.The application reduces dimension from look-up table and weighted accumulation to full-amount geometric operation in real-time calculation load, under the premise that guaranteeing boundary statistical error is less than 1%, the computing time efficiency is improved by more than 90%, memory occupation is reduced by 90%, and can automatically adapt to different scanning modes of radar, provides efficient and accurate data support for flood forecasting and waterlogging early warning.

The present invention discloses a method, system, device and storage medium for determining the source distance of density logging, which belongs to the technical field of pulsed radioactive source logging in oil and gas exploration. The method comprises: establishing a formation detection model using Monte Carlo simulation software; obtaining the relationship between the count rate and the long source distance and the short source distance from the formation detection model, and preliminarily screening the value ranges of the long source distance and the short source distance; further screening the value ranges of the long source distance and the short source distance based on the statistical error and measurement accuracy of the formation detection model; and determining the final value range of the short source distance using the short source distance compensation function and sensitivity requirements. The present invention can quickly determine the value ranges of the long source distance and the short source distance, and has higher accuracy. A reasonable source distance confirmation method for a density logging instrument can help improve the accuracy of density instrument data, obtain high-precision formation density parameters, make subsequent logging interpretation and analysis more accurate, and save a certain amount of logging costs.

The invention relates to the technical field of data analysis, and particularly discloses a commission report automatic generation method and device, equipment and a storage medium. According to the invention, when the commission report generation instruction is received, the data acquisition, calculation and analysis processes can be automatically carried out, and the commission report is generated, so that the automatic generation of the commission report is realized, manual participation is not needed, the data acquisition, statistics and analysis efficiency is improved, human errors are avoided, and the generation efficiency and accuracy of the commission report are improved; and secondly, the business data and the target analysis dimension are acquired according to the user identity information, and the commission statistical analysis is performed, so that the interference of irrelevant data and unnecessary analysis dimensions on the commission statistical analysis is avoided, and the accuracy of the commission report is improved. When the method is applied to the financial insurance business, the commission data of the insurance business personnel can be quickly and accurately counted according to the business data and the target analysis dimension, and the commission statistical error caused by human factors is avoided.

This application provides a testing apparatus, method, and storage medium, relating to the field of equipment testing technology. The apparatus includes a first fixing member, a second fixing member, a counting module, and a motion module connected to either the first or second fixing member. The sensor to be tested is fixed to the second fixing member, and the counting module is connected to the sensor. The motion module drives the first or second fixing member to reciprocate, causing the sensor to repeatedly sense the first fixing member and generate a sensing signal. The counting module counts the sensing signals to obtain the sensor's test result. Therefore, this application eliminates the need for manual testing and statistics, automatically controlling the sensor to generate sensing signals and counting the number of times, reducing testing time, improving testing efficiency, and minimizing statistical errors, thus improving the accuracy of the test results.