73results about How to "Avoid missed judgments" patented technology

The invention discloses a heat supply network pipeline hydraulic and thermal working condition abnormal fluctuation intelligent identification and fault early warning method, and relates to the technical field of computer processing, and the method comprises the following steps: S01, collecting hydraulic and thermal parameters of a heat supply network pipeline in real time; s02, acquiring abnormal data of the time sequence sample set based on the thermodynamic mechanism model, detecting and repairing the abnormal data; s03, extracting characteristic parameters capable of reflecting abnormal fluctuation of the hydraulic and thermal working conditions of the heat supply network pipeline from the repaired time sequence sample set; s04, establishing an abnormal fluctuation identification model by utilizing an intelligent algorithm, and judging whether the hydraulic and thermal working conditions of the heat supply network pipeline have abnormal fluctuation or not; and S05, when the abnormal fluctuation is identified, giving a grading early warning mechanism and risk prevention and control suggestions of the damage degree grade of the associated pipeline. According to the invention, by fusing multi-source data and an intelligent algorithm, full-chain intelligent management of the hydraulic and thermal working conditions of the heat supply network pipeline from abnormal accurate sensing, fault intelligent diagnosis to risk active early warning is realized.

The invention discloses a cuboid and cylinder space collision detection method, which comprises the following steps: based on a preset projection axis set, respectively calculating projection intervals of a cylinder and a cuboid on each projection axis in the preset projection axis set by adopting a projection axis method; if at least one projection axis which enables the projection interval of the cylinder to be not overlapped with the projection interval of the cuboid exists in the preset projection axis set, judging that the cylinder and the cuboid do not collide with each other; and if the projection axis which enables the projection interval of the cylinder to be not overlapped with the projection interval of the cuboid does not exist in the preset projection axis set, judging whether the cylinder collides with the cuboid or not by adopting projection surface convex hull detection. The efficiency and the accuracy of collision detection are effectively considered by comprehensively applying a staged strategy combining rapid projection axis elimination and precise projection surface convex hull judgment.

The invention relates to the technical field of batteries, and discloses a battery self-adaptive safety protection method and system based on data driving, and the method comprises the steps: extracting parameter features of a transient segment, a steady segment and a fluctuation segment after segmentation, constructing a comprehensive feature matrix based on the parameter features, all environmental factors of the battery are screened based on the environmental influence model, the working condition of the battery is determined based on the working condition identification model, the environmental influence factors and the state feature sequence, the working condition is verified based on historical data, and a corresponding monitoring strategy is selected based on the verified working condition or the re-determined working condition. And the acquisition interval is adjusted based on the monitoring strategy, the risk direction of the battery is determined based on the relationship between the standard state feature sequence and the state feature sequence, and whether power-off protection is performed on the battery is judged based on the association relationship of all the risk directions. According to the invention, through data driving of historical data, the flexibility and reliability of battery safety protection are ensured.

The invention discloses an atrial fibrillation anomaly detection method and system based on multi-sensing time-frequency pseudo anomalies, and the method comprises the steps: obtaining an atrial electrophysiological signal sequence through an HDS high-density sensing atrial fibrillation analysis platform, carrying out the time-frequency conversion of the signal sequence, constructing a multi-modal time-frequency tensor model, and extracting a time-frequency feature subset related to the atrial fibrillation anomaly; dynamically distributing feature weights by utilizing an extrusion excitation time-frequency pseudo-selection model so as to optimize features; constructing a double-domain hypersphere feature space based on the optimized features, calculating a pseudo-anomaly distance value through a double-domain hypersphere pseudo-anomaly distance calculation algorithm, and dividing a suspected atrial fibrillation anomaly feature sample set in combination with a preset threshold; and carrying out feature fusion on the suspected abnormal sample set, extracting common abnormal features and generating a detection result. The system corresponds to six units, the comprehensiveness of feature extraction and the accuracy of anomaly recognition are greatly improved, the clinical requirements for atrial fibrillation detection are met, and reliable technical support is provided for early diagnosis of atrial fibrillation.

This invention discloses a data synchronization method and system based on front-end orchestration management, belonging to the field of data synchronization. The method includes the following steps: selecting the data table and field information to be monitored through the front-end interface, generating configuration information, and orchestrating the synchronization process logic according to business needs; storing the configuration information in real time to the configuration center to generate real-time monitoring rules; capturing changed data of the data table and field information, encapsulating it into standard data units and sending it to a message queue; preprocessing the standard data units in the message queue; the synchronization adaptation module matching the corresponding driver type according to the synchronization process logic to generate a synchronization instruction set, and executing data synchronization operations based on the preprocessing results; performing full-link monitoring of the synchronization process, and performing task lifecycle management based on the lifecycle rules configured on the front end. This invention improves synchronization efficiency through dynamic threshold verification, multi-source field fusion weighting, and dynamic encryption strategies, and the full-link monitoring further enhances front-end manageability.

The invention provides a business risk detection method and device, equipment, a medium and a program product, and relates to the field of financial science and technology or the field of big data. The method comprises the steps of obtaining multi-modal business data of a target industry chain, processing the multi-modal business data in each industry to generate a joint feature vector corresponding to each industry, determining business association information among the industries according to the joint feature vectors corresponding to all the industries, and sending the business association information to the target industry chain. Generating a risk detection result of the target industrial chain based on the business association information; according to the method, the multi-modal business data of the multi-industry associated enterprises in the target industry chain is acquired and subjected to targeted processing, the joint feature vector of each industry is generated so as to accurately mine the business associated information between the industries, efficient detection and accurate identification of the target industry chain risk are finally realized, and the efficiency and accuracy of industry chain risk detection are improved.

The present application belongs to the technical field of port safety monitoring, and specifically relates to a method and system for identifying personnel approaching a cable launching area in a port, a terminal and a storage medium, which comprises selecting a fixed cable column of a port berth as a physical reference, using a high-resolution network camera to collect panoramic images of the port berth, using a pre-trained YOLOv8 deep learning model for multi-target segmentation, and performing secondary focusing identification to quickly and accurately identify personnel, cables, cable columns and ship outline targets, and by obtaining dynamic factors such as cable tension and ship docking angle, the reference radius of the dangerous area is corrected by combining the corresponding calculation formula, and a dynamic dangerous area polygon is generated, fully considering the dynamic changes of the port operation environment, which can update the dangerous area in real time, making the division of the dangerous area more in line with the actual situation, avoiding misjudgment and missed judgment due to the fixed dangerous area, and improving the accuracy and effectiveness of safety management.

The application discloses a campus intelligent terminal equipment management method and system based on multi-source state synchronization, and relates to the technical field of intelligent terminals.The campus intelligent terminal equipment management method and system based on multi-source state synchronization comprises the following steps:S1, terminal cooperative collection of context state data sets is carried out, and normalization processing is carried out;S2, a migration image synchronization state data set is constructed, and stage switching and playback migration handover are carried out;S3, a pulse interference detection model is constructed, and interference window suppression and online correction are carried out;S4, a double-time reference transaction consistency check and migration submission judgment closed loop is constructed, and linkage rollback and management are carried out.The application effectively improves the state consistency and operation stability in the cross-node migration process of the campus intelligent terminal, and solves the problem of the pulse interference phenomenon in the equipment state migration.

The invention provides an island detection method and device, a photovoltaic inverter and a storage medium, and relates to the technical field of power system detection. The method is applied to a distributed power generation system. The method comprises the steps of collecting a plurality of electric signal data of a distributed power generation system at a common coupling point within a preset duration; wherein the preset duration comprises a plurality of acquisition periods; performing feature extraction on the plurality of electric signal data to obtain electric signal feature values; and determining whether the distributed power generation system is in an island state according to the electric signal characteristic value. Even if there is interference in a power grid to cause sudden change of a single electrical parameter, the method can still accurately detect whether the distributed power generation system is in an island state, and prevents misjudgment.

The invention belongs to the technical field of smart city information, and particularly relates to a multi-scene adaptive communication protocol software system and an optimization method. And the whole process of communication protocol adaptation, data transmission and abnormity management and control is covered. Core algorithms such as protocol adaptation modeling, data transmission optimization and abnormal management and control early warning are adopted, the technical bottlenecks of'heavy transmission and light adaptation, heavy rate and light reliability, and heavy response and light pre-judgment 'of a traditional communication protocol software system are broken through, and adaptive adaptation, high-reliability and low-delay data transmission and full-process abnormal real-time management and control of communication protocols under multiple scenes are achieved. The adaptability, reliability and stability of a communication protocol software system are remarkably improved, deep fusion of communication protocol software and multi-scene application is promoted, and a brand new intelligent communication solution is provided for the fields of industrial communication, the Internet of Things, intelligent terminals and the like.

The application discloses a kind of control area quick recovery method of non-count axis CBTC system, comprising: step S1, adjacent control area real-time intercommunication communication train and the position and route information of non-communication train;Step S2, after target control area restarts completion, the communication link with upstream control area and downstream control area is restored, and the tracking of communication train in this control area is restored;Step S3, based on the information of upstream control area and downstream control area synchronization, the total number of train in target control area and the number of non-communication train are calculated, and then the communication train and non-communication train in target control area are distinguished;Step S4, for the communication train that has been restored tracking, the route thereof is automatically restored according to the original route information synchronized;Step S5, for non-communication train that has not been restored tracking, the position thereof is preset as the envelope within the original route range, and the original route is restored after artificial confirmation.The application realizes the quick and accurate recovery of train position and route after control area restarts, and reduces the influence on operation.

This invention relates to an automatic detection system and method for elevator landing door locking devices. The system includes a moving base mounted on the car top, a door lock drive mechanism driven by the base, an image acquisition device, a signal acquisition device, and a control device. The door lock drive mechanism has two roller push plates that can move independently or collaboratively, enabling adaptive driving of single-action or double-action roller door locks. The image acquisition device acquires door lock images to identify door lock features and the lock hook. The signal acquisition device acquires the door lock safety circuit break signal. The control device automatically controls the drive mechanism based on the identification results and triggers visual measurement upon receiving the break signal to calculate the lock hook engagement depth and determine whether it meets safety requirements. This invention achieves automatic, accurate, and efficient detection of door locks with various structures, replacing traditional manual methods and significantly improving the objectivity, accuracy, and applicability of the detection.

The application relates to the technical field of network security, in particular to a high-risk operation instruction identification method and device and a storage medium, which comprises the following steps: acquiring keystroke coordinate records. According to the effective coordinates and the time information of the keystroke operation, the column distribution dispersion degree used for representing the horizontal direction distribution width of the keystroke operation on a monitoring target row is calculated, and the active point filling rate used for representing the horizontal direction continuity degree of the keystroke operation on the monitoring target row is calculated. Whether a command input intention exists on the monitoring target row is judged according to the column distribution dispersion degree and the active point filling rate. In response to the judgment result that the command input intention exists, the instruction sequence executed by the user final intention is reconstructed according to the keystroke character, the effective coordinates and the time information of the keystroke operation. The application provides a method for identifying the real command construction intention in a full-screen program.

The present application relates to the technical field of monitoring control, and discloses a heartbeat monitoring triggered program control circuit execution method and device, wherein heartbeat signals of N test channels of a heartbeat circuit breaker box are received, heartbeat interval characteristic sequences of the channels are constructed, a dynamic timeout threshold is calculated, a channel disconnection confirmation flag is generated through multi-stage anti-jitter decision, three-level circuit breaker decisions of channel-level DC, system-level AC coordination and channel-level alarm are executed based on a state control matrix, a circuit execution sequence is generated, a channel to be restored is identified, a restoration priority queue is constructed, staggered electrical restoration is executed, and stable restoration and conflict avoidance are realized by combining gradual voltage soft start and communication time slot allocation; the present application takes the channel as the minimum control granularity, realizes accurate fault isolation and orderly restoration, avoids local channel disconnection triggering global power failure, and improves the continuity and reliability of a multi-station test system.

The present application belongs to the technical field of wear state detection, and specifically discloses a method for detecting the wear state of a drill bit of a roof anchor rod drill of a roof bolter based on balance analysis, which comprises the following steps: collecting axial thrust force and torque to determine a stable state; continuously collecting axial thrust force, drilling speed, drilling depth and drilling deviation after the stable state is reached, comparing the collected data with a temporary reference before a reference value interval is determined and with the reference value interval after the reference value interval is determined, recording abnormal time points and drilling depth; collecting parameters in a verification time window to perform authenticity verification; matching the depth interval with a rock stratum profile after a real abnormality is confirmed, and determining wear when there is a rock stratum change and the deviation amplitude exceeds a fluctuation range; and finally calculating the axial thrust force rise rate, drilling speed drop rate and deviation growth rate, weighting the total deviation coefficient to determine the wear state and provide an early warning. The present application realizes continuous monitoring of the drilling process, eliminates rock stratum change interference and instantaneous disturbance, and reduces the false alarm rate.

The invention provides a monocular vision snakelike running action detection method and device, equipment and a medium. The method comprises the steps that a real-time video stream of a snakelike running test site is collected through a single camera; performing area cutting on the video frame based on the site calibration point to obtain a human body detection area and a rod body detection area; loading and running a deep learning model, performing asynchronous reasoning on the video frame, and obtaining a human body detection frame, a human body posture key point, a rod body detection frame and a rod body state classification result; continuously tracking the detected human body target based on a human body tracking algorithm, and obtaining a motion track of an effective tester; according to the spatial relationship among the human body position, the posture key point and the rod array, the motion stage is judged in real time; in the movement process, detecting at least one illegal behavior in real time; according to the exercise stage and the violation detection result, automatic timing is carried out, a structured report containing exercise performance and violation information is generated, and full-process automatic detection can be achieved only through a single camera.

This application relates to a method and system for testing the fatigue life of a spring. The method includes: simultaneously acquiring instantaneous force and displacement signals of the spring under test, and identifying each loading cycle based on the instantaneous force and displacement signals; extracting characteristic parameters reflecting the mechanical response characteristics of the spring based on the instantaneous force and displacement signals corresponding to each loading cycle; tracking the changing trend of the characteristic parameters with the number of loading cycles, and calculating the rate of change of the characteristic parameters based on the changing trend; and determining the fatigue failure point of the spring based on the changing trend and the rate of change. This invention can significantly improve the reliability of fatigue life test results and provide accurate data support for spring design optimization.

The application provides a relay fault detection method and device, electronic equipment and storage medium, and belongs to the technical field of fault detection. The method comprises the following steps: acquiring electrical data, action time data, shell temperature data and environmental humidity data collected by a relay checker; the electrical data, the action time data, the shell temperature data and the environmental humidity data are respectively preprocessed to obtain a standard feature data set; the electrical data comprises power, current and voltage, and the action time data comprises attraction time and release time; abnormal mark data is determined based on the standard feature data set and rated reference data; correlation feature analysis is performed on the standard feature data set to obtain correlation abnormal mark data; fault risk data is obtained based on the abnormal mark data and the correlation abnormal mark data; and a fault determination result is obtained based on the fault risk data. The application can improve the accuracy of relay fault detection.

The invention relates to the technical field of intelligent household equipment and Internet of Things operation and maintenance, and discloses an electric fireplace fault self-diagnosis method and system, and the method comprises the steps: obtaining multi-dimensional sensing data and historical records; performing feature extraction and clustering calculation according to the multi-dimensional sensing data to obtain a difference feature set; inputting the difference feature set into a pre-constructed causal model for deduction, and extracting to obtain a potential abnormal link; according to the potential abnormal links and the historical records, fusing to obtain a state matrix, constructing a difference directed graph based on the state matrix, and positioning an abnormal source; and inputting the state vector corresponding to the abnormal source into a pre-constructed Bayesian network for deduction to determine a fault starting point. According to the method, the fault root cause of the electric fireplace can be accurately positioned.

The present application relates to the technical field of centrifuge operation monitoring, in particular to a centrifuge data remote monitoring method and system based on a cloud platform. The method comprises: obtaining the vibration intensity, noise decibel value, temperature, actual speed of the screw, liquid flow at the separation liquid discharge outlet, and humidity of the material liquid in the cylindrical area and conical area of the centrifuge during the operation of the centrifuge; evaluating the centrifugal vibration intensity according to the vibration intensity and noise decibel value at each time; obtaining the abnormal factor at each time according to the distribution characteristics of the centrifugal vibration intensity in the local time period; correcting the abnormal factor by using the temperature and temperature change characteristics in the local time period; obtaining the separation abnormal score by combining the actual speed of the screw at each time, the liquid flow, the humidity difference of the material liquid in the cylindrical area and conical area of the drum, and the corrected abnormal factor; and determining whether to give a warning for the centrifuge abnormality according to the separation abnormal score. The present application improves the accuracy of the centrifuge monitoring result.

This invention discloses a method for tracking and tracing sensitive network behaviors, relating to the field of network security technology. The specific steps of this method are as follows: collecting and preprocessing multi-source heterogeneous data in the network environment and storing it in a distributed database; constructing a cross-modal semantic graph using a large language model; training an intent classification model to predict sensitive behavior intents and forming an association set; locating intent trigger points and constructing a complete tracing chain through an intent trigger point causal contribution algorithm; integrating data to generate a standardized tracing report, and presenting it through a visualization tool, supporting interaction and export. This invention first integrates and analyzes multi-source heterogeneous data to construct a cross-modal semantic graph, accurately identifies sensitive behavior intents through model training and filtering, then locates intent trigger points through algorithms, constructs a tracing chain, and finally outputs a visualized report, forming an easy-to-understand report, thus improving the comprehensiveness, accuracy, and convenience of sensitive behavior identification and tracing.

This invention relates to the field of fault diagnosis technology, specifically to a smart street light fault diagnosis and maintenance system. The system includes: a signal collaborative acquisition module, a frequency domain conversion module, a fault identification module, a coupling verification module, and a maintenance scheduling module. In this invention, multi-source data synchronous acquisition and timing alignment technology are used to eliminate the influence of external environmental interference on monitoring data, ensuring the stability and accuracy of photoelectric signals. Stable signal features are extracted through frequency domain conversion and feature filtering. Accurate fault identification is achieved based on frequency components and similarity calculations. Multi-dimensional verification is performed by combining instantaneous power comparison and communication delay detection, improving the accuracy and reliability of fault judgment, thereby avoiding misjudgments and omissions, optimizing maintenance scheduling, improving the fault response efficiency and overall stability of the street light system, effectively reducing maintenance delays and resource waste caused by inaccurate fault diagnosis, and improving the operational reliability and maintenance response speed of street lights.

This utility model relates to the field of roadway roof anchor cable protection, and more particularly to an automatic alarm device for roof anchor cable protection in high-stress areas. The automatic alarm device includes an anchor cable body, a protective sleeve, protective components, and a displacement sensor. The top of the anchor cable body passes through the roadway roof and is placed inside the roadway roof. A tray and a lock for securing the tray are installed at the end of the anchor cable body extending from the roof. This utility model provides an automatic alarm device for roof anchor cable protection in high-stress areas. Through the design of the displacement sensor and pressure plate, it achieves real-time monitoring and automatic alarm of anchor cable deformation. When the spring compression exceeds a preset threshold, the displacement sensor immediately triggers an audible and visual alarm. With both visual and auditory prompts, technicians can quickly locate the anchor cable with potential hazards based on the alarm signal and take timely measures such as inspection and reinforcement, significantly improving the efficiency of hazard handling.

The invention discloses a fault detection method and system for a driving circuit of an electronic circuit board, and relates to the technical field of electronic engineering. According to the fault detection method for the electronic circuit board driving circuit, impedance spectrum scanning, switch stress pulse and dynamic response test signals are injected into the electronic circuit board driving circuit in sequence, response signals are collected, and the impedance characteristic, the resonance mode and the dynamic performance of the circuit are analyzed. The capacitance value and the equivalent series resistance of a direct current bus capacitor are obtained through impedance analysis, the dominant resonant frequency and the damping ratio of a power loop are obtained through resonance mode analysis, and the phase margin of a control loop is obtained through dynamic performance analysis. According to the method, impedance, resonance and control parameters are extracted through multi-signal injection, fault diagnosis reliability and accuracy are improved through combined analysis, and stable operation of a system is guaranteed.

This invention belongs to the field of water pollution source tracing technology, and specifically relates to a source tracing method for water pollution at monitoring sections in river basins. The method includes collecting seven types of basic data, such as industrial and agricultural sources; screening out exceeding pollution standards and corresponding catchment area pollution sources through standardized preprocessing; constructing standardized topological relationships between four types of pollution sources, discharge channels, and exceeding pollution standards, and marking pollution sources without topological relationships; calculating the correlation between nodes based on topological type differences, and calculating spatial correlation for nodes without topological relationships; designing differentiated methods to calculate relative emissions for industrial, agricultural, and domestic sources; combining correlation and relative emissions to calculate a comprehensive correlation, and outputting the source tracing results after sorting. This invention solves the problems of existing water pollution source tracing technologies, such as the lack of systematic topological relationships, biased calculation dimensions, and inaccurate results.

The embodiment of the invention provides a vehicle fog lamp control method and device, a vehicle and a medium, vehicle environment sensing data, driving data and road data are obtained through multi-dimensional fusion, a target fog lamp turn-on condition is dynamically determined based on the road data, whether the turn-on condition is met or not is comprehensively judged in combination with the environment sensing data and the driving data, and the vehicle fog lamp control method and device are provided. The limitation that in the prior art, indexes such as visibility or rainfall are considered only in a single dimension is broken through, accurate evaluation of the driving environment under the low-visibility weather is achieved, risk misjudgment and missed judgment are effectively avoided, the vehicle fog lamp can be accurately and adaptively controlled to be turned on, the fog lamp control reliability under the extreme weather condition is improved, and the vehicle fog lamp control method is suitable for popularization and application. Therefore, the driving safety of the driver is comprehensively guaranteed.

The invention relates to the technical field of fault diagnosis, and discloses a cross-device power adapter fault diagnosis method and system, and the method comprises the steps: collecting an operation data set of multiple types of devices; extracting a universal feature vector; calculating a deviation value between the general feature vector and a preset normal operation vector, and if the deviation value exceeds a preset deviation tolerance threshold value, marking the general feature vector as an abnormal vector and performing classification to obtain a fault classification label; performing cross-device unified correction on the fault feature vectors matched with the tags, and extracting fault distribution features; in combination with the real-time feature vector, standardized fault modes are extracted and integrated, and an initial diagnosis standard is obtained; performing matching analysis on the real-time operation parameters and an initial diagnosis standard, and obtaining an optimized diagnosis standard according to an analysis result; and monitoring the operation state of each device and performing diagnosis by using the optimized diagnosis standard to obtain a final fault diagnosis result. The method can unify the feature data of different devices under the same type of faults, and flexibly deals with the difference between the devices.

The invention relates to the technical field of lithium ion battery manufacturing, in particular to a pole piece component floating judgment method. The method comprises the following steps: selecting a to-be-detected pole piece after coating and drying and before rolling, and performing gradient scraping to obtain a plurality of samples with different thickness layer areas; performing an electrochemical test on the sample in each layer region to obtain the first discharge capacity of the sample; and judging whether a component floating phenomenon exists or not according to the capacity change trend of each layer area, if the gram capacity continuously rises along with the increase of the scraping depth and the difference value of the adjacent layer areas is greater than or equal to 1mAh / g, judging that floating exists, and further dividing a mild grade, a moderate grade and a severe grade according to the capacity difference value delta C of the deepest layer and the outermost layer. The method is high in sensitivity, quantitative in result and suitable for quality control and process optimization of the negative pole piece of the lithium ion battery.

The application discloses a three-network integration residential network fault intelligent diagnosis and self-recovery system and relates to the technical field of communication networks.The system comprises a service identification module, a fault detection module, an isolation control module, a self-recovery strategy module and a resource scheduling module.The application realizes accurate tracking and distinguishing of three types of service flows, namely voice, broadband and IPTV, through a service characteristic fingerprint library, accurately locates service-level faults in combination with multi-dimensional fault detection, realizes logical isolation of faulty services through an SDN flow table, avoids affecting other services of the same user, designs differentiated self-recovery strategies according to different service characteristics, reserves and dynamically adjusts bandwidth resources to guarantee key service requirements, automatically cancels isolation after fault recovery and completely records information, provides data support for network optimization and comprehensively improves the reliability and operation and maintenance efficiency of the three-network integration residential network.