1270 results about "Signal response" patented technology

The invention discloses an online course learning management method and system based on a knowledge graph, and the method comprises the steps: S1, analyzing course data, extracting knowledge points and an association relationship, and generating an initial knowledge graph signal containing knowledge point nodes and association edges; s2, collecting user interaction behavior data and extracting behavior features to generate behavior feature vector signals associated with knowledge point nodes; s3, detecting an abnormal learning mode, triggering a knowledge graph weight updating signal, and dynamically adjusting the associated edge weight; s4, updating the signal according to the initial knowledge graph signal and the knowledge graph weight; and S5, responding to the path optimization signal, and generating an interface sorting adjustment signal and a content push signal. According to the air quality intelligent monitoring system based on sensing data feedback, the problem that a traditional online course management system is single in data acquisition dimension and static and solidified in knowledge dependency relationship can be solved.

The invention relates to the technical field of grinding wheel monitoring, in particular to a centerless grinding machine full-life-cycle grinding wheel state monitoring system and method.According to the centerless grinding machine full-life-cycle grinding wheel state monitoring system and method, through combined difference extraction of a main shaft current mean value fluctuation ratio and a power gradient continuous variation value and assisted by transverse comparison of periodic response intervals, effective recognition of time period boundaries of working condition states is achieved; according to the method, operation stage division does not depend on static threshold judgment any more, a track trend is established through linkage judgment of an amplitude kick point and a slope extreme value, a dynamic evolution path of signal response is clearer, the identification resolution of abnormal changes and local deviation trends is improved, response synchronous identification of parameter state changes is achieved, and the identification accuracy is improved. In multi-signal collaborative analysis, directivity comparison between a temperature rise mutation fragment and a current residual error response is carried out, so that the consistency analysis capability of response logic between different monitoring paths is enhanced, and the real-time performance, stability and anti-interference capability of state identification are improved.

A wearable device configured to monitor physiological parameters of a wearer can include: a physiological parameter measurement sensor configured to monitor a plurality of physiological parameters; a hardware processor; a display in communication with the processor; and a band configured to secure the physiological parameter measurement sensor on a wrist of the wearer. In some implementations, the hardware processor is configured to: obtain a first plurality of signals from the physiological parameter measurement sensor when the band is secured on the wrist at a first tightness; determine a signal quality responsive to the first plurality of signals; and output an indication on the display to adjust tightness of the band with respect to the wrist from the first tightness to a second tightness based on the determined signal quality.

The invention discloses a relay state prediction and fault early warning method and system based on deep learning, and the method comprises the steps: S1, building a constraint condition of a generative adversarial network based on a relay physical model, and forming an enhanced fault waveform signal according with a physical rule through adversarial training; s2, receiving a real-time current and voltage signal and a mechanical vibration signal, and extracting an electric signal feature vector by using a time sequence convolutional network; s3, inputting the combined feature tensor into the lightweight assessment model, and outputting a health degree scoring signal; s4, responding to the meta-learning activation instruction, loading historical data of equipment to construct a parameter optimization set, performing online fine tuning on the early warning model based on a meta-learning framework, and generating a fault determination parameter; and S5, analyzing real-time signal characteristics according to the fine-tuned judgment parameters, and outputting graded early warning signals to a monitoring terminal. According to the method, the problems of early state prediction and accurate early warning of the relay under small sample fault data can be solved.

The invention provides a marine engine lubricating oil system fault diagnosis method and system based on transfer learning from a simulation domain to a real domain, and the method comprises the steps: carrying out the fault simulation of different working conditions based on a built marine engine lubricating oil system simulation model, and obtaining a simulation fault signal response; acquiring real domain fault data of different working conditions of an engine lubricating oil system based on an engine experiment platform; a feature fusion structure based on an encoder-decoder is adopted to obtain simulation domain fault data; an engine lubricating oil system fault diagnosis model based on data migration and algorithm migration dual migration learning is obtained; and based on the engine lubricating oil fault diagnosis model, performing real-time fault diagnosis on the marine engine lubricating oil system to obtain a diagnosis result. According to the method, transfer learning from simulation domain fault features to real domain fault features is realized, so that the problems of high construction cost and insufficient generalization performance of a diagnosis model are solved.

The invention relates to the technical field of water quality pollution detection, in particular to a water quality pollution rapid detection method driven by a quantum sensing technology. A quantum sensor array is deployed in a water area to be detected, and quantum signal response data of the water area is collected; constructing a pollutant quantum recognition model, and inputting quantum signal response data into the model to obtain an initial predicted value of pollutant concentration; generating an initial detection parameter of the quantum detection instrument based on the initial predicted value, executing primary pollution detection by the instrument according to the parameter, and collecting primary deviation data of an actual detection value and an expected detection value; determining a detection error according to the deviation data, further correcting the initial detection parameter, and generating an optimized detection parameter; and finally, the instrument performs secondary pollution detection based on the optimized detection parameters. According to the method, complex water sample pretreatment is not needed, water quality pollution detection can be rapidly and accurately completed, detection requirements of different water areas are met, and the detection efficiency and accuracy are improved.

The invention discloses an electrical stimulation type nerve regeneration method based on calcium signal regulation and control, and relates to the technical field of electrical stimulation type nerve regeneration, and the method comprises the following steps: based on a Schwann cell population calcium signal response feature set, identifying whether the calcium ion concentration is in a microliter stage which breaks through a lowest activation threshold and does not reach a stable state; judging whether the target nervous tissue is in a calcium signal activation critical state or not based on the behavior mode change of the Schwann cell population; based on the judgment result of the calcium signal activation critical state, an electrical stimulation adjustment control instruction is generated in real time in combination with the calcium ion concentration fluctuation trend and Schwann cell population response characteristics, and the calcium ion concentration stability is optimized and the activation state is maintained by adjusting the electrical stimulation intensity, the electrical stimulation pulse width, the electrical stimulation waveform type and the electrical stimulation application time sequence. According to the method, the problem that a calcium signal is difficult to recognize and dynamically optimize in a microliter stage is solved, and precise maintenance of Schwann cell activation and improvement of nerve regeneration efficiency are realized.

The invention discloses a brain deep nerve stimulation method and system based on adaptive adjustment, and relates to the technical field of brain deep nerve regulation, and the method comprises the steps: collecting a local field potential signal of a brain deep target region of a target patient, and extracting a beta frequency band power spectrum density and a gamma frequency band phase synchronization index as neural activity characteristic parameters; determining an individual baseline value and a preset threshold value based on historical data, and outputting a stimulation adjustment trigger signal when the beta frequency band power spectral density exceeds the individual baseline value and the gamma frequency band phase synchronization index is lower than the preset threshold value; in response to the trigger signal, calculating an optimal stimulation parameter combination through a gradient descent optimization algorithm and executing nerve regulation; and monitoring the signal change after regulation and control, calculating a relative change rate and updating a threshold value. Through a two-parameter joint judgment mechanism and a threshold updating strategy, individualized adaptive adjustment of stimulation parameters is realized, and the stimulation accuracy and the treatment effect are improved.

The invention relates to the technical field of intelligent illumination, and discloses an intelligent illumination explosion-proof single lamp controller optimization scheduling method and system, and the method comprises the steps: firstly obtaining the deployment position of a controller, determining a target illumination region, collecting ambient light data to construct an illumination distribution diagram, and recognizing a distribution control link; monitoring real-time energy consumption of a link, analyzing load characteristics and calculating an optimal dimming coefficient; acquiring a signal response frequency band based on the dimming coefficient, fitting to generate a dimming response curve, identifying a defect response section and calculating a harmonic distortion rate; illumination compensation is carried out according to the harmonic distortion rate, scheduling grouping is carried out after a compensation threshold value is determined, high-load nodes are identified, and power is corrected; and finally, acquiring the temperature change gradient of the lamp according to the load correction parameter, generating a regulation and control instruction, and formulating an optimal scheduling strategy. According to the invention, the scheduling optimization of the explosion-proof single lamp can be improved.

The invention relates to the technical field of operation and maintenance management, in particular to a medical equipment operation and maintenance management system based on information mining analysis. According to the method, accurate screening of data abnormal features is introduced, so that the evaluation of the equipment operation state is more refined. According to the method, abnormal data can be effectively identified based on the mean offset of the data measured by the blood oxygen sensor, and the accuracy of equipment state evaluation is ensured in combination with the distribution trend of measurement errors. The influence of environmental factors on the equipment performance is deeply excavated, the dynamic change trend of the equipment performance under different environmental conditions can be identified by utilizing the correlation calculation of the environmental temperature change and the power consumption offset, and the sensitivity to the influence of external factors is improved. The evaluation mode of the operation state is more comprehensive, the subtle change trend of the equipment operation state can be accurately described through the collaborative analysis of the measured frequency fluctuation amplitude and the signal response time, and the accuracy of fault prediction is improved.

The invention relates to an unmanned aerial vehicle inspection method and system based on an overhead transmission line, and the method comprises the steps: S1, generating an unmanned aerial vehicle three-dimensional space coordinate signal, and outputting a position correction signal based on a tower topology database; s2, in response to the position correction signal, controlling a multispectral sensing module to synchronously acquire a visible light image signal, an infrared temperature signal and a laser radar point cloud signal of the line; s3, inputting the visible light image signal into a defect identification model to generate a first defect feature signal; s4, fusing the first defect characteristic signal and the second defect characteristic signal to form a cross-modal diagnosis signal, and triggering a defect classification decision signal; and S5, classifying decision signals and cross-modal diagnosis signals according to defects. According to the air quality intelligent monitoring method and system based on sensing data feedback, the problems of inaccuracy in routing inspection positioning, defect missing detection and insufficient endurance in a complex environment can be solved.

The invention belongs to the technical field of pressure sensors, and particularly relates to a wireless passive pressure sensor for detecting bolt pretightening force, which comprises a pressure-sensitive capacitor and an outer ring encapsulation ring, the voltage-sensitive capacitor comprises an inner ring basin cavity, and an upper insulation pad, an upper polar plate, an elastic cushion layer, a lower polar plate and a lower insulation pad which are sequentially arranged in the inner ring basin cavity from top to bottom, the bottom of the inner ring pelvic cavity, the upper insulating pad, the upper polar plate, the elastic cushion layer, the lower polar plate and the lower insulating pad are provided with concentric holes to form a central through hole of the voltage-sensitive capacitor; the outer ring potting ring wraps the outer ring of the inner ring basin cavity, and a circuit and an antenna are arranged in the outer ring potting ring; the circuit is a frequency conversion circuit which is connected with the upper polar plate and the lower polar plate; and the circuit is also connected with the antenna. The sensor realizes wireless passive real-time monitoring, is convenient to install, does not need direct current power supply, does not have a signal processing unit inside, only transmits frequency signals, and is high in response speed.

The invention discloses a cross-channel marketing automation method and system based on real-time behavior triggering. The method comprises the following steps: capturing a user behavior event flow in real time through a front-end acquisition unit; performing real-time mode matching on the event stream by utilizing a complex event processing engine, and generating a marketing trigger signal when a preset rule is matched; dynamically selecting an optimal channel for the user based on a real-time scoring model in response to the signal; the marketing content is sent to the selected channel through the unified execution module; and finally, tracking user feedback and updating model parameters and user preferences in real time to form closed-loop optimization. The corresponding system comprises a front-end data acquisition module, a streaming event processing module, a real-time intelligent decision-making module, a multi-channel execution module and a closed-loop optimization module which are used for implementing the steps. According to the method, millisecond-level intention perception, cost and experience optimal channel intelligent decision and data-driven adaptive optimization closed loop are realized, and the problems of delayed response, extensive channel and lack of self-adaption of traditional marketing are solved.

The invention relates to the technical field of debugging systems, in particular to an adaptive debugging system and method for touch screen FW parameters, and the system comprises a signal acquisition module, a trend triggering module, a temperature compensation calculation module, a window generation module and a parameter output module. According to the invention, the edge of the driving voltage is carefully collected, the sliding difference algorithm is introduced to filter out high-frequency noise, meanwhile, real-time sampling of environment temperature and baseline capacitance adjustment are combined, the influence of external variables on signals can be dynamically corrected, and accurate judgment of capacitance fluctuation is improved by utilizing periodic delay deviation and regression trend analysis. By means of main frequency feature extraction and zero crossing point sudden change detection, threshold setting can be refined, self-adaptive window expansion can be achieved, touch signal response is kept sensitive and consistent all the time, adjustment and optimization can still be automatically completed even under the condition that the temperature changes frequently or signal interference is complex, parameter drift and debugging failure are effectively prevented, and user experience is improved. And the parameter automatic matching efficiency and the finished product consistency in batch production are improved.

The invention relates to the technical field of medical instruments, and discloses an implantable neural electrode for long-term electrophysiological signal monitoring and a preparation method and application thereof. The neural electrode comprises an upper hydrogel insulation packaging layer, a lower hydrogel insulation packaging layer, an electrode site, a connecting line and a bonding pad, wherein the electrode site, the connecting line and the bonding pad are arranged between the upper hydrogel insulation packaging layer and the lower hydrogel insulation packaging layer, and the electrode site and the bonding pad are connected through the connecting line. The electrode sites, the connecting lines and the bonding pads are made of conductive hydrogel; the upper hydrogel insulation packaging layer and the lower hydrogel insulation packaging layer are made of insulation polymers and hydrogel. The insulating polymer is a plasma surface-modified insulating polymer. The preparation method of the neural electrode is simple and efficient, biotoxic materials are not introduced in the preparation process, good biocompatibility is achieved, continuous monitoring in a living body can be achieved for one year, important application value is achieved for studying signal response and neural circuits of all brain regions, and a beneficial tool is provided for long-term in-vivo monitoring.

A method for validating operation of a driver integrated circuit includes providing a signal using an output node. The signal is provided using multiple set points in response to a change in state of an input signal. Each set point corresponds to a different phase of a multi-phase transition of the signal. The method includes providing a timer value at an end of a phase of the multi-phase transition and determining whether the signal is in a target signal range of the phase based on the timer value at the end of the phase, a predetermined value defining the target signal range of the phase, and a predetermined time limit for the phase. A current through the output node may be provided using the multiple set points, and a voltage on the output node may have the multi-phase transition.

The invention relates to the technical field of organic material detection, in particular to an imine molecular sensor with a five-detection function, two-component gel as well as a preparation method and application of the imine molecular sensor. The imine molecular sensor has three signal responses of fluorescence on-off, ultraviolet absorption and color change to Fe < 3 + >, Co < 2 + > and Ni < 2 + > in a solution state, and has ultraviolet absorption and fluorescence on-off dual-detection performance to acid and alkali changes; the imine molecular sensor and cholesteryl half ester can form two-component gel through a heating-low-temperature ultrasonic cooling method; after Fe < 3 + >, Co < 2 + >, Ni < 2 + >, NaOH and HCl are respectively added, the orange of the gel becomes milky white, reddish brown, transparent red, milky white and milky white under sunlight, and the fluorescence of the orange of the gel disappears under an ultraviolet lamp, so that the rapid and sensitive detection of Fe < 3 + >, Co < 2 + >, Ni < 2 + >, acid and alkali under two states of the imine molecular solution and the gel is realized. The imine molecular sensor provided by the invention has the advantages of mild synthesis conditions, simple preparation and the like, and creates favorable conditions for popularization and application of the imine molecular sensor.

The invention discloses a transformer area phase identification method and system based on non-contact voltage measurement. The method comprises the following steps: acquiring voltage data of each monitoring node on a power line of target power distribution network transformer area power transmission equipment; performing intelligent judgment on the voltage data, and generating a corresponding high-frequency noise scene signal; in response to the high-frequency noise scene signal, a monitoring result of the target power distribution network area power transmission equipment is obtained in the process of processing the voltage data based on a Kalman filtering algorithm, the processing process is configured to obtain a first prediction result corresponding to each monitoring node based on a state prediction equation, and the first prediction result is configured to obtain a second prediction result corresponding to each monitoring node; inputting a fusion analysis result of a measurement noise matrix determined by a Bayesian fusion algorithm for each first prediction result and a feature extraction result of the corresponding voltage data into an observation update equation; and carrying out transformer area phase identification on the target power distribution network transformer area power transmission equipment based on a monitoring result so as to realize accurate detection of weak signals.

The invention relates to the technical field of circuit breaker switch monitoring, and provides a method for monitoring the position state of a circuit breaker switch based on a video recognition technology, and the method comprises the steps: collecting a real-time image of a circuit breaker through a camera device, judging the physical state of the circuit breaker, and determining a first judgment result; acquiring real-time data of the relay protection device, recording the operation state of the circuit breaker, and determining a second judgment result; inputting the first judgment result and the second judgment result into a preset signal response device to generate a corresponding response action; wherein the response action comprises an opening action, a fault action and a closing action.

The invention discloses an electronic component quality control method and system, and relates to the technical field of transistor performance quality control. The quality control method for the electronic component comprises the following steps: evaluating transistor switch abnormity; switching speed delay regulation and control; and evaluating the input signal response control accuracy. Transistor switching abnormality evaluation is carried out in the transistor switching process, then whether switching speed delay optimization is carried out or not is judged based on a quantization result, if switching speed delay optimization is carried out, switching speed delay regulation and control are carried out, and if switching speed delay optimization is not carried out, input signal response control accuracy evaluation is carried out. And finally, judging whether to carry out input signal response control optimization or not based on a quantification result of the input signal response control accuracy evaluation, thereby achieving the effect of improving the response control sufficiency of the transistor on the input signal in the switching process. The problem that the switch response difference is not fully considered in the response control process of a transistor to an input signal in the prior art is solved.

The invention relates to the field of acupuncture teaching simulation, in particular to an acupuncture teaching simulation system and method. The method comprises the steps that based on acupuncture operation position data in historical stages, acupuncture point coordinates in acupuncture operation in all the stages are corrected; further calculating a positioning accuracy evaluation value of each stage based on the acquired acupuncture operation data; calculating the stimulation intensity of each acupuncture operation in each stage based on acupuncture operation data, and further calculating the comprehensive biological signal response in each stage; calculating a learning effect quantized value of each stage by using a learning effect evaluation algorithm based on the positioning accuracy evaluation value of each stage and the comprehensive biological signal response of each stage; and calculating the difficulty of the next stage based on the learning effect quantized value of each stage. The problems that in traditional acupuncture teaching, a standard acupuncture point model generally cannot adapt to individual differences of all students, each acupuncture operation of the students is difficult to be evaluated immediately and accurately, and the difficulty cannot be dynamically adjusted are solved.

The present disclosure relates to an electronic device, a method, and a computer program product for beam management. Various embodiments for performing beam management in a wireless communication system are described. In one embodiment, an electronic device includes processing circuitry configured to transmit a pass-inductance integrated signal through a first plurality of transmit beams; receiving a first group of echo signals corresponding to the terminal equipment in response to the sending of the communication-inductance integrated signal; estimating the position of the terminal device based on the first group of echo signals; and sending a first notification to the terminal device, so that the terminal device can determine a first receiving beam matched with the base station.

The invention relates to the technical field of intelligent battery management, and discloses an intelligent battery hybrid parallel access system and a control method. According to the method, a battery pack is divided into a basic energy storage unit and a dynamic adjustment unit, a hybrid parallel access network is constructed based on a layered interaction architecture, unit voltage, loop current and temperature field distribution data are acquired through a multi-dimensional sensing module, feature extraction and weight fusion are performed by using a time sequence association processor, and a temperature field is obtained. And the input state decision module adjusts an access mode, and the two-way instruction analyzer executes mode switching. Meanwhile, real-time data and reference parameters are compared through a grading evaluation mechanism, after operation deviation is determined, an adjusting signal is transmitted through a feedback channel, an operation record is generated, and the response speed of the adjusting signal is in positive correlation with the deviation. The method comprises a hybrid architecture construction module, a multi-source data processing module and an operation deviation feedback module. According to the invention, efficient management and accurate control of the battery pack are realized, and the flexibility, stability and safety of the system are improved.

The invention relates to the technical field of electronics, in particular to a dynamic threat spectrum library construction method based on a gallium oxide solar blind antenna detection module. According to the method, through cooperative acquisition and analysis of a gallium oxide solar blind antenna detection module and a radio frequency signal, a low-altitude target is accurately positioned by utilizing the low-noise characteristic of solar blind ultraviolet detection, the signal response speed is effectively improved, the target positioning capability and speed in a complex environment are improved, and the target positioning accuracy is improved through protocol feature extraction and dynamic fingerprint construction. Identity recognition and behavior tracking of a threat source are achieved, a closed-loop optimization mechanism is formed, the system has the continuous self-adaptive active detection capability, and the protection level of an existing low-altitude defense system from passive defense to active early warning is effectively upgraded.

The invention discloses a fluorescent colorimetric sensor for detecting circulating tumor cells and a preparation method of the fluorescent colorimetric sensor. The preparation method comprises the following steps: S4, adding a prepared detection antibody modified with horse radish peroxidase and used for detecting the circulating tumor cells, and incubating; s5, adding a Tris buffer solution and a H2O2 solution, and incubating; s6, preparing an EuMOF nanoflower solution; and S7, adding the EuMOF nanoflower solution and 3, 3 ', 5, 5'-tetramethyl benzidine to react, detecting the fluorescence intensity in the presence of circulating tumor cells with different concentrations by using a luminoscope, detecting the ultraviolet absorbance value in the presence of circulating tumor cells with different concentrations by using a multifunctional microplate reader, and constructing a fluorescence intensity-concentration working curve and an ultraviolet absorbance value-concentration working curve. The method is used for qualitative and quantitative analysis and detection of the circulating tumor cells, realizes bimodal signal response to the circulating tumor cells, and has high sensitivity and simplicity and convenience in operation.

The invention discloses a power construction progress intelligent management method and system, and the method comprises the steps: carrying out the periodic cruise according to a preset height measurement position through an unmanned plane, and collecting a video stream of iron tower construction in real time; identifying the current construction height based on the video stream, comparing the current construction height with a preset height threshold value, judging that a construction progress node is reached when any threshold value is reached, and generating a trigger signal; responding to the signals to obtain coordinates of corresponding installation monitoring points, and controlling the unmanned aerial vehicle to collect videos at fixed points; component installation state analysis is carried out on the fixed-point video, and an abnormal alarm is generated when the feature conformity is lower than a threshold value; marking the timestamps of the video clips corresponding to the thresholds, and associatively storing the timestamps to a construction progress node; and generating a visual progress interface based on the association result. Through unmanned aerial vehicle cruise acquisition, video analysis and data association technologies, quantitative management of the construction progress, accurate detection of the installation quality, full-dimension tracing of the process and safety risk prevention and control are realized, and the construction efficiency and safety of the electric power iron tower are remarkably improved.

A method for determining an angle of arrival and / or a direction of arrival of an electromagnetic wave from a mobile device to a receiving unit, in particular a UWB receiver. The receiving unit includes at least two receiving antennas, For determining the angle of arrival and / or the direction of arrival, a phase difference of arrival between signal responses at the receiving antennas is ascertained. The phase difference of arrival is ascertained at such a location in the signal responses that is still situated in the signal responses prior to a particular midpoint of a first signal path.

A tool for movement sequence analysis utilizing printed circuits. The tool determines a workflow sequence based, at least in part, on one or more printed circuits within a printed organic component. The tool activates the workflow sequence utilizing applied external stimuli on the one or more printed circuits. Responsive to activating the workflow sequence, the tool analyzes a signal response from the one or more printed circuits. The tool generates one or more printing recommendations based, at least in part, on the signal response analysis.

The invention relates to the field of display, and discloses a short-circuit protection circuit, an array substrate, a display device and a short-circuit protection method.The short-circuit protection circuit is used for an OLED device and comprises the steps that an information sensing module obtains the actual working current of the OLED device and real-time parameters related to the working state of the OLED device; the dynamic expectation calculation module calculates the dynamic expectation working current n of the OLED device according to the real-time parameters and a preset OLED electrical characteristic model; the decision module synthesizes the actual current, the expected current and the current change rate / fluctuation amplitude to generate a risk judgment signal; and the response control module executes protection operation according to the judgment signal. According to the OLED short-circuit protection method, the accuracy, the sensitivity and the intelligent management level of OLED short-circuit protection are remarkably improved through the technology of dynamically calculating the expected current and carrying out decision making and parameter self-adaptive adjustment by fusing the actual current time sequence characteristics.

The invention relates to the technical field of electronic connector performance monitoring, in particular to a connector performance detection method, and aims to solve the problem that a method for realizing performance early warning through dynamic correlation analysis of vibration signals and contact resistance in the prior art is not suitable for an L-shaped pin connector without a sheath. According to the method, micro-strain signals and contact resistance signals are synchronously collected, analysis time periods are divided in combination with plugging events, the plastic deformation accumulation degree and signal response delay characteristics are quantitatively evaluated, performance degradation coefficients are generated through fusion, and trend analysis is carried out; the problem that the relevance between the mechanical deformation and the electrical performance cannot be quantitatively evaluated in the prior art is effectively solved, and the method has the advantages of realizing early warning, improving the monitoring accuracy and reducing the maintenance cost.