204results about How to "Solve misjudgment" patented technology

The invention discloses a battery production defect inspection method, system, medium and equipment, and relates to the technical field of battery defect inspection. The method comprises the following steps: acquiring a video stream corresponding to each battery production line, and extracting a key frame sequence corresponding to each video stream; performing fusion analysis on spatial features and time sequence features of the key frame sequences to obtain abnormal state features; performing multi-stage screening on each key frame sequence based on the abnormal state features to obtain a target key frame with defects; performing space-time mapping on the target key frame, and determining an associated station corresponding to the abnormal production line; and according to the process parameters of the associated stations, carrying out grading evaluation on the abnormal state features, and generating abnormal early warning information. By implementing the technical scheme provided by the invention, misjudgment or missed judgment of abnormal conditions on the battery production line can be effectively avoided, so that the production quality of battery products is improved.

The invention discloses a basketball goal number calculation method based on computer vision, which relates to the technical field of computer vision, and comprises the following steps: synchronously capturing match pictures in a basketball court through a plurality of high-resolution PTZ (Pan / Tilt / Zoom) cameras, carrying out time calibration on data of different PTZ cameras, and generating a multi-view synchronous image data stream; tracking the flight path of the basketball in real time according to a time sequence analysis result, judging whether the basketball successfully enters the basket or not, and recording a shooting result; and performing comprehensive analysis on the shooting result, the three-dimensional action model and the time sequence analysis data, and generating a shooting success rate, shooting action evaluation and technical improvement suggestions. According to the method, multi-view image data are efficiently fused and accurately synchronized, so that the accuracy and reliability of basketball goal number calculation are remarkably improved, and the problem of misjudgment under complex shielding and view angle deviation in a traditional method is solved.

The invention relates to an MPPT (Maximum Power Point Tracking) control method based on dynamic optimization of a lightweight convolutional neural network, and belongs to the field of artificial intelligence control power tracking. The method comprises the following steps: S0, constructing a convolution-fuzzy neural network model which at least comprises an input layer, a convolution layer, a fuzzy control layer, a deep reinforcement learning layer and an output layer; s1, key parameters of photovoltaic equipment are collected in real time to serve as input data of an input layer; s2, performing convolution operation on the input data by using a convolution layer, extracting a feature vector, and transmitting the feature vector to a fuzzy control layer; s3, combining a fuzzy control layer with a deep reinforcement learning layer, and dynamically adjusting an optimization process of a fuzzy rule through a reward signal; and S4, the fuzzy control layer generates a control signal, and the control signal is transmitted to a DC / DC converter of the photovoltaic system through the output layer. The control method is suitable for a dynamic environment of a photovoltaic power generation system, can be expanded to a grid-connected system, and provides a new thought and technical support for efficient operation of photovoltaic power generation.

The invention discloses a steel plate butt weld pseudo defect ultrasonic detection method, system and device and a medium, and relates to the technical field of weld detection, the method comprises the following steps: setting a plurality of detection areas on a steel plate butt weld based on acquired structure parameters and surface characteristic data of a to-be-detected steel plate; performing multi-frequency and multi-angle ultrasonic scanning according to a preset first detection parameter by taking each detection area as a basic unit to obtain corresponding echo signal data; analyzing and identifying potential pseudo-defect signals, and calculating corresponding pseudo-defect characteristic values according to the pseudo-defect signals; taking each detection area as a basic unit, performing pseudo defect feature analysis according to the second detection parameters, and determining reliability evaluation data of pseudo defects; based on the pseudo-defect reliability evaluation data and the pseudo-defect characteristic value corresponding to each detection area, the pseudo-defect condition of the steel plate butt weld is analyzed, and a final weld quality comprehensive evaluation result is generated. According to the invention, the detection accuracy of steel plate butt weld detection is improved.

The invention relates to a substation operation risk identification method based on a multi-view video and high-precision positioning, and the method comprises the steps: obtaining monitoring video streaming images of a plurality of monitoring video point locations, and extracting the image features of an operator; rejecting monitoring video stream images with unclear or incomplete image features of operators; the coordinates of the operating personnel are determined through a Beidou high-precision positioning system or a UWB high-precision positioning system or a system combining the Beidou high-precision positioning system and the UWB high-precision positioning system, and the spatial position of the operating personnel is determined by combining the distances between the operating personnel and a plurality of monitors; determining a current operation process and link according to the spatial position of the operator; and judging the operation risk behavior type of the operating personnel in the current operation process and link according to the image features of the operating personnel and the spatial position of the operating personnel. According to the method, the problems that in the prior art, due to equipment shielding and illumination angle problems in a transformer substation, personnel operation risk behaviors cannot be accurately recognized through monitoring, and misjudgment is caused due to the fact that the spatial distance cannot be accurately quantified are solved.

The invention discloses a subsurface defect multi-mode laser ultrasonic C scanning image reconstruction method. The method comprises the following steps: carrying out two-dimensional scanning on a detected object by utilizing a laser ultrasonic detection device to obtain a multi-mode ultrasonic A scanning time domain signal data set; converting the data set into a frequency domain signal, and performing position coding according to the acquisition position of the signal; splicing the frequency domain signals with the position codes, and calculating the similarity between the signals; according to the calculated signal similarity, selecting a set number of signals to construct a graph data set; and inputting the graph data set into a trained graph neural network model to obtain a classification result of the defect signal at each position, judging whether the classification result is from a defect area or not, and performing C scanning image reconstruction according to the original acquisition position of each A scanning signal and the classification result. According to the invention, high-resolution scanning imaging of the subsurface defect can be realized, and the accuracy and reliability of subsurface defect detection are obviously improved.

According to the method, a VanilaNet network structure in the field of computer vision is used for reference and improved and then is applied to the gesture recognition problem based on electromyographic signal processing, and the VanilaNet network is difficult to be directly applied to electromyographic signal processing in consideration of the difference of image signals and electromyographic signals in data dimension and feature complexity, so that the recognition accuracy is improved. According to the invention, the VanilaNet network structure is improved in terms of data input and structure simplification, so that the VanilaNet network structure can be applied to electromyographic signals. And finally, under the condition that the recognition precision is ensured, model lightweight can be realized. Furthermore, in the data preprocessing stage, the mode decomposition mode and the data multi-domain fusion are improved, the problem of mode aliasing is avoided, the accuracy is further improved, and the robustness is improved; meanwhile, in the real-time control process, a data caching method is further designed to solve the delay phenomenon caused by the intelligent bionic hand device.

The invention discloses a vehicle-mounted camera visibility inversion method and device, a medium and electronic equipment, and the method comprises the steps: obtaining an image frame data set shot by a vehicle-mounted camera, carrying out the preprocessing, and constructing a visibility inversion data set; a visibility inversion model is constructed, and the visibility inversion model takes the visibility true value as output and is obtained by training and optimizing network weight; and inputting a picture shot by a vehicle-mounted camera in real time into the optimized visibility inversion model to obtain a current visibility true value. According to the method, the corresponding visibility can be accurately estimated, and high-precision visibility real-time inversion is realized.

The invention relates to the technical field of power equipment state monitoring, and discloses a power transformer state monitoring method, device and equipment and a computer program product. The method comprises the steps that sound signals in the operation process of a transformer are collected, and after windowing processing, self-adaptive cochlea filtering, wavelet transformation and normalization processing are carried out, the operation state of the transformer is analyzed based on an information entropy weighted grey relational degree algorithm. Compared with the limitation of only depending on a traditional signal processing method in the prior art, and particularly under a strong noise environment or a complex signal condition, the technical problem that fault judgment on the state of the transformer cannot be realized is solved, due to a processing mode of combining adaptive filtering and multi-resolution wavelet transform, the fault judgment on the state of the transformer can be realized; according to the invention, high-precision analysis of the sound signal of the transformer can be realized, so that the problem of misjudgment caused by noise interference is avoided, and the accuracy and real-time performance of fault detection are improved.

The invention discloses a cable defect positioning method based on a frequency domain reflection-constant false alarm rate and a related device, and belongs to the technical field of cable local defect positioning. The method comprises the following steps: firstly, calculating according to distribution parameters of a defective cable to obtain a head-end impedance spectrum of the defective cable, and then carrying out discrete Fourier transform on the head-end impedance spectrum to extract impedance spectrum characteristic information to obtain a cable defect positioning spectrogram; and finally, substituting the existing positioning spectrum data into an algorithm to carry out one-dimensional calculation by utilizing an adaptive threshold value of CFAR, and if the amplitude value of a data point is greater than the threshold value, judging that the data point is a defect point and keeping the defect point. Otherwise, judging that no defect point exists and setting the data to be zero so as to extract the position of the actual defect point. According to the method, the threshold value can be adaptively changed, the position and the peak value of the defect in the positioning spectrum are extracted, and misjudgment caused by human subjective factors and objective factors on a test site is reduced.

The invention provides a historical information processing method and device, and relates to the technical field of communication. The method provided by the invention comprises the following steps: a first device judges whether specific switching or transformation occurs in a cell; under the condition that the specific handover or transformation occurs in the cell, the first equipment executes one of the following operations: generating terminal historical information comprising a first identifier, the first identifier being used for indicating that the specific handover or transformation occurs in the cell; stopping the recording of cell handover or transformation; and generating terminal residence information, wherein the terminal residence information is used for indicating the duration of residence of the terminal on the network node. According to the scheme of the invention, the problem of ping-pong switching caused by network misjudgment switching is solved.

The invention relates to the technical field of coal mill powder pipes, in particular to a powder leakage defect automatic identification method based on digital twinning and AI video analysis, and the method comprises the steps: obtaining operation parameters and environmental parameters of a coal mill powder pipe, calculating a powder leakage risk characterization coefficient, and judging whether there is a potential risk of powder leakage; image data of the surface and the surrounding area of the powder pipe in the initial starting period are collected through an AI video analysis module, powder leakage characteristic parameters are extracted, a characteristic change curve segment is drawn, similarity comparison is conducted on the characteristic change curve segment and the reference characteristic curve segment, and whether a suspected powder leakage area exists or not is judged; actual operation parameters and model prediction parameters of the powder pipe in a stable operation period are obtained based on a digital twin model, the fluctuation degree of parameter deviation is calculated, and whether the powder leakage defect exists or not is comprehensively judged by combining a suspected powder leakage area judgment result; the early-stage accurate identification of the powder leakage defect is realized, the detection efficiency and precision are improved, and the operation and maintenance cost and the safety risk are reduced.

The invention relates to a high-voltage switch cabinet insulation diagnosis device circuit based on a pulse current method and a use method. The high-voltage switch cabinet insulation diagnosis device circuit comprises a three-phase pulse current signal conditioning circuit module, an arc light monitoring signal conditioning circuit module, a communication circuit module, a storage circuit module, a display circuit module, an MCU master control circuit module, a power supply circuit module, an environment temperature and humidity detection circuit module, a background noise acquisition circuit module, a three-phase cable sheath circulation monitoring and acquisition circuit module and the like. The pulse current signal conditioning circuit module is composed of a coupling capacitance sensor, a pulse current filtering sub-module and the like and can achieve the functions of pulse current data measurement and the like. In addition, functions such as pulse current transient break variable suppression and filtering are added, the problems such as error interference are effectively solved, the product judgment accuracy is improved, the arc phenomenon can be sensed in advance, the secondary circuit and personal safety are protected, misjudgment is reduced, equipment insulation monitoring is assisted, the switch cabinet pulse current detection method is more perfect, and the detection efficiency is improved. And the operation and maintenance efficiency and the switch cabinet health and stability level are improved.

The embodiment of the invention provides a dynamic region detection method, a dynamic region detection device and dynamic region detection equipment. A plurality of images shot by a camera at different moments and pose change information between the moments are fused; by calculating the difference (third optical flow value) between the optical flow (first optical flow value) caused by the movement of the camera and the optical flow (second optical flow value) generated by the actual movement of the image content, the interference generated by the movement of the camera instead of the movement of the object in the scene is effectively eliminated, and the accuracy of the dynamic region detection is further improved. The third optical flow value is used for carrying out clustering analysis on the pixel points, target dynamic areas are effectively distinguished and extracted, the areas directly reflect the motion state in the scene, the method overcomes the misjudgment problem possibly caused by only depending on the difference between the images in a traditional method, and the accuracy of the target dynamic area is improved. The detection efficiency and robustness of the dynamic area in a complex dynamic scene are remarkably improved, and more reliable data support is provided for subsequent applications such as visual analysis, target tracking and behavior recognition.

The invention relates to the technical field of medical instrument detection, in particular to a method and a system for detecting coating uniformity of a medical catheter, and solves the technical problem of low detection accuracy in the prior art. The method comprises the following steps: acquiring liquid-solid three-phase line contour information of each measurement point in a preset grid on the surface of a medical catheter sample and a corresponding initial contact angle; the preset grid is composed of a plurality of longitudinal measurement point sets; according to the liquid-solid three-phase line contour information of each measurement point in the preset grid and the corresponding initial contact angle, carrying out hydrophilic change trend analysis, and determining a local morphology disturbance degree corresponding to each measurement point and a comparability coefficient between different longitudinal measurement point sets; performing spatial interpolation correction on the initial contact angle based on the local morphology disturbance degree and the comparability coefficient to obtain a corrected contact angle of each measurement point; and performing coating uniformity detection on the medical catheter according to the corrected contact angle of each measuring point.

The present application relates to the field of motor detection technology, and specifically to a non-invasive detection method and system for isolating switch motors, the method comprising: collecting temperature data, current data, voltage data, and power data, obtaining voltage-current correlation functions, and then obtaining electrical response indexes; calculating real-time motor thermal sensitivity indexes at each sampling moment; obtaining temperature data with same and different effects, power data with same and different effects, temperature data with non-different effects, and power data with non-different effects; obtaining motor hot spot power influence factors; obtaining updated contraction factors based on motor hot spot power influence factors, and performing abnormal data detection on power sequences. The present application solves the problem of misjudgment caused by temperature changes and realizes accurate diagnosis of motor status.

The utility model relates to the technical field of automobile water pump shells, in particular to a gas detection mechanism for a water pump shell, which comprises a bearing plate, and a pressing device, a sealing device, a positioning device and a coding device which are respectively arranged on the bearing plate, the pressing device, the sealing device, the positioning device and the code printing device are arranged around the peripheral side of the fixing hole, a first airtight channel is formed in the pressing device, a second airtight channel is formed in the sealing device, and the first airtight channel is communicated with the second airtight channel. The first airtight channel and the second airtight channel are used for communicating the interior of the water pump shell with an airtight instrument. According to the air detection mechanism for the water pump shell, air tightness detection of the water pump shell can be achieved without visual judgment of an operator, the misjudgment problem is effectively avoided, and a product meets the high-precision requirement; manual participation steps are reduced, the labor intensity of workers is effectively reduced, and the production efficiency is further improved.

The invention discloses an unmanned express delivery vehicle control system and method based on operation state perception, and relates to the field of unmanned express delivery vehicle control systems. The method comprises the following steps: acquiring vehicle-mounted data in a driving period through a vehicle-mounted sensor array, performing time alignment and validity marking on the vehicle-mounted data to obtain a data quality label, constructing an evidence item set based on the data quality label, generating a sub-portrait label set according to the evidence item set, and displaying the sub-portrait label set in the driving period. And generating a portrait parameter set based on the sub-portrait label set through a preset priority rule and a persistence judgment strategy. Although the scheme has excellent performance in the aspects of improving system adaptability, safety, dynamic decision-making capability, reviewable performance and resource utilization efficiency, the problems of sensor faults, data loss, real-time data processing bottleneck, label interpretation errors and the like may influence the real-time response and decision-making precision of the system in a complex or extreme environment. Therefore, the overall performance and stability are reduced, especially under the condition of high load or low signal.

The invention provides a communication connection adjustment method and device, electronic equipment and a storage medium, and the method comprises the steps that first communication equipment determines a received signal strength indication of a communication signal received from second communication equipment, and determines a data packet error rate of the communication signal received from the second communication equipment; determining a target communication parameter according to the received signal strength indication and the data packet error rate; and adjusting the communication connection between the first communication device and the second communication device according to the target communication parameter. According to the embodiment of the invention, the PER is used as a core link quality evaluation index, a cooperative discrimination mechanism is formed with the RSSI, two typical link states of high signal strength but obvious interference and low signal strength but stable transmission are effectively distinguished, the problem of misjudgment caused by only depending on RSSI evaluation in the prior art is solved, and the accuracy of rate switching decision and the environmental adaptability are improved.

The invention discloses a semantic structure feature-based ancient book content integrity detection method and system, and relates to the technical field of information processing, the system comprises a data acquisition unit, a chapter integrity analysis unit, a paragraph integrity analysis unit, an integrity comprehensive analysis unit, a result feedback unit and a display terminal; structural features of chapters and paragraphs are accurately extracted by utilizing a semantic structure recognition technology, and the content integrity of the ancient books is comprehensively detected from the aspects of chapters and paragraphs in combination with an integrity analysis model, so that the defect that a traditional means depends on manual proofreading or simple page number comparison and keyword extraction, and the efficiency is high is effectively overcome. According to the method, the problems of typesetting confusion, chapter page missing, quotation omission and fuzzy paraphrasing which are common in the ancient books are difficult to deal with, automatic and multi-level analysis of the structural content and semantic level content integrity of the ancient books is realized, and the detection and recognition efficiency of the content integrity of the ancient books is improved.

The present invention discloses a method and system for intelligent analysis, prediction and early warning of the health status of chronic kidney disease, and relates to the technical field of medical data analysis and prediction. The method for intelligent analysis, prediction and early warning of the health status of chronic kidney disease obtains several historical health measurement data of the patient, and the historical health measurement data includes historical blood data, historical urine data, and historical physiological data; the historical health measurement data of each time of the patient is evaluated and analyzed respectively. The present invention integrates and dynamically analyzes the historical blood, urine and physiological data to construct a health assessment index for each time, and combines these indexes to form a comprehensive view of the health status of the kidney. Compared with traditional methods, this method can more accurately predict changes in renal function and potential lesions by considering multiple health dimensions and using trend analysis of historical data, and solves the problem of misjudgment that may be caused by a single data point in the prior art.

This invention provides a label defect detection method, apparatus, electronic device, and storage medium, belonging to the field of machine vision technology. The method includes: acquiring a registered and aligned binarized image of a template edge and a binarized image of the edge to be tested; performing dilation processing on the template edge binarized image and finding its intersection with the binarized image of the edge to be tested; subtracting this intersection from the binarized image of the edge to be tested to obtain a first defect region with redundant features; performing dilation processing on the binarized image of the edge to be tested and finding its intersection with the template edge binarized image; subtracting this intersection from the template edge binarized image to obtain a second defect region with missing features; and determining the defect detection result based on the aforementioned defect regions. This invention, through a bidirectional dilation tolerance differential mechanism, effectively accommodates local deformation caused by label wrinkles and positional offset of edge pixels, solving the problem of numerous false positives caused by local deformation, and significantly reducing the false alarm rate while ensuring a high defect detection rate.

The application provides an intelligent cruise garbage pickup and classification vehicle, method, equipment and medium to solve the problem that the existing laser radar can only obtain two-dimensional point cloud data and cannot identify garbage material, volume and other characteristics. The garbage pickup and classification vehicle comprises the following components: an upper computer, a lower computer, a laser radar, a depth camera, an odometer, an IMU, a mechanical arm and a wireless communication port. Through the heterogeneous data cooperation of the laser radar and the depth camera, the limitations of a single sensor are effectively eliminated. The laser radar provides high-precision two-dimensional spatial information, and the depth camera supplements three-dimensional geometric and visual semantic features, significantly enhancing the comprehensive perception ability of the garbage material, shape and volume. This fusion not only solves the problem of garbage material misjudgment in the traditional scheme, but also supports the adaptive grabbing strategy of the mechanical arm, reducing the risk of grabbing failure caused by environmental complexity. A double-bus communication redundancy design is adopted to ensure the stable transmission of key signals.

The present application relates to the technical field of automatic control and machine vision, and particularly relates to a path planning and blind area elimination method for a crawler-type cleaning robot, which comprises the following steps: collecting a photovoltaic module surface image through a vision sensor arranged on a robot body, extracting photovoltaic cell grid line features and establishing a local coordinate system; generating a path reference line based on the grid line direction, and calculating a lateral deviation and an angle deviation between a current position of the robot and the path reference line in real time; dynamically adjusting a robot walking path through a fuzzy control method; dynamically adjusting a cleaning interval by calculating a current cleaning width and an expected overlap rate; and executing an obstacle crossing or board crossing decision based on an inclination angle data when sensor data conflicts. A multi-sensor data fusion technology improves the anti-interference capability of the robot, so that the robot can stably operate in a strong light, a reflective light and the like.

The invention discloses a pipe blockage monitoring device, an application type medicine infusion device and a monitoring method, and relates to the technical field of medical instruments, in particular to a pipe blockage monitoring device comprising a Hall encoder used for detecting the rotation angle of a ratchet wheel in a ratchet wheel driving assembly and comprising a code disc and a Hall element, the code disc and the ratchet wheel are coaxially and fixedly installed, and the Hall element is used for detecting the rotation angle of the ratchet wheel in the ratchet wheel driving assembly; the Hall element and the medicine storage bin are oppositely and fixedly arranged; according to the tube blockage monitoring device, the application type medicine infusion device and the monitoring method, the rotation angle of the ratchet wheel is monitored through the non-contact code disc and the Hall element in the Hall encoder, then the problems of poor contact and increase of the rotation resistance of the ratchet wheel are avoided, and meanwhile the counting module is used for counting the action times of the driving shifting piece; the difference value between the rotation angle of the ratchet wheel and the action times of the driving shifting piece is calculated, when the difference value is larger than a set value, it is indicated that the infusion device has the ratchet wheel slipping problem caused by pipe blockage, the monitoring result is accurate, limitation of the length of a medicine storage bin is avoided, and applicability is high.

This invention provides a test method for determining injection fusion in multiple injections of a high-pressure common rail system, comprising the following steps: S1. Constructing a high-pressure common rail system injection pattern test system to test the injection pattern of two injections: pre-injection + main injection; S2. Constructing a high-speed photography direct-view test system for the injection process of the high-pressure common rail system to test the spray development characteristics under injection intervals; S3. Processing the images of the spray development process of multiple injections of the high-pressure common rail system, and repeating the spray development characteristic test until the fuel sprays of the two injections merge. The test method for determining injection fusion in multiple injections of a high-pressure common rail system described in this invention employs a spray visualization test method, obtaining the actual development process of real fuel spray in the cylinder, which can accurately determine whether actual fuel spray fusion has occurred in the cylinder, solving the problem of misjudgment of injection fusion based on control signals and injection pattern curves.

This invention provides a method and system for constructing a negative obstacle risk map, relating to the field of robot environmental perception technology. The method includes: acquiring multimodal sensing data of a legged robot in the current operating environment to obtain the types of negative obstacles, multiple candidate regions, and the corresponding confidence and uncertainty of each candidate region; using a risk diffusion algorithm, performing ink blurring processing based on the type, confidence, and uncertainty to generate a continuous risk field corresponding to each candidate region; dividing the continuous risk field to generate a continuous risk gradient distribution corresponding to each candidate region; performing terrain modeling based on laser point clouds, updating the continuous risk gradient distribution using Bayesian fusion to obtain a multi-level grid map, and then performing tactile closed-loop correction on the multi-level grid map to generate a risk cost map. This invention improves the accuracy of constructing a negative obstacle risk map.

The invention discloses a blood oxygen signal denoising method and system based on adaptive filtering, and the method comprises the steps: synchronously collecting an original blood oxygen signal and a three-axis acceleration signal through a sensor module, and obtaining an original blood oxygen signal sequence and a three-axis acceleration signal sequence which are aligned in time; the three-axis acceleration signals are fused into one-dimensional motion artifact reference noise signals used for representing the limb motion state of the user; the method comprises the following steps: dynamically calculating an adaptive step length factor sequence through a nonlinear mapping function based on multilevel energy analysis of a motion artifact reference noise signal; constructing a time-varying step size adaptive filter, and calculating noise components in the original blood oxygen signal by using the motion artifact reference noise signal and an adaptive step size factor; and subtracting the calculation noise signal from the original blood oxygen signal, and reconstructing to obtain a pure blood oxygen signal without motion artifacts. According to the method, accurate calculation and efficient suppression of motion artifacts can be achieved, and the purification quality and processing efficiency of blood oxygen signals are remarkably improved.

The present application relates to a kind of detection method and system for air bag bag production, it is related to the field of automobile passive safety technology, it includes obtaining current process number;Determine current tool number;Call in report record;Call in tool use information;Analysis report record and tool use information, to output abnormal reason;Real-time acquisition global overhead view and air bag fabric side view;Determine air bag fabric fluctuation point;Frame select air bag fabric fluctuation point corresponding fluctuation area;Determine fluctuation area height feature;Determine fluctuation area texture feature;Determine coating thickness anomaly, and output defect air bag bag signal;When there is no coating thickness anomaly, determine wrinkle area;When there is wrinkle area, execute flattening operation, and re-execute step 9 to step 12;When there is still wrinkle area after flattening operation, determine permanent wrinkle and output defect air bag bag signal.The present application has the effect of timely maintenance to tool and accurate traceability abnormal point in production process.

The invention provides a flower quality grading quality inspection method and system based on AI and image processing, and belongs to the technical field of computer vision and pattern recognizing.The method comprises the steps that an original image of the surface of a flower is collected through high-resolution imaging equipment, and high-frequency sub-band data representing tiny physical characteristics are extracted through multistage discrete wavelet transform; meanwhile, a sliding window is adopted to traverse the image, the color information entropy of a local area is calculated, and a color entropy graph is constructed. And after vectoring and splicing the two types of features, inputting the two types of features into a deep belief network model based on a multilayer restricted Boltzmann machine, and extracting deep abnormal feature codes. And finally, performing linear discriminant analysis on the code by utilizing a classification projection vector based on inter-class and intra-class distance optimization to generate an insect attack infection index, and realizing automatic grading quality inspection of the flower quality according to the insect attack infection index. According to the method, precise recognition and quantitative grading of tiny insect pests and recessive lesions on the surfaces of the fresh flowers are realized.