525 results about "Calibration coefficient" patented technology

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 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 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 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 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.

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.

A device may estimate targets and angle-of-arrival (AoA) and angle-of-departure (AoD) pairs for the targets based on a sensing-aware beam-forming (SABF) signal and a sensing-aware beam-nulling (SABN) signal received from another device. The device may perform post-processing of the AoA and AoD pairs to modify estimation accuracies for the AoA and AoD pairs, and may estimate path loss values for paths of the targets. The device may determine positions of the targets based on the AoA and AoD pairs, and may perform one or more actions based on the positions of the targets. The device may receive communication pilots from the other device, and may determine transmitter calibration coefficients for the other device and receiver calibration coefficients for the device based on the communication pilots.

An end-to-end color imaging system chromaticity characterization method based on hyperspectral calibration belongs to the field of color imaging, color display and imaging chromaticity measurement, and comprises the following steps: firstly, acquiring or calling hyperspectral cube data, and measuring red, green and blue three-channel spectral sensitivity curves and calibration coefficients of imaging equipment; fixed weight linear mapping is adopted, a pixel-level RGB image and a corresponding XYZ tristimulus value image are generated, and paired calibration samples are formed. And an end-to-end deep network is constructed to map any RGB image into an XYZ image. The method has good prediction precision and robustness, and can be widely applied to scene chromaticity measurement, color imaging color management, display calibration, camera color recovery and other chromaticity consistency demand scenes.

The invention discloses an automatic switching metering method suitable for multiple ranges of a pressure gauge, and the method comprises the steps: S1, obtaining the information of a current pressure measurement environment, inputting a pressure range prediction model, and outputting an initial recommended range; s2, selecting a measurement parameter of a corresponding measuring range, and performing preliminary measurement on the pressure at the initial sampling frequency to obtain a preliminary measurement pressure value; s3, comparing the preliminarily measured pressure value with the upper range limit and the lower range limit of the selected range, and judging that a higher / lower range needs to be switched; s4, the calibration coefficient of the range to be switched is obtained and corrected, and a corrected pressure measurement value is obtained; s5, dynamically adjusting the sampling frequency; and S6, the pressure change rate is monitored in real time, and the measuring range capable of covering the current pressure change range is preferentially selected for measurement. According to the invention, multi-range intelligent switching of the pressure gauge is realized, and the measurement precision and response speed in the full-range range are improved.

The invention belongs to the technical field of satellite communication and antenna arrays, and relates to a low-orbit satellite ultra-large folded array antenna beam and polarization adaptive calibration system. According to the system, through a feed network of an antenna and a coupler of a satellite-borne detection path, a Jones matrix of each array element is obtained by adopting time division multiplexing excitation, and amplitude and phase calibration in a substrate is realized by utilizing least square pseudo-inverse compensation. Self-adaptive fusion is carried out according to the energy of the left-hand and right-hand circular polarization channels, the residual error of a fusion signal and an ideal signal is calculated, and abnormal array elements are removed in combination with amplitude outlier and phase jump detection. Performing low-rank denoising and sparse correction processing on the phase residual error, calculating the plane coefficient of each substrate through weighted least square plane fitting, and realizing smoothing and compensation iteration by using Kalman filtering and phase updating constraint. And finally, correcting each array element by the spaceborne digital beam forming unit according to the calibration coefficient, thereby realizing accurate calibration of the antenna beam and polarization.

The invention provides a high fill roadbed settlement prediction method, and belongs to the technical field of engineering construction.The method comprises the steps that firstly, a large test box interface test system is established, and a 4 * 4 sensor monitoring network is arranged on the interface of filler and a foundation soil layer; the influence of different parameter combinations on interface mechanical properties is researched through a parameter change experiment system, and a parameter database is established; obtaining actual measurement data of typical engineering and determining a calibration coefficient; establishing an interface element model, and obtaining an interface friction angle, cohesion and rigidity parameters; calculating the deformation of each layer by adopting a layered accumulation method; introducing a time effect correction factor to consider consolidation characteristics; the slip influence is evaluated through an interface slip test, and the prediction deviation caused by neglecting the interface effect in a traditional method is corrected; and finally, constructing a deep learning prediction model, and verifying prediction precision and reliability through actually measured data.

The invention relates to the technical field of LED display, solves the problems that in the prior art, dynamic light attenuation compensation based on the real-time operation state of an LED chip cannot be achieved, and long-term uniformity and display quality of a display screen are difficult to guarantee, and provides an LED display quality stability control method, device and equipment and a medium. The method comprises the following steps: correcting the LED display screen according to an initial calibration coefficient; in the operation process of the corrected LED display screen, operation parameters of each LED chip in the LED display screen are collected in real time; acquiring the light attenuation degree of the LED display screen according to the operation parameters and a pre-constructed chip light attenuation model; when the light attenuation degree of the LED display screen meets a preset condition, adjusting the initial calibration coefficient according to the light attenuation degree to obtain a target calibration coefficient; and correcting the LED display screen according to the target calibration coefficient. The display stability, the service life and the maintenance convenience of the LED display screen are improved.

The invention provides a display screen dynamic control method and system, and relates to the technical field of data processing, the method comprises the following steps: constructing a space coordinate system comprising a plurality of entity nodes, the entity nodes comprising a display screen preset angular point, a user binocular vision center and a handheld interaction device; analyzing a relative pose relationship among the nodes by calculating a projection dot product of a space vector corresponding to each node; constructing a dynamic topology network based on the relative pose relationship, and synchronously collecting environment illumination intensity, user fixation point coordinates and user pose data; performing time sequence synchronization and Kalman filtering preprocessing on the acquired multi-modal data to obtain an initial feature set; and generating a spatial calibration coefficient according to the distribution characteristics of the dynamic topology network, and performing normalization compensation on the initial feature set through the calibration coefficient to obtain a calibrated multi-modal sensing feature vector. According to the invention, accurate and intelligent dynamic control is realized.

The invention provides a brightness calibration coefficient storage method, a related device and a storage medium. The method comprises the following steps: acquiring an actually measured brightness value of each pixel in the display panel; dividing the display panel into a plurality of initial blocks, and calculating the variance of the actually measured brightness value of each initial block; recursively merging the adjacent initial blocks and / or merged blocks until the variance of the actually measured brightness values of the merged blocks is greater than a preset threshold value; according to a preset storage structure, the brightness calibration coefficient of each block is stored with the block as the unit, and the brightness calibration coefficient comprises the base value of the actually measured brightness value of each block and the difference matrix. According to the embodiment of the invention, the storage space required by the brightness calibration coefficient of the display panel is reduced, so that the space occupation of an external flash memory and an on-chip buffer is reduced, and the layout design difficulty in the display panel is reduced.

According to the xerophthalmia core index multi-task AI detection system, method and terminal provided by the invention, the xerophthalmia multi-modal image is collected and exclusive preprocessing is completed, and core index detection is carried out on the preprocessed image based on the xerophthalmia multi-index detection model, so that the xerophthalmia core index detection result is obtained. Outputting detection results such as meibomian gland deletion rate, tear film rupture time, staining classification, tear river height and blepharitis marginal inflammation classification; and dynamically adjusting the index result according to a calibration coefficient corresponding to the type of the data acquisition equipment, and finally generating a standardized detection report. A xerophthalmia multi-index detection model is constructed based on an improved U-Net3 + architecture, a dry eye feature enhancement encoder and a cross-scale feature fusion decoder are adopted, a customized multi-task detection head is matched, an inter-task attention collaboration mechanism is established, meanwhile, a preprocessing algorithm and a dynamic calibration mechanism matched with a dry eye image are designed, and the detection accuracy of the xerophthalmia is improved. And multi-index synchronous, high-precision and high-efficiency detection is effectively realized.

The invention discloses a differential pressure sensor precision calibration method for high-temperature environment monitoring, and relates to the technical field of sensor calibration, and the method comprises the steps: carrying out the high-temperature factor extraction and simulation parameter design of the application scene information of a differential pressure sensor, and obtaining a high-temperature test parameter table of the sensor; a standard differential pressure source is arranged in the high-temperature environment controllable simulation chamber; acquiring a multi-high-temperature parameter differential pressure test data set of the standard differential pressure source; establishing a multi-high-temperature parameter differential pressure compensation model set; obtaining a high-temperature calibration coefficient differential pressure compensation model set; and performing calibration matching calibration on the application scene information of the differential pressure sensor to be calibrated to obtain a differential pressure sensor precision calibration result. The technical problem that the measurement precision and stability of the sensor are poor due to the fact that the measurement precision of the differential pressure sensor is difficult to effectively calibrate in the high-temperature environment in the existing differential pressure sensor precision calibration is solved, and the technical effects of improving the measurement precision of the differential pressure sensor and improving the measurement stability and reliability are achieved.

The invention provides a real-time online self-calibration method and system for a charge and discharge test channel, and relates to the technical field of automatic calibration. According to the method, key parameters of each test channel are continuously monitored through an upper computer, and once the control precision of a certain channel exceeds a preset threshold due to deviation, a system automatically identifies the channel as a to-be-calibrated channel. And then, the system intelligently matches and allocates an available target independent calibration channel according to the channel information and the real-time operation state of each calibration channel in the calibration module. Through automatic operation of the switch matrix, a to-be-calibrated channel is disconnected from a test object and connected with a target calibration channel, the target calibration channel is controlled to carry out multi-point calibration on the to-be-calibrated channel, data are collected to generate a calibration curve, a new calibration coefficient is calculated according to the calibration curve, the coefficient is written into the to-be-calibrated channel, and after calibration is completed, the to-be-calibrated channel is calibrated. And the channel automatically recovers the original test process. On-line and closed-loop full-automatic calibration is realized in the whole process, and continuity and accuracy of test data are ensured.

The embodiment of the invention discloses an environment monitoring quality control intelligent supervision method and system, and the method comprises the steps: deploying at least three similar gas sensors at a same monitoring station to form a sensor array, and organizing the monitoring data of each sensor into an n-tuple structure; dynamically selecting at least one sensor in the sensor array in turn as a current pseudo fault injection target, and taking the rest sensors as a reference group; establishing a pollution historical convolution model for a memory effect of a pseudo fault injection target, reversely deducing a current indication error of the pseudo fault injection target through a historical exposure spectrum, and reversely estimating an undisturbed output value based on Choquet integration in combination with n-tuple output of a reference group sensor; calculating and updating an individual calibration coefficient and a confidence coefficient weight of the pseudo fault injection target; and carrying out dynamic correction and fusion output on the sensor array according to the updated calibration coefficient and confidence coefficient weight. According to the invention, real-time updating of the calibration coefficient and the confidence coefficient weight is realized, and the monitoring quality is improved.