243results about How to "Guaranteed detection efficiency" patented technology

The invention relates to a high-safety iron tower climbing operation protection system which comprises a safety belt body with two safety hooks, a detection control mechanism, a locking mechanism, a cloud server and a mobile monitoring platform. The detection control mechanism comprises an infrared sensor arranged on the inner ring of the safety hook, a contact sensor arranged on the opening and closing part of the safety hook, a UWB wireless positioning module arranged on the safety hook and the waistband, a posture detection mechanism arranged in the safety rope, and a control chip, a wireless transmission module and a buzzer which are arranged on the buckle of the waistband; the locking mechanism comprises an electromagnetic lock arranged on a handheld driving part of the safety hook; the detection control mechanism and the locking mechanism cooperate with each other to realize virtual hanging, double unlocking, low hanging and high use monitoring of the safety hook, the monitoring data is uploaded to the cloud server, a guardian monitors the climbing operation through the mobile monitoring platform, and the safety of operators in the process of the climbing operation is improved.

The invention discloses a wafer film defect detection system and method, and relates to the technical field of wafer film defect detection.The wafer film defect detection method comprises the following steps that in the wafer film defect detection process, laser beams are emitted through a laser scanner according to the preset light beam coverage rate, and the surface of a wafer is covered for preliminary scanning; in the laser beam scanning process, the intensity and the consistency of laser reflection signals are analyzed in real time. According to the invention, preliminary scanning is carried out by presetting the light beam coverage rate, the significance of the potential flaw area is evaluated by using the convolutional neural network, accurate classification of the flaw obvious area and the flaw non-obvious area is realized, high-density secondary scanning is carried out by dynamically adjusting the light beam coverage rate for the flaw non-obvious area, and finer surface information is captured. The detection efficiency is improved, the risks of missing detection and false detection are effectively reduced, the accurate detection of tiny flaws is ensured, the quality control of wafer film pasting is remarkably improved, and the production loss is avoided.

The invention discloses an AI-driven information security big data supervision method and system, and relates to the technical field of data supervision. Comprising the following steps: receiving data streams from different sources in real time, preprocessing the data streams, performing multi-dimensional dynamic label processing, and storing the data streams in different nodes in a distributed manner; calling an adaptive AI model for the distributed storage data in real time, and automatically adjusting parameters of the adaptive AI model based on the traffic change condition; when the adaptive AI model monitors an abnormal data stream, performing secondary intelligent grading analysis, and judging the type, the source and the potential threat level of the abnormality; when a high-risk anomaly is detected, an event-driven response mechanism is automatically triggered; and an event response result and a processing state are fed back to the adaptive AI model, and learning parameters and decision logic of the model are optimized. Under the support of multi-dimensional dynamic label processing, mass data streams can be flexibly and efficiently processed.

The invention relates to the technical field of soil auxiliary detection, and discloses an acid soil auxiliary detection device which comprises a U-shaped frame and further comprises a connecting plate horizontally arranged below the transverse edge of the U-shaped frame; the sampling assembly is arranged at the bottom of the connecting plate and is used for sampling to-be-detected soil; the liquid adding assembly is mounted at the bottom of the connecting plate, and the liquid adding assembly is used for adding liquid into the sampling assembly; the mixing detection assembly is arranged on the sampling assembly, and the mixing detection assembly is used for mixing the sampled soil and then detecting the mixed soil. According to the soil detection device, sampling can be conducted after the sampling column reaches the designated position, soil and deionized water are mixed after sampling, then the detection head detects mixed liquid of the soil and the deionized water, accurate detection on the soil is achieved, and then the using effect of the device is improved.

The invention discloses a contact lens flaw detection method and system based on image recognition, and the method comprises the steps: carrying out the material type and surface mesh division of a to-be-detected contact lens, calling a trained neural network model to carry out flaw detection, obtaining the output result of flaw detection, carrying out the analysis and processing of acoustic characteristic data and expected detection depth, and carrying out the detection of the contact lens. The method comprises the following steps: generating a frequency selection coefficient, calibrating an ultrasonic probe, obtaining reference datum data, transmitting ultrasonic waves of a frequency selection coefficient selected frequency band, obtaining a detection intensity value and a detection time delay value of the ultrasonic waves, and analyzing and processing a datum intensity value and the detection intensity value to obtain a first comparison coefficient; and analyzing and processing the reference time delay value and the detection time delay value to obtain a second comparison coefficient, and combining analysis to obtain an output result fine tuning index. According to the invention, the accuracy and reliability of contact lens flaw detection can be remarkably improved while the detection efficiency is ensured, and an efficient and accurate automatic detection scheme is provided for production quality control of contact lenses.

The invention belongs to the technical field of seam welding detection, and particularly discloses and provides a roof waterproof roll seam welding detection method which comprises the following steps: constructing a three-dimensional model of a to-be-constructed welding area, and marking the type of a welding detection point; welding characteristic analysis is conducted on the welding area, and all welding characteristic indexes are obtained; the number of welding detection points is determined, and the welding detection points are marked; confirming a standard passing threshold value of each welding detection point corresponding to each welding detection index; building a welding quality inspection model; sequentially carrying out quality inspection according to a set welding quality inspection plan, and recording quality inspection values; and the welding quality score value is output, and a welding quality inspection report of the waterproof coiled material is constructed and fed back. According to the method, the defect that current welding detection points are arranged comprehensively is effectively overcome, the specific welding characteristics of the waterproof coiled material are fully combined, the adaptability of a seam welding detection scene of the roof waterproof coiled material is improved, and meanwhile the representativeness and rationality of a welding detection result are guaranteed.

The invention discloses an ammonia nitrogen detection system and an application method thereof, and ammonia nitrogen detection test paper, the ammonia nitrogen detection system is prepared by the following steps: step SA1) preparing a dipping mixed solution, the dipping mixed solution comprises: a potassium sodium tartrate solution with a concentration of 3-60 g / L; a sodium salicylate solution with a concentration of 20-320 g / L; the concentration of the sodium nitroprusside solution is 0.1 to 0.8 g / L; and deionized water. On the basis of the principle of salicylic acid-pypocholoride spectrophotometry, the impregnated test paper, the reagent tube and the standard colorimetric card are combined, and the rapid ammonia nitrogen detection system special for medium-concentration sewage detection is successfully developed. The toxicity problem of mercury iodide in a Nessler reagent method and the toxicity problem of phenol in a phenol-pypocholoride spectrophotometric method are avoided, main reagents are non-toxic and harmless to a human body, interference of metal ions in a water sample can be effectively eliminated by adopting sodium potassium tartrate tetrahydrate as a chelating agent, and the detection stability and accuracy are improved.

The invention provides a titanium flange connection strength detection device, and relates to the technical field of flange strength detection, the titanium flange connection strength detection device comprises a detection installation member, and the detection installation member is provided with an indentation positioning member; a circle of compression strength detection piece is mounted on the indentation positioning piece; the compression strength detection pieces are used for detecting the compression strength of the flange; a rotary driving part is mounted at the top of the support frame on the detection mounting part; the rotary driving part is used for driving, adjusting and detecting the position of a flange thread, the abrasion loss can be adapted and compensated conveniently, the service life is prolonged, the thread detection precision is guaranteed, and the problems that the strength quality of threads of an existing titanium flange connection strength detection device is not convenient for digital display visual detection, missing detection is likely to be caused, and the abrasion clearance amount is not convenient to compensate are solved.

The utility model discloses a single-photon detector, which comprises a controller, a bias voltage generating circuit, a refrigeration temperature control circuit, a gating voltage generating circuit, an avalanche signal extraction circuit and an avalanche photodiode (APD) refrigeration box, and is characterized in that one end of the bias voltage generating circuit, one end of the gating voltage generating circuit and one end of the avalanche signal extraction circuit are connected to the controller; one end of the refrigeration temperature control circuit is connected to a TEC of the APD refrigeration box, the other end of the refrigeration temperature control circuit is connected to the controller, the other end of the avalanche signal extraction circuit is connected to an anode of an APD in the APD refrigeration box through an alternating current coupling capacitor C2, the anode of the APD is grounded through a sampling resistor R2, the other end of the bias voltage generation circuit is connected to a cathode of the APD through a resistor R1, and the APD refrigeration box is connected to the APD refrigeration box. And the other end of the gating voltage generation circuit is connected to the cathode of the APD through an alternating current coupling capacitor C1. According to the technical scheme of the utility model, the passive quenching of the free operation working mode is realized, the dead time processing circuit is simplified, and the noise level of the detector is reduced.

The invention discloses a personnel off-post detection method and device, a storage medium and a computer program product, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a current frame monitoring image in a target monitoring scene, and transmitting the current frame monitoring image to a YOLO target detection model to obtain a first image personnel number; if the number of the first image personnel is smaller than the preset number of post personnel, detecting whether the post lacking duration reaches the preset duration or not; if the off-duty duration reaches the preset duration, detecting the current frame of monitoring image through a multi-modal target detection model to obtain a second image personnel number; and if the number of personnel in the second image is smaller than the number of post personnel, determining that personnel leaving exists in the target monitoring scene. According to the method and the device, the high efficiency of the YOLO target detection model and the high accuracy of the multi-modal target detection model are combined, so that the relatively high detection efficiency is maintained, and the accuracy of personnel off-post detection is improved.

The invention discloses a wide energy gamma ray imaging system of a strip-shaped orthogonal self-coding detector and a method thereof. An adopted imaging detector carries out coding through a strip-shaped scintillator detector. A plurality of strip-shaped scintillator detectors are arranged and combined to form a strip-shaped array similar to a coding plate, wherein the projection pattern of the strip-shaped array has uniqueness (anisotropy) to response in all directions, and the imaging efficiency (aperture ratio) is considered. The detector system has fewer electronic channels, larger sensitive volume and lower cost. The MLEM iterative algorithm is fused with the coded aperture imaging method and the Compton imaging method, wide-energy and high-efficiency gamma ray imaging is achieved, and the gamma ray imaging device has large sensitive volume and few electronic reading channels.

The utility model discloses a water leakage detection device for waterproof material construction, which comprises an equipment bottom plate, an automatic material changing assembly and a position adjusting assembly, one side of a closed shell is provided with a detection material storage shell, one side of the detection material storage shell is rotatably connected with a connecting roller, and the top of the detection material storage shell is provided with a guide bracket; according to the water leakage detection device, the pressing plate is driven by the jacking hydraulic cylinder to move upwards in the detection process, moisture test paper is pressed at the bottom of a material to be detected, the water leakage test is carried out on the material in cooperation with the water storage shell, and the moisture test paper is wound through the arranged automatic material changing assembly after the detection is completed. The test paper does not need to be replaced manually, so that the labor cost of water leakage detection is reduced; in the detection process, the position adjusting assembly automatically adjusts the position of the water storage shell relative to the material, the whole detection process can be completed without repeatedly adjusting the position of the material, and therefore the detection efficiency of the device is guaranteed.

The invention discloses a thrown object detection method and system based on a traditional algorithm and deep learning. The method comprises the following steps: sequentially carrying out background filtering, category labeling, data enhancement, rasterizing operation and rasterizing partitioning, ground filtering and point cloud compensation on an original point cloud set to obtain a post-processing point cloud set; performing model training by taking the post-processing point cloud set as a training sample, and introducing a terrain clearance factor to obtain a target point cloud segmentation network model; performing background filtering, ground filtering and point cloud compensation on the to-be-detected point cloud in sequence to obtain to-be-detected post-processing point cloud; inputting the post-processing point cloud to be detected into the target point cloud segmentation network model for prediction to obtain the category of each point; and extracting the points of which the category is the throwing object, and calculating an external frame of the points to obtain the center position and the length, width and height size information of the throwing object. The method provided by the invention can accurately detect the small target thrown object, and improves the detection precision while ensuring the detection efficiency of the thrown object.

The invention discloses a defective product removing device based on machine vision, and relates to the technical field of product detection. Comprising a chain plate conveying mechanism used for conveying products, a mechanical arm mechanism used for grabbing the products is arranged on one side of the chain plate conveying mechanism, and a visual detection mechanism used for detecting the products is arranged on the other side of the chain plate conveying mechanism; the chain plate conveying mechanism comprises a conveying table, and a chain plate conveying assembly is installed on the conveying table. And the positioning pieces are distributed on a plate body of the chain plate conveying assembly at equal intervals. By arranging the chain plate conveying mechanism, the manipulator mechanism and the visual inspection mechanism, the chain plate conveying mechanism can be used for orderly conveying products, the visual inspection mechanism is used for carrying out image acquisition and detection, and qualified products are carried to the next station in the process through the manipulator mechanism; unqualified products are conveyed and discharged along with the chain plate conveying mechanism, so that the purpose of removing defective products is achieved, the automation degree is high, and the detection efficiency is guaranteed.

The invention relates to the field of intelligent image recognition, in particular to a real-time copper foil defect detection method which comprises the following steps: establishing a data set of copper foil surface defects, constructing an environment corresponding to a basic Yolo V8 model, and improving the Yolo V8 model by using a dual convolution (DualConv) structure, a deformable large kernel attention (D-LKA Attention) mechanism and a Shape IoU loss function. And training and optimizing the YOLO network model, generating weight files, storing the weight files to the local, and identifying and classifying the copper foil surface defects by using the weight files. According to the method, the accuracy of defect detection is remarkably improved, the high speed of the detection process is ensured, and the method is suitable for the real-time application requirement in an industrial production environment.

The invention discloses an underwater small target detection method based on feature screening and context fusion, and the method comprises the steps: improving a YOLOv3 network model, carrying out the feature screening and context fusion in a backbone network, constructing a target detection YOLOv3-CTE network model, carrying out the sparse training and optimization processing of a pruning network model of the target detection YOLOv3-CTE through a sample training set, and carrying out the detection of an underwater small target. Obtaining an optimal target detection network model; the sample verification set is adopted to verify the optimal target detection network model, a network model verification result is obtained, and the optimal target detection network model is updated according to the network model verification result; and predicting the sample test set based on the updated optimal target detection network model to obtain a detection result of the underwater small target. According to the method, in the underwater small target detection process, the parameter quantity can be reduced to a great extent, meanwhile, the calculation speed of the model is improved, and the classification and recognition accuracy of the underwater small target is further improved on the premise that the detection efficiency is guaranteed.

The invention discloses a lacrimal river height detection method, device and equipment and a storage medium, and relates to the technical field of medical image.The method comprises the steps that a to-be-detected eye image is acquired, and the to-be-detected eye image is preprocessed through a preset gray level co-occurrence matrix enhancement algorithm; the preprocessed to-be-detected eye image is input into a preset lacrimal river segmentation model, a lacrimal river segmentation result is obtained, the preset lacrimal river segmentation model is constructed based on a Unet network, and a preset encoder and a preset decoder in the preset lacrimal river segmentation model each comprise a double-layer convolution layer replacing an original convolution layer; and determining a plurality of measurement key points based on the lacrimal river segmentation result, and determining a lacrimal river height value according to the height information corresponding to each measurement key point. According to the method, the image is preprocessed by adopting the preset gray level co-occurrence matrix enhancement algorithm, and the tear river segmentation model is constructed based on the improved Unet network, so that the accuracy and reliability of tear river height detection can be effectively improved.

The utility model discloses a wind power blade crack detection mechanism, which belongs to the technical field of wind power blade detection and comprises a guide rail, two side walls of the guide rail are respectively provided with a limit groove, a slide block is mounted in the guide rail, balls are mounted on contact surfaces of the slide block and the limit grooves, and two groups of telescopic folding covers are symmetrically mounted on two sides of the slide block. According to the utility model, by designing a group of spraying and marking mechanism consisting of the storage barrel, the material guide pipe, the metering pump and the nozzle, in the detection process, when a crack is detected, the metering pump quantitatively extracts the coating in the storage barrel through the material guide pipe and sprays the coating to the crack through the nozzle, so as to mark the crack; on one hand, detection efficiency of the device is ensured, on the other hand, subsequent determination by workers is facilitated, and device use effect is improved.

The utility model relates to the technical field of steel plate processing, in particular to a steel plate thickness continuous monitoring device which comprises a base, a detection table for supporting is arranged above the top end of the outer wall of the base, a detection assembly for detecting the thickness of a steel plate is arranged in the detection table, and the detection assembly comprises a thickness monitoring part and a marking part. According to the steel plate thickness detection device, the detector shell is matched with the upper detection roller so that the thickness of a steel plate can be detected in real time, when the detected thickness of the steel plate is changed, a change value can be detected through the micro-pressure sensor or the laser ranging head, and meanwhile a signal can be sent to a control end; and the control end can control the material conveying pump to spray the fluorescent agent from the sprayer to mark the steel plate while sending the numerical value to the PC end of the personnel, so that the device can verify the steel plate subsequently without shutdown, and the detection efficiency of the steel plate is ensured.

A clamping gasket stress detection device of the utility model comprises a detection box, the bottom of the inner wall of the detection box is fixedly connected with a placing table, the placing table is provided with a weight box, the two sides of the weight box are provided with pressure detection plates, the detection box is internally provided with a transverse plate, and the two sides of the top of the detection box are fixedly connected with hydraulic rods. The output ends of the two hydraulic rods penetrate through the detection box and are fixedly connected with the top of the transverse plate, mounting plates are slidably connected to the bottom of the transverse plate, a gasket mounting plate is detachably connected to the side, close to the weight box, of each mounting plate, and a gasket body is arranged on the side, close to the corresponding pressure detection plate, of each gasket mounting plate; the beneficial effects of the utility model are that the device can effectively improve the disassembly and replacement speed during the stress detection of the gasket, thereby effectively guaranteeing the detection efficiency and the use convenience of the equipment, and effectively avoiding the situation that the disassembly and assembly of the gasket are time-consuming and labor-consuming, and the detection efficiency and the use effect of the equipment are affected when the traditional equipment is used.

The invention relates to an input shaft final inspection machine which comprises a machine table, a transferring device and a compliance detection device, the transferring device comprises a moving mechanism and a clamp, the compliance detection device comprises a notch measuring mechanism and a base, the notch measuring mechanism comprises a double-shaft moving platform, a transverse plate and a notch measuring assembly, the transverse plate is arranged at the output end of the double-shaft moving platform, and the transverse plate is arranged at the output end of the double-shaft moving platform. The notch measuring assembly comprises a socket gauge, a third linear driving part and a plug gauge, the socket gauge is connected to the end, away from the double-shaft moving platform, of the transverse plate, a first through hole extending in the first direction and a second through hole extending in the second direction are formed in the socket gauge, and the third linear driving part is arranged on the socket gauge; one end of the plug gauge is connected to the output end of the third linear driving piece. Through cooperation of the moving mechanism, the clamp and the gap measuring assembly, the input shaft can be automatically transferred, the passing ability of the semi-crescent gap can be automatically detected, the detection efficiency can be ensured, the detection precision can be ensured, and the delivery quality of the input shaft can be ensured.

The invention relates to a duct piece ring simulation assembling method, device, equipment, system and medium, in particular to the technical field of shield duct piece manufacturing, according to a target data set corresponding to at least six acquired prefabricated duct pieces, a corresponding duct piece three-dimensional model is established, according to the specific number of the duct piece rings, the mounting position of a top sealing block is determined, and the duct piece rings are formed. According to the installation position, a target assembly path of the segment ring is determined, and the segment three-dimensional models corresponding to the prefabricated segments are sequentially called according to the target assembly path to complete simulated assembly operation, so that the segment three-dimensional models are established according to the collected target data set during use, and after the target placement and installation position is determined, the segment three-dimensional models are subjected to simulation assembly operation. According to the method, the built segment three-dimensional model is used for segment ring splicing according to the target splicing path, the splicing operation of the prefabricated segments can be completed without actually splicing the prefabricated segments, time and labor do not need to be consumed, the detection efficiency is ensured, and industrial or assembly line work can be achieved.

The invention discloses a structural damage grading identification method and system based on a deep learning classification algorithm, and relates to the technical field of structural health monitoring, and the method comprises the following steps: carrying out the preprocessing and enhancement of structural damage image data in a first-stage data set, and forming a second-stage data set; retaining the structure damage image with the optimal quality as a third-level data set; taking the category with the maximum classification probability value as the damage type of the damaged image block; and splicing the non-damaged image blocks and the marked damaged image blocks to obtain a final identification result. According to the method, a multi-level structure damage identification function is realized based on a deep learning classification algorithm, and compared with a traditional single-layer model or other existing detection models, the deep neural network model has the characteristic of gradually refining detection and identification through modular design; the method has the structural damage self-adaptive identification capability capable of automatically identifying various damage types, positions and degrees of the structure.

The invention discloses an inspection system suitable for a steel box girder, which belongs to the technical field of bridge engineering, and is characterized in that a walking track is arranged in the steel box girder, an inspection robot is arranged on the walking track, and a chassis walking mechanism, a space mechanical arm and a shooting module are combined to inspect the steel box girder. The shooting module can be driven by the chassis walking mechanism to penetrate through the partition plate in the box girder to walk when the space mechanical arm is in the initial stacking state, and is driven to the corresponding shooting position through folding / unfolding control of the space mechanical arm after moving in place, and therefore detection of the interior of the steel box girder is completed. The inspection system provided by the invention is simple in structure and convenient to use, can automatically complete the detection of the interior of the steel box girder, ensures the efficiency and accuracy of the detection of the interior of the steel box girder, avoids position omission during manual detection, improves the efficiency of the detection of the interior of the steel box girder, reduces the cost of the detection of the interior of the steel box girder, and improves the detection efficiency of the interior of the steel box girder. The internal detection quality of the steel box girder is ensured, and the practical value is good.

The invention discloses a millimeter-wave radar operation management and control system based on anti-interference processing, relates to the technical field of radar operation management and control, solves the technical problem that the operation trend of a millimeter-wave radar cannot be predicted in the prior art, and particularly relates to a method for analyzing the interference influence of the millimeter-wave radar in a detection area by an interference influence analysis unit. Interference information and influence information are collected, and low-efficiency detection signals or high-efficiency detection signals are generated according to information analysis; the operation fault detection unit performs operation fault detection on the millimeter wave radar, collects fault detection information, obtains an operation fault detection coefficient, and generates a detection maintenance signal or a detection qualified signal through coefficient threshold comparison; the operation trend analysis unit analyzes the operation trend of the millimeter wave radar, collects frequency adding information and constant frequency information, and generates an efficiency reduction signal or an efficiency normal signal according to information analysis; and the operation management and control platform performs operation management and control according to the corresponding type signal.

The invention belongs to the technical field of battery cluster thermal runaway detection, and particularly relates to a detection positioning method, system and device suitable for thermal runaway of a battery pack in a battery cluster and a medium. The method comprises the following steps: grouping channels such as battery packs, battery cabins and electrical cabins in a battery cluster in a manner of combining grouping detection and dichotomy positioning, and sequentially carrying out thermal runaway detection; and when a thermal runaway early warning or alarm occurs in a certain channel group, a thermal runaway channel is quickly positioned by adopting a bisection method. According to the method, an air suction type thermal runaway detection technology is utilized, gas in the battery pack is extracted for analysis, and thermal runaway detection of the battery pack is achieved. The application of the dichotomy search algorithm further improves the accuracy of thermal runaway channel positioning. Compared with a traditional detection method, the method has the advantages of being short in detection period, accurate in positioning, low in cost and the like, is suitable for battery pack thermal runaway detection scenes such as electrochemical energy storage and the like, and has high application value.

The present invention relates to the technical field of neutron scattering, and in particular to a hyperbolic single crystal graphite analyzer used in a secondary spectrometer of a neutron spectrometer, which improves the energy resolution and detection efficiency of the neutron spectrometer by optimizing the geometric shape of the analyzer; the analyzer comprises a substrate, and both the horizontal (x) and vertical (y) directions of the substrate are designed into a hyperbolic trapezoidal structure according to a fourth-order polynomial, which determines the overall geometric shape of the analyzer; the present invention effectively solves the problems existing in the prior art through an innovative design of a hyperbolic single crystal graphite analyzer, significantly improves the performance of the neutron spectrometer, and has important value for neutron scattering research and applications in related fields.

The utility model discloses an SIM card tray detection device which comprises a workbench, two supporting plates are fixedly connected to the top of the workbench, two rotating rollers are rotationally connected between the two supporting plates, a conveying belt is arranged on the outer sides of the two rotating rollers, and a plurality of fixing seats are fixedly connected to the outer side of the conveying belt at equal intervals. The beneficial effects of the utility model are that: it is novel in structure, simple to operate, easy to master, not only compact in structure, but also stronger in practicality, and more convenient to use. Compared with a traditional device, by arranging the fixing base, the rotating shaft, the electromagnet, the magnet, the connecting rod, the clamping base, a first spring, a touch switch, a gear ring, a touch rod and a rack, the electromagnet can be controlled to be powered on by triggering the touch switch after the fixing base moves to the clamping position, then the touch switch generates repulsive force on the magnet, and the clamping effect is achieved. In this way, the first spring is compressed and the clamping seat is driven to clamp the SIM card support.