407 results about "Parallel detection" patented technology

The invention relates to the technical field of artificial intelligence, in particular to a multi-mode agent RAG-ReAct double-engine cooperative training method. The method comprises the following steps: acquiring multi-modal data, and converting the multi-modal data into a high-dimensional vector; constructing a knowledge graph based on the high-dimensional vector; encoding the semantic relationship of the knowledge graph into a model fine adjustment gradient direction by using a dynamic distillation technology; designing a distributed architecture based on the high-dimensional vector; performing hybrid retrieval based on a distributed architecture to obtain hybrid retrieval data; executing distributed reasoning based on a preset recursive reflection mechanism and the mixed retrieval data to generate distributed reasoning data; performing data parallel detection according to the distributed reasoning data to obtain data parallel parameters; and performing node resource scheduling based on the data parallel parameters so as to obtain node load balancing data. Based on the artificial intelligence technology, the reasoning accuracy and the resource utilization rate of the multi-modal agent in a complex task environment are effectively improved.

The invention discloses a protocol self-adaption method and device for household photovoltaic data access, and the method comprises the steps: transmitting a predefined multi-protocol detection instruction set to a newly accessed household photovoltaic terminal when the access of the household photovoltaic terminal is detected for the first time, and the predefined multi-protocol detection instruction set comprises standardized instructions of at least two heterogeneous communication protocols; monitoring response data of the household photovoltaic terminal, and identifying a communication protocol type supported by the household photovoltaic terminal based on a feature matching relationship of the response data; dynamically generating a corresponding data analysis template based on the identified communication protocol type, and establishing a protocol adaptation channel; and data acquisition and analysis are carried out on the household photovoltaic terminal through the protocol adaptive channel, so that protocol adaptive access is realized. Parallel detection of heterogeneous protocols is realized by pre-defining a multi-protocol detection instruction set, non-preset library identification of protocol types is completed in combination with response feature matching, and edge-side adaptive access is achieved by using a dynamically generated analysis template and a protocol adaptive channel.

The invention discloses an intelligent road disease detection method and equipment based on dynamic multi-scale convolution. The method comprises the following steps: performing target category labeling on a training sample set to form a corresponding relationship between sample data and labels; establishing a detection framework including a backbone network, a neck network and a detection network, the backbone network extracting features through convolution layer and cross-stage local layer stacking, introducing spatial pyramid pooling to enhance multi-scale expression, and enhancing fine-grained disease area attention by enhancing spatial attention; the neck network is integrated with dynamic multi-scale convolution and is matched with an upper sampling layer and a cross-stage local layer to fuse high and low layer features; the detection network is provided with a plurality of parallel detection heads, and disease detection is carried out corresponding to different scale feature maps. According to the method, rapid detection and accurate positioning of disease targets of various sizes can be realized, and the detection capability of sparse and small-scale disease targets is remarkably improved through collaborative optimization of a dynamic multi-scale convolution kernel and an enhanced space attention mechanism.

The invention relates to the technical field of image analysis, in particular to an automatic marking robot calibration method based on visual guidance, which comprises the following steps of: establishing an image set comprising different resolution levels based on operation site image data acquired by a marking robot, and performing corner detection and straight line segment detection on each level image in parallel. According to the method, through a parallel detection mechanism of a multi-resolution hierarchical image set, angular point and straight line segment features under different scales are synchronously extracted, and a multi-scale feature point set with high robustness is constructed in combination with cross-hierarchical coordinate stability measurement and response intensity quantification. And performing dynamic screening and grouping association on the feature points based on a preset geometric constraint condition, eliminating noise interference and false detection features, and generating a candidate calibration structure set with spatial consistency. Weighted contribution value fitting is adopted, cross-scale stability and detection confidence of feature points are integrated, and geometric accuracy and anti-interference capability of calibration reference point coordinates are improved.

The invention relates to a medical image automatic labeling method and system based on multi-model voting, and the method comprises the steps: firstly obtaining a medical image, carrying out the standardized preprocessing, then carrying out the parallel detection of the preprocessed medical image through employing a plurality of target detection models of different architectures, and outputting a multi-model detection result. Thirdly, performing quality evaluation on the detection frame of each model through confidence normalization and detection frame weight calculation; finally, a decision strategy combining soft voting and hard voting is adopted, voting decision making is carried out on the position and the category of the detection frame of each detection target, and postprocessing optimization is carried out on a result. The invention further relates to a corresponding system, electronic equipment and a storage medium. According to the method, parallel detection is carried out by integrating the target detection models of various architectures, the accuracy and the labeling efficiency of automatic labeling of the medical image are remarkably improved by combining the frame quality score and the soft and hard voting decision strategy, and reliable technical support is provided for analysis of the medical image.

The invention relates to the technical field of blood chemical analysis, in particular to a parallel task scheduling optimization method and system for a blood detection process, and the method comprises the steps: correcting the attenuation rate of a temperature-sensitive component, a protein component and a light-sensitive component in blood according to real-time environmental parameters, and obtaining the corrected attenuation rate of the blood under the current environmental condition; calculating the concentration change rate of each detection item according to the correction attenuation rate, and establishing a multi-dimensional priority evaluation matrix in combination with the clinical importance coefficient and the detection time demand; identifying component pairs and reaction types of the interactive influence; establishing a coupling reaction kinetic model, and predicting the concentration value of each component at a set time point; sorting the to-be-detected items according to the multi-dimensional priority evaluation matrix; when the detection item combination contains mutual influence components, adjusting a detection sequence according to a coupling attenuation prediction result; and distributing the adjusted detection task to the corresponding parallel detection equipment according to the equipment compatibility, and generating and executing a task scheduling scheme.

The invention relates to the technical field of biomedicine, in particular to a primer probe combination for broad-spectrum screening of common respiratory pathogens and application of the primer probe combination. Through screening and optimization, the respiratory pathogen nucleic acid detection primer probe combination for broad-spectrum screening of common acute respiratory infection and community-acquired pneumonia is obtained; the primer probe combination covers 18 respiratory tract pathogens, has the advantages of high accuracy, good specificity, strong anti-interference capability, good inclusiveness, high sensitivity, hyperjoint detection and the like, can realize parallel detection of 20 targets in cooperation with totally-closed single-tube PCR amplification, greatly improves early diagnosis of respiratory tract diseases with complex pathogen structures, and has wide application prospects. The method has very important significance on prevention, control and treatment of infectious diseases.

The invention discloses an SAR image ship small target robust detection method and system based on improved YOLOv11, a storage medium and electronic equipment, and the method comprises the following steps: embedding an S2-MLPv2 module at the tail end of a backbone network, and suppressing speckle noise through spatial displacement operation and dynamic filtering; the SAFMN module is used for replacing traditional up-sampling, and the multi-scale feature fusion capability is enhanced in combination with a deformable convolution and gating mechanism; a SimAM non-parameter attention module is introduced, and ship texture and geometric features are adaptively focused based on an energy function; designing a TSIoU loss function, fusing a central point diagonal distance measurement and an end point distance measurement, and optimizing bounding box regression precision; a slice auxiliary reasoning strategy is applied, and the small target recall rate is increased through multi-scale slicing and parallel detection. The method solves the problems of strong noise interference, insufficient small target feature extraction, poor multi-scale adaptability and low convergence efficiency in the prior art.

The invention discloses an array type optical fiber ultrasonic imaging system based on multi-path delay parallel detection, and belongs to the technical field of ultrasonic detection and imaging. The main working process of the system is as follows: continuous laser output by a laser is modulated into pulse laser to be transmitted to an optical fiber ultrasonic detector array, and ultrasonic waves emitted by an ultrasonic wave generating device act on each detection array element to cause the property change of a detection optical signal; through multi-path time delay with the optical fiber as the medium, the detection optical signal forms different transmission time in each channel, is distinguished in a time division mode and is combined into a single path to be output. After photoelectric conversion, electric signals containing multi-channel detection information are collected in parallel, the signals are analyzed at a terminal processor by means of an imaging algorithm with an array parallel architecture, information of a to-be-detected target is obtained, and image reconstruction is completed. The array type optical fiber ultrasonic imaging system has the advantages of being accurate and rapid in scanning detection, simple and compact in system structure and efficient and high-quality in image reconstruction, and large-scale and low-cost array type optical fiber ultrasonic imaging is achieved.

The invention provides a laser radar ranging method based on parallel detection, which relates to the technical field of laser radar ranging, and comprises the following steps: generating N lasers with different wavelengths, splitting beams by a beam splitter, separating optical channels with N independent wavelengths by a demultiplexer, performing frequency shift processing, combining N paths of optical signals after frequency shift through a beam combiner, and combining the N paths of optical signals after frequency shift through a beam splitter; generating a beam of composite reference light containing N wavelengths, wherein each wavelength has a specific frequency shift; signal light returned from a target and the composite reference light are jointly input into a coupler for frequency mixing so as to generate an optical beat frequency signal, and operation processing is performed to calculate the target distance and the target radial speed corresponding to each wavelength. According to the laser radar ranging method provided by the invention, parallel detection of the laser radar can be realized, beat frequency signals corresponding to a plurality of different wavelengths can be distinguished only by integrating a group of detectors, a cross-group amplifier and an analog-to-digital converter, the cost is greatly reduced, and the complexity of the system is reduced.

The invention discloses a detection kit and method for detecting allergic inflammatory factors based on a centrifugal micro-fluidic chip, and relates to the field of kits, the detection kit comprises the centrifugal micro-fluidic chip and a preset reagent; the centrifugal micro-fluidic chip comprises a chip base body, a sample adding cavity, a liquid level sensor, a liquid level sensor, a liquid level sensor, a liquid level sensor and a liquid level sensor, the nucleic acid extraction and purification cavity comprises a plurality of amplification cavities; a reagent storage chamber; a waste liquid chamber; and a capillary valve. The functions of nucleic acid extraction, variable temperature amplification and multi-target synchronous detection are integrated through the centrifugal micro-fluidic chip, full-closed operation is achieved by means of centrifugal force or other driving force such as air pressure and electroosmotic flow, and the pollution risk caused by manual step-by-step operation is thoroughly eliminated; a multi-wavelength distinguishable fluorescent probe and a grouping preset primer combination are adopted to synchronously complete parallel detection of the allergic inflammatory factor mRNA and the drug accompanying diagnosis target, cross interference is avoided, and large instruments and equipment do not need to be relied on.

The invention relates to the technical field of data processing and traceability, and discloses a traditional Chinese medicinal material full-link traceability anomaly detection method based on graph propagation and trust scoring, which comprises the following steps of: obtaining multi-source heterogeneous data of a traditional Chinese medicinal material full link, and constructing a traceability graph containing a traditional Chinese medicinal material circulation entity node and an associated edge relationship; performing parallel detection on the to-be-detected nodes in the traceability map by using a sub-model library to obtain original abnormal scores of multiple dimensions; and calculating an adaptive fusion weight according to the feature adaptation degree of the sub-model and the to-be-detected node. The adaptive fusion weight is introduced in the local anomaly refining step, so that the system can automatically improve the weight of the sub-model sensitive to the high-risk feature, and the system can dynamically recognize and preferentially acquire the optimal model for the current data feature; the problem that the traditional static fusion method is insufficient in robustness when facing diversified abnormal modes is avoided.

The invention relates to the technical field of body posture recognition, and particularly discloses an automatic body posture recognition system based on video analysis, which comprises a video acquisition module, a preprocessing module, a key point detection module, a skeleton tracking module, an action recognition module and a cross-view fusion module. According to the scheme, a parallel detection and information fusion mode is adopted, and the detection precision of the key points of the human body is remarkably improved by utilizing the accurate position of the high-resolution feature and the rich semantics of the low-resolution feature; the target is tracked according to the topological structure and the key point position of the human skeleton, the method has extremely high robustness for illumination and dressing changes, and a more stable and continuous human skeleton movement track is generated; the time sequence convolution and the space-time diagram convolution are combined to carry out joint modeling on the space and time double-domain features, complete action representation is obtained, and the stability, the accuracy and the adaptability of body posture recognition are effectively improved.

The invention discloses an intelligent obstacle recognition method for an unmanned loader, and aims to solve the problems of low obstacle recognition precision, poor real-time performance and insufficient coordination of obstacle avoidance and operation in a complex operation scene. The method comprises the following steps: establishing a multi-source sensing system such as a laser radar and a camera, and realizing data time sequence synchronization, space unification and noise optimization through FPGA hardware; obstacle space and category features are extracted through double-branch parallel detection, and a modal weight fusion result is dynamically distributed in combination with a scene; an improved Hungary algorithm and a classification tracking model are adopted to realize obstacle ID stable association and trajectory tracking, and trajectory prediction is completed based on LSTM and Kalman filtering; and a dynamic avoidance area is constructed, and an obstacle avoidance path is generated through global-local bilevel programming and a safety potential field algorithm and is corrected in real time. The obstacle recognition robustness and real-time performance in a complex environment are improved, and safe and efficient operation of the unmanned loader is guaranteed.

The invention discloses a semiconductor etching end point detection method and a multi-channel detection system, and the detection method comprises the following steps: outputting detection light; expanding the detection light into a continuous spectrum band; imaging the continuous spectral band to a modulation surface of a digital micromirror device, and establishing a pixel group corresponding to each narrow-band wavelength of the continuous spectral band; performing spatial sampling on the continuous spectrum band, and distributing and writing a unique radio frequency modulation frequency f for each pixel group; respectively executing vibration type switch modulation on each pixel group at a radio frequency modulation frequency f so as to convert wavelength information of a continuous spectrum band into a time domain frequency optical signal; converting the time domain frequency optical signal into a time domain electric signal; performing frequency domain analysis on the time domain electric signal, and demodulating gas absorption light intensity corresponding to each modulation frequency; and judging the etching end point of the semiconductor according to the change trend of the gas absorption light intensity. According to the invention, parallel detection of a plurality of spectrum channels can be realized through a single detector so as to judge an etching end point.

The invention discloses a medical image data management method and system based on artificial intelligence, and relates to the technical field of data management, and the method comprises the steps: collecting medical image data, converting the medical image data into an initial five-dimensional tensor, carrying out the preprocessing through a pulse neural network, and outputting a spatial-temporal characteristic spectrum; performing spatio-temporal joint feature face analysis on the spatio-temporal feature map by adopting an incremental feature space updating algorithm, extracting cross-slice features in combination with a three-dimensional convolution kernel, and generating a dimensionality reduction feature vector sequence; inputting the desensitization feature vector into a parallel detection network to generate a credibility scoring report; and triggering federal learning according to the credibility scoring report, dynamically updating the feature space parameters, and synchronizing the feature space parameters to the edge node through a secure communication protocol. Through high-dimensional tensor pulse coding and spatio-temporal joint feature analysis, the calculation efficiency and feature representation precision of the multi-modal medical image are improved.

The invention relates to the technical field of high-speed monitoring intelligent detection, in particular to a small target rapid enhancement detection method, device and equipment based on an image hot spot area and a medium. Intercepting an image slice through a hot spot region maintained by an asynchronous thread; forming an image array by the original image and the slice image, and inputting the image array into a target detection model supporting Batch reasoning for parallel detection; the slice detection result is mapped back to an original image coordinate system and then fused, and a final detection result is output; in the asynchronous thread, based on a detection result, screening a focused target, reversely calculating a candidate slice window and marking the candidate slice window to the difference graph; when conditions are met, the difference graph is constructed into an integral graph, the area with the highest heat degree is positioned as a new hot spot area, hot spot information is smoothly updated in combination with a sliding window mechanism, the optimal detection area can be accurately extracted, redundant calculation is reduced, the detection efficiency and the small target recognition rate are improved, and high-quality support is provided for follow-up tracking and analysis.

The invention discloses a physicochemical index detection method for canned food production, and relates to the technical field of food detection, and the method comprises the following steps: deploying annularly arranged near infrared spectrum, eddy current electromagnetic and biological impedance three-mode sensing units, and collecting tank reflection spectrum, eddy current loss and complex impedance response signals in a non-contact manner; extracting characteristic parameters of sulfur dioxide, heavy metals and microorganisms through wavelet packet decomposition, Hilbert transform and principal component analysis; constructing a ternary coupling correction equation set to perform cross correction on the original data, and outputting an accurate detection result; and a self-calibration mechanism and an abnormal product automatic sorting function are integrated. By constructing four core technology systems of multi-modal synchronous acquisition, cross-modal feature coupling, dynamic threshold decision and online self-calibration, lossless, efficient and multi-index parallel detection is realized, the precision is stable, the cost is reduced by 60%, and the real-time quality control and tracing requirements of a full-automatic production line are met.

The invention relates to the technical field of high-energy physics and particle detection, and discloses a cosmic ray muon detector based on non-optical coupling, the cosmic ray muon detector comprises a plurality of detection layers, each detection layer comprises a plurality of columns of detection units arranged in parallel, each column of detection units is formed by aligning and arranging a plurality of scintillator strips end to end in a mechanical mode, and optical coupling does not exist between the adjacent scintillator strips; each detection unit is provided with a wavelength shift optical fiber group, and the wavelength shift optical fiber groups are fixed through mechanical clamping grooves formed in the side faces of the scintillator strips and are continuously laid along the whole column of detection units; the light emitting end of the wavelength shift optical fiber group is coupled to the photoelectric conversion module. According to the invention, mechanical splicing without optical coupling is adopted to construct a long detection column, so that the detector can be quickly assembled and deployed on site by using a standard assembly which is low in cost and easy to transport, and high cost, high risk and complex process of precise optical coupling of a long-strip-shaped scintillator are thoroughly avoided.

The application discloses a dual-channel parallel detection airborne phased array radar ground moving target extraction method, comprising the following steps: acquiring coherent pulse train data of an airborne phased array radar; forming sum-difference beam data according to preset sum-difference beam weighting coefficients; constructing a pulse compression matching function to perform pulse compression on the sum-difference beam data; performing platform motion compensation and pulse Doppler processing on the pulse compressed sum-difference beam data; performing high-speed channel determination according to amplitude statistical results of each Doppler unit of the sum beam, and performing CFAR detection; performing low-speed channel determination according to the amplitude statistical results of each Doppler unit of the sum beam, processing low-speed channel data by using sum-difference 3DT-STAP algorithm, and performing CFAR detection and amplitude normalization processing on the processed data; merging the CFAR detection results of the high-speed channel data and the CFAR detection and amplitude normalization processing results of the low-speed channel data, and extracting a point track.

The invention provides a detection system and a detection method. The detection system comprises a first bright field detection light path, a second bright field detection light path, a dark field detection light path, a first platform and a second platform, when the dark field detection light path is used for performing dark field detection on the ith to-be-detected object at the dark field position, the target light path is used for performing bright field detection on the (i + 1) th to-be-detected object at the target position; the target light path is a first bright field detection light path or a second bright field detection light path, and the target position is a first bright field position or a second bright field position. The bright field detection light path and the dark field detection light path are separated, and each light path performs detection independently, so that mutual influence between light sources is avoided, and the detection precision of bright field detection and dark field detection is guaranteed. Besides, when bright field detection is carried out on one object to be detected, dark field detection can be carried out on the other object to be detected, that is, parallel detection on the two objects to be detected can be realized, and the detection efficiency is greatly improved.

The invention relates to the technical field of rail transit, and discloses a wire harness detection system for a rail vehicle, which comprises a master control unit, a first detection unit, a second detection unit and a self-adaptive communication module, and is characterized in that the master control unit is used for storing a topological information database of a to-be-detected wire harness; the database comprises wire harness numbers, terminal position codes and rated test parameters; the first detection unit and the second detection unit are respectively provided with an anti-misplug structure, and the anti-misplug structure comprises a magnetic code positioning interface which identifies terminal magnetic pole codes through a Hall sensor; the multi-channel parallel detection circuit realizes parallel testing of multiple wire harnesses by adopting a time division multiplexing technology. According to the invention, the system can effectively prevent the problems of wrong insertion and missing insertion of the terminal, the magnetic coding positioning interface accurately identifies the magnetic pole code of the terminal through the Hall sensor, it is ensured that only the matched terminal is allowed to be inserted, and manual operation errors are fundamentally eradicated.

The invention relates to the technical field of data transmission, and provides a parallel CRC error detection device, method and equipment, and the device comprises a signal transmitter which is used for outputting original data; the signal receiver is connected to the signal transmitter and is used for receiving the original data; in the signal transmitter and the signal receiver, each communication channel is provided with a group of parallel CRC detection modules which are used for parallelly calculating CRC check codes corresponding to original data of the signal transmitter and performing consistency judgment so as to determine whether the original data received by the signal receiver are correct or not. Through the technical scheme, the error detection function can be completely realized, the calculation of the CRC check code can be realized at a relatively high speed, and the working efficiency of the system is improved.

The invention relates to the technical field of water treatment, in particular to a PHG different-direction bridging reaction system for front-end pretreatment of wastewater, which comprises a reaction monitoring module, a data analysis module, a strategy execution module and an early warning treatment module. According to the system, parallel detection light is projected to a reaction area, scattered light and transmission light are received, and image acquisition is synchronously combined, so that multi-dimensional monitoring of floc micromorphology and macroscopic spatial distribution is realized. The data analysis module is used for carrying out primary abnormity judgment according to the visual characteristics of the floc, diagnosing an abnormity source in combination with scattered light, and distinguishing abnormal hydraulic stirring conditions or abnormal flocculant response. And the strategy execution module generates a differential control instruction according to the diagnosis result, adjusts stirring or dosing parameters, and evaluates the effect after adjustment. The system provided by the invention has the functions of automatic early warning and advanced self-treatment, realizes closed-loop intelligent regulation and control of the flocculation process, and improves the quality stability of effluent and the self-adaptive capability of the system.

The invention discloses a multi-band adaptive communication method, device and equipment based on a power line carrier, and belongs to the technical field of power line carrier communication, and the method comprises the following steps: in the receiving process of a power line carrier signal, under the condition that a leading signal is detected to arrive, receiving the power line carrier signal; filtering the received signal in parallel through a plurality of bandwidth-configurable filters, and determining a plurality of cross-correlation values of a plurality of parallel filtered signals of the received signal and the same local sequence, the local sequence being set according to the overall detection frequency band; determining a sending frequency band of the received signal according to the cross-correlation value; the received signal is processed according to the sending frequency band, so that parallel detection of a plurality of frequency bands can be realized, detection of the frequency bands one by one is not needed, equipment can quickly and accurately determine a proper working frequency band for network access, the network access efficiency and the communication rate are improved, and different services are supported to select different frequency band communication and multi-frequency-band parallel communication.

The invention discloses a multichannel tissue-derived neutrophil detection chip and an application system, the chip is a multichannel detection chip integrating migration-related markers and functional markers, rapid and synchronous identification of neutrophil tissue sources is realized, the migration-related markers are CD62L and CXCR4, the functional markers are CD44 and MPO, and the migration-related markers are CD62L and CXCR4. According to the method, migration related markers and functional state markers are subjected to integrated and collaborative analysis, tissue sources are locked from the cell state and function two dimensions, four-channel parallel detection is performed, and the tissue sources of the neutrophil are accurately judged through expression profile modes of the four components instead of a single marker, so that the neutrophil detection accuracy is improved. According to the method, the neutrophil tissue source is rapidly, synchronously and accurately identified, the technical bottleneck of neutrophil tissue source detection is broken through, high efficiency, accuracy and universality are achieved, and an efficient and accurate tool is provided for immune mechanism research and clinical diagnosis.

The invention provides a control panel circuit module fault detection method, which relates to the technical field of electronic fault detection, and comprises the following steps: acquiring key electrical parameters of each functional unit of a control panel circuit module, establishing a dependency graph of the key electrical parameters, and constructing a multi-level parallel detection sequence; a variable-length window function is adopted to carry out synchronous sampling on detection items of the same level, a level feature matrix is generated, improved short-time Fourier transform is executed, a frequency spectrum deviation curve of each level is generated through sliding cross-correlation operation, a fault transmission chain is established, and a specific fault type is judged through a topological structure of the fault transmission chain; according to the method, the problems of low fault positioning efficiency and poor accuracy caused by difficulty in capturing fault transfer characteristics and insufficient capability of a traditional detection method in multi-level feature extraction and analysis can be solved.

The invention discloses a robust human body existence sensing method and system based on a millimeter wave radar in a complex interference environment, and aims to realize high-precision and high-robustness sensing of a personnel existence state in a complex indoor scene through a signal processing and multi-index fusion mechanism. The system takes a millimeter-wave radar as a core sensor, and through a signal processing flow comprising adaptive background modeling and coherent subtraction based on a complex number distance spectrum, a cleanliness index constructed by extracting multi-dimensional features from a micro-Doppler spectrum, and a dual-channel parallel detection mechanism for moving and static targets, the detection precision of the moving and static targets is improved. The core challenges that static detection is difficult, environment interference is sensitive, and system adaptability is insufficient are effectively overcome. According to the method, the environment confidence, the signal cleanliness, the moving target evidence and the static target evidence are fused for layered joint judgment, non-target movement and real human body movement can be accurately distinguished in the indoor environment with various typical interferences, and continuous and reliable detection of the full state of the person from moving to static is achieved.

The invention discloses a design method of a gallium nitride Hall current sensor, and relates to the technical field of current detection and electric energy metering. The device comprises a magnetic field conversion unit which is configured to convert a measured current into a magnetic field signal which is proportional to the magnitude of the current; and the multi-channel parallel detection unit comprises at least two programmable Hall sensing channels. Through the differential configuration design of the multi-channel parallel detection unit, a closed-loop structure does not need to be introduced, full-range high-precision current measurement can be realized, a small-range sensing channel adapts to a small current interval, the amplitude of an output signal is amplified so as to reduce the zero error proportion, the measurement precision of a rated range interval of 1%-5% is improved, the national standard requirement of electric energy measurement is met, and the electric energy measurement efficiency is improved. The wide-range sensing channel guarantees saturation resistance and linearity of large-current measurement, does not depend on limit performance of a single sensor, improves tolerance of a system to device consistency and zero drift, and reduces a device type selection threshold.

The invention discloses a full-automatic production line based on visual identification detection, and relates to the technical field of solar screen printing plate detection. The full-automatic production line comprises a main body structure, a transposition structure is arranged in the middle of the main body structure, adsorption structures are detachably installed on the transposition structure at equal intervals, and the adsorption structures are detachably arranged on the main body structure. According to the invention, parallel detection and multi-dimensional fast switching are realized, a traditional linear single-station detection mode is broken, multi-area parallel detection is realized, detection efficiency is improved, multi-angle observation and auxiliary light source adaptation are realized, hidden defects such as screen wrinkles and back impurities are prevented from being missed, and ambient light interference is reduced in cooperation with lighting of the lamp strip main body; a detector body can recognize details of the screen printing plate more clearly, the defect misjudgment rate is reduced, the structural flexibility is high, the adsorption structure is matched with double scenes, one object has two purposes, the whole process is automatic, manual intervention is reduced, and the reject ratio and the labor cost are reduced.