57 results about "Inspection time" patented technology

The invention provides an intelligent substation inspection method and system based on the Internet of Things, and the method comprises the steps: collecting a multi-mode perception data set, and constructing a real-time three-dimensional map of a substation; constructing a cross-modal generation type fault detection model, and extracting fusion features to obtain a diagnosis result; formulating an optimal inspection path and plan by using a double-layer reinforcement learning framework and an evolutionary algorithm; and executing inspection based on the map to obtain a result. According to the method, multi-source equipment data are fused through the bionic sensing network, and the complex fault recognition capability is improved in combination with the generative fault detection model; the real-time three-dimensional map is based on laser radar SLAM and UWB fusion positioning, and is dynamically updated by using an ICP algorithm, so that the static map problem is solved, and the collision risk is reduced; double-layer reinforcement learning and an evolutionary algorithm are combined to realize multi-objective collaborative optimization, so that high-efficiency routing inspection is guaranteed, energy consumption is reduced, and time is shortened; and a closed loop verification mechanism dynamically adjusts the strategy, so that the adaptive capacity of the system is enhanced, and the inspection accuracy, efficiency and flexibility are improved.

The invention belongs to the technical field of locomotive equipment maintenance, and provides an automatic inspection system and method for a locomotive cooling tower, and the method comprises the steps: obtaining the basic information of the locomotive cooling tower, planning an inspection path for an inspection machine, controlling the inspection machine to inspect along the inspection path, and collecting the visual information of the locomotive cooling tower, the method comprises the following steps: constructing a local three-dimensional grid map in real time, detecting obstacles, evaluating a collision risk between the obstacles and an inspection machine, if the collision risk is high, triggering the inspection machine to avoid obstacles, constructing a global three-dimensional grid map when the inspection machine completes an inspection path, and determining an inspection blind area under the global three-dimensional grid map. And judging whether the current inspection time period is ended or not, if not, triggering supplementary inspection, otherwise, planning an inspection path for the next inspection time period, and after the inspection time period is ended, performing anomaly detection and positioning on each part of the locomotive cooling tower based on visual information acquired by an inspection machine through a machine learning algorithm.

The invention discloses an unmanned aerial vehicle inspection system and method for an intelligent street lamp based on multi-source video fusion, and relates to the technical field of unmanned aerial vehicle inspection, and the system comprises an inspection data collection module, an inspection image analysis module, an inspection mode switching module and an inspection task dynamic evaluation module. The inspection data acquisition module, the inspection image analysis module, the inspection mode switching module and the inspection task dynamic evaluation module are in communication connection with one another; wherein the inspection data acquisition module is used for performing flight inspection on street lamps in a target inspection area one by one through an unmanned aerial vehicle with a visible light camera, and setting image calibration array points to match the accuracy of inspection image acquisition; the inspection image analysis module is used for processing and analyzing the acquired image data; according to the invention, the problem that the inspection time consumption and the data processing burden are greatly increased in the existing multi-source image fusion processing mode is solved.

The invention relates to the technical field of intelligent construction sites, in particular to an intelligent inspection method, device and system for an intelligent construction site based on a space-time diagram convolutional network, and a storage medium, and the method comprises the steps: installing video collection equipment at a construction site, and carrying out the image data collection of construction activities, equipment and stockpile of each region of the construction site; modeling the constructor behavior prediction model, and predicting the flow trend and density of constructors in each region by integrating the construction site construction layout and construction information; processing the acquired image information of each construction area by using an image recognition technology, and recognizing the type, density and related distribution position of equipment; the construction site environment information is fused, the estimated inspection time of each construction area is evaluated, and the relation between the construction equipment density and the inspection time is analyzed; and determining the guarantee range of the spare part maintenance points according to the analysis result of the construction equipment, and adjusting and optimizing the number distribution of the spare part maintenance points according to the utilization efficiency of the existing spare part maintenance points, the flow of construction personnel and the area of the construction region. A reinforcement learning technology is used to optimize inspection roads of inspection personnel, and based on construction personnel flow trend prediction and construction equipment quantity analysis, routing inspection is arranged preferentially in a route of high-utilization-rate equipment and a time period with less construction operation, so that fault hidden dangers are found in time, and the influence on normal construction operation is reduced; and the execution condition of the inspection task is monitored in real time, and the inspection efficiency and the fault risk early warning level are evaluated in combination with the condition fed back by the inspection personnel.

Disclosed is an IoT system for smart gas inspection supervision and distribution, comprising: a public user platform, a citizen cloud service platform, a government gas supervision management platform, a government gas supervision sensor network platform, a government gas supervision object platform, a gas company sensor network platform, and a gas equipment object platform. The government gas supervision management platform is configured to obtain an inspection route; determine a plurality of inspection sub-routes; generate a calling instruction; generate an acquisition instruction and send the acquisition instruction to the gas equipment object platform; determine an inspection type parameter of the inspection sub-routes; divide the inspection sub-routes into three categories of objects to be inspected, and determine candidate assignment parameters of the three categories of objects to be inspected; determine predicted inspection time; determine an inspection assignment parameter; generate an inspection instruction and send the inspection instruction to the gas equipment object platform.

The embodiment of the invention provides a tower cylinder bolt abnormity identification method and device. The method comprises the steps that an image acquisition device arranged on a tower cylinder inspection robot is used for acquiring a front image and a side image of each tower cylinder bolt; performing preprocessing operation on the front image and the side image to obtain a front image block corresponding to the front image and a side image block corresponding to the side image; performing abnormal region identification on the front image block and thread feature identification on the side image block respectively, and outputting identification results including an abnormal type, a quantization parameter and confidence respectively; performing grading processing on the recognition result according to the confidence coefficient in the recognition result, and outputting a judgment result; and the judgment result, the bolt ID and the inspection time are stored in an associated mode, and alarm information is output according to the judgment result and pushed to a manager terminal device. According to the invention, the safety and the detection efficiency of tower bolt inspection can be improved.

The invention discloses an intelligent inspection method for concrete appearance quality, and relates to the technical field of concrete appearance quality detection.The method comprises the following steps that the optimal inspection height is configured for intelligent inspection of an unmanned aerial vehicle based on the detection precision requirement and the detection efficiency requirement of voids and pitted surfaces; the unmanned aerial vehicle inspects the surface of the concrete structure according to the preset route and the set optimal inspection height, and the airborne high-resolution imaging system is used for continuously shooting the detection area. Through a dynamic inspection mechanism based on confidence score driving, the unmanned aerial vehicle can actively and adaptively adjust the inspection height and the inspection time when finding a suspected slight pitted surface, the image resolution and the defect feature detail expression capability are improved, the recognition capability of the convolutional neural network on the slight pitted surface and a dark honeycomb is enhanced, and the detection accuracy is improved. The defect omission ratio and the false detection rate in the inspection process are effectively reduced, and accurate, stable and efficient recognition of hidden defects such as slight pitted surfaces and deep honeycombs on the surface of the concrete structure is achieved.

This invention discloses a material inspection and monitoring method and device based on UWB positioning and multi-view linkage. The method includes: acquiring the sample number of the target material, wherein the target material is equipped with a UWB tag, and the UWB tag and the sample number correspond one-to-one; collecting the inspection time of the target material entering each inspection area according to the UWB tag, and constructing a time-location correlation matrix; and combining the time-location correlation matrix with a preset multi-view relationship model with the inspection area to form multi-view monitoring content, thereby completing the monitoring of the target material inspection process. By constructing a time-location correlation matrix and piecing together multi-view monitoring content, the monitoring of the target material inspection process is completed, providing a basis for rapid and accurate traceability of the target material inspection process afterward, while improving the level of material quality supervision and control, promoting quality inspection efficiency and effectiveness, and realizing full-process tracking and monitoring of the material inspection process.

The invention discloses a transformer substation and converter station equipment intelligent inspection method and system and terminal equipment, and belongs to the technical field of power system operation management. According to the method, equipment information of power transmission, power transformation and power distribution links is integrated by constructing a power transmission, power transformation and power distribution combined inspection model, and an intelligent terminal cluster is cooperatively scheduled to execute a cross-link combined inspection task; collecting visible light images, infrared thermal imaging data and operation state data of the equipment according to preset point positions, performing deep learning on the collected data, automatically identifying abnormal conditions including equipment appearance damage, meter reading deviation, internal and external heating and discharging of the equipment and foreign matter invasion, and obtaining inspection data; statistical analysis is carried out on the inspection data, a visual report containing inspection time, equipment states and defect information is generated, and historical data tracing and multi-source data association analysis are supported. Automatic and efficient inspection and intelligent identification analysis of the equipment are realized, the inspection efficiency and accuracy are improved, and the method is suitable for operation and maintenance management of large-scale complex power grid equipment.

The invention relates to the Internet of Things video analysis technology, in particular to an intelligent construction site remote monitoring system based on the Internet of Things, which is characterized in that firstly, a risk point location analysis module is combined with historical fault data to intelligently analyze the risk index of each region, and then a data acquisition module is used for collecting personnel information and video monitoring data; the video analysis module analyzes the video monitoring data and records the troubleshooting time of the staff in each region, and the evaluation accuracy analysis module adjusts the corresponding standard troubleshooting time in combination with the regional risk index. And the evaluation accuracy of the working personnel on the target area is calculated by considering the influence of the working experience of the working personnel on the troubleshooting accuracy, so that a more objective and accurate evaluation result is obtained. The warning module can give an alarm in time when it is found that the evaluation accuracy is insufficient according to a set accuracy threshold value, so that correction measures are taken in time when the evaluation accuracy of workers is insufficient, and the safety management level of the construction site is greatly improved.

The invention discloses a knowledge recheck method, equipment, a storage medium and a device. Task execution parameters are configured based on an inspection mode corresponding to a knowledge reinspection task; calling a target inspection tool to execute inspection based on slice information and task execution parameters in a preset knowledge base, and obtaining an execution record; and performing problem positioning and slice tracing on the execution records to obtain knowledge optimization suggestions. Compared with the situation that real-time synchronization of knowledge and a valid system cannot be guaranteed through manual auditing, and the auditing efficiency is low, the method calls an inspection tool to execute inspection through slicing information and task execution parameters configured in a user-defined mode to achieve modular extraction and slicing of self-adaptive structured knowledge content, the data integrity is greatly improved, and the efficiency of the self-adaptive structured knowledge is improved. The inspection time is greatly shortened, and the inspection efficiency is improved.

The present invention relates to the technical field of fabric surface defect detection, and specifically discloses a machine vision-based fabric surface defect detection method and system. The method comprises analyzing the pilling characteristics of a fabric surface image to obtain the ratio of the number of abnormal areas, judging the fabric quality, and generating an unqualified signal and a suspected qualified signal; analyzing the abnormal marking results of the fabric surface areas to obtain a pilling trend value, determining the impact of fabric surface pilling on fabric surface defects, and generating a strong impact signal; and extracting all fabric samples with unqualified signals and strong impact signals within a test time, recording them as unqualified traceability samples and strong impact traceability samples, respectively. The present invention optimizes the fabric inspection time by determining the fabric optimal inspection time and the inspection time of fabric production equipment, and analyzing the fabric production inspection time. This not only improves the pertinence and efficiency of the inspection, but also helps to promptly discover and resolve problems in the production process, thereby ensuring the quality of the fabric.

The invention discloses an inspection control method based on a robot with a body and a related device. The method comprises the following steps: determining inspection boundaries of an open area and a non-open area; performing path planning on the plurality of inspection points in the to-be-inspected area according to the inspection boundary to obtain navigation information; if the robot with the body detects a first obstacle when moving according to the navigation information, executing a passing skill operation corresponding to an entering mode of the first obstacle in a skill library; determining the maintenance time of the passing state according to the leaving mode of the first obstacle and the inspection time demand; when it is detected that the robot with the body arrives at the target inspection point, activating a carried inspection device for inspection based on the inspection index of the target inspection point to obtain a first inspection result; performing visual analysis on the obtained inspection object image in the target inspection point to obtain a second inspection result; and generating an inspection report according to the first inspection result and the second inspection result. According to the invention, the inspection efficiency and the intelligent level of inspection are improved.

The invention discloses a metro vehicle bottom fastener looseness detection method based on target detection and image processing, which comprises the following steps: firstly, acquiring an image of a metro vehicle bottom fastener area, constructing a training set and a test set based on the image, constructing an improved YOLOv11 target detection model, training the model by using the training set, and detecting the looseness of the metro vehicle bottom fastener area. The method comprises the steps of training a target detection model, detecting fasteners in a fastener area of a subway vehicle bottom based on the trained target detection model, cutting to obtain a single fastener image, and finally detecting the extracted single fastener image to judge whether the fasteners are loosened or not. Compared with a traditional manual inspection mode, the scheme has the advantages that the inspection time is greatly shortened through a target detection technology and an image processing method, more vehicle bottom areas can be covered in shorter time, large-scale and frequent detection requirements are met, the influence of human factors can be eliminated, the stability and consistency of detection are improved, and the detection efficiency is improved. And the detection result is more reliable.

The present invention relates to the field of data processing, and specifically to a smart inspection management method and system. When an inspection user conducts an inspection, the pre-constructed reference information is provided to the inspection personnel for reference, so that the inspection personnel can understand the reference range and inspection time of each inspection point of each inspection item. This helps the inspection personnel who are not familiar with the project quickly understand the inspection project. In addition, the present application determines the priority of each inspection point by using the environmental parameters collected in real time by the sensors set on the construction site project and the real-time positioning of the inspection personnel. When the inspection personnel are performing the inspection task, the priority and reference information are used to guide and supervise the inspection personnel. The present application can effectively guide and supervise the inspection process of the inspection personnel, and help the inspection personnel improve the inspection efficiency and inspection quality.

The invention belongs to the technical field of railway operation and maintenance, and discloses an operation and maintenance equipment inspection data prediction method, system, equipment and medium, and the method comprises the steps: obtaining first historical inspection data of a detection item corresponding to operation and maintenance equipment; preprocessing the first historical inspection data of the detection item to obtain second historical inspection data related to inspection times; based on the second historical inspection data and an inspection data state transition model, determining state transition reference inspection data of the detection item; based on the second historical inspection data, the state transition reference inspection data and the state transition probability matrix, constructing a state transition probability prediction model; and predicting the current inspection data in the detection item by using the state transition probability prediction model to obtain the probability of transition of the current inspection data to the next state. According to the scheme of the invention, the inspection plan of a fixed shift can be converted into inspection according to the state, and the density of inspection work can be effectively reduced.

The utility model discloses a microscope rotating tray device, which relates to the technical field of wafer detection and comprises an objective table, a base and an air guide column. A vacuum cavity is formed in the objective table; a plurality of adsorption holes communicated with the vacuum cavity are formed in the top surface of the objective table; the air guide column is perpendicular to the objective table, and the top of the air guide column is rotationally connected with the bottom of the objective table through a rotary joint; an air guide channel in the air guide column is connected and communicated with the vacuum cavity through a rotary joint; the air guide column is rotationally connected with the base, and the rotating center line of the air guide column is perpendicular to the rotating center line of the objective table. The objective table can realize transverse rotation adjustment and vertical rotation adjustment so as to adjust the inclined state; adjustment is simple, convenient and flexible, inspection time can be saved, and inspection efficiency is improved.

The application relates to the technical field of patrol path optimization, and discloses an intelligent recommendation system for an external stand pipe inspection path, which comprises the following: an inspection unit records facade positions, center heights and inspection operation modes; an evaluation unit performs risk assessment on each inspection unit according to historical defect information, stand pipe types and environmental exposure conditions, obtains an inspection unit risk level, and forms an inspection unit time window constraint; a processing unit constructs an inspection service graph; a recommendation unit determines a to-be-inspected unit, generates a candidate inspection path on the inspection service graph, combines the candidate inspection paths into multiple inspection task packages, performs resource scheduling in combination with skill information and available time information of an inspection team, and obtains an inspection path recommendation result corresponding to each inspection team. The application reduces the overall inspection time and the number of high-cost inspection operation mode switching times, and improves the external stand pipe inspection safety and operation and maintenance management efficiency.

The invention discloses universal clamping equipment for a three-coordinate measuring instrument, which is characterized by comprising a clamping seat and a plurality of clamping pieces, an adjusting mechanism is arranged between the clamping pieces and the clamping seat, the clamping pieces can rotate and stretch out and draw back through the adjusting mechanism, the end part of each clamping piece is provided with a clamping structure I, and a workpiece can be fixed through the clamping of the clamping structure I. The workpiece can be fixed through clamping of the first clamping structure, the workpiece can be clamped from different positions through cooperation of the multiple clamping pieces, the fixture can be universally used regardless of the shape of the workpiece, the fixture does not need to be replaced every time, a large amount of detection time is saved, and the detection efficiency is improved.

The utility model relates to driving plate type safety inspection equipment, which comprises a dial plate and a pointer, a pointer is arranged on the front surface of the dial plate, the first end of the pointer is rotationally connected with the center of the dial plate, and the other end of the pointer points to the patrol time period marking devices; according to the utility model, patrolling and patrolling time standard recording can be realized visually.

A smart, human-centered technique that uses artificial intelligence and mixed reality to accelerate essential tasks of the inspectors such as defect measurement, condition assessment and data processing. For example, a bridge inspector can analyze some remote cracks located on a concrete pier, estimate their dimensional properties and perform condition assessment in real-time. The inspector can intervene in any step of the analysis / assessment and correct the operations of the artificial intelligence. Thereby, the inspector and the artificial intelligence will collaborate / communicate for improved visual inspection. This collective intelligence framework can be integrated in a mixed reality supported see-through headset or a hand-held device with the availability of sufficient hardware and sensors. Consequently, the methods reduce the inspection time and associated labor costs while ensuring reliable and objective infrastructure evaluation. Such methods offer contributions to infrastructure inspection, maintenance, management practice, and safety for the inspection personnel.

The utility model relates to the technical field of contact chip detection, in particular to an automatic contact chip detection device which comprises a first conveying mechanism, a second conveying mechanism, a defective product box, a discharging station, a positioning mechanism, a first detection mechanism, a second detection mechanism and a carrying mechanism. According to the automatic detection device for the contact piece, the product containing the contact piece is placed on the placing seat at the discharging station, the positioning mechanism positions and shapes the contact piece of the product on the placing seat, and the first detection mechanism detects the appearance of the top surface of the contact piece of the product on the placing seat. The second detection mechanism detects the appearance of the side face of the product contact piece on the placement seat, and when the two times of detection are qualified, the carrying mechanism carries the product on the placement seat to the head end of the second conveying mechanism and conveys the product to the next procedure; when at least one time of detection is unqualified, the carrying mechanism carries the product on the placing seat to the defective product box, the detection speed is high, the detection time can be reduced to 8s, the reject ratio does not exist, and the use is convenient.

The utility model relates to a sample analysis system. The sample analysis system comprises a detection area, a main conveying mechanism, a temporary storage mechanism, an inspection mechanism and a carrying mechanism, the detection area is used for detecting a sample; the caching mechanism is positioned on one side of the detection area and is used for storing samples; the main conveying mechanism is located on one side of the detection area, and the main conveying mechanism is used for receiving a sample input from the outside, conveying the sample to the cache mechanism, sending the sample to the detection area or outputting the detected sample; the inspection mechanism is used for conveying a sample to the detection area; the temporary storage mechanism conveys samples back and forth through the carrying mechanism and the main conveying mechanism or conveys the samples to the inspection mechanism through the carrying mechanism. According to the scheme provided by the invention, the sample transportation path can be shortened, and the inspection time is saved.

This invention relates to the field of pharmaceutical testing technology, and in particular to a device for detecting defects in the appearance of pharmaceuticals in all directions. The device includes a feeding mechanism, an end-face acquisition mechanism, a first rejection mechanism, a side-face acquisition mechanism, and a second rejection mechanism arranged sequentially along the conveying direction of the material to be inspected. The feeding mechanism conveys the material to be inspected to the end-face acquisition mechanism, which acquires the end face of the material and sends it to the first rejection mechanism. The side-face acquisition mechanism acquires the side face of the material and sends it to the second rejection mechanism. This invention automatically realizes feeding and material inspection, completely detecting the end face and side face information of the material to be inspected, without delaying the inspection time, improving the quality of material inspection, and increasing production efficiency.

This invention provides a method, system, storage medium, and device for generating power line inspection work orders. The method includes: calculating the total inspection time for each power line to be inspected based on its line information; calculating the available time for each inspection team based on their work information; sorting all inspection teams in ascending order of their available time and generating a team ranking table; and allocating power lines to be inspected to all inspection teams according to the total inspection time for each power line to be inspected and the available time for each inspection team, based on a preset allocation rule and in the order of the team ranking table, to generate corresponding work orders. By allocating work orders to inspection teams in ascending order of available time, teams with shorter available time can be prioritized for finding matching power lines to be inspected, thus minimizing the occurrence of no work orders being generated for teams with shorter available time.

This invention relates to the field of inspection management technology and discloses an intelligent inspection management method and system based on cloud-edge collaboration. The method includes: acquiring inspection task work orders to be executed; acquiring the path length and number of inspection points for each inspection segment in the inspection task work order; analyzing the path length and number of inspection points to obtain the time quota for each inspection segment; obtaining differentiated time quotas by analyzing the path length and number of inspection points for each inspection segment; generating a task delay risk coefficient by combining real-time basic data and inspection point status; collaboratively calculating additional time requirements when an inspection point is abnormal; and evaluating the buffer capacity of the remaining work period to obtain an inspection management adaptation value. This solution can intelligently and flexibly adjust the inspection time during the inspection process to avoid insufficient inspection and effectively prevent excessive extension from impacting the overall inspection task. It achieves dynamic optimization of inspection path time and ensures the management effect of cloud-edge collaborative intelligent inspection.

The application discloses a kind of equipment and method for functional valve seal assembly quality visual inspection.It includes monocular color industrial camera, plane diffuse light source, camera light source fixing plate, two kinds of workpiece positioning devices and other accessories.Monocular color industrial camera can provide good illumination environment for monocular color industrial camera image acquisition;In addition, by being designed with two kinds of workpiece positioning devices in the application, the same equipment can simultaneously meet the inspection needs of large quantities of functional valve seals and adapt to new models of functional valve seals, realize the automatic acquisition, analysis and determination of quality information of seal rubber ring and protective ring as detection feature points, solve the problem of misloading and missing loading, greatly reduce the limitation that traditional manual inspection can only check one sleeve shaft rubber ring at a time, shorten the inspection time and retain product quality certificate function, effectively improve the detection quality and efficiency of sleeve shaft rubber ring assembly.

The present invention provides a method and system for automatically checking the electroplated gold data network. Through the functions of "coordinate point selection" and "graphic overlap comparison", it can automatically and accurately identify and process multi-layer network overlap and touch, improve the accuracy of inspection, and reduce errors and defects. Compared with manual inspection, the present invention realizes automation and greatly shortens the inspection time. The system includes an inspection execution unit, a record display unit, a graphic viewing and modification unit, and an error linking unit, which simplifies the process, provides detailed records, intuitively displays the error location and supports instant modification, quickly locates problems through error linking, reduces rework, and improves the user experience. Overall, the system integrates multiple functional units, realizes the automation and intelligence of the inspection process, reduces manual intervention, ensures the accuracy and consistency of inspection, and provides an efficient and reliable solution for the inspection of electroplated gold data network.

A method for a component of a gas turbine engine includes obtaining images of the component for a plurality of sequential inspection time periods, at least a portion of the images depicting degradation of the component. A first machine learning model (MLM) includes an input layer, an output layer, and a latent space therebetween. The latent space includes a plurality of clusters of nodes corresponding to respective image features. The method includes, for a plurality of the inspection time periods, utilizing the first MLM to determine which one or more of the clusters of the latent space the image most closely aligns with. The method also includes, for a plurality of the inspection time periods, utilizing a second MLM, which is a different type of MLM than the first MLM, to predict, based on the latent space of the first MLM, a degradation of the component that will occur prior to a subsequent one of the inspection time periods. The method includes determining a difference between the prediction and the image of the component from said subsequent one of the inspection time periods, and providing a notification to a user based on the difference. A system for analyzing degradation of a component of a gas turbine engine is also disclosed.

The invention belongs to the technical field of data processing, and relates to an exception handling method, which comprises the steps of judging whether current time reaches patrol time corresponding to a target function module of a target system or not; if yes, calling an inspection document corresponding to the target system; acquiring an inspection strategy corresponding to the target function module based on the inspection document; analyzing the target function module based on the patrol strategy to obtain a patrol result; carrying out anomaly identification on the inspection result, and judging whether an anomaly exists in the inspection result or not; if yes, abnormal data are extracted from the inspection result, and corresponding abnormal notification information is generated based on the abnormal data; and performing exception feedback processing based on the exception notification information. The invention further provides an exception handling device, computer equipment and a storage medium. The method can be applied to abnormity monitoring business scenes in the financial field and the medical field, abnormity inspection of the target system can be automatically and accurately realized through the method, and the stability and reliability of the target system are improved.