974 results about "Contact sensor" patented technology

The invention provides a detection method and system for an insulation detection function. Wherein in the operation state of the to-be-detected electrical equipment, the temperature change of the surface of the to-be-detected electrical equipment is monitored in real time through a non-contact sensor, and a dynamic thermogram is formed; according to a temperature fluctuation mode of a preset area in the dynamic thermogram, in combination with an environment temperature compensation algorithm, identifying a potential insulation defect area, and generating a preliminary insulation defect report; for the insulation defect area marked in the preliminary insulation defect report, simulating electromagnetic field distribution conditions of the insulation defect area under different working conditions by adopting an electromagnetic field analysis technology, evaluating the aging degree and damage risk of the insulation material, and obtaining an evaluation result; and integrating the preliminary insulation defect report and the evaluation result, calculating the probability that the insulation defect area develops into an actual fault through a fault prediction model, and outputting a final insulation performance detection report. According to the technical scheme provided by the invention, the operation efficiency and safety of the equipment are improved.

The invention relates to the technical field of psychological health monitoring, in particular to a self-injury behavior early warning and intervention method and system based on multi-modal physiological data and AI.The method comprises the steps that physiological signals, behavior data, text data and environment parameters of a user are collected in real time based on a contact sensor and non-contact sensing equipment, and the physiological signals, the behavior data, the text data and the environment parameters of the user are obtained; generating a multi-source original data set; performing time synchronization and spatial correlation analysis on the multi-source original data set to form a fusion feature vector; inputting the fusion feature vector into a preset multi-modal deep learning model, obtaining a self-injury behavior risk score value, and dividing risk levels based on the self-injury behavior risk score value; and triggering a hierarchical intervention strategy of AI psychological counseling, emergency contact notification and medical resource linkage according to the risk level. The method has the effect of improving the precision and quality of teenager mental health assessment and self-injury behavior early warning results.

The invention discloses a sleep state monitoring and analyzing system based on multi-sensor fusion, and relates to the technical field of health monitoring, the sleep state monitoring and analyzing system comprises a multi-modal sensor module used for collecting multi-dimensional data related to a sleep state, the multi-dimensional data comprises a bio-electricity signal, a physiological parameter, body movement data and an environment parameter, and the multi-modal sensor module is used for collecting the multi-dimensional data; the multi-modal sensor module comprises a non-contact sensor, a flexible electronic skin sensor and a bio-electricity signal sensor, and the data fusion and processing module is used for carrying out preprocessing, dynamic self-adaptive fusion and federal learning modeling on collected original data. According to an existing contact type sleep state monitoring scheme, more flexible and accurate sleep state data are realized through a non-contact type monitoring sensor in cooperation with dynamic adjustment of sleep monitoring content and adjustment of weights of various sensors for monitoring the sleep state; and a more accurate and intuitive reference report is provided for the sleep state and the health state of the subsequent user.

A header height sensor and adjustment system capable of differentiating between the ground and object above the ground. The system is able to differentiate between lodged / downed stalks and the ground. The system includes one or more non-contact sensors, such as Time-of-Flight (ToF) sensor and / or radar sensors. The system may optionally include a contact sensor. The disclosed header height sensor and adjustment system is able to automatically or semi-automatically adjust the height of the header in response to detected objects and terrain in order to maximize yield (e.g., lowering to harvest lodged stalks) and avoid header damage (e.g., raising to avoid debris or contour terrain).

The invention relates to the technical field of sensors, in particular to a transformer dynamic magnetic bias current detection method and device based on magnetoelectric coupling sensing, and the detection device composed of a magnetoelectric coupling sensing element, an exciting coil and a rear-end processing circuit is used for measuring direct current magnetic bias current. The working principle of the magnetoelectric coupling sensing element is based on stress coupling between the magnetostrictive material and the piezoelectric material, then an output signal is generated on the piezoelectric material, and the sensitivity is remarkably improved by using the resonance amplification effect of the magnetoelectric coupling sensing element. Non-contact current detection can be realized by detecting the magnetic field generated by the magnetic bias current of the neutral point grounding wire of the transformer, and direct physical contact with power equipment is not needed, so that the safety of the system is improved, and the problem of high installation difficulty of a contact sensor is avoided; high-sensitivity, high-precision, anti-interference and real-time transformer direct-current magnetic bias current monitoring is achieved, and the transformer direct-current magnetic bias current monitoring device has the advantages of being easy to install and deploy and small in size.

The invention particularly relates to a quartered sleep state monitoring method and a quartered sleep state monitoring system based on a non-contact vibration sensor. The quartered sleep state monitoring method and the quartered sleep state monitoring system are particularly suitable for realizing non-sensitive sleep quality evaluation through an intelligent bed in a family environment. Comprising the following steps that 1, vibration signals of a human body in the sleep process are continuously collected through a non-contact vibration sensor; step 2, preprocessing the vibration signal, including denoising and segmentation processing, to obtain time domain vibration data; step 3, performing frequency domain transformation on the time domain vibration data, and extracting frequency domain features including respiratory rate, heart rate and heart variability parameters; 4, time alignment is carried out on the frequency domain features and sleep staging labels synchronously obtained through a polysomnography, and a training data set is constructed; an XGBoost classification model based on time-frequency domain feature fusion is provided, fundamental frequency and harmonic energy proportions of respiratory signals are extracted through short-time Fourier transform, and quartering classification is achieved in combination with the LF / HF ratio of heart rate variability.

The invention provides an ink-jet method of a Micro OLED, and relates to the technical field of ink-jet printing of Micro OLEDs, the ink-jet method comprises an ink-jet unit and a laser following unit, the ink-jet unit comprises an ink-jet head, an ink-jet platform and an ink-jet control system, the laser following unit comprises a first non-contact sensor fixedly connected with the ink jet head, a second non-contact sensor fixed on the ink jet platform and a laser following control system, and the ink jet platform comprises an operation area and a correction area. Laser follows dynamic calibration and drawn patterns and is transmitted to the ink jet control system to control the ink jet head to jet ink, and the problems that in the prior art, the height of the ink jet head and the wafer target ink jet area is difficult to control, the glue amount precision is insufficient, and glue overflows or is not fully filled are effectively solved.

The present invention is a wireless vehicle tank monitoring system using non-contact fluid level sensors with adjustable sensitivity to measure fluid levels in recreational vehicle holding tanks. A smart device application on a portable computer receives real-time data via Bluetooth Low Energy (BLE) communication. The user-friendly interface displays graphical tank states. The system optimizes power efficiency through deep sleep and selective notification techniques, extending battery life. Sensors' sensitivity adapts to different tank wall thicknesses for accurate readings. The integration of non-contact sensors and power-efficient communication ensures reliability, easy installation, and real-time data transmission. This cost-effective solution effectively manages fluid levels in recreational vehicles.

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 relates to the technical field of image processing, and discloses a non-contact vital sign detection method and device based on self-supervised learning. The method specifically comprises the following steps: generating a visual-text pair based on a visual sample and a text cue word, extracting visual features and text features by adopting a visual-language model, and aligning the visual features and the text features by using a contrast loss function; reconstructing a shielded video region in the visual sample based on the visual features and the text features, and optimizing the reconstructed video sample by using a reconstruction loss function; the predicted physiological signal is optimized using a frequency contrast loss function and a frequency ranking loss function. A self-supervised learning method is adopted, accurate estimation of the physiological indexes can be realized without using an external PPG signal as supervision, and the demand on computing resources is reduced; through the design of the model and the loss function, the accuracy of signal extraction and the generalization performance of the model are improved; no contact type sensor in any form needs to be worn, the economic cost is low, and the privacy is good.

A non-contact micro-vibration measurement and fault diagnosis method based on dynamic visual signal alignment comprises the steps that firstly, a dynamic visual sensor-event camera is used for collecting event data of vibration of a rotating machine in a non-contact mode, and an event data characterization method is used for converting event streams into event frame sequences which are equal in interval, not overlapped and continuous; then micro-vibration information of each pixel point is extracted from the event frame sequence through a deep neural network, the difference of vibration signals of adjacent pixel points is reduced through a signal alignment method, and contact sensing data is used as a reference for optimizing model performance through a feature clustering method; and finally, performing intelligent fault diagnosis by using the obtained micro-vibration data. According to the invention, the applicability of the non-contact sensor in the fields of vibration monitoring and fault diagnosis of rotating machinery is improved.

The invention discloses a teaching auxiliary device for a female pelvic floor organ prolapse repair operation, and belongs to the technical field of female pelvic floor repair teaching aids. The pelvic floor teaching device comprises a pelvic floor simulation mold, pelvic floor teaching gloves and an auxiliary display system, wherein audible and visual alarms and contact sensors are arranged at the positions of organs in the pelvic floor simulation mold. The pelvic floor teaching glove solves the problems that an existing green hand is difficult to practice an operation and resources of a corpse dissecting teaching aid are tight, the pelvic floor teaching glove is inserted into the pelvic floor simulation mold through the vagina by wearing the pelvic floor teaching glove, the probe at the front end and the contact type sensor are used for sensing each other, and if the pelvic floor teaching glove mistakenly enters an organ which is not required to be examined, the audible and visual alarm gives an alarm; various simulation teaching scenes are set, the image is blurred through the image blurring module to simulate the serious bleeding phenomenon, an operator observes the actual condition of a simulation operation through the display terminal, it is ensured that the teaching auxiliary device has the visualization, guiding and feedback functions, and the defects that a green hand is difficult to learn and simulation tools are tight are overcome.

The invention relates to the technical field of equipment state monitoring, in particular to an emergency cut-off valve bolt looseness detection method and system based on multi-modal fusion. The method specifically comprises the following steps of multi-source data synchronous acquisition, accelerometer installation and data processing, environmental adaptability preprocessing, bolt area optical flow feature extraction, Kalman filtering multi-source fusion, bolt looseness detection and loose bolt positioning. According to the emergency cut-off valve bolt looseness detection method based on multi-modal fusion, online, automatic and real-time accurate monitoring and early warning are achieved, the reliability and the anti-jamming capability of the system are remarkably improved, a high-precision and quantifiable objective diagnosis result is provided, good economical efficiency and large-scale deployment feasibility are achieved, and the method is suitable for popularization and application. The industrial pain point that a traditional contact type sensor scheme is difficult to apply to an industrial site with a large number of bolts in a large scale due to too high cost and technical complexity is effectively solved.

A system and a method for capturing a movement pattern of a person. The method comprises capturing a plurality of images of the person executing a movement pattern by means of a non-contact sensor, the plurality of images representing the movements of the body elements of the person, generating at least one skeleton model having limb positions for at least some of the plurality of images, and calculating the movement pattern from the movements of the body elements of the person by comparing changes in the limb positions in the at least one skeleton model generated.

The invention relates to the technical field of elevators, in particular to an elevator traction machine vibration reconstruction method and system based on a millimeter wave radar. The method comprises the steps that in the elevator running process, echo signals of a millimeter wave radar are collected; firstly, a continuous phase sequence is obtained through echo signals; generating a rough vibration signal in a radar sight line direction according to a phase-displacement mapping relation, calculating a physical confidence coefficient, constructing a dual-channel physical prior tensor, synthesizing a three-axis reconstruction vibration signal tensor by using a PGGN physical gating generation network, and finally performing physical rationality evaluation on the three-axis reconstruction vibration signal tensor. And adjusting the gating parameters of the anisotropic physical gating unit according to the evaluation result. On the premise that a contact sensor does not need to be installed on the surface of the traction machine for a long time, physical consistency reconstruction of the three-axis vibration signals of the elevator traction machine is achieved.

The invention relates to the technical field of corn cultivation, and discloses a corn variety cultivation device based on a molecular marker assisted technology, the corn variety cultivation device comprises a base and a plurality of fixed guide rails fixed in the base, a sliding plate is slidably arranged on the base, and a plurality of movable guide rails perpendicular to the fixed guide rails are slidably connected in the base; a sliding column is fixedly installed at the bottom of each movable guide rail, a plurality of sliding grooves are formed in the sliding plate, the multiple sliding columns are in sliding fit in the multiple sliding grooves in a one-to-one correspondence mode, and a planting assembly is arranged at the intersection position of each fixed guide rail and the corresponding movable guide rail; the planting assembly comprises a moving seat, a planting box and a vertical plate; wherein a moving plate is slidably arranged on the vertical plate of one planting assembly, and a contact sensor is fixed to one end of the moving plate. According to the invention, automatic adjustment of the spacing of corn plants in different growth stages can be realized, the operation is simple, and the efficiency is high.

The invention discloses a child mouth breathing monitoring method, device and equipment and a medium, and the method comprises the steps that a non-contact sensor group is used for synchronously collecting multi-mode physiological data of a target child in the sleep period, and the multi-mode physiological data at least comprises a face thermal imaging video stream, a thoracic and abdominal micro-motion signal and an environment audio signal; the multi-modal physiological data is processed, multi-modal features related to respiration are extracted respectively, and the multi-modal features comprise thermodynamic change features of mouth and nose areas extracted based on a face thermal imaging video stream, respiratory effort waveforms extracted based on thoracic and abdominal micro-motion signals, and the respiratory effort waveforms extracted based on the thoracic and abdominal micro-motion signals; extracting a sound source spatial position and a spectrum feature of breathing sound based on the environment audio signal; inputting the multi-modal features into a pre-trained mouth breathing recognition model, and outputting a judgment result of the functional mouth breathing event of the target child within a specific time period; and generating a mouth breathing monitoring report of the target child based on the judgment result.

The invention discloses a rotating blade vibration measurement method based on vision, and relates to the technical field of measurement. In order to solve the technical defect that circumferential and radial vibration displacements of a blade cannot be simultaneously and synchronously obtained in a high-speed rotating state in the prior art, the technical scheme provided by the invention is as follows: calculating the time when the blade reaches a preset measurement position based on a non-contact sensor, and respectively triggering a high-speed camera to collect circumferential and radial original images; the method comprises the following steps: performing micro motion amplification processing on an image, tracking pixel movement by using a sparse optical flow algorithm and converting the pixel movement into vibration displacement, and finally performing time domain and frequency domain feature extraction on circumferential and radial vibration data to obtain vibration feature parameters. The method is suitable for online vibration monitoring and analysis work of rotating blades of wind driven generators or aero-engines and the like under the condition of high-speed rotation.

The embodiment of the invention provides a snore recognition method and system based on a non-contact sensor, and the method comprises the steps: obtaining vibration data collected by the non-contact sensor, and carrying out the preprocessing of the vibration data, and obtaining vibration signals of a plurality of time windows; calculating a time domain feature, a frequency domain feature and a time frequency feature of the vibration signal; training a weak classifier model, and training a strong classifier by taking a prediction result of a weak classifier as an input feature; collecting a real-time vibration signal, inputting the time domain feature, the frequency domain feature and the time frequency feature of the real-time vibration signal into the weak classifier to obtain an output prediction probability value, and inputting the prediction probability value into the strong classifier to obtain an output snore recognition result; and detecting a snore recognition result, correcting the snore recognition result based on a detection result in combination with the prediction probability value, and outputting a final snore result after correction.

The invention discloses a non-contact measurement method for the thickness of a circular tube, and the method comprises the steps: employing a non-contact sensor assembly to achieve the inclined measurement of the inner wall and the outer wall of the circular tube, and enabling the non-contact sensor assembly to comprise at least five distance measurement sensors which are distributed on the same circumference, and the detection directions of the distance measurement sensors to point to the center of the circumference; the included angle between the detection directions of every two adjacent distance measuring sensors is equal and does not exceed 45 degrees, selecting first distance data of five continuous distance measuring sensors when the inner wall of the circular pipe is measured and second distance data of the five continuous distance measuring sensors when the outer wall of the circular pipe is measured, and converting the first distance data and the second distance data into first coordinates and second coordinates, and obtaining a first elliptic equation and a second elliptic equation according to coordinate fitting, and calculating the difference value of the minor semi-axis lengths of the first ellipse and the second ellipse to obtain the thickness of the circular tube. The invention also discloses a device for realizing the measurement method. According to the invention, the contact with the circular tube can be avoided for measurement, and accurate and highly repeatable measurement results can be provided.

The invention provides an equipment vibration measurement device based on machine vision and a laser radar. The equipment vibration measurement device comprises a collaborative sensing system, a visual vibration inversion module, a multi-modal feature fusion and fault knowledge base module and an edge end lightweight intelligent diagnosis module. The collaborative sensing system is used for collecting a video stream of a target area and providing an absolute displacement reference; the visual vibration inversion module is used for processing the video stream to generate a vibration spectrogram; the multi-modal feature fusion and fault knowledge base module is used for constructing a multi-dimensional feature vector and a feature knowledge base; and the edge end lightweight intelligent diagnosis module is used for identifying a fault type and outputting a diagnosis result and confidence. According to the invention, non-contact, high-precision and full-automatic vibration state sensing and fault diagnosis are realized, the core target is to completely get rid of the dependence on a contact sensor, the limitation of a pure vision scheme in a complex industrial environment is overcome, and finally millisecond-level real-time fault identification and early warning are realized on the edge side with limited resources.

A self-adaptive control system for height and operation of ratooning rice stubble cutting includes a stubble righting device, a profiling contact sensor, a speed radar, and a controller; the stubble righting device is installed at the rear of the harvester, and is connected to the bracket by the stubble righting device hydraulic cylinder; the profiling contact sensor is configured to detect the height of the header above the ground and transmit data to the controller; the speed radar is configured to obtain and transmit speed information of the harvester to the controller; the hydraulic valve block is installed on the chassis frame and connected to the header lifting hydraulic cylinder and the stubble righting device hydraulic cylinder respectively; input terminals of the controller are connected to the profiling contact sensor and the speed radar, and output terminals of the controller are connected to the motor and hydraulic valve block.

The invention discloses a prefabricated temperature measurement system for a sleeve side of an all-insulation ring main unit. The prefabricated temperature measurement system comprises a wireless three-phase temperature sensor, a host module, an Internet of Things gateway and an in-situ monitoring terminal. A sensor probe is directly arranged in an insulating gap between a cable head and a sleeve, is made of a high-temperature-resistant insulating material and is internally provided with an electromagnetic shielding layer, and 2.4 GHz wireless communication is supported. A temperature rise rate analysis algorithm is built in the host module, an early warning mechanism is triggered when the slope k is calculated to be larger than or equal to 0.5 DEG C / h by adopting a least square method, and an environment temperature compensation factor is introduced to correct errors. A factory pre-integration + plug-and-play mode is innovatively adopted, rapid deployment is realized through a DIN guide rail and an anti-misplug aviation plug, and a dual-mode power supply system is matched at the current fault; the low-frequency sampling of the storage battery is automatically switched at 20A, and the wake-up period is dynamically adjusted through PWM. According to the scheme, the problems of large delay of traditional infrared temperature measurement, complex installation of a contact sensor and failure of small load are solved.

The induction type automatic scattering mechanism comprises an equipment frame, a line body and a bowl body, a supporting frame is installed on an installation frame, and a probe type contact sensor is installed at the output end of an air cylinder; a rotary frame is rotationally connected in the butt joint frame, and a driving piece for controlling the rotary frame to swing is arranged on the material scattering nozzle; a pressing structure is arranged on the sliding connection frame, and a limiting piece is arranged on the outer side of the butt joint frame. According to the powder sagger, firstly, materials can be more uniformly distributed in the sagger body through accurate track control, the quality and consistency of powder sagger filling are improved, the requirement of the production technology for material scattering precision is met, secondly, abrasion and corrosion of impurities to the screen are reduced, the replacement frequency is reduced, and the production efficiency is improved. Therefore, the purchasing cost of the screen and the labor cost required by replacement are reduced, finally, the replacement process of the screen is simple, the replacement efficiency is improved, the requirement for the skill of an operator is reduced, and the replacement work is more convenient.

The invention discloses a cattle oestrus monitoring method based on multi-camera data fusion, and relates to the technical field of cattle oestrus monitoring. According to the cattle oestrus monitoring method based on multi-camera data fusion, cattle behaviors under complete shielding are visualized through multi-camera dynamic cooperation and skeleton movement deduction; a space-time slice attention mechanism is combined with joint dynamics calculation, target actions are reversely deduced from adjacent cattle body movements, the problem of climbing misjudgment caused by shielding of a traditional visual system is thoroughly solved, and the monitoring reliability in dense cattle herds is remarkably improved; the method comprises the following steps: establishing a differential filtering model of limp gaits and oestrus behaviors; based on acceleration signal time-frequency characteristics and duration determination, a false alarm signal is dynamically suppressed, the inherent defects of a contact sensor in a special physiological state are overcome, and the manual re-checking cost is reduced.

The present invention relates to a smart mattress that primarily uses non-contact sensors to measure the user's physiological data. Through a non-contact sensing method, it is capable of detecting REM sleep stages, monitoring heart rhythm, and measuring vital information such as respiration, as well as recording and storing physiological data such as bed-leaving movements and sleeping position. By connecting to a mobile device or a computer via a control box, all the recorded information can be displayed as a screen output or uploaded to a cloud database for storage. This enables long-term measurement of the user's physiological data or real-time monitoring, thus contributing to targeted patient care.

The utility model relates to the technical field of hot air blowing, in particular to hot air blowing equipment for coating, which comprises a hot air generating component, a shell, an induction component and a power supply control module, the shell is connected with the hot air generating component, the induction component detects the taking-up and putting-down states of the shell, and the power supply control module is respectively connected with the induction component and the hot air generating component. The power control module controls on-off of the hot air generation assembly according to signals of the induction assembly. The shell protects the hot air generating assembly, the hot air generating assembly is used for generating hot air, the sensing assembly adopts a gravity sensing or contact type sensor and can detect the taking-up and putting-down states of equipment, and the power supply control module controls the hot air generating assembly to be powered on and powered off according to signals of the sensing assembly. According to the intelligent induction type automatic power-on and power-off wrapping hot air blowing equipment, the convenience and safety of the wrapping process can be remarkably improved, the operation difficulty and the safety risk of staff are reduced, and wide application prospects are achieved.

The utility model discloses a tray contact type redundancy in-place detection device of a bidirectional telescopic pallet fork. The tray contact type redundancy in-place detection device comprises a bottom plate, a left contact plate, a right contact plate, a spring, a pin shaft, an induction type sensor and a contact type sensor. The two ends of the left contact plate and the two ends of the right contact plate are respectively provided with two sets of concentric round holes, one set of holes of the left contact plate and one set of holes of the right contact plate are hinged together through a pin shaft, the whole bottom plate is in a U shape, the two ends of the bottom plate are provided with through kidney-shaped grooves, and the other set of round holes of the left contact plate and the other set of round holes of the right contact plate can move in notches of the bottom plate through pin shafts. And a spring is connected between the two pin shafts for connecting the left contact plate, the right contact plate and the bottom plate to ensure that the pin shafts lean against the inner sides of the two waist-shaped notches of the bottom plate when the tray is not in place. The device is installed at the two ends of the outer side of the fork teeth of the bidirectional telescopic pallet fork and adjusted to the proper height, the left contact plate and the right contact plate can move towards the bottom plate side under extrusion of the pallet, feedback of the two in-place switches is triggered, and whether the pallet is in place or not can be detected.

The invention relates to the technical field of intelligent health monitoring, and particularly discloses a multi-modal AI-fused senior non-inductive assessment method and system and electronic device.The method comprises the following steps that in the daily living environment of the senior, original multi-modal data reflecting the physiological and behavior states of the senior are collected in a non-inductive mode through at least two non-contact sensors; and preprocessing the original multi-modal data, and extracting a single-modal health feature vector from the data of each modal by using a preset feature extraction model. According to the invention, non-inductive data acquisition is realized by deploying the non-contact multi-mode sensor in the daily environment of the elderly, the elderly does not need to cooperate deliberately, and the use convenience and acceptability are effectively improved; through preprocessing and feature extraction of multi-modal data, multi-dimensional health features can be mined from visual, audio and radar data, the limitation of single data dimension in the traditional technology is broken through, and comprehensive representation of physiological and behavior states of old people is realized.

The utility model particularly relates to a comprehensive detection platform for photovoltaic frame detection and an automatic detection line thereof, and the comprehensive detection platform comprises a pedestal which is used for providing structural support; the detection transmission line is arranged on the base and has a transmission function; a visual detection station, a length detection station and a bending and twisting degree detection station are arranged along the transmission path of the detection transmission line; the visual detection station comprises a first jacking mechanism, a turnover mechanism and a visual detection machine position, the first jacking mechanism and the turnover mechanism are arranged on the two sides of the detection transmission line, and the visual detection machine position is arranged opposite to the transmission line; the length detection station comprises a displacement sensor and a second jacking mechanism; and the bending and twisting degree detection station comprises a contact sensor and a third jacking mechanism. One of the main conception of the utility model is that visual detection, length detection and bending and twisting degree detection are integrated on one detection platform, so that the detection comprehensiveness and the detection efficiency are improved.