20results about How to "Detect abnormalities in time" patented technology

The invention relates to the technical field of power system monitoring and fault diagnosis, and discloses an electromagnetic voltage transformer internal defect multi-parameter online monitoring method, which comprises the following steps: S1, detecting a discharge arc light signal in a transformer by using a photomultiplier; s2, capturing a partial discharge ultrasonic signal in the mutual inductor by adopting an ultrasonic sensor; s3, monitoring voltage and current signals of the mutual inductor by using a current sensor; s4, comprehensive internal defect analysis is carried out on the mutual inductor according to the detected optical signals, ultrasonic signals and voltage and current signals, early discovery and early warning of internal defects of the voltage mutual inductor can be achieved through a multi-parameter online monitoring method, the overall operation efficiency and safety of an electric power system can be improved, and the potential safety hazard of the electric power system can be reduced. Through the real-time and comprehensive monitoring, the maintenance cost and the potential risk caused by the fault of the voltage transformer can be greatly reduced.

The invention discloses an equipment maintenance management method and device. The method comprises the following steps: collecting vibration data of equipment in different motion states; performing feature extraction and labeling on the vibration data; a training sample is generated according to the extracted feature values and corresponding labeling information, the labeling information is used for indicating equipment states corresponding to the vibration data, and the equipment states comprise a normal state and a specific fault state; training a fault diagnosis model by using the training sample; and performing fault diagnosis on the equipment by using the real-time monitoring data of the equipment and the fault diagnosis model, and determining the current state of the equipment. By means of the scheme, the real-time performance and intelligence of equipment vibration monitoring can be improved, and normal operation of equipment can be better guaranteed.

The invention relates to the technical field of data processing, in particular to an intelligent data processing method and system based on surgical nursing, and the method comprises the steps: firstly obtaining food intake and physiological indexes of a patient within a preset time, comparing the food intake and physiological indexes with a standard food intake set, and generating a food intake standard score; in conjunction with the physiological metric, the system determines a real-time feeding score and a total feeding score. By comparing the real-time and total feeding scores at different time points, the system finally generates a feeding balance score of the patient. According to the method, food intake and physiological data are effectively integrated, a scientific and quantitative food intake evaluation tool is provided for surgical nursing, nutrition management of a patient is optimized, nursing quality is improved, the absolute value of the food intake is considered in the evaluation, the relevance between time distribution of food intake and physiological indexes is concerned, and the evaluation accuracy is improved. Therefore, more comprehensive and in-depth patient state information is provided for nursing personnel. Especially, due to the introduction of a feeding balance degree score, an important basis is provided for formulating a more reasonable nutrition intervention scheme.

The invention provides a refrigerating machine room health prediction diagnosis and control system and method based on intelligent electric meter data analysis. The system comprises a plurality of control devices; the intelligent electric meters are configured in one-to-one correspondence with the control devices so as to monitor power utilization data of the devices in real time, and each control device and the matched intelligent electric meter form a control loop; the power utilization data at least comprise three-phase voltage, three-phase current and three-phase power; and the control system is connected with each control loop and is used for performing early warning analysis according to monitoring data of the intelligent electric meters in the control loops and performing state adjustment on the control loops based on an early warning analysis result. Real-time comparative analysis is carried out by combining rated working condition data of equipment, abnormal operation of the system is found in time, corresponding faults are automatically controlled and processed, and stable operation of the system is guaranteed. And meanwhile, an electric energy use strategy can be optimized, and by identifying high-energy-consumption equipment or time periods, measures are taken in a targeted manner to reduce energy consumption and optimize and adjust the operation condition of the system.

The invention provides a train control equipment operation and maintenance method and a train control equipment operation and maintenance device, and relates to the technical field of computers. The method comprises the following steps: initializing a digital twinborn model of the train control equipment based on equipment information of the train control equipment; the method comprises the following steps: collecting operation and maintenance data of train control equipment in real time, performing entity recognition processing on the operation and maintenance data, extracting entity knowledge information, performing fusion processing on the entity knowledge information, and constructing an operation and maintenance knowledge graph of the train control equipment; and importing the operation and maintenance knowledge graph into a database of a digital twin model, simulating an actual operation state of the train control equipment through the digital twin model, predicting a future operation state of the train control equipment, and determining an operation and maintenance strategy of the train control equipment based on the future operation state. Real-time monitoring and remote diagnosis of the equipment are achieved through the digital twinborn technology, operation and maintenance data are managed and analyzed through the knowledge graph technology, intelligent operation and maintenance decision support is provided, and then the reliability and safety of the train control equipment in the complex environment are improved.

The present invention discloses an intelligent inspection device for a chemical fiber spinning process silk path, wherein the silk path includes a frame and a spinneret with a plurality of spinneret holes arranged on the frame. When the spinneret hole is working, the spinneret hole sprays out silk thread units downwards, and the inspection device includes a track fixedly arranged on the upper part of the frame, a bracket assembly slidably arranged on the track, and at least one detection device arranged on the bracket assembly for detecting the number of silk thread units sprayed by each spinneret. Since the bracket assembly of the present invention slides along the track arranged at a high place, the detection device can move with the bracket assembly for detection, is not restricted by the complex conditions on the ground, and is not easy to interfere with the normal production order. Since the present invention adopts a mobile detection device instead of manual inspection, it can timely detect abnormalities in the high silk path, and the efficiency is about 20 times that of manual inspection.

The present invention relates to the field of security monitoring technology, and in particular to a method and system for detecting abnormal operation of a network camera, including training a basic data set to form a large model, collecting normal and abnormal images, marking and preprocessing after block processing, training through multi-task learning of a CNN network structure model, using SSIM as a loss function and generating simulated abnormal data to enhance generalization ability, and evaluating model performance; obtaining key frames or fragments of a video stream and then using a large model to identify the result R0, reviewers regularly review, and output if abnormal, and then train the large model after accumulating certain results. The system includes modules such as data collection, model training, detection data acquisition, data block, abnormal detection, review and model optimization. The present invention improves detection efficiency and accuracy, reduces manual intervention, and effectively solves the problems of low video multi-channel detection performance, cumbersome threshold setting and low detection accuracy in the prior art, and is suitable for various security monitoring scenarios.

The invention relates to the field of intelligent monitoring, in particular to a power failure intelligent monitoring method and system for a power system, and the system comprises a plurality of collection modules which are used for transmitting real-time voltage values and collecting minute-level high-frequency voltage collection data, a receiving module which is used for receiving the minute-level high-frequency voltage collection data, carrying out the pre-learning, generating corresponding pre-learning data, and transmitting the pre-learning data to a server. The learning module is used for selecting a plurality of index characteristics for learning and generating a corresponding voltage curve graph, and the processing module is used for receiving the voltage curve graph, judging whether the power system is powered off or not according to whether a breakpoint occurs in the voltage curve graph, and sending power failure information to a power supply bureau and repairing the power system if the power system is powered off. Intelligent monitoring and quick response of power failure of the power system are achieved, the influence of power failure on users is reduced in an automatic mode, the reliability and operation efficiency of the power system are improved, and a power company is helped to better monitor and maintain stable operation of a power grid.

The application discloses a tunnel construction process automatic monitoring method, and belongs to the technical field of tunnel engineering construction monitoring. The method comprises the following steps: step 1, automatic monitoring equipment is arranged at key positions of a tunnel opening area, an advanced support section, an excavation face, an initial support structure, a waterproof layer construction area and a secondary lining structure; step 2, each automatic monitoring equipment is started, and monitoring data is collected at a preset sampling frequency; step 3, after receiving the monitoring data, a central monitoring platform uses a big data analysis algorithm to deeply process the monitoring data; and step 4, the central monitoring platform feeds back monitoring results and early warning information after analysis to a tunnel construction control system in real time. The application realizes real-time data acquisition and analysis through 5G technology, especially the UWB positioning system collects data once per second, realizes instant acquisition and analysis of monitoring data, and compared with traditional manual monitoring, the data update frequency is improved by tens of times, and abnormal conditions in the construction process can be found in time.

This application relates to the field of temperature control equipment technology, specifically a coolant flow regulation and leak prevention device for semiconductor temperature control equipment. The device utilizes a liquid pump in a coolant regulation component to circulate coolant in cooling pipes, which connect the coolant regulation component and the semiconductor manufacturing equipment. Several sets of cooling pipes are equipped with flow meters and flow regulation devices, and the cooling pipes run through the semiconductor manufacturing equipment. The coolant regulation component includes a liquid pump and a variable frequency refrigeration compressor, both connected to a main controller. The leak prevention component includes several sets of leakage sensors corresponding to the cooling pipes and a first solenoid valve located on the cooling pipe at the inlet of the semiconductor manufacturing equipment. Each leakage sensor is externally connected to an alarm and a user controller, which is signal-connected to the main controller. This application enables real-time monitoring of the fluid state in the cooling pipes, ensuring the stability and reliability of the liquid supply during semiconductor manufacturing, thereby improving manufacturing efficiency and product quality.

The invention discloses an equipment management method and a communication device, and relates to the technical field of communication, and the method comprises the steps: carrying out the omnibearing and real-time monitoring of a plurality of pieces of equipment through employing a monitoring technology, and precisely obtaining the operation state data of each piece of equipment; classifying the equipment by using an intelligent algorithm according to the acquired running state data; and adaptive management strategies are adopted for different types of equipment. Omnibearing real-time monitoring is achieved through a high-precision sensor, the operation state of equipment is accurately mastered, the equipment is classified through an intelligent algorithm, management strategies are customized for different types of equipment, stable operation of normal equipment is ensured, potential fault equipment is prevented in advance, the fault equipment is rapidly repaired, and personalized information services are provided for a communication device. Related personnel can conveniently grasp equipment conditions at any time, data accuracy is guaranteed through the self-diagnosis and self-calibration functions of the sensors, integrated intelligent management is achieved through cooperative work of the strategy execution modules, and the equipment management efficiency, accuracy and intelligent level are improved.

This invention discloses a structural truss stress detection method based on an automated monitoring system. The method includes: receiving and executing acquisition commands from a data center using a sensor module; acquiring stress data at key nodes and connections of the structural truss in a photovoltaic system to obtain stress data acquisition results; and uploading the stress data acquisition results to the data center via a transmission module. The method also involves acquiring photovoltaic field data from the photovoltaic system using acquisition equipment in the transmission module and uploading this data to the data center; storing the stress data acquisition results and the photovoltaic field data in the data center's database; and fusing and analyzing the stress data acquisition results and the photovoltaic field data using a computer device in a control module to obtain analysis results. This invention enables multi-channel remote real-time monitoring using an automated monitoring system, effectively monitoring structural status and providing timely early warnings.

This invention relates to the field of medical technology, specifically to a method for monitoring anesthesia depth based on a neural network model. It includes the following steps: collecting physiological indicator data of patients under different degrees of anesthesia; preprocessing the physiological indicator data to obtain interference-free physiological indicator data; and transmitting the processed physiological indicator data to a data management system; constructing a neural network model; inputting the physiological indicator data into the neural network model through the data management system; and training the neural network model. This invention, by collecting physiological indicator data of patients under different degrees of anesthesia to establish a training dataset, and training the neural network model, enables the neural network to accurately predict the patient's anesthesia depth. This method of collecting and processing the training dataset provides sufficient data samples, allowing the neural network model to be trained on diverse data, thus improving the model's generalization ability.

This application discloses a battery type determination system and method based on weight loss curve modeling, relating to the field of battery type determination technology. The system includes a first acquisition module for acquiring real-time weight values ​​of the battery under test at fixed intervals 'a'; a curve fitting module for constructing a weight loss fitting curve for the battery under test using a fitting method; a second acquisition module for determining the liquid substance determination value of the battery under test based on weight loss characteristic values; a judgment module for determining whether to compensate the liquid substance determination value based on test confidence level; a compensation module for determining the compensation coefficient of the liquid substance determination value and obtaining the compensated liquid substance determination value; and a battery type determination module for determining the battery type of the battery under test. This application effectively overcomes the drawbacks of existing methods that rely on simplified processing based on the difference between initial and final mass.

The invention discloses a static therapy infusion nursing device with automatic detection and early warning functions, and relates to the technical field of medical treatment. The device comprises a first infusion tube, a drip cup fixedly penetrates through one end of the first infusion tube, and a second infusion tube fixedly penetrates through one end of the drip cup and the first infusion tube; the first infusion tube fixedly penetrates through the second infusion tube through the drip cup, the first infusion tube and the second infusion tube are made of hose materials, and the drip cup is made of high-performance polyolefin materials. Through mutual cooperation of the extrusion force of the extrusion plate and components such as a fixed long plate, a fixed square plate and a detection alarm in the alarm device, automatic detection of the infusion process is realized, timely discovery of abnormal conditions is facilitated, the treatment effect and safety of a patient are improved, better treatment experience is provided, and the medical safety of the patient is improved. The stability and durability of the device are enhanced, the treatment effect is improved, and the safety of a patient is ensured.

This application provides a control method, device, smart glasses, medium, and program product for smart glasses. The control method includes: periodically acquiring eye-tracking images of the wearer according to a default cycle using an eye-tracking device during the wearing of the smart glasses; determining the wearer's eye usage data based on the eye-tracking images; adjusting the acquisition cycle of the eye-tracking images based on the eye usage data; and providing eye health reminders. By combining real-time eye usage information with eye health reminders, it is beneficial to improve the eye habits of smart glasses wearers and enhance eye protection. Simultaneously, by dynamically adjusting the acquisition cycle of the eye-tracking images based on eye usage information, eye-tracking image acquisition can be performed at a lower frequency when eye usage is healthy, thereby reducing the power consumption of eye monitoring.

This utility model discloses a prefabricated modular permeable well system, including a prefabricated well casing, a well ring, a well cover base, a well cover, an anomaly monitoring module, and several permeable bricks. The well ring is located at the upper opening of the well casing, and the well cover base is located at the upper opening of the well ring. The well cover is fitted onto the well cover base, and several permeable bricks are laid around the outer circumference of the well cover base. A permeable mortar layer is laid at the bottom of the permeable bricks, and the permeable mortar layer is laid around the outer circumference of the well ring. Several permeable through-tubes are arranged at circumferential intervals around the well ring, and the permeable through-tubes pass through the side wall of the well ring. The anomaly monitoring module includes a fiber optic grating sensor and an edge computing terminal. The fiber optic grating sensor is embedded in the well cover and is used to monitor the displacement and pressure data of the well cover in real time. The edge computing terminal is used to process the data collected by the fiber optic grating sensor. This utility model is easy to transport, replace and maintain. It can monitor the status of manhole covers in real time and detect abnormalities in a timely manner. It can also improve water permeability and effectively solve the problem of road water accumulation.

The present application provides a tool life management system and method. The system includes: a tool information acquisition module, the tool information acquisition module is connected to a machine tool, and is used to obtain tool information of the machine tool, and the tool information includes the length of the tool and the number of tool processing times; a statistical module, the statistical module is communicatively connected to the tool information acquisition module, and is used to count the tool information and generate tool statistical information; a control module, the control module is connected to the statistical module and the machine tool, and the control module is used to control the machine tool according to the tool statistical information. The system can obtain the remaining life of the tool according to the machine tool parameters, detect the abnormality of the tool in time, improve the product quality of the processed workpiece, reduce downtime, and improve production efficiency.

The invention discloses a data monitoring method and device, equipment and a medium, and the method comprises the steps: collecting the operation state data of each piece of monitored equipment according to a preset data collection mode corresponding to each piece of monitored equipment; each monitored device comprises a network device, a storage device, a server device, a middleware database, a big data cluster and a container cluster; acquiring basic environment data of each monitored device according to the environment data acquisition method corresponding to each monitored device; and carrying out data source integration on the basic environment data and the operation state data corresponding to each monitored device to obtain monitoring fusion data, and carrying out visual display on the monitoring fusion data. According to the invention, intelligent operation and maintenance monitoring of the monitored equipment of the cloud platform can be realized, so that the abnormity of the working state of the monitored equipment can be found in time, an administrator is helped to make a response and process more quickly, and the stability and safety of the system are improved.

The utility model relates to the technical field of purification devices, in particular to a cell supernatant exosome purification device which comprises a machine body, a control panel is fixedly connected to the upper surface of the machine body, a cabin door is connected to the inner wall of the machine body in a sliding mode, a horizontal rotor is installed on the inner wall of the machine body, and an observation device is arranged on the surface of the machine body. The observation device comprises a circular groove, the circular groove is formed in the inner wall of the machine body, a sliding block is slidably connected to the inner wall of the circular groove, a fixing plate is fixedly connected to the surface of the sliding block, a lens is fixedly connected to the surface of the fixing plate, and a limiting rod slidably penetrates through the surface of the fixing plate; and one end of the limiting rod is fixedly connected with a pull ring. According to the utility model, the problems that a worker needs to wait for a few minutes to start equipment until the reagent tube is in a static state, and the waiting mode is inconvenient for the worker to observe whether the reagent tube is in the static state or not, so that the working efficiency is reduced are solved.