652 results about "Calibration coefficient" patented technology

The invention relates to a high-precision multi-channel phased array radio measurement calibration method and a high-precision multi-channel phased array radio measurement calibration system. The method comprises the following steps: carrying out electromagnetic characteristic modeling on N array element channels and an antenna housing of the multi-channel phased-array antenna to obtain a channel measurement model; carrying out electromagnetic field numerical calculation on the multi-channel phased-array antenna to obtain an initial error data matrix; mapping the initial error data matrix to a two-dimensional weight matrix, and performing optimal matching solution on the two-dimensional weight matrix to obtain a theoretical calibration coefficient matrix; connecting the standard gain antenna and the multi-channel phased-array antenna by adopting a vector network analyzer, and performing far-field scanning measurement on the multi-channel phased-array antenna to obtain actually measured amplitude-phase characteristic data; and performing weighted least square iterative calculation on the actually measured amplitude-phase characteristic data and the theoretical calibration coefficient matrix to obtain a target calibration compensation coefficient. According to the invention, accurate measurement of the amplitude-phase characteristics of the multi-channel phased-array antenna is realized, and the stability of the calibration process is improved.

The invention relates to the technical field of power electronics, in particular to a photovoltaic off-grid inverter control method and system, and the method comprises the following steps: applying a test signal to identify an output interaction characteristic parameter, predicting the power generation power through combining with weather and attenuation, calculating the power fluctuation, and adjusting a current control parameter set. And calculating voltage and reactive power compensation parameters to generate an inverter control instruction, and combining a temperature load prediction trend to adjust a power allowable value to obtain a predictive power calibration coefficient. According to the invention, by analyzing the output interaction characteristics, enhancing the perception capability of the inverter to the actual operation environment, combining with the prediction of the photovoltaic power generation amount, realizing the prediction and influence evaluation of the power fluctuation, improving the adaptive adjustment capability of the current control parameters, improving the output voltage and reactive power control precision by utilizing the interaction characteristics, and optimizing the electric energy quality; and through thermal management of multi-point temperature and load prediction, the operation safety is improved, the service life of equipment is prolonged, and the operation performance of the photovoltaic off-grid system in a complex environment is improved.

The invention relates to the technical field of termite monitoring and killing, in particular to a termite monitoring and killing method based on multi-modal sensing and a dynamic threshold value, and adopts the technical scheme that multi-source signal acquisition is adopted, and biological activity signals of a target area are synchronously acquired through a vibration sensor, a sonic sensor, a chemical gas sensor and a thermal imaging sensor; the anti-interference performance is improved, so that the false alarm rate is reduced; environmental parameter compensation is carried out, temperature, humidity and soil conductivity data are collected in real time, a dynamic calibration coefficient is generated to correct sensor original data, and environmental adaptability is improved; the method comprises the following steps: acquiring data of a current area, performing dynamic threshold calculation, inputting the acquired data into an LSTM-Transformer hybrid network, and outputting a self-adaptive early warning threshold of the current area so as to reduce the possibility of leak detection; through multi-stage early warning judgment, the real-time performance is improved, and the early warning delay is reduced; and starting a corresponding disposal process according to the early warning level, performing response execution, and narrowing the spraying range, thereby reducing pollution.

The invention provides an automatic processing method for real-time observation data of an ocean station, and belongs to the technical field of ocean observation data processing. A wavelet packet decomposition multi-scale noise separation algorithm is established to distinguish environmental noise and real signals, dual-sensor redundancy configuration is combined with Bayesian inference to identify sensor drift, and a calibration coefficient is updated in real time through a recursive least square method. A one-dimensional time sequence is mapped to a high-dimensional phase space by utilizing a phase space reconstruction algorithm to realize high-precision prediction of a chaotic signal, a hierarchical data storage architecture is established, and a data migration strategy is iteratively optimized through a hierarchical correlation degree function; the technical problem that time synchronization signals are difficult to reconstruct accurately according to asynchronous sampling data of multiple sensors of an ocean station is solved.

The invention discloses an automatic focusing control method based on a displacement sensor, and relates to the technical field of motion control, and the method comprises the steps: collecting a distance signal of a detection target, and converting the distance signal into a physical distance value through a calibration coefficient; the motion control card performs difference operation on the physical distance value and the standard focusing distance to obtain a position deviation value, performs data smoothing processing by using a Kalman filtering algorithm, establishes a state prediction model by using latest N frames of cache data, generates position compensation data, converts the position compensation data into a pulse control quantity, and when the pulse control quantity exceeds a preset threshold value, outputs the position compensation data; generating a motor driving instruction according to a PID control algorithm; and controlling the stepping motor driver to drive the lens assembly to perform position compensation according to the motor driving instruction, so that a standard focusing distance is kept between the lens assembly and the detection target. According to the invention, the problems of response lag and poor anti-interference capability in a traditional automatic focusing system are solved, and the dynamic response characteristic and the control precision of the system are improved.

The invention discloses a calibration and error correction method and system based on a stereoscopic vision measurement system, and relates to the technical field of measurement system optimization, and the method comprises the steps: carrying out the scanning of an object with a standard size, and collecting data points; calculating an error between a measured length and an actual length for each data point, calculating an average value and a standard deviation of all measured values, and excluding the measured values exceeding the errors; and calculating a calibration coefficient and offset to obtain corrected side length data, and dynamically adjusting the calibration coefficient and the offset. Through detailed algorithm steps and a closed-loop feedback control mechanism, the machine measurement system can realize automatic data collection, real-time error analysis and dynamic adjustment of calibration parameters. Therefore, the accuracy and the stability of measurement are improved, and the high efficiency and the reliability of the system in long-term operation are ensured. Through regular calibration and real-time error correction, the algorithms can significantly improve the overall performance of the measurement system.

The invention discloses a method for calibrating multiple channels of a photon calculation chip, which comprises the following steps of: inputting same calibration optical signals to a calculation module channel by channel, and acquiring a calibration output value of each channel; selecting a certain channel as a reference channel, and taking a calibration output value of the reference channel as a reference calibration output value; the other channels are used as channels to be calibrated; and the input optical signal of the calculation module of each to-be-calibrated channel is adjusted according to the external control electric signal, so that the calibration output value of each to-be-calibrated channel of the calculation module is the reference calibration output value under the condition that the light source module inputs the calibration optical signal. Original errors caused by manufacturing process errors and optical fiber coupling are adjusted through input optical signals, so that final output structures are consistent. According to the invention, the calibration module is arranged on hardware to adjust the optical signal, and a calibration coefficient does not need to be added into the calculation module, so that the burden of the calculation module is reduced.

The invention relates to the technical field of laser heat treatment, and provides a calibration method of a full-automatic circuit board cutting machine. The method comprises the following steps: acquiring physical coordinates of a circuit board of a cutting device through an intelligent sensor, and constructing a reference coordinate system matrix based on the physical coordinates; determining vibration parameters of the cutting device according to coordinates of laser spots emitted by a laser and the reference coordinate system matrix, and generating a nonlinear error component according to the vibration parameters and power information of the laser; generating an error function based on an error matrix formed by the error components, and determining a calibration coefficient vector by solving the error function; closed-loop control is conducted on the laser path of the cutting device through the calibration coefficient vector, the adaptability of the cutting device to complex working conditions is improved by integrating multi-source error factors and establishing a nonlinear mapping relation, and the cutting precision and stability are ensured.

The invention relates to the technical field of power system relay protection, and discloses a relay protection device mutual inductor adjustment system and method, and the system comprises a system connection initialization module, a data collection reference data generation module, a power frequency background signal offset module, a pilot frequency current injection error calibration module, and a calibration result verification output module. The method comprises the following steps: initializing sampling frequency of a to-be-calibrated mutual inductor and calibration source output precision of a calibration system, collecting amplitude and phase data of real-time power frequency current of the mutual inductor, generating offset current with equal amplitude and opposite directions through power electronic compensation based on reference data, optimizing offset current parameters through a closed-loop adjustment algorithm, and adjusting the offset current parameters through a closed-loop adjustment algorithm. Power frequency background signal offset is completed, pilot frequency calibration parameters are set, a difference value between a mutual inductor pilot frequency output signal and a calibration source standard signal is extracted by adopting a zero pointing technology, an optimal calibration coefficient is automatically calculated, verification of a calibration result is completed, and accuracy and reliability of the calibration result are ensured.

The invention provides an on-orbit relative radiometric calibration coefficient obtaining method and device of a spaceborne camera, and the method comprises the steps: obtaining an on-orbit relative radiometric calibration coefficient relation model which is used for representing the relation between on-orbit relative radiometric calibration coefficients under different imaging parameters; determining a bright field uniform area and a dark field uniform area of the spaceborne camera under the first imaging parameter; on the basis of the bright field uniform region and the dark field uniform region, obtaining an on-orbit relative radiation calibration coefficient under the first imaging parameter; on the basis of the on-orbit relative radiometric calibration coefficient relation model and the on-orbit relative radiometric calibration coefficient under the first imaging parameter, on-orbit relative radiometric calibration coefficients under other imaging parameters are obtained, and the technical problem that in the prior art, the on-orbit relative radiometric calibration coefficient obtaining efficiency is low is solved.

The invention discloses a well drilling vibration measurement and real-time calibration system based on a vibration sensor, and relates to the technical field of data processing. The system comprises a signal measurement part, a signal correction compensation part, a signal analysis part and a signal calibration part, the signal measuring part is used for installing a vibration sensor and an accelerometer near a drill bit or a drill column and generating a fundamental frequency vibration signal; the signal correction compensation part is used for performing stick-slip effect compensation on the fundamental frequency vibration signal to obtain a first compensation signal; calculating the resonant frequency of the drilling system; calculating the bending stress of the drill string; calculating well track deviation; the signal analysis part is used for calculating the dynamic load of the drilling system to obtain the vibration energy dissipation of the drilling system; calculating the system response of the drilling system; and the signal calibration part is used for calculating a calibration coefficient. According to the invention, the precision and calibration capability of vibration signal measurement are significantly improved.

The invention discloses a high-precision electrical calibration method and system for a wedge flowmeter. The method comprises the following steps: step 1, data acquisition and preprocessing; step 2, dynamic working condition identification; 3, updating the self-adaptive model; 4, multi-source data fusion calibration is carried out; and 5, performing closed-loop verification and compensation. According to the invention, multiple types of signals are collected in real time through the multi-dimensional sensor array and de-noised to construct a data set, so that comprehensive and accurate data collection is realized, and a good basis is provided for calibration; carrying out dynamic working condition identification by utilizing a support vector machine, triggering model updating, and endowing calibration with dynamic self-adaptive capability; model parameters are updated by adopting a recursive least square method, compensation items are established, and the characterization capability of the model is enhanced; a calibration coefficient is generated by means of a data fusion algorithm, and the calibration precision is improved; through verification and compensation of a digital twinborn model, traditional defects are effectively overcome, model transplantation errors are reduced, the measurement precision of the wedge flowmeter is improved under extreme working conditions, and production stability and product quality are guaranteed.

The invention provides an intelligent fire-fighting method and system for a photovoltaic power station based on the Internet of Things, and the method comprises the steps: collecting temperature data through a distributed optical fiber temperature measurement unit, avoiding electromagnetic interference through optical signal conversion, analyzing the spectral feature difference between electro-arc light and combustion flame through a spectral feature separation unit, and carrying out the analysis of the spectral feature difference. Correlating the particulate matter concentration with the specific gas component through the multi-source coupling smoke sensing unit to obtain anti-interference data; space-time probability fusion is executed, and fire confidence is generated through alignment; a trigger response is calculated according to the combination of the fire confidence coefficient, the temperature rise trend slope and the smoke diffusion speed; running a self-adaptive parameter adjustment engine, and generating a sensing layer calibration coefficient and a decision rule optimization instruction; the parameter optimization instruction is issued to the sensing device, the calibration effect is verified, the influence of dust, electromagnetic interference and other factors is effectively avoided through the collected anti-interference data, the response is determined in combination with temperature rise and delay diffusion, the probability of false triggering is effectively reduced, and the accuracy of fire detection is improved.

The invention relates to the technical field of signal calibration, in particular to a near-field calibration method based on near-field antenna offset error estimation, and the method comprises the steps: carrying out the near-field calibration of a target phased-array antenna, obtaining the phase value of each channel, comparing the phase value with near-field reference data, and obtaining the original calibration value of each channel; wherein the number of the target phased-array antennas is M rows and N columns; dividing the original calibration value of each channel into M sections according to rows, respectively performing phase unwrapping operation on each section to obtain M phase vectors, respectively performing linear fitting on each phase vector, and estimating a slope value corresponding to each row; based on the slope value corresponding to each row, matching a corresponding offset in an offset error slope corresponding table, and calculating to obtain an estimated offset according to each offset; respectively calculating the phase difference of each channel caused by the estimated offset, and compensating the original calibration value based on the phase difference to obtain a compensated calibration value; and correcting the calibration coefficient based on the compensated calibration value.

The invention relates to the field of optical fiber optics, in particular to a distributed optical fiber temperature measurement system based on Raman scattering, which comprises an optical signal excitation and separation module, a signal acquisition and preprocessing module, a temperature resolving module, a calibration and correction module, a real-time monitoring and early warning module and a management database, the system performs digital accumulation noise reduction on scattering signals through separation of Stokes light and anti-Stokes light, real-time monitoring of optical power and division of spatial positions, generates a temperature distribution curve through temperature calculation and determination of the spatial positions corresponding to the temperatures, generates calibration coefficients through selection of constant-temperature reference points and fitting of a temperature deviation curve, and performs calibration on the scattering signals. The temperature is corrected, a calibration curve is calibrated, meanwhile, light intensity attenuation is compensated, and the light temperature can be accurately measured and early warning can be carried out in time by setting multi-stage temperature early warning threshold values and monitoring temperature abnormal points.

The invention relates to the technical field of three-dimensional real-time wind speed measurement, and discloses a large-span roof three-dimensional ultrasonic anemometer and a measurement method thereof, and the method comprises the steps: building a three-dimensional coordinate system through laser ranging, and analyzing and compensating installation errors; an initial calibration coefficient is generated through a self-inspection and optimization algorithm, and the initial calibration coefficient is compared and analyzed with a standard instrument for initial calibration; ultrasonic pulse emission is controlled, full-path scanning and redundancy measurement of all axes are completed, signal quality is improved through multi-modal signal processing detection, and abnormal values are eliminated through weighted median values; the sound velocity is corrected based on real-time temperature data, the influence of humidity and air pressure on the sound velocity is adjusted through a nonlinear regression model, and a Reynolds stress correction term is introduced to compensate for sound wave path bending in an eddy current field; a three-dimensional turbulence intensity distribution diagram is constructed by fusing ultrasonic and LiDAR data, meteorological parameters are calculated, an extreme weather event is early warned by using a machine learning model, a visual three-dimensional wind speed field is provided through a cloud platform, and a potential risk area is identified.

The invention relates to a lightning arrester leakage ammeter self-calibration method and system, and the method comprises the following steps: disconnecting a main leakage ammeter from an external main measurement loop, and closing a calibration loop of a redundancy calibration sensor and a reference current source after a preset time is delayed; controlling a reference current source to output standard signals with different current magnitudes, collecting the standard signals by using a redundancy calibration sensor, extracting effective signal components, and performing environment compensation; iteratively calculating a relative error between the effective signal component and the standard signal, if the relative error is less than or equal to a second threshold value, updating a calibration coefficient according to a ratio of the standard signal to the effective signal component, and correcting a measurement result of the main leakage ammeter based on the calibration coefficient; if the relative error is greater than a third threshold value, locking output and uploading fault information; otherwise, recording as one exception, and carrying out maintenance early warning according to the number of exceptions. Compared with the prior art, the self-checking and real-time calibration of the leakage ammeter of the lightning arrester can be completed on the premise of not influencing the operation of power equipment.

The invention discloses an intelligent calibration method, system and equipment for an ambient air monitoring sensor. The method comprises the following steps: acquiring data of the ambient air monitoring sensor and data of a standard detector in real time and preprocessing the data; performing correlation analysis on the preprocessed data to obtain data in a preset range; performing spatial interpolation calculation and prediction on the data in the preset range to obtain an interpolation estimation value and an air concentration field; re-fitting the air concentration field for the interpolation estimation value to obtain distribution and hour mean value data of the pollutants in the environmental space; performing multi-order linear regression analysis on the obtained hourly mean value data and the hourly mean value data of the sensor to obtain a calibration coefficient; and carrying out calibration calculation by adopting the calibration model to obtain sensor calibration data consistent with the standard detector. The system comprises a module corresponding to the method, and the device comprises a first detection unit, a second detection unit and a processing unit, so that the calibration precision and the calibration efficiency of the sensor can be improved.

The invention discloses a matrix type resistance output control system and method, and belongs to the field of industrial control, the system comprises a multi-channel resistance output card supporting a plurality of independent channels, each channel is provided with a resistance network, the resistance network comprises a base resistor and a plurality of member resistors which are connected in series, and each member resistor is connected or disconnected through a relay; the measuring module is used for measuring actually measured resistance values of the basic resistor and the member resistor; the calibration module is used for simulating an actual measurement environment to generate calibration coefficients of different channels; the main controller is used for calculating actual target resistance values of different channels according to the calibration coefficient and the actual output resistance values; and the controller is also used for performing traversal calculation according to the actual target resistance value to obtain an optimal relay state combination in different channels, controlling the relay to access the corresponding member resistor, and further controlling the output of the actual output resistance value. According to the invention, 8421BCD coding, input large current measurement and introduction of a calibration coefficient are combined, so that high-precision resistance output requirements in different application scenes are met.

The invention discloses a dynamic adaptive black level correction method and device, and relates to the technical field of image processing. According to the dark current space distribution difference, an effective pixel area in each frame of original image is dynamically divided; determining an initial black level calibration coefficient of each space block based on the dark pixel noise level; obtaining the current temperature and the temperature change rate of each space block, and obtaining the level calibration coefficient of each space block after temperature self-adaptive calibration based on the initial black level calibration coefficient corresponding to each space block; fusing the calibration information of the previous frame and the level calibration coefficient of the current frame to obtain a cross-frame stable calibration result; and correcting the effective pixels in each space block based on a cross-frame stable calibration result to obtain a corrected pixel value, and reconstructing the corrected pixel value into an output image. The problems that an existing black level calibration technology is poor in space uniformity, insufficient in temperature change adaptability and unstable in calibration coefficient are solved.

The invention relates to the technical field of display, in particular to a Mini LED backlight module intelligent control system and method of a distributed driving architecture, and the system comprises a processor unit, an LED driving chip, a Mini LED module and a sensor. The processor unit converts an RGB color space into a backlight brightness signal in an XYZ tristimulus value form based on a topological mapping theory; the LED driving chip receives the signal, controls the light intensity of the Mini LED module, and executes verification and compensation based on a Bayesian inference framework; the Mini LED modules are arranged in a distributed architecture, receive the brightness signal and output backlight brightness; a sensor collects backlight brightness signals of an RGB color space to form closed-loop feedback, a calibration coefficient matrix is generated through a polynomial fitting calibration algorithm optimized through matrix decomposition, and high-precision and high-reliability backlight control is achieved in combination with adaptive parameter adjustment and a dynamic compensation mechanism.

The invention discloses a household line fault detection method. The method comprises the steps of preprocessing original data to remove noise and divide periodic time windows, calculating a consistency deviation rate based on parameter difference of adjacent sensors, generating a dynamic calibration coefficient to correct sensor output, and compensating performance drift caused by aging. Then, performing difference calculation on the corrected data to generate a feature sequence, identifying a mutation point and marking a suspected abnormal interval; and calculating an abnormal possibility score in combination with a sensor correction data distribution rule, outputting a correction signal, comparing the correction signal with a preset threshold value, accurately positioning a fault position, and generating a corrected detection result. According to the method, the problem of inaccurate detection results caused by aging of the sensor after long-term operation is effectively solved, the reliability and safety of the system are improved, the requirement of manual inspection is reduced, early fault early warning is realized, and the safety of household electricity utilization is guaranteed.

The invention discloses a gas analysis method and system for a gas source purification process, and relates to the technical field of gas detection and analysis. The method comprises the following steps: synchronously acquiring optical, electrochemical and conductivity detection signals in a gas source purification pipeline, and combining environmental parameters such as temperature, humidity and flow; carrying out filtering, anomaly elimination and normalization processing on the detection signal, constructing a multi-dimensional feature vector, and carrying out dimensionality reduction to obtain a principal component feature; and dynamically distributing weights through a self-adaptive weighted fusion model, and calculating a gas purification characteristic value. Establishing a drift prediction model based on historical data, inputting environmental parameters and operation duration to calculate a predicted drift amount, and correcting a gas purification characteristic value; when the drift distance exceeds a threshold value or reaches a calibration period, standard gas is introduced to detect the average response value of the drift distance, a calibration coefficient is calculated according to the concentration of the standard gas, the calibration coefficient is fed back and updated to the weighted fusion model and the drift prediction model, and self-correction and high-precision analysis of the gas purification process are achieved.

The invention provides a satellite-borne laser radar calibration method and system based on background noise iteration. The method comprises the following steps: firstly, constructing an ideal background atmosphere total attenuation backscattering coefficient, obtaining night background noise and a calibration coefficient by adopting a robust linear fitting iteration method, and realizing calibration of a satellite-borne laser radar night detection signal; in combination with a strategy of a CALIPSO official calibration method, a day and night calibration conversion area is set, simple level detection is carried out, and a clean atmosphere calibration conversion area is screened out; calculating an attenuation scattering ratio of a day and night clean atmosphere calibration conversion area, obtaining a calibration conversion coefficient, and combining a night calibration coefficient to complete iterative calculation of a day-to-day calibration coefficient and background noise, thereby realizing calibration of a satellite-borne laser radar day-to-day detection signal; according to the invention, satellite-borne laser radar day and night calibration can be realized without collecting background noise, and the application range is expanded compared with a traditional method. The satellite-borne laser radar on-orbit calibration method is suitable for satellite-borne laser radar on-orbit calibration under different height detection conditions, and has practicability and high accuracy.

A data processing method can be applied to the field of artificial intelligence and comprises the steps of obtaining first attribute information and at least one calibration feature of a first user and a first article; the calibration feature indicates at least one of a recommended scene, an item, or a provider of the item; obtaining a calibration coefficient corresponding to each calibration feature; obtaining a first recommendation score for recommending the first article to the first user through a recommendation model according to the first attribute information; and adjusting the first recommendation score according to the calibration coefficient. According to the method, the corresponding calibration coefficients are set for different calibration dimensions, and the calibration coefficient of the calibration dimension related to the current to-be-recommended data is utilized to adjust the output of the model, so that the recommendation effect and precision of the model can be improved.

The invention discloses a multi-parameter fusion ultrasonic water meter intelligent calibration system which comprises an ultrasonic sensor module used for collecting ultrasonic signals of water flow, including flow velocity, flow, temperature and pressure parameters; the data processing module is used for receiving the data acquired by the ultrasonic sensor module and carrying out preprocessing and feature extraction; the multi-parameter fusion module is used for fusing the extracted characteristic parameters to generate comprehensive calibration parameters; the intelligent calibration module is used for dynamically adjusting the calibration coefficient of the water meter according to the comprehensive calibration parameters to realize intelligent calibration; and the communication module is used for carrying out data exchange with external equipment to realize remote monitoring and calibration. Calibration is carried out by fusing various parameters such as the flow velocity, the flow, the temperature and the pressure, the limitation of single parameter calibration is overcome, and the calibration precision is improved; the intelligent calibration module is adopted, dynamic adjustment is conducted according to real-time data, the water meter adapts to complex water flow conditions, and the measurement stability of the water meter is improved.

Systems and methods for measuring the content of an element in a soil comprises: a neutron source for irradiating the soil with neutrons; a detector assembly configured to detect an INS gamma spectrum of the soil; an instrument for measuring a moisture content of the soil; and a processor in communication with the detector assembly, the processor configured to: apply a moisture calibration coefficient to calculate a net peak area of a characteristic peak of the element in the INS gamma spectrum, the moisture calibration coefficient calculated to account for the moderation of fast neutrons by hydrogen atoms of water present in the irradiated soil at the location under analysis; and generate a concentration of the element in the soil. The instrument for measuring a moisture content of the soil may comprise the detector assembly. Systems and methods incorporating a temperature-controlled housing for the gamma detector assembly are also provided.

The invention discloses a calibration test method and system for a pressure sensor, and relates to the technical field of pressure sensor calibration. According to the method, original temperature and voltage data are collected in real time, ideal pressure is obtained through an ideal state equation, original output voltage is obtained through a preset relation model in combination with the temperature, then precise compensation of zero drift and sensitivity drift is completed in sequence through a multi-dimensional calibration coefficient, and further correction is performed through a linear regression relation polynomial, so that the accuracy of the zero drift and the sensitivity drift is improved. And finally, a detection pressure value is obtained. The output pressure value is closer to the real physical quantity, the application requirements of high-precision scenes such as medical equipment are met, and the calibration effect and the pressure measurement precision are improved.

The invention provides a power grid composite chain disaster multi-source monitoring damage assessment method and system, and relates to the technical field of data processing, and the method comprises the steps: dividing a reference geographic coverage area, generating a plurality of independent analysis units, enabling each three-dimensional discrete point to belong to the corresponding independent analysis unit, and carrying out the calculation to obtain a unit space calibration coefficient; performing regional correction on the fused disaster monitoring image data set by using the unit space calibration coefficient to obtain calibrated disaster monitoring image data; based on the calibrated disaster monitoring image data, disaster damage features are extracted through a deep learning semantic segmentation network; and based on the disaster damage characteristics, carrying out spatial diffusion path simulation and time evolution process analysis of disaster influence to obtain disaster spatio-temporal evolution characteristics, and carrying out comprehensive quantitative evaluation of damage degree and risk level on power grid facilities to generate a comprehensive damage evaluation result. According to the invention, the accuracy of power grid disaster damage monitoring and the timeliness of evaluation are improved, and the risk early warning and coping capability of power grid facilities is enhanced.

The invention relates to the technical field of radio measurement, and discloses a multi-band radio measurement calibration method and system, and the method comprises the steps: S1, carrying out the sampling and preprocessing of a multi-band radio signal, and obtaining a preprocessed signal; s2, performing signal classification to obtain a mixed signal; s3, performing signal reconstruction on the mixed signal to obtain a pure target signal; s4, performing dynamic sub-band division on the pure target signal, introducing a regularization factor into each sub-band, and iteratively calculating a minimum mean square error until a residual error is smaller than a first target value to obtain an initial calibration parameter; s5, establishing logarithmic interval frequency point distribution based on the initial calibration parameter, and obtaining a compensation calibration coefficient; and S6, verifying the compensation calibration coefficient by adopting the standard calibration signal, and when the root-mean-square error exceeds a second target value, repeatedly executing the steps S4-S6 until the precision requirement is met to obtain a target calibration result, so that the interference signal is effectively suppressed, and the calibration precision is improved.