37results about How to "Eliminate subjective errors" patented technology

The invention discloses a roadway deformation real-time detection method and system based on binocular vision, and the method comprises the steps: firstly, installing and debugging a mining industrial binocular camera, and training an anchor rod end target detection algorithm; then real-time acquisition and preprocessing of images are carried out, and environmental noise is removed by using a self-adaptive median filter; and based on the preprocessed image, identifying and positioning the end of the anchor rod by using a trained target detection algorithm. A binocular vision technology is utilized to calculate three-dimensional coordinates of the end of the anchor rod, and feature matching and parallax calculation between images are carried out. And finally, comparing the three-dimensional coordinates of the ends of the anchor rods at different time points, and inputting the three-dimensional coordinates into a roadway deformation calculation module to obtain a deformation result of the roadway so as to realize real-time deformation monitoring and early warning of the roadway.

The invention discloses an AI-based PCBA circuit board defect detection system. The AI-based PCBA circuit board defect detection system comprises the following steps: S1, an image acquisition module, wherein the image acquisition module comprises a camera shooting assembly and a light source assembly; wherein the camera shooting assembly comprises a high-resolution camera, and the high-resolution camera is used for capturing an image of a PCBA circuit board to be detected; s2, an image processing module, wherein the image processing module comprises image preprocessing, image segmentation and image recognition; according to the invention, automatic defect detection is carried out on the PCBA circuit board by using an artificial intelligence technology, the system combines image processing and deep learning technologies to realize rapid and accurate detection of surface defects of the circuit board, and meanwhile, through an automatic and intelligent detection means, the detection precision, efficiency and consistency are greatly improved; and the system not only can meet the current production requirements, but also can be continuously optimized and expanded through data driving, and has remarkable competitive advantages.

The invention provides a non-contact on-line measuring device and method for excavator structural members, a double-scanning system cooperation mode is adopted, a tracker and a ball cage scanner are respectively used on two sides of a detection device, the ball cage scanners are installed on a cooperative robot to execute automatic scanning actions, and meanwhile, the robot is driven by the robot to move. The tracker and the robot are both installed on the linear guide rail, displacement operation can be carried out, the scanning and collecting range of the system is expanded, and therefore full scanning work of the large structural part is completed. The two scanning systems scan and collect the structural member from the left side and the right side at the same time, then data are spliced together, a three-dimensional point cloud model of the structural member is obtained, size information is analyzed and extracted, a detection report is generated, communication with a workshop data management system is carried out, and measurement data are integrated and applied.

This invention belongs to the field of materials testing technology and discloses a deep learning-based method and system for identifying the interface of SiC modified asphalt. It acquires multi-dimensional interface images through a layered time-series acquisition method using four devices: optical microscope, SEM, EDS-Mapping, and Raman spectrometer. Adaptive algorithms are used for targeted denoising, normalization, and registration, while attention mechanisms and weighted fusion strategies are combined to enhance interface features. Simultaneously, a multi-condition dataset containing a high proportion of minor defects is constructed to achieve deep fusion and accurate identification of multi-modal features, eliminating subjective errors from manual judgment and improving the fine-grained accuracy and detection efficiency of SiC modified asphalt interface identification. The U-Net model is improved for specific scenarios and designed to be lightweight. By optimizing the encoder-decoder structure, introducing a dual-channel attention mechanism and a condition-adaptive branch, and combining a loss function, the feature extraction capability of interface boundaries and minor defects is enhanced.

The present application discloses a monitoring method, device, equipment and storage medium for a transformer substation protection pressure plate, and relates to the field of electrical digital data processing technology. The present application adopts dual monitoring means of electrical monitoring and visual monitoring to ensure more accurate monitoring results. By monitoring the current throw-in / out state and visual throw-in / out state of each connection piece respectively, and verifying whether the connection piece is in the same state of the current throw-in / out state and the visual throw-in / out state at the same time, it is determined whether the connection piece is abnormal, and the connection piece whose current throw-in / out state does not match the visual throw-in / out state is defined as an abnormal connection piece. Compared with the prior art, the present application does not require manual participation in the monitoring process, thereby eliminating subjective errors and reducing labor costs, and the dual judgment mechanism can further improve the monitoring accuracy.

The application is suitable for the technical field of shield engineering data processing, and provides a multi-modal data fusion slag discharge quantity monitoring and early warning method, device and terminal equipment. The method comprises the following steps: acquiring first slag discharge quantities of each tunneling ring measured by a shield machine belt weighing system, weight time series data of a gantry crane during the process of hoisting and transporting slag, and preset upper and lower limit thresholds of the slag discharge quantity; determining actual and empty bucket weights of each slag bucket corresponding to each tunneling ring according to the weight time series data; determining a second slag discharge quantity of each tunneling ring according to the actual and empty bucket weights of each slag bucket corresponding to each tunneling ring; and monitoring and early warning the shield machine slag discharge quantity according to the difference between the first slag discharge quantity and the preset upper and lower limit thresholds of the slag discharge quantity, the difference between the first slag discharge quantity and the average of the slag discharge quantities of the previous N tunneling rings, and the difference between the first slag discharge quantity and the second slag discharge quantity. The application can realize high-precision accounting and real-time early warning of the slag discharge quantity.

The application relates to the technical field of interface measurement, and discloses an electrolytic aluminum electrolyte aluminum liquid interface measurement system based on conductive characteristics, which comprises a data acquisition module that obtains impedance distribution data at different depth positions by controlling a probe to move in a vertical direction and collecting impedance signals; the data acquisition module adopts a multi-frequency excitation mode to obtain impedance responses at different frequencies during the movement of the probe, and adaptively adjusts the movement speed of the sampling probe according to the stability of the collected signals; an impedance change rate is extracted according to the impedance distribution data, the interface is judged based on the impedance change rate, and a candidate interface of the electrolytic aluminum electrolyte aluminum liquid is determined; one candidate interface of the electrolytic aluminum electrolyte aluminum liquid is selected, random multi-point measurement is carried out in the horizontal direction of the candidate interface, measurement information in the horizontal direction of the candidate interface is collected, and an evaluation model is constructed; and the application helps to improve the recognition accuracy of the interface.

This invention belongs to the field of high-temperature heat pipe performance testing technology, specifically relating to a fully autonomous adaptive heat pipe heat transfer performance testing method. It includes the following steps: Step S1: Generating a heat flux density benchmark based on geometric features; Step S2: Using P... base Based on this, differentiated power loading is performed using a stage-dependent loading coefficient β. During step S2, steps S3 to S5 are executed in parallel: Step S3: Parallel execution of adaptive physical stage switching based on a dual criterion of "temperature-anomaly"; Step S4: Parallel execution of autonomous steady-state determination for each power loading at key temperature points in the linear heat transfer stage and during each power loading in the limit approximation stage; Step S5: Parallel execution of full-cycle automated safety protection based on monitoring the second derivative of the evaporation section temperature. The beneficial effects are: improved adaptability of the testing method, compatible with heat pipes of different geometric dimensions; and effective improvement of testing efficiency through the implementation of a staged control strategy.

The application discloses a tibiofemoral joint line included angle measuring method and related device. Wherein, the method comprises: segmenting the femur and tibia in the three-dimensional medical image to obtain the femur point cloud set and the tibia point cloud set; determining the femur distal articular surface tangent line based on the femur point cloud set and determining the tibia proximal articular surface tangent line based on the tibia point cloud set; determining the tibiofemoral joint line included angle based on the femur distal articular surface tangent line and the tibia proximal articular surface tangent line, so as to not only automatically identify and determine the femur articular surface tangent line, eliminate the subjective error when manually drawing the tangent line, ensure the objectivity and consistency of the tangent line positioning, but also realize the full-automatic measurement of the tibiofemoral joint line included angle, avoid the visual deviation when manually measuring the angle, significantly improve the accuracy and repeatability of the measurement result, and provide reliable quantitative indexes for the diagnosis and treatment, operation planning and curative effect evaluation of the knee joint disease.

The invention discloses an optical glass stress detection system and method, and relates to the field of optical measurement, and the system comprises the following components: a high-speed image processing module which carries out the image enhancement processing after an image processing unit receives image data, improves the contrast ratio and definition of an image, carries out the denoising processing of the enhanced image, and obtains a high-speed image; according to the invention, the Gaussian filtering algorithm of the high-speed image processing module effectively suppresses the noise interference existing in the image due to the influence of environment and equipment factors, improves the signal-to-noise ratio of the image, enables the subsequent feature extraction and stress analysis to be more accurate, and enables the image to be more accurate while smoothing the image through Gaussian filtering. According to the method, the edge information of the image can be well reserved, the system can identify and analyze the stress distribution condition more accurately, and meanwhile, the fuzzy degree of Gaussian filtering can be controlled by adjusting the standard deviation sigma of the Gaussian function.

The present application relates to the technical field of lithium battery production, and particularly relates to a kind of detection method of lithium ion battery positive pole slurry stability, comprising the following steps: S1: immediately after slurry preparation, sample is removed to rheometer, amplitude scanning test is carried out, and storage modulus G' and phase angle delta are recorded;S2: slurry is prepared again, immediately after slurry preparation, it is removed to rheometer, and stress scanning test is carried out, and yield stress is recorded;S3: the stability of slurry is evaluated in combination with yield stress, storage modulus G' and phase angle delta three indexes.The present application simultaneously collects yield stress, storage modulus G' and phase angle delta three dimensional indexes, respectively represents the strength, stiffness and solid-like characteristics of slurry, realizes the multi-angle, three-dimensional evaluation of internal network structure stability of slurry, and solves the technical problems that the existing detection method has poor accuracy, long time consumption, pre-treatment destroys the original structure of slurry and the single evaluation index leads to misjudgment.

The invention relates to the technical field of EDTA (Ethylene Diamine Tetraacetic Acid) titration, in particular to a road lime soil content rapid titration detection end point judgment device and a use method thereof. The suction cup is matched with the band-pass optical filter and the photoresistor, so that the resistance value of the photoresistor can be changed along with the color change of a solution to be detected, the real-time current displayed by the ampere meter is changed, and when the difference percentage of the real-time current and the comparison current is observed to be less than 10%, the titration experiment reaches the titration end point; the detachable suction cup is matched with the protrusion and the clamping groove, so that the band-pass optical filter is convenient to replace, and it is guaranteed that the position of the band-pass optical filter and the position of the photoresistor are always relatively fixed so as to control variables. According to the method, the appropriate optical filter is selected to be matched with the titration experiment, optical signals are converted into electric signals for objective characterization by utilizing optical characteristics of the optical filter and the photoresistor, subjective errors of end point judgment of the titration experiment are eliminated, and the accuracy of the experiment is ensured while a part of labor force is saved.

This invention discloses a multi-algorithm offline prediction system and deployment method for automotive safety based on Windows-WSL, involving the interdisciplinary field of automotive safety and computer science. The system utilizes WSL to build a Linux computing environment on the Windows side, transforming multi-source CAE / CAD data and operating parameters into standardized feature matrices through an automated pipeline. It employs an environment isolation mechanism to independently manage multiple prediction algorithms, achieving dynamic scheduling of computing power and automatic cache reclamation. Deployment scripts establish the data link between the Windows engineering software and the Linux inference engine. This invention achieves unified processing of heterogeneous data and stable management of the algorithm environment, significantly improving the generalization accuracy of offline prediction, the reliability of system operation, and the deployment efficiency in engineering sites.

The invention provides a method for detecting insoluble particles in an electrode auxiliary material of a secondary battery, the auxiliary material is a binder or a thickener, and the method comprises the following steps: (S1) dissolving the auxiliary material containing the insoluble particles in a solvent to obtain a solution containing the insoluble particles; (S2) coating the solution containing the insoluble particles obtained in the step (S1) on a transparent plate to obtain a coated transparent plate; (S3) shooting the coated transparent plate obtained in the step (S2) through an optical microscope to obtain an image; and (S4) the image obtained in the step (S3) is processed through an image processing device, the image processing device comprises an input module, a judgment module, a data analysis module and an output module, and the image processing device recognizes insoluble particles through an image recognition algorithm. Therefore, detection can be completed quickly and accurately, and subjective errors of manual judgment and counting are eliminated.

The present application belongs to the field of medical image processing and biomedical engineering, and particularly relates to a dynamic contrast-enhanced magnetic resonance imaging reconstruction method based on pharmacokinetic model optimization. The steps are as follows: obtaining original image data, performing multi-scale data correction preprocessing on the original data to generate preprocessed image data; extracting a large blood vessel region based on the preprocessed image data as a candidate region of a contrast agent input function; constructing a heterogeneous nonlinear pharmacokinetic model; establishing a cooperative reconstruction mechanism of the heterogeneous nonlinear pharmacokinetic model and the preprocessed image data; integrating the kinetic constraint condition of the heterogeneous nonlinear pharmacokinetic model into the objective function of the preprocessed image data reconstruction as a loss term, and further iteratively updating the intermediate parameters and the initial reconstructed image. The method of the present application improves the accuracy of parameter estimation in the tumor lesion region through the adaptive heterogeneous nonlinear pharmacokinetic model.

The invention discloses a vehicle mobile phone volume change track detection method, device and equipment and a storage medium. According to the method, a Python automation script is used for controlling terminal equipment to execute a sound detection process, a target sound source is automatically triggered, a volume gear is adjusted, a sound scene is switched, and an operation environment is provided for sound data collection; according to an operation environment, a browser sound collection interface is synchronously called to capture physical parameters of loudspeaker sound of terminal equipment in real time, original collection data are obtained, the original collection data are calibrated and filtered, standardized sound data are generated, and the standardized sound data are displayed in real time through a visual interface. And after the detection is completed, the full-amount detection data is automatically packaged and stored according to the preset format, so that the full-automatic operation of the volume change track detection of the vehicle-mounted terminal and the mobile phone can be realized, the detection efficiency is remarkably improved, the subjective error of manual operation is eliminated, the environmental noise interference is effectively overcome, and the objectivity and accuracy of the detection data are ensured.

The invention provides a circulating tumor cell rapid detection method based on deep learning, and the method comprises the steps: firstly taking a RetinaNet network structure as a basis, employing RepVGG as a backbone network Backbone, employing a multi-branch structure during training, and employing a single-path structure during reasoning; a route from top to bottom is added on the basis of the FPN, and semantic information of a bottom layer and semantic information of a top layer are fused; simplifying a detection head Head, and optimizing a classification and regression sub-network; the loss function is reasonably optimized for different stages; and processing a new image collected from the biological sample by using the rapid detection model, and outputting a CTCs detection result. Cell recognition, detection and classification are carried out on the fluorescent microscopic image, the rapid detection model takes into account a plurality of performance indexes such as cell detection efficiency and accuracy, has relatively high accuracy and relatively strong robustness, and solves the problems of low circulating tumor cell detection speed, low accuracy and the like in the prior art.

The application provides an anchorage zone damage mechanism analysis method and system based on finite element verification, relates to the technical field of simulation and simulation, and comprises the following steps: local and global modeling of the anchorage zone of a multi-scale bridge expansion device is performed by using a finite element model, interface contact behavior is simulated, and corresponding mechanical indexes and damage variables are obtained; each mechanical index is subjected to correlation regression processing with interface bonding damage parameters and concrete matrix damage parameters, relevant factors of the two types of damage parameters are determined, the interface bonding damage parameters and the concrete matrix damage parameters are coupled based on the relevant factors, comprehensive damage parameters are obtained, and a first mapping relationship between the comprehensive damage parameters and the mechanical indexes is established; the comprehensive damage parameters are divided into a plurality of mapping intervals with different numerical ranges, in each mapping interval, a corresponding damage master control factor is obtained, the first mapping relationship is corrected, a target mapping relationship is obtained, and a damage evolution process of the anchorage zone is determined.

The invention provides a portable in-place detection device, a cabinet and equipment. The portable in-place detection device comprises a shell, a limit switch, an alarm device and a power supply. A mounting cavity is formed in the shell. The limiting switch is installed in the installation cavity of the shell and comprises a trigger ejector rod, and the trigger ejector rod penetrates through the side wall of the shell and extends out of the shell. The alarm device is fixed to the side wall of the shell, one end of the alarm device extends into the mounting cavity, the other end of the alarm device is exposed out of the shell, and the alarm device is connected with the limiting switch; the power source is installed in the installation cavity of the shell and connected with the limiting switch and the alarm device. When the trigger push rod is triggered, the limit switch is switched from an open state to a closed state, a closed loop is formed between the alarm device and the power supply, and the alarm device gives an alarm.

The invention discloses a monitoring method, device and equipment for a transformer substation protection pressing plate and a storage medium, and relates to the technical field of electric digital data processing.The double monitoring means of electric monitoring and visual monitoring are adopted to ensure a more accurate monitoring result, and the current on-off state and the visual on-off state of each connected piece are monitored respectively, so that the monitoring accuracy of the transformer substation protection pressing plate is improved. Whether the connected sheets are in the same state of the current on-off state and the visual on-off state is verified to judge whether the connected sheets are abnormal or not, and the connected sheets of which the current on-off state is not matched with the visual on-off state are defined as abnormal connected sheets. Compared with the prior art, manual participation is not needed in the monitoring process, subjective errors are eliminated, meanwhile, the labor cost is reduced, and the monitoring accuracy can be further improved through a dual-judgment mechanism.

The application provides an epoxy asphalt curing state and construction feasibility analysis method, device, equipment, medium and program product, and relates to the technical field of road engineering.The method comprises the following steps: acquiring working condition data of to-be-tested epoxy asphalt mixture; the working condition data is data affecting the curing reaction progress and construction performance of the epoxy asphalt; based on the working condition data, curing degree prediction is performed through a pre-constructed curing degree dynamic prediction model to determine the curing degree of the to-be-tested epoxy asphalt mixture; based on the curing degree, construction feasibility analysis is performed through a pre-constructed grading judgment model to determine the curing state analysis result, construction feasibility analysis result and compaction analysis result of the to-be-tested epoxy asphalt mixture.Through the above method, subjective errors caused by manual experience judgment can be eliminated, the accuracy of the analysis result is improved, the road construction quality and control efficiency of the epoxy asphalt mixture are improved, material waste can be effectively avoided, and the construction period loss is reduced.

The invention relates to the technical field of abrasive disc processing equipment, in particular to a method for intelligently manufacturing a metal mineral polished section, which comprises the following steps: S1, roughly grinding a sample through water and sand adding, surface grinding and plane treatment operations; s2, the sample is subjected to advanced fine grinding treatment through a grinding material; s3, performing high-precision wafer grinding treatment on the sample through timed grinding with grinding powder and polished wafer thickness fine detection operation, and using a thickness sensor and a roughness sensor in combination to ensure that the surface quality of the sample meets a high standard; and S4, under the condition that the thickness reaches the standard, the sample is polished, a roughness sensor is used for detecting the surface smoothness of the sample, the polishing machine stops working after the specified smoothness is achieved, and the metal mineral polished section meeting the requirement is obtained. Detail parameters in the grinding and polishing processes are monitored and adjusted in real time through a sensor system, and high consistency and high standard quality of final products are ensured.

The application discloses a road construction safety monitoring method based on unmanned aerial vehicle image shooting, and belongs to the technical field of construction safety monitoring. The road construction scene is first divided into three risk partitions of a roadbed, a bridge and a culvert, and a foundation pit operation area, a differentiated unmanned aerial vehicle collection scheme is formulated, and a standardized image set with a time-space label of each partition is obtained; then, for each partition core danger source, corresponding safety monitoring parameters are extracted, and exclusive safety data sets of each risk partition are constructed; coupling analysis is carried out on the safety data set through the construction of parameter coupling correlation rules, and a danger hidden danger index of each partition is output; finally, risk grading alarm is completed in combination with a preset threshold rule, a safety monitoring report is integrated and generated and is pushed to corresponding management personnel. The application realizes global precise monitoring, risk quantitative evaluation and intelligent early warning of road construction safety, and greatly improves the efficiency and intelligent level of construction safety control.

This application relates to the field of automotive manufacturing process design, and discloses a method, apparatus, equipment, and storage medium for the layout design of standard parts. A local coordinate system of the mechanism is established using a coordinate system distance positioning algorithm. The mechanism layout surface of the standard part is identified based on this local coordinate system. The total weight is calculated based on the mechanism layout surface and the envelope size and material density of the standard part to match the standard part model, thus obtaining the target standard part. The initial layout position of the target standard part is calculated according to layout rules. An avoidance algorithm is used to eliminate interference areas of other standard parts, generating multiple initial layout points. The GA-PSO hybrid optimization algorithm is used to optimize these initial layout points to obtain the optimal layout point. Kalman filtering is introduced to predict and correct the layout position in real time, obtaining the target layout point. Adjustments are made to the target layout point using integer rules (e.g., whole numbers of five or ten), enabling intelligent calculation of the screw and pin layout positions.

The utility model discloses a portable fruit and vegetable monitor, this portable fruit and vegetable monitor includes: near infrared spectrometer, camera, processing plant and display device, near infrared spectrometer is used for emitting light to fruit and vegetable, and collects the spectral data of fruit and vegetable reflection or projection, camera is used for gathering the image of fruit and vegetable, processing plant is connected with camera and near infrared spectrometer communication respectively, and processing plant is used for determining the internal information of fruit and vegetable based on spectral data, determines the external information of fruit and vegetable based on image, and display device is connected with processing plant communication, and is used to show internal information and external information. Through the mutual cooperation of camera and near infrared spectrometer, utilize visual technology and spectral analysis technology to carry out nondestructive testing to fruit and vegetable, make the selection process of fruit and vegetable more efficient, convenient and accurate. And, reduce the personnel and fruit and vegetable contact, ensure the quality and safety of food.

The invention discloses a spinal cord injury post-neurological function comprehensive evaluation system based on big data. The system comprises a data acquisition module, a spinal cord injury multi-modal feature depth selection module, a pre-injury neurological function baseline construction module and a double-reference spinal cord injury neurological function comprehensive evaluation module. The invention relates to the technical field of medical data processing, in particular to a spinal cord post-injury neurological function comprehensive evaluation system based on big data, which innovatively combines a pre-injury neurological function baseline construction module and a double-reference spinal cord injury neurological function comprehensive evaluation module to improve the comprehensiveness and accuracy of evaluation results; a collaborative correction feature screening algorithm fusing ternary mutual information is provided, and the model evaluation precision and stability are improved; the clustering algorithm is innovatively improved by fusing a high-dimensional vector included angle variance quantification method and a core point secondary evaluation strategy based on a reverse neighborhood number evaluation mechanism, the accuracy of a clustering result is improved, and the accuracy of a neural function evaluation result after spinal cord injury is improved.

This invention discloses a micro-displacement measurement device and method based on a Michelson interferometer and a wedge. The device includes a wedge assembly, a loading test platform, and a vertical Michelson interferometer. The vertical interferometer guides the measurement beam vertically downward through a beam splitter. The wedge assembly is located in this optical path and can move laterally with the deformation of the sample under test, thereby changing the thickness of the medium through which the beam passes, causing changes in the interference fringes. The method automatically identifies the number of fringe changes through image acquisition and processing, calculates the micro-displacement by combining it with the wedge parameters, and then solves for material parameters such as Young's modulus and coefficient of linear expansion. This invention solves the problem of spatial integration with large loading equipment by using a vertical optical path, avoids frictional interference from the traditional moving mirror method by using a laterally moving wedge, and improves measurement accuracy and efficiency through automated image processing.

This invention, entitled "A Method and System for Fetal Biological Angle Ultrasound Imaging Measurement Based on a Clock Coordinate System," belongs to the field of ultrasound imaging medical technology. The technical problem it aims to solve is the cumbersome operation, lack of intuitive results, and significant influence from changes in body position in existing fetal biological angle measurements. The key technical points are: acquiring fetal ultrasound cross-sectional images; determining the anatomical reference point and the target point to be measured; constructing a virtual clock coordinate system using the anatomical reference point as the origin and the direction pointing from the origin to a preset anatomical reference structure as the reference scale direction, and superimposing it on the ultrasound cross-sectional image; connecting the origin and the target point to be measured to form a target vector; calculating the physical angle of the target vector relative to the reference scale direction; and using an angle-scale mapping algorithm to convert the physical angle into a clock scale value and display it on the ultrasound cross-sectional image.

The invention provides a ship lock navigation operation state evaluation method, and the method comprises the steps: dividing a ship lock navigation operation state into a plurality of navigation operation states, enabling the navigation operation states to serve as a target layer, and correspondingly determining a first-stage index layer according to the navigation operation states, respectively and correspondingly dividing all the first-level index layers into corresponding second-level index layers; constructing a second-level index actual value matrix based on the obtained second-level index actual data corresponding to the second-level index layer, and processing the second-level index actual value matrix to finally obtain a second-level index weight; calculating according to the second-level index weight to obtain each first-level index weight; dividing the navigation operation state levels of the ship lock, calculating classic domain / section domain matter elements of each index according to the division result, determining matter elements to be evaluated in combination with the actual data of the second-level index, and then forming a second-level index correlation degree model; and finally, according to a maximum membership degree principle, determining a ship lock navigation operation state grade comprehensive evaluation result.

This utility model relates to the field of textile equipment technology, specifically to a rapid testing device for the tensile strength of elastic fabrics. The device includes a frame, a material guiding mechanism, and a loading mechanism. The material guiding mechanism comprises a first and a second set of guide rollers. The loading mechanism includes a loading rod and a linear drive. One end of the linear drive is connected to the frame, and the other end is hinged to the loading rod. A pressure sensor is mounted on the loading rod. Through this design, the linear drive, controlled by a program, can precisely execute pressure loading, pressure holding time control, and unloading actions, completely replacing manual bidirectional tensile testing. This thoroughly solves the problems of inconsistent testing speed and unstable pressure holding time, ensuring completely consistent testing conditions for each test.