741 results about "Signal variation" patented technology

The invention relates to the technical field of communication engineering, and discloses a power line carrier and wireless dual-mode fusion optimized communication method, which comprises the following steps of: 1, acquiring signal quality, noise and delay data of a power line and a wireless link in real time, and constructing a prediction model by utilizing historical data; step 2, dynamically adjusting a judgment threshold value of link switching in real time based on the prediction model, and ensuring that switching is triggered only when the signal change exceeds a preset range; step 3, based on the dynamic threshold, combining multiple indexes of signal-to-noise ratio, delay, packet loss rate and network load; according to the method, the necessity of link switching can be more intelligently judged by dynamically adjusting the judgment threshold of link switching and adopting a fuzzy logic decision mechanism, frequent switching during tiny fluctuation of signals is avoided by dynamic threshold adjustment, and a fuzzy logic system integrates multiple factors, so that the decision is finer, and the reliability of link switching is improved. And unnecessary delay and resource waste are reduced, so that the stability of a communication system is improved.

The invention relates to the technical field of power system monitoring and control, and discloses a power grid oscillation monitoring system and method based on an intelligent sensor, and the system comprises an intelligent sensor module which is used for collecting the signal data of the operation of a power grid, is internally provided with a self-adaptive sampling mechanism, dynamically adjusts the sampling frequency to achieve the capturing of the signal change, and meanwhile, transmits the signal data to the intelligent sensor module; de-noising and preprocessing are carried out on the collected signal data, the processed signal data are transmitted to an edge calculation module, and high-quality input is provided for oscillation signal feature extraction; and the edge calculation module is used for receiving the preprocessed signal data from the intelligent sensor module. Through the intelligent sensor module, a self-adaptive sampling mechanism is combined with multi-mode signal acquisition, the rapid change characteristic of sampling frequency capture signals is dynamically adjusted, accurate capture of oscillation signals is ensured, the redundant calculation burden and energy consumption of the system can be reduced while the precision is ensured, and technical innovation is provided for real-time monitoring of a complex oscillation scene of a power grid.

The invention discloses a power line carrier communication fault detection system, and relates to the technical field of power line fault detection, the fault detection system comprises a data acquisition module, an abnormity analysis module, a fault diagnosis positioning module, a fault grading evaluation module, a response measure matching module and an alarm module, and the modules are in electric signal connection. According to the invention, the signal change on the power line is rapidly captured by monitoring the modulation signal after carrier demodulation on the power line, including the sending performance index and the electrical performance index, and the performance trend of the power system can be timely evaluated and the abnormal modulation signal can be timely detected by calculating the sending performance trend index and the electrical performance trend index. Key information is provided for fault positioning and grading, the accuracy and response speed of fault detection are greatly improved, the influence of faults on a power system is reduced, and the reliability of power supply is improved.

The invention relates to the technical field of power transmission line anomaly recognition, and particularly discloses a power transmission line anomaly recognition model construction method combined with edge calculation, which comprises the following steps of: gradually increasing electromagnetic interference intensity test, acquiring current and voltage signals in real time, and monitoring electric field intensity and signal change by combining a high-precision sensor; dynamically calculating an influence value of electromagnetic interference; recursively estimating the dynamic influence of the electromagnetic interference through a Kalman filter, accurately modeling the influence of the electromagnetic interference by combining the system state and measurement data updating, and realizing the real-time evaluation of the influence of the interference on the system by calculating an electromagnetic interference coefficient and an electromagnetic shielding efficiency expected deviation; according to the method, a spectral analysis and high-frequency current and voltage fluctuation feature extraction method is adopted, and accidental interference and system faults are effectively distinguished by calculating a spectral ratio; through multi-level data analysis and optimization, real fault signals and electromagnetic interference signals can be accurately distinguished, and false alarms and missing alarms are reduced.

The invention belongs to the field of power equipment monitoring, and discloses an electrical signal acquisition system based on intelligent dynamic sampling, which comprises a signal acquisition module, a signal conditioning module, an abrupt change detection module, an impedance calculation module and an upper computer, and is characterized in that the signal acquisition module comprises a first ADC module, a second ADC module, a first MCU module and a second MCU module. Short-circuit impedance real-time calculation and waveform abrupt change detection are adopted for cooperative judgment, and when equipment operates stably, the sampling rate of the system is kept low; when impedance changes or waveform changes suddenly, the sampling rate is improved automatically, important signal changes are recorded accurately, and waveform abrupt change detection is carried out by adopting an edge detection algorithm improved based on an FIR (Finite Impulse Response) filter. The system ensures the time sequence consistency of data under different sampling frequencies through multi-channel data synchronization and timestamp management, and meanwhile, smooth transition is performed by applying an interpolation algorithm during sampling switching, so that the continuity of a data sequence is ensured. The data redundancy is reduced; and the integrity of key information is ensured.

The invention relates to the technical field of industrial equipment management, in particular to an intelligent power equipment inspection system based on artificial intelligence, which comprises a fault mode generation module, a fault detection module, a fault classification module, an inspection feature optimization module and an anomaly prediction and evaluation module. According to the method, the comprehensiveness of equipment state sensing is optimized by collecting the multi-dimensional operation parameters of the power equipment and analyzing the signal amplitude distribution and frequency domain change, the potential fault features are accurately recognized by combining the dynamic feature range and the signal distribution deviation matching, the signal anomaly detection accuracy is improved, and the fault detection accuracy is improved. The method comprises the following steps: extracting differentiated characteristic values of current and temperature signals, optimizing fault type classification, improving the positioning capability of a problem root, dynamically extracting and matching a signal trend, generating an inspection parameter matrix, realizing global dynamic monitoring of an operation state, and predicting a model based on a signal change rate and a time node range. The real-time performance and precision of abnormal trend prediction are improved, and the reliability of equipment operation and maintenance is enhanced.

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 provides a wireless charging power-off protection method for detecting metal foreign matters based on signal change, which comprises the following steps: monitoring magnetic field change through a Hall effect sensor, detecting temperature abnormity in combination with a temperature sensor, carrying out real-time data processing by utilizing an embedded MCU, and automatically entering a calibration mode before charging each time; the method comprises the following steps: acquiring stable magnetic field distribution as a reference value, tracking magnetic field change by using a self-adaptive filter, continuously monitoring magnetic field intensity change in a charging process, comparing the magnetic field intensity change with the reference value, judging whether the magnetic field intensity change exceeds a normal range or not by setting a threshold value, immediately cutting off a power supply and giving an alarm to a user if foreign matters are detected, and after the user confirms that the foreign matters are removed, stopping charging. According to the method, the foreign matters can be accurately detected in different environments through dynamic threshold adjustment and feature optimization, so that the safety of wireless charging and the user experience are improved.

The invention discloses a bidirectional transceiver circuit with automatic direction and edge acceleration, which comprises a first transceiver and a second transceiver, and the two transceivers have the same structure and are in a symmetrical structure after being connected. The transmission direction of the bidirectional transceiver can be automatically identified and configured, a direction control signal is not needed, the bidirectional transceiver internally generates a pulse signal at the moment that an input signal changes to open strong driving output, the change of the output signal is accelerated, and the output driving capability and the transmission rate are improved; and meanwhile, an internal enable signal is generated to close strong driving output of an input side, so that input signals are prevented from being influenced.

The invention provides a non-intrusive diagnosis method for typical rotor faults of a synchronous phase modifier, and the method comprises the steps: carrying out finite element modeling and fault working condition setting, carrying out simulation to obtain magnetic field distribution data under each working condition, carrying out the extraction and feature analysis of stray magnetic field signals, extracting time domain and frequency domain signals of a stray magnetic field under healthy and various fault working conditions, and carrying out the diagnosis of the typical rotor faults of the synchronous phase modifier. Fundamental wave, odd-even harmonic components and signal change trends are compared and analyzed, stray magnetic field characteristics corresponding to faults are extracted and recognized, diagnosis criterion establishment and fault recognition are carried out, diagnosis criteria and threshold values of rotor turn-to-turn short circuit, dynamic eccentricity and shaft-diameter composite eccentricity faults are established according to the stray magnetic field characteristics, and the fault diagnosis accuracy is improved. And when the specific harmonic amplitude or change characteristic of the stray magnetic field signal exceeds the criterion threshold, determining the rotor fault of the corresponding type and degree. Equipment dismounting or structure reconstruction is not needed, the detection system is simple in structure, internal fault characteristics of the phase modifier can be reflected in real time, and high sensitivity and practicability are achieved.

The invention relates to the technical field of laser ranging, in particular to a laser ranging method and a laser ranging sensor, and the method comprises the steps: obtaining a laser pulse signal transmitted by the laser sensor and a received echo signal; obtaining a spectrogram of the echo signal, and extracting candidate peak points and peak intervals thereof; judging whether each candidate peak point is a peak point or not; converting the frequency domain signal in the peak interval of each peak point to obtain a characteristic echo signal; obtaining an interfered index of the characteristic echo signal corresponding to each peak point; obtaining a local signal change degree of each characteristic echo signal in each filtering window; obtaining an optimal filtering window by combining the endpoint difference of the peak interval between the peak points; and filtering the characteristic echo signal of each peak point, and calculating distance data according to the phase difference between the laser pulse signal and the filtered characteristic echo signal. The invention aims to improve the ranging precision and efficiency of the laser ranging sensor.

The invention discloses a transformer iron core vibration monitoring and fault diagnosis method based on voiceprint characteristics, and belongs to the technical field of power equipment monitoring and fault diagnosis, and the method comprises the steps: obtaining voiceprint signals of each monitoring point about the vibration of an iron core in a preset transformer, and collecting the voiceprint characteristics according to the voiceprint signals of different monitoring points, analyzing the change rule of each voiceprint signal; according to the change rule, distinguishing the change of the voiceprint signal according to light change and moderate change, and obtaining the operation state of the preset transformer under the condition of light change; the operation state comprises current parameters of a preset transformer; and giving a monitoring period according to the light change, and presetting a critical threshold value related to the vibration frequency change of the voiceprint signal in different monitoring periods. According to the invention, by monitoring and analyzing the voiceprint signal and combining the technical means of multiple monitoring points, dynamic monitoring and enhanced learning, early fault early warning and accurate diagnosis of the operation state of the transformer are realized, and the method has relatively high practicability and innovativeness.

The invention provides an LED lamp adaptive speed regulation heat dissipation method and system based on real-time junction temperature monitoring. The method comprises the following steps: S100, acquiring a PWM signal or an analog signal of an LED driving command signal in real time; s200, on the basis of the change of the driving instruction signal, feedforward prediction is carried out by using a dynamic thermal inertia mapping model, and a feedforward fan control quantity is generated; s300, LED junction temperature is monitored in real time through a forward voltage method, and feedback fan control quantity is generated through a feedback controller according to the deviation between the real-time junction temperature and the target junction temperature; and S400, synthesizing the feedforward control quantity and the feedback control quantity to generate a fan PWM control signal, outputting the fan PWM control signal to a fan driving circuit, and adjusting the rotating speed of the cooling fan. According to the method, driving signals and junction temperature information are processed in parallel, and feedforward and feedback control is combined, so that self-adaptive accurate regulation and control are realized, thermal load change is quickly responded, system lag is effectively inhibited, and LED heat dissipation performance is optimized.

The invention discloses an enhanced RTK (Real Time Kinematic) positioning method for blind compensation of a laser inertial navigation odometer, which belongs to the field of computer vision and comprises the following specific steps: I, calibrating an initial sensor and performing real-time data fusion; iI, predicting a motion state and carrying out real-time monitoring and evaluation on a GNSS signal; iII, switching a positioning mechanism according to the change condition of the GNSS signal; iV, optimizing a switching process and analyzing radar data in real time to establish an environment model; according to the invention, positioning schemes can be rapidly and accurately switched, positioning errors caused by reduction of signal quality are reduced, the problem of inaccurate positioning caused by unstable GNSS signals is reduced, the robustness and stability of the system in a complex environment are improved, the strain capacity of the whole positioning system is improved, and the positioning accuracy is improved. The positioning error caused by improper path selection is reduced, the strategy can be dynamically adjusted according to the environment change, the dependence on the GNSS signal is reduced, and the response speed and the calculation efficiency of the system are improved.

The invention relates to the technical field of frequency detection, in particular to a frequency measurement method and device based on Kalman filtering, electronic equipment and a storage medium, and the method comprises the steps: obtaining a posterior estimation value of frequency measurement data at a previous moment and an observation value at a current moment; calculating a prior estimation value at the current moment by using the posterior estimation value at the previous moment, calculating an observation error between the prior estimation value at the current moment and the observation value at the current moment, and judging whether the observation error is greater than a preset error threshold value or not; and if the observation error is greater than a preset error threshold value, updating the prior estimation value at the current moment by using a preset Kalman filter, and taking the updated prior estimation value at the current moment as an output value of the frequency measurement data at the current moment. Therefore, the problem that the frequency measurement requirements of complex signal processing, real-time monitoring and quick response to signal change are difficult to meet in the related technology is solved, accurate system state estimation can be provided, and the method has good real-time updating and signal processing capabilities.

The invention discloses a calculation method and system for multi-point detection of a gas nonmetal pipeline based on an active sound source, and relates to the technical field of pipeline monitoring and management, and the method comprises the following steps: 1, monitoring the change of a sound signal in the gas nonmetal pipeline according to the change of a transmitted laser signal through an optical fiber of a distributed acoustic assembly as a sensing medium, according to the invention, the optical fiber of the distributed acoustic assembly is used for monitoring the change of the acoustic signal in the gas non-metal pipeline, the frequency offset, intensity and delay change of the laser signal are converted into the frequency, amplitude intensity and sound wave source of the acoustic signal in a correlation manner, and the adaptive filter is used for dynamically updating the filter coefficient. A window function is adopted to carry out framing processing on sound signals, short-time Fourier transform is applied, real classification labels are distributed to the sound signals through a random forest algorithm, a triangulation positioning method is applied to determine space coordinates of the sound signals, and accurate monitoring and classification of the pipeline state are achieved.

The invention discloses a distribution box operation state monitoring method and system, and relates to the field of distribution boxes, and the system comprises an acquisition module which is used for collecting current and voltage signals of each loop in a distribution box, surface temperature distribution of a box body and opening and closing state signals of a cabinet door, and converting the collected analog signals into a digital signal sequence; the extraction module is used for receiving the digital signal sequence and extracting a signal fluctuation feature, a temperature field distribution feature and a state signal change feature to generate a three-dimensional feature set; the system can obtain loop electrical parameters, box body temperature and cabinet door state in real time, accurately analyze operation characteristics to deduce state trend, quickly position defective loop components and influence range in case of abnormity, scientifically evaluate health level, timely give an early warning, synchronously disconnect power supply of associated equipment in case of severity, effectively reduce fault shutdown, and improve work efficiency. The power utilization safety and the maintenance efficiency are improved, and stable operation of the distribution box is guaranteed.

The invention relates to the technical field of GNSS (Global Navigation Satellite System) testing, in particular to a real-time dynamic testing method for a navigation type GNSS receiver, which comprises the following steps of: collecting GNSS signal data, carrying out time window sample segmentation on a received GNSS signal, analyzing signal intensity fluctuation and loss events of each sample, recording geometric coverage of each segment, calculating the number of coverage points and generating fractal dimension data. According to the invention, by collecting and analyzing the signal samples in different time windows, the fluctuation and loss events of the signal intensity can be evaluated more accurately, and the instant identification capability of signal loss and interference is enhanced. Through fractal dimension calculation and difference analysis, abnormal changes in a signal mode are effectively identified, and the understanding of navigation accuracy in a complex signal environment is improved. Besides, the signal complexity is analyzed and combined with climate and geographical environment data, so that the attribution of the signal change is more accurate, and the adaptability of the receiver under different environment conditions is optimized.

The invention relates to the technical field of discharge detection, in particular to an optical fiber ultrasonic sensor for partial discharge detection and a detection method. The fundamental frequency is determined according to the peak multiple distribution degree and the uniform distribution condition of the frequencies of the sound wave signals, and the smooth sound wave signals are obtained; determining the change time of the optical fiber ultrasonic sensor through the distribution of local amplitudes, and determining the discharge starting time of the optical fiber ultrasonic sensor according to the change time distribution approximation condition; obtaining the accessibility of each optical fiber ultrasonic sensor through the amplitude change trend correlation degree; and determining the partial discharge position and the discharge time through the accessibility based on the three-point positioning in combination with the position of the optical fiber ultrasonic sensor and the discharge starting time. According to the method, the partial discharge receiving time is determined by smoothing the signals of the optical fiber ultrasonic sensors, the credible condition of each optical fiber ultrasonic sensor is determined through the signal change trend, and the positioning analysis process is adjusted to determine the more accurate partial discharge position and time.

The present invention relates to the technical field of industrial equipment management, specifically an intelligent power equipment inspection system based on artificial intelligence. The system includes: a fault mode generation module, a fault detection module, a fault classification module, an inspection feature optimization module, and an abnormal prediction and evaluation module. In the present invention, by collecting multi-dimensional operating parameters of power equipment, analyzing the signal amplitude distribution and frequency domain changes, the comprehensiveness of equipment status perception is optimized. Combining the dynamic feature range and signal distribution deviation matching, potential fault features are accurately identified, and the accuracy of signal anomaly detection is improved. By extracting the differential characteristic values of current and temperature signals, the fault type classification is optimized, and the positioning ability of the problem root cause is enhanced. Dynamically extracting and matching signal trends, generating an inspection parameter matrix, and realizing global dynamic monitoring of the operating state. Based on the prediction model of signal change rate and time node range, the real-time performance and accuracy of abnormal trend prediction are improved, and the reliability of equipment operation and maintenance is enhanced.

A power transmitter (101) provides power to a power receiver (105) via an inductive power transfer signal which is also used by the power receiver (105) for communication by load modulation. The power receiver (105) comprises a transmitter (509) arranged to transmit symbols in accordance with a first or second communication mode where the first mode modulates data symbols by a chip sequence from a set of sequences and the second communication mode does not. The power receiver (105) may transmit data symbols requesting a power transfer signal variation using a chip sequence from the set. A detector (515) may detect if the variation occurs, and if so a selector (513) selects the first communication mode and otherwise it selects the second communication mode. The approach may allow selection of an appropriate communication mode without requiring data to be transmitted from the power transmitter. The approach may provide improved backwards compatibility.

The invention discloses an instrument electric signal detection system, which comprises a signal acquisition module, a signal processing module, a data display module and a data storage library, and relates to the technical field of electric signal detection. According to the instrument electric signal detection system, the voltage waveform curve graph is established according to the converted digital signals, the change trend of the corresponding digital signals is determined according to the curve processing algorithm, a plurality of zero crossing points in the change process are searched, then curve segmentation operation is carried out with each zero crossing point as a node, and the segmented curves are covered. According to the method, the signal change period is determined, and the corresponding calculation period is compared with the set period of the output source, so that the electric signal detection efficiency is improved, meanwhile, the accuracy of a data result is verified, the detection operation can be quickly distinguished aiming at waveform change data, and actual application is facilitated.

The invention provides an electric blanket heating wire state judgment method and system, a medium and a product, and relates to the technical field of safety monitoring. In the method, a control processing unit firstly samples at a first preset frequency and calculates a signal change rate; and when the signal change rate value exceeds the standard rate threshold value, the control processing unit judges that the electric blanket is in a suspected heat accumulation state, and at the moment, the output power of the heating wire is controlled to be reduced to a preset duty ratio. Then, the control processing unit adopts a second preset frequency to collect signals and filter the signals, extracts signal values at the first moment and the second moment, and calculates the characteristic value of the thermal attenuation trend; and finally, the control processing unit realizes the distinguishing between the local wire twisting state and the folding state based on the deviation degree of the characteristic value and the standard thermal attenuation characteristic value. According to the method, the technical problem that the high-temperature cause cannot be distinguished only through the instantaneous temperature is relieved, and accurate recognition of the twisted wire fault and the folding working condition is achieved.

The invention relates to the technical field of power systems, in particular to an intelligent substation relay protection secondary circuit verification device. A time synchronization signal in the intelligent substation is received through the time synchronization time synchronization module, after a local clock is calibrated, synchronous connection between the verification device and external time is disconnected, the time of the device is maintained to be stable through the time synchronization high-precision time keeping module, and when a time synchronization signal interface is lacked, the time synchronization signal is provided through the time synchronization time service module; the switching value acquisition and recording module records signal changes of an intelligent terminal device and a primary device mechanism action contact, the detection devices establish data connection with the relay protection tester through the tester communication interaction module and perform communication interaction, and a communication network of the multiple detection devices and the relay protection tester is constructed. By simplifying the verification process and improving the test reliability, a more efficient solution is provided for the power industry, and safe operation and management of the intelligent substation are promoted.

The embodiment of the invention provides a chip, a communication method and a consumable box, and the chip is used for determining to start to execute instruction information when a clock signal is changed from a continuous first level signal to a first level signal and a second level signal which are alternated; receiving first type instruction information or second type instruction information sent by the image forming device; if the instruction information is the first type of instruction information, determining a target reference moment based on the received clock signal; if it is not detected that the clock signal is changed from the first level signal to the second level signal within a preset target duration after a target reference moment, it is determined that execution of the instruction information is ended; if the instruction information is the second type of instruction information, it is determined that execution of the instruction information is ended at the ending moment of the second type of instruction information, and the ending moment is determined by the content of the second type of instruction information. The accuracy of data communication is improved.

The present disclosure relates to a delay module for a CAN device. The delay module is configured to delay only a single signal change of an RXD signal, wherein the single signal change forms the end of an idle state. Use of the delay module allows a second RXD signal to be generated. The present disclosure further relates to a CAN device comprising two CAN controllers. Each of the two CAN controllers may be provided with one of the two RXD signals. The CAN device may further be configured to detect possible errors based on the decoded bits of the RXD signals. As a result, the CAN device can communicate error-free with both distantly located further CAN devices and closely located further CAN devices, while ensuring a high data rate. The present disclosure also relates to a method for the delay module.

The invention belongs to the technical field of nuclear magnetic resonance spectrums, and particularly relates to a preparation method of a responsive multi-component material and application of the responsive multi-component material in 129Xe / 1H dual-mode signal change. According to the method, the Fe3O4 (at) SiO2 nanoparticles are used as a precursor, KMnO4 is used as a raw material, the Fe3O4 (at) SiO2 (at) MnO2 nanoparticles are synthesized, and the synthesized nanoparticles are complete in morphology and uniform in size. A transverse relaxation rate 1 / T2 signal of protons of the multi-component material obtained by the strategy is quenched, a dissolved state signal of 129Xe is basically unchanged, but after the reaction with 10mM glutathione, the 1 / T2 signal is recovered, the dissolved state signal of 129Xe is obviously reduced, the change of a 129Xe / 1H double nuclear magnetic resonance signal is realized, and the change of the 129Xe / 1H double nuclear magnetic resonance signal is realized. And the method has certain significance for enriching the application of the hyperpolarized 129Xe magnetic resonance probe and the development of a multi-mode magnetic resonance imaging nano platform.

The invention provides an ultrasonic guided wave probability imaging method for structural damage in a temperature change environment, an improved U-Net neural network is constructed, input data of the improved U-Net neural network comprises an original guided wave signal and normalized temperature offset, and a model comprises a three-stage down-sampling module, a double-convolution layer and a three-stage up-sampling module. The attention mechanism module is connected behind the downsampling blocks of all levels and used for dynamically adjusting the feature weight, the representation capability of temperature features is enhanced, and the network can learn nonlinear mapping of temperature changes and signal changes. After model training data are obtained, filtering processing is carried out on original ultrasonic guided wave signals, normalized temperature deviation processing is carried out on temperature data, and the ultrasonic guided wave signals at the standard temperature are output through model prediction, so that the amplitude and phase interference of the temperature on ultrasonic guided waves is reduced, and the accuracy of ultrasonic guided wave detection is improved. And high-precision positioning of structural damage is realized in combination with a probability imaging technology. The method is small in data demand and few in execution steps, and the damage positioning efficiency is better than that of a traditional method.

The invention relates to an intelligent protocol configuration method for a Cat1 module. The method comprises the following steps: performing signal analysis on communication signal data to obtain an initial state sequence; performing multi-dimensional analysis on the signal change characteristics to obtain adaptive communication parameters; performing recursive analysis on the adaptive communication parameters to obtain a protocol configuration set; a configuration priority is obtained through calculation of the communication efficiency index; traversing the protocol parameter linked list to obtain a parameter sequence; analyzing and evaluating the parameter sequence to obtain effective configuration; performing mapping conversion through a protocol parameter mapping table to obtain a protocol instruction sequence; obtaining a protocol identifier according to the response feature; and executing the module configuration instruction and recording a configuration result. According to the invention, continuous acquisition and analysis of signal features are realized, the technical problem that a traditional single fixed window cannot give consideration to long-term trend and short-term fluctuation at the same time is solved, and standardized management and flexible adjustment of parameter configuration are realized.

The invention discloses an amplifying circuit for improving a common-mode rejection ratio, relates to the field of sensor analog front-end circuits, and aims to improve the common-mode rejection ratio of a circuit system by suppressing common-mode signal change and differential-mode signals caused by the common-mode signal change. A capacitive coupling structure and a chopping stabilizing circuit are combined, so that the problems of an instrument amplifier with a three-operational-amplifier structure are solved, firstly, the amplifier drives a passive network, and the power consumption is reduced; secondly, the AC capacitor is connected in series to isolate a common-mode signal, so that the CMRR of the circuit is improved; thirdly, the chopping stabilizing circuit modulates the offset voltage and the common-mode signal change voltage to high frequency, the offset voltage and the common-mode signal change voltage are filtered by a filter, the circuit gain is improved, and meanwhile, the CMRR is also improved; and fourthly, the problems of residual offset and output ripple caused by the chopper circuit are reduced through the DSL and the RRL, so that saturation of a post-stage circuit is avoided.