52 results about "Frequency drift" patented technology

This invention relates to the field of precision mechanical control technology, specifically to a method based on a magnetoelectric converter and linearity control. The method includes: acquiring raw magnetic induction data through a magnetoelectric converter; obtaining a three-dimensional magnetic field distribution through electromagnetic field spatial mapping and extracting the axial gradient vector field; constructing a virtual magnetic streamline model based on this to identify local disturbance regions where magnetic field distortion exceeds a threshold; performing multi-scale time-frequency analysis on the data in this region to separate high-frequency fluctuations caused by mechanical vibration and low-frequency drift components caused by thermal deformation; inputting the two components into a cross-coupled compensation decision network to generate high-frequency suppression commands and low-frequency compensation trajectories, which are then merged to form a comprehensive drive signal for compensation. This method can accurately locate the source of linearity disturbance and perform targeted decoupling control of errors from different physical sources, improving control accuracy and stability under complex operating conditions.

This invention discloses an AI-based spectral monitoring and early warning system and method for performance degradation of key power supply components, relating to the field of power supply component performance monitoring technology. The system includes the following steps: Under high-temperature, high-carrier excitation conditions, a phase-continuous mapping field characterizing nonlinear interactions is generated by establishing a time-frequency coherent baseline of multi-source signals and injecting micro-amplitude phase perturbations; a cross-scale energy differential inversion chain is constructed based on this mapping field to extract energy residuals and identify transient energy aggregations; a dynamic pseudo-peak constraint chain is formed through envelope self-reflection calibration; further, time-frequency drift correction and dynamic weight refeedback are performed to generate an adaptive health matrix; finally, the energy spectrum is topologicalized, and continuous monitoring and intelligent early warning of degradation risks are achieved based on topological perturbations. This invention achieves proactive identification and intelligent early warning of power supply component degradation by dynamically fusing energy and phase characteristics through time-frequency drift correction and the topological health matrix, thereby improving the accuracy of performance degradation monitoring for key power supply components.

This invention discloses a wireless, passive, and visualized cerebrospinal fluid drainage tube flow monitoring sensor, system, and fabrication method, belonging to the field of biomedical sensing and microelectromechanical systems (MEMS) technology. It includes a flexible substrate, an interdigital capacitor-open resonant ring structure disposed on the substrate surface, and a microchannel pressure conversion structure bonded to it; the microchannel corresponds vertically to the position of the interdigital capacitor. The pressure generated by the cerebrospinal fluid flow drives the displacement of the liquid metal, modulating the equivalent dielectric constant of the interdigital capacitor and causing a resonant frequency shift. The frequency drift is wirelessly read by an external device, and the flow rate is calculated using an algorithm, achieving passive wireless continuous monitoring. This invention, employing the aforementioned sensor, system, and fabrication method, solves the problems of high infection risk, low accuracy, and inability to continuously monitor existing drainage monitoring methods that rely on manual observation or wired sensors. It has the advantages of high sensitivity, flexible integration, and good safety.

The application provides an electronic watch running time precision regulation system, and relates to the technical field of data processing.The system is used for collecting temperature values, voltage values and cumulative running time, counting the number of pulses output by a crystal oscillator in a unit time, obtaining state data and basic frequency data, calculating frequency offset values in different periods, performing window sliding, calculating drift trend values in different windows, calculating the difference between different states between adjacent periods, obtaining state change values, combining and analyzing the state change values with a frequency drift trend sequence, obtaining a state response coefficient set, identifying effective disturbance components in state change vectors of different periods, calculating pulse compensation values in different periods, obtaining pulse compensation data, correcting timing pulses, obtaining a pulse output sequence, and updating the time of the electronic watch according to the pulse output sequence.The application can regulate the pulse signal of the electronic watch and ensure the precision of running time.

The application discloses a Helicobacter pylori breath test signal denoising fitting method and system, and belongs to the technical field of medical detection and signal processing. The method processes the continuous monitoring signal of the 13CO2 / 12CO2 isotope ratio in exhalation: firstly, the original signal is subjected to band-pass digital filtering to suppress high-frequency noise; then, low-frequency drift is eliminated through adaptive baseline correction to generate a drift-removed signal; subsequently, a robust peak value recognition algorithm is used to extract physiological response characteristics; finally, the identified peak value is taken as the center, a nonlinear function with physiological constraints is used for local fitting, and the Delta Over Baseline value is calculated based on the generated fitting curve with high precision. The application effectively solves the signal distortion problem caused by breathing fluctuations, instrument noise and the like in in vivo detection, realizes high-fidelity restoration of the Helicobacter pylori metabolic response, and significantly improves the detection accuracy and reliability of the breath test.

This invention discloses a method, system, device, and medium for suppressing wide-frequency synchronous oscillations in a distribution network system, belonging to the field of oscillation suppression technology. The method includes: realizing energy transfer between the power grid and charging piles through a three-phase AC / DC isolation conversion module; determining the operating state type based on the energy transfer direction and using corresponding modulation strategies to control the bidirectional switching unit; injecting a wide-frequency excitation signal into the distribution network system; acquiring the response current signal of the distribution network system; obtaining impedance values ​​at different frequencies through frequency domain transformation; decomposing the impedance values ​​to obtain impedance characteristic parameters; designing virtual impedance compensation parameters based on the impedance characteristic parameters; generating control signals based on the virtual impedance compensation parameters and impedance characteristic parameters; generating converter drive signals using a multi-objective controller; and adjusting the output of the three-phase AC / DC isolation conversion module based on the control signals and converter drive signals. This invention is based on adaptive algorithm-based impedance regulation and multi-objective control, adapting to frequency drift scenarios.

This invention discloses a comprehensive management method for transparent inspection of power grid materials based on the Internet of Things (IoT), belonging to the field of power material management technology. The method includes the following steps: deploying a three-axis vector probe array at the material entry channel to collect multi-point spatiotemporal signals and calculate the field strength distribution, generating an electromagnetic disturbance spatiotemporal matrix, and outputting a radio frequency identification (RFID) tag resonance drift risk matrix. This invention models electromagnetic disturbance sources using a three-axis vector probe array, combines resonance registration fingerprinting and frequency band compensation to achieve dynamic correction of RFID frequency drift, and integrates phase-encoded backscattering and strain acoustic features to ensure identification consistency. By utilizing optical time reference synchronization and phase-programmable metasurfaces to reconstruct the near-field environment, an adaptively adjustable identification space is constructed, improving the identification stability and traceability reliability of power grid materials under high-disturbance environments, thus breaking through the bottlenecks of traditional identification technologies.

The application claims a MEMS frequency accurate tracking and locking method based on a resonant phase-locked loop (R-PLL). The application relates to the technical field of MEMS (micro-electro-mechanical system) resonator control and frequency tracking, and the method takes the output of a voltage-controlled oscillator as an interference signal, takes the physical response (such as weak electromagnetic leakage or acoustic radiation) of a disturbed MEMS device as a feedback signal, compares the phase difference between the feedback signal and a reference signal through a phase detector, adjusts the interference frequency, and forms a closed-loop locking system. The application adjusts the interference source frequency through a phase detector and a filter, can track the target resonant frequency drift caused by factors such as temperature change in real time, makes the MEMS resonator keep in a phase-locked state with the target resonant frequency, and ensures that the interference energy is always efficiently coupled.

The application discloses a tobacco cut tobacco variable frequency motor state monitoring method based on a common mode loop and belongs to the motor state monitoring field. In view of the problem that early-stage faults of insulation deterioration of a variable frequency motor are difficult to detect in a high-dust, high-humidity and strong electromagnetic interference environment of a tobacco cut tobacco workshop, the application utilizes the correlation characteristics between a common mode loop signal and a motor insulation state, firstly establishes a common mode loop impedance model considering a common mode inductance of a stator winding, an inter-turn equivalent capacitance and a stray capacitance to ground, and calculates a common mode loop resonance frequency; then high-frequency oscillation loop models and medium-frequency oscillation loop models are respectively constructed to obtain an analytical relationship between a common mode current oscillation frequency and an insulation capacitance; a variational mode decomposition algorithm is adopted to separate multi-frequency oscillation characteristics in the common mode current, and high-frequency and medium-frequency common mode oscillation frequencies are extracted; and through online monitoring of an oscillation frequency drift amount, the deterioration degree of phase terminal insulation and internal insulation to ground of the motor winding is evaluated in real time. The application realizes non-invasive online precise monitoring of early-stage insulation faults of the tobacco cut tobacco variable frequency motor, and effectively reduces the risk of unplanned shutdown of a cut tobacco production line.

A method for synchronous excitation of multiple exciters relates to the field of dynamic testing and vibration control technology for large civil structures. The method includes the following steps: after constructing a unified time reference based on satellite navigation signals and a rubidium atomic clock, excitation amplitude and phase parameters are obtained based on the target modal requirements, and these parameters are sent to all exciter slave stations; the exciter slave stations generate a reference trajectory based on the excitation amplitude and phase parameters, enabling the exciter motor shaft angle to follow the reference trajectory in real time and output the target excitation; the phase error is obtained based on the measured excitation phase value and the reference trajectory, and then the motor angular velocity of the exciter is corrected based on the phase error. This invention solves the problems of startup phase error and long-term frequency drift in master-slave triggering schemes, ensuring synchronous start-up of all exciters. Combined with dynamic correction of the exciter motor angular velocity, it suppresses phase drift during long-term operation, significantly improving the excitation efficiency of higher-order modes and the clarity of the response signal.

This invention discloses an acoustic detection method for unmanned aerial vehicles (UAVs) based on dual-domain harmonic enhancement features, belonging to the field of acoustic signal processing and target detection and recognition. The method first performs time-frequency analysis on the acoustic signal to obtain a reference power spectrum; then, it performs two-way feature enhancement in parallel: in the time-frequency domain, a floor-scaled soft comb mask is constructed based on the estimated fundamental frequency, and selective gain is implemented to highlight harmonic ridges; in the cepstral domain, a harmonic structure robust to fundamental frequency drift is extracted through adaptive decomposition and energy ratio-based gain modulation. The two enhanced features are respectively input into a lightweight dual-branch network using rectangular convolutional kernels and depthwise separable convolutions for feature extraction. After fusion, the detection and recognition results are output through a classifier. This invention does not rely on blind source separation and can stably enhance UAV harmonic features under conditions of low signal-to-noise ratio, frequency drift, and multi-source aliasing, while also possessing advantages such as high computational efficiency and suitability for edge deployment.

The invention relates to a method for correcting a transmission frequency for an electronic device comprising a temperature sensor, a transmitter, and a microprocessor suitable for transmitting a transmission setpoint to the transmitter, the method comprising the following steps: - measuring (step E1) the temperature of the transmitter via the temperature sensor; - determining (step E2) a correction coefficient by searching a lookup table of correspondences between different transmitter temperatures and correction coefficients suitable for compensating for frequency drift of the transmitter as a function of its temperature, the lookup table being stored in the electronic device; - adjusting (step E3), by the microprocessor, the transmission setpoint as a function of the determined correction coefficient; and - transmitting (step E4), by the transmitter, an electromagnetic wave according to the adjusted transmission setpoint.

The application relates to the technical field of motion regulation and driving, in particular to a reciprocating motion amplification device and method of a flexible structure of a swing bridge. The reciprocating motion amplification device comprises a loading unit, an excitation execution unit, a self-adaptive identification unit and an energy supply unit. The excitation execution unit and the self-adaptive identification unit are both installed in the loading unit. The self-adaptive identification unit collects vibration response signals of the flexible target structure in real time and identifies the real-time natural frequency, controls the excitation execution unit to adjust the excitation frequency, so that the excitation frequency is automatically matched with the real-time natural frequency, resonance effect is excited, and reciprocating motion amplification is realized. Through closed-loop self-adaptive control, frequency drift is automatically tracked without manual intervention, excitation power consumption is reduced while the significant amplification effect is maintained, and the system adaptability and intelligent level are improved.

The invention belongs to the technical field of industrial process control, and particularly relates to a color master batch filtering pressure constant adjusting method based on proportional integral derivative control, and the method comprises the steps: obtaining the current pressure, the current flow and the target pressure, and calculating the pressure deviation and the deviation change rate; based on the current pressure and the current flow, stage parameters representing the filtering resistance state are obtained; extracting low-frequency drift characteristics of the pressure deviation on a time sequence and calculating a deviation degree according to the low-frequency drift characteristics; performing fuzzy reasoning on the pressure deviation and the deviation change rate to obtain an original increment; adjusting the original increment according to the stage parameters and the deviation degree to obtain a target increment; and superposing the target increment to the historical instruction to obtain a flow instruction, and outputting the flow instruction to the pumping device for execution. According to the invention, stage parameters and low-frequency drift characteristics cooperate to drive the regulatory factors, and constant control of the filter pressure of the color master batch in the whole period is realized.

The application relates to the technical field of communication network measuring instruments, in particular to a MEMS device frequency drift self-compensation method and system. The method comprises the following steps: collecting monitoring parameters of the MEMS device; calculating a temperature disturbance coefficient through the correlation between temperature and frequency, the temperature change rate, the time offset amount of temperature and frequency and the actual frequency difference; calculating a coupling degree factor by constructing a correlation matrix according to the correlation between the remaining parameters and temperature; calculating a lag degree coefficient by combining the time offset amount of the remaining parameters and temperature, the temperature disturbance coefficient and the fluctuation of temperature; calculating a thermal lag compensation factor through the temperature disturbance coefficient and the lag degree coefficient; determining a dynamic compensation amount by using a proportional-integral controller based on the thermal lag compensation factor; and completing compensation by correcting the frequency. The application improves the accuracy and quality of the MEMS device frequency drift compensation.

The present application relates to the technical field of eddy current pulse thermography detection, and specifically discloses an eddy current pulse thermography detection system based on LCC resonance topology and a control method thereof, aiming at the problems of resonance frequency drift and excitation current fluctuation caused by the change of lift-off height of the traditional eddy current pulse thermography excitation source, the present application adopts LCC resonance topology, sets compensation inductance, parallel compensation capacitor and series compensation capacitor to meet specific parameter conditions, decouples the excitation coil current from the lift-off height and keeps it constant, and at the same time ensures that the system realizes soft switching in the full load range. On this basis, a voltage closed-loop control strategy is further introduced, the real-time lift-off height is calculated, and the output voltage of the full-bridge inverter is adjusted accordingly to realize constant power output and stable temperature rise of the tested piece under the change of lift-off height. The present application effectively overcomes the influence of the change of lift-off height on the consistency of the detection result, and improves the reliability and on-site operation flexibility of the system.

This utility model discloses a vibration-compensated motor vibrating cutter head, belonging to the technical field of vibrating cutter heads. It solves the problem of excessively high vibration frequency during soft material cutting or excessively low vibration frequency during hard material cutting caused by crystal oscillator frequency drift leading to timer counting errors or interference rewriting of the PWM duty cycle register. If the vibration frequency is too high when cutting soft materials, the material melts and sticks; if the vibration frequency is too low when cutting hard materials, the blade will chip. The vibrating cutter head includes a vibrating cutter head body and a drive motor connected to it. The drive motor is electrically connected to an anti-interference frequency stabilization circuit. This anti-interference frequency stabilization circuit establishes a frequency reference and monitors the output frequency in real time, controlling the drive motor to shut down when a threshold is exceeded. This utility model establishes a frequency reference and monitors the output frequency in real time through its anti-interference frequency stabilization circuit, controlling the drive motor to shut down when a threshold is exceeded.

Clock frequency-drift compensation is described for a clock generator. In an example, an oscillator circuit includes a clock generator configured to generate an output clock signal with a clock frequency, a first variable resistor coupled to the clock generator to vary the clock frequency, and a second variable resistor. A voltage divider has a reference resistor and the second variable resistor. The voltage divider is configured to generate a reference stress voltage between the reference resistor and the second variable resistor, and a correction feedback block is configured to compare the reference stress voltage to a reference voltage, to adjust a resistance of the first variable resistor, and to adjust a resistance of the second variable resistor in response to the comparing.

This invention discloses a harmonic analysis method for 18-pulse port and shipping rectified power supplies based on an improved VMD algorithm, belonging to the field of power quality monitoring and signal analysis technology. Curve fitting and detrending processing of the filtered signal can eliminate the influence of long-term stable changes or slow drifts in the current signal, making the actual fluctuations and harmonic components in the signal more prominent. Compared with traditional methods, this processing can prevent low-frequency drift or operating condition changes from shifting the mode decomposition, improving the sensitivity of subsequent decomposition algorithms to transients and local frequency bands. Baseline correction is performed after detrending, causing the corrected signal to fluctuate around the zero center, eliminating the influence of bias and DC components on signal feature extraction. This improvement ensures the symmetry and stability of modes in the subsequent VMD decomposition process, while providing a reliable basis for the extraction of amplitude, phase, and power spectral density, making each mode feature more accurately reflect the actual harmonic state.

The invention provides a control method and device of a pulse laser and the pulse laser, and belongs to the technical field of lasers, and the method comprises the steps: controlling the linear loss in a resonant cavity to be at a first loss level through a linear loss modulator before a pulse is established, maintaining the first loss level for a preset time, and enabling the interior of the resonant cavity to establish preliminary oscillation light; the longitudinal mode selector is used for screening out a target longitudinal mode from the preliminary oscillation light; and utilizing the linear loss modulator to control the linear loss in the resonant cavity to be at a second loss level so as to drive the target longitudinal mode to be quickly amplified in the resonant cavity, thereby forming and outputting pulse laser. According to the invention, the first loss level is forcibly maintained for a period of time before the pulse is generated, and the precise screening of the target longitudinal mode is completed in the initial oscillation light circulation of the long period of time by using the longitudinal mode selector, so that the problem of frequency drift between pulses in the pulse laser is effectively solved.

The application discloses a digital event triggering method and system based on baseband data sequence edge detection, relates to the field of baseband data detection, and comprises the following steps: removing direct current bias, suppressing low-frequency drift and filtering noise from an original baseband data sequence to obtain a preprocessed baseband data sequence; determining a morphological structure element according to a signal-to-noise ratio and an expected event width of a target service scenario, and extracting a local mutation profile through an open operation and a top-hat transformation; generating a double threshold based on a morphological gradient, statistical characteristics and noise estimation to extract a candidate event interval; performing multi-dimensional feature matching on the candidate event segment in combination with a reference event feature template to determine a target effective event; and determining an event time center point and start and end boundaries according to a local event energy sequence and event positioning constraint information and outputting triggering information containing an event timestamp and event segment data. Thus, the stability, accuracy and time positioning reliability of digital event triggering in a complex interference environment are improved.

The application relates to a bearing fault diagnosis method, device and equipment across domains, which solves the frequency drift problem in the cross-domain scene by performing spectrum normalization processing on an original vibration signal, mapping discrete drift spectrum peaks to unified physical semantic coordinates, introduces double-domain collaborative feature extraction, realizes stable and accurate extraction even in strong noise and weak fault, and finally uses cross-reconstruction to constrain adaptive fusion of the normalized spectrum and the original vibration signal, reduces semantic deviation and information loss caused by manual fusion, thereby solving the problem that accurate bearing features are difficult to extract in the cross-domain scene, and thus the fault diagnosis accuracy is low.

The invention discloses a radar antenna beam domain adaptive conformal method and system under main lobe interference, and relates to the technical field of radar antennae, and the method comprises the following steps: collecting real-time energy change sequences of a target signal and an interference signal in a dynamic frequency drift process; expanding the target signal frequency component and the interference signal frequency component under a unified time reference, and establishing a transient identification basis of frequency coupling; and according to the established frequency coupling transient identification basis, performing fine decomposition on the identified overlapped section energy spectrum, and extracting the energy peak distribution of the frequency coupling center. Through frequency coupling transient identification and dynamic energy indication, effective distinguishing of a target and interference in a time dimension is realized, a target self-elimination phenomenon under main lobe interference is suppressed, and in combination with frequency avoidance rhythm, energy rearrangement and dynamic phase regulation, the shape and direction of a main lobe are kept stable; and the target detection reliability and precision in a complex interference environment are improved.

This application provides a method for optimizing resonance and torque pulsation in an electric vehicle prime mover, comprising: S2, inputting real-time dynamic fluctuation generation indicators into a preset finite element analysis model to simulate the resonance frequency drift trend and calculate potential torque pulsation anomalies; S4, using acquired information on the uneven distribution of the electromagnetic field, combined with real-time sensing state data to generate a vicious cycle formation risk assessment score; S6, updating the torque control model by stabilizing the resonance frequency parameters to optimize the torque output curve to suppress pulsation anomalies; S7, after obtaining the optimized torque output curve, inputting a feedback loop mechanism to verify the material physical property response and determine whether the source of dynamic fluctuations has been eliminated; S8, if it is determined that the source of dynamic fluctuations has been eliminated, recording the adjustment log and updating the temperature load change database for subsequent simulation use. This invention achieves a significant improvement in the stability and efficiency of prime mover operation.

This invention discloses a fire early warning system based on the Internet of Things (IoT) and edge computing, relating to the field of fire early warning. It primarily addresses the shortcomings of sensors in the early stages of a fire, where crystal oscillator frequency drift and local clock rate changes can negatively impact early warning effectiveness due to temperature rise. This invention utilizes IoT coverage to construct distributed edge computing nodes, using sensors at various locations as edge nodes for data acquisition and preprocessing. It identifies and eliminates clock interference by using timestamp micro-jitter, verifies early warning accuracy and avoids false alarms through sudden anomaly detection, and improves system efficiency after prevention and control through recovery phase detection. Ultimately, it achieves early warning, precise prevention and control, and source tracing assistance for fires, solving problems such as delayed fire warnings, high false alarm rates, weak interference resistance, and slow system recovery after prevention and control, thereby improving the intelligence and precision of fire early warning and prevention.

The present application relates to the technical field of power metering equipment testing, and discloses a kind of smart meter waterproof dust detection method and equipment, comprising: the test environment of low-pass filter isolation unit in series is constructed, and the dielectric reference model of thermal response in dry state is established;Start spraying and control the power modulation sequence of electric meter execution, utilize thermal expansion and cold contraction to establish the alternating pressure difference inside and outside the shell;Synchronous acquisition leakage current vector, channel impedance spectrum and internal temperature data;Solve the resistive leakage current component, impedance spectrum resonance frequency drift and thermal response phase lag, and thus comprehensively determine the sealing performance of electric meter.The present application blocks power interference by isolation unit, simulates real working conditions by using the breathing effect caused by power modulation, and solves the problem that traditional methods are difficult to identify trace moisture intrusion by combining electrical and thermodynamic multi-dimensional feature analysis, realizing high sensitivity online monitoring of early sealing failure risk of smart meter.

The present application relates to the technical field of intelligent vertical detection of pile foundation, in particular to a rotary pile verticality intelligent detection method based on laser measurement, which comprises the following steps: collecting original displacement data by continuously scanning a rotary descending drill pipe through a pile orifice laser measuring instrument, constructing a dynamic noise benchmark library to complete background noise mode matching and adaptive deduction, and obtaining a pure displacement data stream; calculating a pile body center horizontal projection track, separating low-frequency drift and high-frequency vibration components, inputting the low-frequency components into an attitude evolution model to predict the deviation trend and generate a pre-correction instruction with a time label, distinguishing normal vibration from abnormal vibration caused by hole wall collapse for the high-frequency components and triggering an emergency flag, and fusing to generate a comprehensive control instruction to issue a correction mechanism. The method can realize accurate noise removal, accurate pile body track restoration, early correction and real-time determination of hole wall abnormalities.

This invention provides a temperature-monitored field stabilization method and system, relating to the field of permanent magnet magnetic resonance (PMMR). The method acquires temperature data from a magnet and simultaneously measures the proton resonance signal frequency using a magnetic resonance probe to obtain temperature-frequency data. The data is preprocessed and feature extracted, and a specially tuned feature extraction neural network and a time-series analysis neural network structure are introduced to construct a nonlinear mapping model between the spatiotemporal distribution of the temperature field and frequency drift, enabling frequency prediction. A Z0 compensation coil then generates a compensation magnetic field to fine-tune the magnetic field. This invention significantly reduces frequency drift caused by ambient temperature fluctuations without requiring a complex hardware platform, compressing the drift from hundreds of Hz to the order of several Hz. This effectively improves the testing accuracy, long-term stability, and repeatability of permanent magnet PMMR systems, and is applicable to scenarios such as permanent magnet PMMR analysis instruments, permanent magnet magnetic field control systems, and long-term online monitoring equipment.

This application discloses a method and system for monitoring the temperature of power cables based on surface acoustic wave (SAW) sensors, belonging to the field of power detection. This application is applicable to power cables with dynamic loads, by simultaneously acquiring frequency drift data and real-time current waveform data from a SAW sensor array along the power cable. The frequency drift data is converted into multiple temperature points and subjected to spatial interpolation and differentiation to obtain measured temperature gradient information. Harmonic component information is extracted from the current waveform and input into a deep neural network to predict theoretical temperature gradient information. Kalman filtering is used to iteratively fuse the predicted temperature gradient information with the measured temperature gradient information to generate an optimized target temperature gradient. Finally, based on this target temperature gradient and starting from a known temperature point, the complete temperature distribution data of the power cable is reconstructed through integral calculation, enabling comprehensive and accurate temperature monitoring of the power cable.