298 results about "Parallel detection" patented technology

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 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 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 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 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.

The invention discloses a multi-modal content real-time detection and dynamic replacement method and system. The method comprises the following steps: buffering an input audio / video stream for a fixed time length and synchronously decomposing the input audio / video stream into a video image, an audio text and a picture text; performing sensitive content detection on the three types of data in parallel, and judging overall violation according to at least one violation; and according to the violation type, selecting a global replacement mode or a local mask mode to carry out real-time replacement processing. The system comprises corresponding function modules. According to the invention, multi-modal decomposition and parallel detection are combined with cross-modal cooperative determination, so that the problem of high missed determination rate of single detection is solved; the detection precision and the real-time performance are balanced through fixed buffering and dynamic replacement strategies; particularly, a text detection and recognition fusion model is adopted to improve the dynamic subtitle recognition rate; wide-temperature hardware and fan-free design are combined, stable operation of the system in severe environments such as outdoors is guaranteed, and accuracy, real-time performance and reliability of content security control are remarkably improved.

The invention discloses a refrigerator food material taking and placing identification method, and belongs to the technical field of household appliances, and the refrigerator food material taking and placing identification method comprises the following steps: obtaining a first image of a first visual field and a second image of a second visual field, and carrying out parallel detection and identification on hands in the first image and the second image, the IDs of the hands in the first image and the second image and the refrigerator rack area where the hands are located are determined; when it is detected that the IDs of the hands in the first image and the second image disappear or exceed a preset number of frames, cross-region tracking is conducted on the hands in the first image and the second image, and cross-region tracking results of the hands in the first image and the second image are obtained; and based on a cross-region tracking result, judging whether the action of the hand in the first image and the second image is food material putting or food material taking. The refrigerator food materials are detected and recognized through the images of the first visual field and the second visual field, cross-region tracking recognition is carried out on the hands in the first image and the second image, food material recognition can be carried out more accurately, and missing detection is avoided.

The invention relates to the technical field of artificial intelligence security, in particular to a large language model illusion detection system and method based on a multi-expert voting mechanism. The method comprises the steps of obtaining a target text generated by a large language model; inputting the target text into an expert model set in parallel for detection, the set comprising at least two types of expert models for detection from different dimensions, so as to generate respective detection scores; dynamically adjusting the weight corresponding to each expert model according to the historical detection performance of each expert model; and based on the dynamically adjusted weight, performing weighted fusion on the detection scores of the expert models to generate a final hallucination detection result. Through multi-expert parallel detection and dynamic weight decision making, the text can be comprehensively evaluated from multiple dimensions, the strategy can be adaptively adjusted, and the accuracy and the adaptive capacity of illusion detection are remarkably improved.

The application discloses a physicochemical index detection method for food can production and relates to the technical field of food detection. The method comprises the following steps: deploying a near-infrared spectrum, eddy current electromagnetic and biological impedance three-mode sensing unit in a ring arrangement, and non-contact collecting can body reflection spectrum, eddy current loss and complex impedance response signals; extracting sulfur dioxide, heavy metal and microbial characteristic parameters through wavelet packet decomposition, Hilbert transform and principal component analysis; constructing a three-element coupling correction equation group to cross correct original data and output accurate detection results; and integrating a self-calibration mechanism and an abnormal product automatic sorting function. The application realizes nondestructive, efficient and multi-index parallel detection by constructing four core technical systems, namely, multi-modal synchronous acquisition, cross-modal feature coupling, dynamic threshold decision and online self-calibration, has stable precision and reduces costs by 60%, and meets the real-time quality control and traceability requirements of a full-automatic production line.

This invention provides a method and apparatus for identifying raw wireless signal targets based on model fusion decision-making, relating to the field of intelligent signal sensing technology. The method involves inputting raw wireless signal data into the signal sensing and preprocessing layer of a signal target identification model to obtain dimensional representation information output by the signal sensing and preprocessing layer. Each signal representation data in the dimensional representation information is then input into the parallel detection and feature extraction layer of the signal target identification model to obtain structured detection evidence corresponding to each signal representation data output by the parallel detection and feature extraction layer. All structured detection evidence is then input into the intelligent fusion and decision-making layer of the signal target identification model to obtain the fusion decision result output by the intelligent fusion and decision-making layer. Finally, the fusion decision result is input into the result output layer of the signal target identification model to obtain the target identification result of the raw wireless signal data output by the result output layer. The technical solution of this invention improves the accuracy of signal identification.

The invention provides a double-channel visual inspection device which comprises a feeding mechanism, a discharging mechanism, a first conveying mechanism, a second conveying mechanism, a first detection mechanism and a second detection mechanism, and the first conveying mechanism and the second conveying mechanism are arranged in parallel and extend in the first horizontal direction. The feeding mechanism carries products to be detected to the first conveying mechanism and the second conveying mechanism, and the discharging mechanism conducts discharging on the products at the discharging ends of the first conveying mechanism and the second conveying mechanism. The first detection mechanism and the second detection mechanism are arranged on conveying paths of the first conveying mechanism and the second conveying mechanism in a spaced mode, the first conveying mechanism and the second conveying mechanism convey products to be detected to the first detection mechanism and the second detection mechanism in sequence, and the first detection mechanism conducts visual detection on the first surfaces and the second surfaces of the products. The second detection mechanism at least carries out visual detection on the side face of the product passing through the first detection mechanism, a double-channel parallel detection mode is achieved, and then the detection efficiency is improved.

The invention discloses a security detection method and device for network transmission data, and belongs to the field of data security. The method comprises the following steps: performing security detection on network transmission data by using a security detection model and a clustering model; and outputting a detection result based on comparison of detection results of the security detection model and the clustering model. When the comparison result is inconsistent, calculating a comprehensive safety coefficient, and storing the network transmission data into an experience sample pool; and respectively carrying out model optimization on the security detection model and the clustering model by utilizing samples in the empirical sample pool. According to the scheme, the supervised security detection model and the unsupervised clustering model are used for parallel detection, and bimodal high-precision detection is generated; through cross-modal conjoint analysis of two modal models, doubtful network transmission data is stored in an experience sample pool, parallel optimization of a supervised security detection model and an unsupervised clustering model is realized by using a sample of the experience sample pool, online closed-loop hot update of the models is realized, dynamic perception of novel attacks is improved, and the misjudgment rate is reduced.

The invention discloses a method for detecting natural plant hormones and exogenous growth regulators of vegetables, efficient separation and accurate detection of the natural plant hormones and the exogenous growth regulators are realized through combination of hydrophilic interaction chromatography and mass spectrometry, a hydrophilic interaction chromatographic column is adopted, and conditions such as mobile phase composition and flow velocity are optimized; the selectivity of polar substances is improved by utilizing hydrophilic interaction, so that compounds with similar structures achieve baseline separation, and chromatographic peak overlapping interference is avoided; the mass spectrometric detection only responds to a specific ion signal by screening characteristic parent ion / daughter ion pairs of a target object, so that matrix impurities and non-target ion interference are effectively eliminated, the false positive risk is remarkably reduced, and the detection sensitivity and specificity are improved; the combined technology is combined with the efficient separation capacity of the hydrophilic interaction chromatographic column and a multi-reaction monitoring mode, synchronous separation of multiple compounds with similar polarities in single analysis is achieved, parallel detection of dozens of target objects is supported, and the analysis time is greatly shortened.

The application discloses a one-way valve component missing loading detection system and method, and relates to the technical field of visual detection.The system comprises an image acquisition and positioning end, an angle and posture correction end and a hierarchical comparison and detection end.The image acquisition and positioning end acquires a component area image of a to-be-detected one-way valve, and preliminarily positions the image with a pre-stored qualified product image.The angle and posture correction end corrects the to-be-detected image to the same detection posture as the template image by calculating the rotational deviation of the to-be-detected image and the template image and the affine transformation technology.The hierarchical comparison and detection end divides the corrected image into a plurality of component corresponding areas, calculates the feature difference of each area, and judges whether there is missing loading.The application can eliminate light interference through image quality adaptive enhancement, overcome position deviation through posture correction, realize multi-component parallel detection through hierarchical comparison and detection, improve the precision and robustness of missing loading detection, and support online switching detection of different models of products.

The invention provides an S100B and NSE double-signal electrochemical immunosensor, a preparation method, application and a detection product, and belongs to the technical field of electrochemical detection. According to the preparation method, the PAMAM dendritic polymer rich in amine-terminated functional groups is covalently grafted to the MXene conductive sheet layer with a large surface area to prepare the PAMAM-MXene composite material, so that the immobilization efficiency and interface electron transfer of immune molecules are remarkably improved through modification, and enhanced conductivity and relatively high specific surface area are shown; and the biomolecule loading capacity and the signal transmission efficiency of the electrode are also remarkably improved, and double-signal detection can be performed on S100B and NSE at the same time. And the electrochemical immunosensor has good reproducibility, long-term stability and anti-interference capability on the two biomarkers. According to the sensor, modular design and signal decoupling are adopted, double targets can be accurately detected in parallel, and an extensible strategy is provided for multiplexing biomarker analysis.

This application relates to the technical field of grain processing quality inspection, and in particular to a grain quality infrared image recognition equipment, which includes a housing with a turntable rotatably mounted inside the housing. A drive source is provided between the turntable and the housing, and multiple storage cylinders are arranged on the turntable. This utility model, through the annular layout design of the turntable carrying multiple storage cylinders, combined with the rotation control of the drive source, can realize multi-channel parallel detection of grain samples. When one storage cylinder is under the infrared detector for detection, other storage cylinders can simultaneously complete operations such as feeding, unloading, or vibrating and spreading, avoiding the "intermittent detection" drawback of traditional single-channel equipment. At the same time, the two discharge pipes, combined with the eccentric setting of the electric telescopic rod, can automatically switch the opening and closing state of the baffle according to the detection results, realizing dynamic sorting of qualified and unqualified grains without manual intervention, significantly improving the detection and sorting efficiency in large-scale grain processing scenarios.