7191 results about "Measurement precision" patented technology

The invention relates to the technical field of electricity meter metering, and discloses an electricity meter adaptive error compensation method and system, and the method comprises the steps: calibrating an electricity meter, collecting baseline data under different environment conditions, and recording a measurement error; environment data and ammeter data are collected in real time through an ammeter, and key features are extracted; constructing an error model, and predicting the error of the current ammeter data; and performing real-time correction and parameter adjustment according to the prediction error, and outputting the corrected measurement data. By introducing a real-time error prediction and dynamic compensation mechanism based on environmental data and combining a particle swarm optimization algorithm to optimize regularization parameters in a ridge regression model, the measurement precision of the electric meter under a complex environmental condition is effectively improved. The method can adaptively adjust the measurement data of the electric meter, reduces errors caused by environmental factors, improves the accuracy and stability of electric power measurement, and provides more reliable data support for an electric power management and monitoring system.

The invention discloses a zero point correction method for an electromagnetic flowmeter based on pressure compensation, which relates to the technical field of industrial flow measurement, and is characterized in that abnormal data is corrected through multi-parameter data acquisition and preprocessing by using Kalman filtering denoising and an isolated forest algorithm, so that the accuracy of the data is ensured; a multi-parameter compensation model is further constructed, an LSTM network is combined with an attention mechanism to dynamically distribute weights, and the weights are lightly deployed to an embedded microcontroller through a TensorFlow Lite framework, so that rapid reasoning and real-time correction are realized; in the operation process, an embedded system reads preprocessed data in real time, a model is input to obtain a zero drift compensation value, compensation is carried out by comprehensively considering factors such as fluid density, pipeline vibration and electromagnetic interference, and a self-adaptive weight adjustment mechanism is introduced to optimize compensation precision; the measuring precision and the long-term operation reliability of the electromagnetic flowmeter are remarkably improved, and the electromagnetic flowmeter is suitable for flow measurement under complex working conditions.

The invention discloses a high-temperature airflow two-dimensional temperature field and velocity field synchronous measurement system and method based on laser-induced phosphorescence, and the system comprises phosphorescence particles, a low-frequency double-pulse laser, an image collection device, a synchronous controller, and an image processing device. The image processing device analyzes the gray intensity ratio of different wave band images acquired by the two PIV cameras at the same time, and combines a temperature response function calibrated by an experiment to realize inversion of a temperature field; meanwhile, a double-frame time-resolved image acquired by any PIV camera is subjected to cross-correlation calculation, particle displacement is extracted, and then a velocity field is reconstructed. According to the invention, synchronous acquisition of temperature and speed based on the same data source is realized, and the system has the remarkable advantages of simple structure, high measurement precision and wide application environment.

The invention relates to the technical field of industrial automation control, in particular to a container liquid level measurement method, system and equipment of a pressure sensor and a medium, and provides a method for eliminating gas phase pressure influence based on a double-sensor differential measurement mechanism and dynamically correcting liquid density and sensor drift errors in combination with a temperature compensation model. The temperature data are linked in real time through a three-dimensional compensation function, density calculation and drift correction are synchronously adjusted, and multi-parameter dynamic decoupling and self-adaptive compensation are achieved; a collaborative measurement mechanism is adopted to integrate bottom and top sensor data, and a built-in temperature probe and a preset threshold are combined to complete multi-source signal fusion and compensation calculation; a dynamic calibration method is designed, and system errors are eliminated through reference pressure point calibration and structure coefficient correction; constructing a closed-loop signal processing flow, and integrating high-precision analog-to-digital conversion, digital filtering and real-time algorithm to output a compensated liquid level value; the method improves the measurement precision and stability, and is suitable for temperature change, gas phase pressure fluctuation and multi-medium scenes.

The embodiment of the invention discloses a multi-mode adaptive industrial instrument intelligent control system based on deep learning, and relates to the technical field of industrial instrument intelligent systems. The system comprises a multi-modal data acquisition module used for acquiring multi-modal data of an industrial instrument in real time, the multi-modal data comprising at least two of image, sound, temperature and vibration data; the heterogeneous data fusion module is used for carrying out space-time alignment and feature fusion on the multi-modal data; the deep reinforcement learning control module is used for dynamically optimizing a control strategy and generating a control instruction; the self-adaptive human-computer interaction interface is used for providing visual operation and real-time feedback; and the predictive maintenance subsystem is used for predicting faults and generating maintenance suggestions based on the equipment state. The multi-modal data fusion technology of dynamic weight distribution is adopted, the problem that a traditional single sensor loses efficacy under the complex working condition is solved, and the performance of an industrial instrument in the aspects of measurement precision, self-adaptability and operation and maintenance efficiency is improved.

The invention relates to the technical field of calibration tests, in particular to an intelligent metering calibration method and system, and the method comprises the following steps: calculating the similarity between data points, constructing a similarity matrix, further calculating the fitting degree, carrying out the spectral decomposition, extracting a feature vector, carrying out the dimension reduction, mapping to a low-dimensional space, carrying out the data point clustering based on a feature vector matrix, and carrying out the calibration of the data points. An error cluster is identified and an error pattern is determined. According to the method, by calculating the similarity between the data points and mapping the similarity to the low-dimensional space, the error modes can be efficiently recognized and classified, the error correction path can be dynamically adjusted, error correction is more flexible and real-time, the error analysis depth is improved through spectral decomposition and feature vector extraction, and the error analysis accuracy is improved. Therefore, the error trends of the equipment under different conditions are accurately identified, the measurement precision and stability are remarkably improved, the error correction path parameters are updated in real time, the adaptability of the system to the operation change of the equipment is enhanced, and the calibration time is effectively shortened.

The invention relates to the technical field of signal parameter measurement, and provides a parameter measurement method for a frequency modulation monitoring antenna, which realizes self-adaptive monitoring and accurate measurement of a complex electromagnetic environment through multi-dimensional data acquisition, intelligent analysis and dynamic optimization, and deeply integrates environment perception, signal processing and parameter optimization. A complete technical chain is formed, so that the parameter measurement method can have self-learning and self-adjusting capabilities, can cope with environmental changes and interference challenges in real time, remarkably improves the monitoring efficiency and the measurement precision, and provides a systematic solution for the application of a frequency modulation monitoring antenna in a complex scene.

The invention relates to a vehicle vibration response prediction method based on multi-modal feature depth fusion, which belongs to the field of computer vision and signal processing, and is characterized by comprising the following steps: constructing a vehicle vibration excitation and response triple data set based on multi-modal data; constructing a vehicle vibration response prediction model based on multi-modal feature deep fusion; training, verifying and testing the vehicle vibration response prediction model; and predicting a vehicle vibration response signal. According to the method, the problems that the traditional road excitation measurement precision is relatively poor and the calculation complexity and the structure fineness are difficult to balance by vibration signal prediction are solved, and the image feature extraction advantage of an EfficientNet framework and the time sequence feature extraction advantage of a Transformer framework are applied to the regression prediction of the vehicle vibration response signal; multi-modal features are fused through a bidirectional cross attention mechanism obeying Dirichlet distribution, and high prediction accuracy is obtained. And a method with relatively high prediction accuracy is provided for the field of vehicle vibration response signal prediction.

The invention relates to the technical field of vision, in particular to an object monitoring method based on a multi-camera joint calibration technology and a monitoring camera thereof. The method comprises the following steps: driving all cameras to synchronously shoot a calibration reference object with known geometric characteristics, and solving internal and external parameters of each camera and an accurate space pose relationship between the internal and external parameters by utilizing shot images to form a joint space relationship chain; controlling the camera array to synchronously shoot a target object, and correspondingly converting the two-dimensional image points acquired by the cameras into spatial point coordinates in a unified three-dimensional coordinate system by using the joint spatial relation chain to generate three-dimensional point cloud data of the target object; and processing the generated three-dimensional point cloud data, extracting key geometric features of the target object in real time, performing comparative analysis on the extracted features and a preset standard or a historical state, and outputting a state monitoring result of the target object. According to the invention, the influence of temperature drift and mechanical vibration on the measurement precision is effectively suppressed, and the stability of long-term monitoring of an industrial field is guaranteed.

The invention discloses an absolute type planar two-dimensional time grating displacement sensor based on an alternating electric field and a measuring method. Excitation signals are applied to X excitation pairs in sequence, when an induction electrode generates an induction signal, the excitation signals are stopped from being applied to the remaining X excitation pairs, and four paths of electric signals generated by an induction group are processed, so that the absolute type planar two-dimensional time grating displacement sensor based on the alternating electric field is obtained. Obtaining the X excitation antipode of the movable ruler base body and the displacement position of the movable ruler base body in the X excitation antipode so as to obtain the two-dimensional time grating absolute displacement value of the movable ruler base body relative to the fixed ruler base body in the X direction; similarly, a two-dimensional time grating absolute displacement value of the movable ruler base body in the Y direction is obtained; and then taking the two-dimensional time grating absolute displacement values in the XY direction as the coordinates of the movable ruler base body in the XY direction to obtain the absolute displacement of the movable ruler base body. The absolute positions in the X direction and the Y direction are obtained in a scanning mode so as to achieve planar two-dimensional absolute displacement measurement, accumulated errors and random errors can be reduced, the measurement precision can be improved, and wide-range high-precision measurement can be achieved.

The invention relates to an intelligent self-adaptive gas sensor adjustment controller and a working method thereof, and belongs to the technical field of gas detection. The adjustment controller comprises a main control module, a gas detection module, an environmental parameter module, an adjustment execution module, a communication module and a power management module, the main control module compensates detection parameters obtained by the gas detection module according to environmental parameter information obtained by the environmental parameter module in combination with built-in standard parameters and a compensation algorithm, and the adjustment execution module performs adjustment according to the compensation parameters. And whether the calibration execution module is started to calibrate the gas detection module is determined by judging the output stability of the gas detection module. According to the control method of the adjustment controller, through intelligent and self-adaptive adjustment control, the measurement precision, stability and applicability of the gas sensor are remarkably improved, and a reliable solution is provided for gas detection in a complex environment.

The invention discloses an integrated measurement method and system for hydrological elements in a high-salinity and high-sand environment, and relates to the technical field of hydrological monitoring, and the method comprises the steps: correcting the theoretical signal receiving strength of each sonar through an established sound attenuation model, and then calculating an effective signal-to-noise ratio, thereby achieving the measurement of the underwater topography in the high-salinity and high-sand environment. According to the method, a dynamic weight fusion algorithm is adopted to perform data fusion on the water depth data of each sonar to obtain fused water depth data, and an inversion method based on residual error minimization is adopted to perform iterative optimization on model parameters, so that the accuracy is relatively high. When the water velocity and the flow rate are measured in the high-salt and high-sand environment, iterative decoupling is carried out based on the sediment particle motion comprehensive model to obtain the sediment particle velocity, then the water velocity is updated based on the measured apparent velocity and the difference value, and after the updated water velocity is converged, the flow rate is calculated. And the accurate water flow rate can be calculated by combining the flow cross section area. The measurement precision of the unmanned ship on the hydrological elements in the saline-alkali area can be improved.

The invention relates to the technical field of topographic survey, in particular to an overwater and underwater topographic survey method based on cooperation of an unmanned ship and an unmanned aerial vehicle. The method comprises the following steps: acquiring platform parameter data of an unmanned ship and an unmanned aerial vehicle; according to the platform parameter data, isomerization grouping based on the residual electric quantity, the communication signal strength, the cruising ability and the measurement precision is carried out, a collaborative formation scheme is determined according to a preset water area measurement task sequence, and collaborative parameter data is obtained; acquiring environment data of a measurement area; and performing regional division modeling based on water area topographic features and environmental complexity according to the environmental data of the measurement region, and applying the collaborative parameter data to a regional model to obtain a topological model of the measurement region. The unmanned ship is used as a mobile charging platform, real-time electric quantity monitoring and docking charging mechanisms are combined, the endurance guarantee of the unmanned aerial vehicle is realized through energy supply strategy optimization, and the continuity and stability of tasks are ensured.

The invention discloses a highway engineering road and bridge measurement method based on BIM, and belongs to the technical field of highway engineering measurement. According to the method, the problems that the modeling efficiency and accuracy are difficult to consider, the modeling precision of a non-important area is redundant and the like in the existing road and bridge measurement method for the highway engineering are solved. The method comprises the following steps: acquiring satellite positioning data by using a satellite positioning system in a measurement area, acquiring point cloud data by using laser scanning equipment, and acquiring road and bridge images by using image acquisition equipment; converting satellite positioning data into unified coordinate system data information, carrying out spatial registration on the unified coordinate system data information and the point cloud data, and dividing an important region and a non-important region; constructing a precise three-dimensional point cloud model for the important area, constructing a path point cloud model for the non-important area, and integrating road and bridge images; and finally fusing the model to obtain road and bridge parameters. The method can improve the model efficiency and reduce the model resource overhead while effectively improving the measurement precision, and is suitable for the measurement work of roads and bridges of highway engineering in various environments.

The invention discloses a full-automatic cable vibration high-precision measurement method based on a machine vision technology, and relates to the technical field of structural vibration measurement. The method comprises the following steps: installing and calibrating equipment, and ensuring that a cable plane coincides with an imaging plane; high-frame-rate video acquisition is carried out, and comparison verification is carried out in combination with an accelerometer; screening effective pixels based on the pixel intensity time sequence variance, and constructing a pixel intensity space-time matrix by using the time sequence of the pixels; sVD decomposition is adopted to extract an accumulated energy ratio gt; 90% of the main modes are reconstructed, and real signals are revealed; a plurality of inhaul cables are automatically positioned and coded through gradient features and Hough transform; sub-pixel-level vertical displacement is calculated by applying an optical flow method, and median filtering is combined to resist noise; fourier transform is carried out to obtain a spectrogram, and a fundamental frequency is identified; and calculating cable force based on a string pulling theorem. According to the method, remote, full-field and multi-target synchronous monitoring is realized, the displacement measurement precision reaches a sub-pixel level, and a high-precision and full-automatic solution is provided for health monitoring of structures such as bridges.

The invention relates to the technical field of sensor noise reduction, and particularly discloses a fiber bragg grating sensing system based on deep learning and a noise reduction method.The method comprises the steps that firstly, original reflection spectrum data of a fiber bragg grating sensor and temperature data of the environment where the fiber bragg grating sensor is located are synchronously collected, and a data processing algorithm based on deep learning is introduced; the method comprises the following steps: performing empirical mode decomposition and waveform feature extraction on original reflectance spectrum data to capture intrinsic intrinsic mode waveform features of the original reflectance spectrum data, then further combining environment temperature data, and performing implicit query interactive response coding on environment temperature features and the intrinsic mode waveform features of the original reflectance spectrum to obtain the intrinsic mode waveform features of the original reflectance spectrum; therefore, the dynamic influence mode of the environment temperature on the reflectance spectrum data can be understood, and the temperature compensation and noise reduction of the reflectance spectrum data can be realized. Through the mode, the influence of temperature fluctuation on the reflection spectrum can be adaptively identified and compensated, the noise caused by environment temperature fluctuation is effectively inhibited, and the measurement precision of the fiber grating sensor is improved.

The invention discloses a deep foundation pit excavation deformation real-time monitoring system based on relative measurement. The deep foundation pit excavation deformation real-time monitoring system comprises a relative measurement sensor group, a data acquisition and preprocessing module, a wireless data transmission module, a cloud data processing and analysis module, an intelligent risk assessment module, a visual alarm module and a solar power supply and energy storage management module. The relative measurement sensor group collects deformation data of the deep foundation pit, the data acquisition and preprocessing module performs primary processing on the data, the wireless data transmission module stably transmits the data to the cloud, the cloud data processing and analysis module performs deformation prediction, and the intelligent risk assessment module performs risk grading. The visual alarm module gives an alarm in real time and carries out emergency notification according to different risk levels, and the solar power supply and energy storage management module guarantees continuous operation of the system. The system solves the problems of measurement precision, data transmission, risk assessment, power supply stability and the like of an existing monitoring system, provides powerful support for safe construction of the deep foundation pit, and has remarkable benefits.

The invention relates to wide-range multi-component sensor calibration equipment and a wide-range multi-component sensor calibration method. The method comprises the following steps: firstly, checking equipment parts and setting a target temperature range and a compensation model of each temperature interval; then, dynamic temperature control is started, jig deformation is monitored in real time, a transient temperature gradient suppression technology is applied, multi-physical-quantity calibration is executed, and a compensation measurement value is output; then setting multi-environment coupling calibration test conditions to simulate actual working conditions, and monitoring and recording calibration data of each physical quantity; and finally, calculating a calibration error by combining a calibration result and a reference standard value. According to the process, by precisely setting parameters and combining dynamic control, real-time monitoring and multi-physical-quantity calibration, the transient temperature gradient influence is effectively inhibited, and the measurement precision of the sensor in a complex environment is ensured; the temperature control performance is improved through the micro soaking film and the intelligent temperature control strategy, the actual working condition is simulated through multi-environment coupling testing, the accuracy and reliability of the calibration result are remarkably improved through compensation and error calculation, and guarantee is provided for precise application of the sensor.

The invention discloses a high-precision electric power measurement method based on an intelligent electric meter, and relates to the technical field of electric power measurement. According to the invention, a plurality of high-precision voltage and current sensors with temperature compensation are uniformly arranged in a circuit, a low-noise front-end conditioning and multi-channel high-resolution ADC synchronous sampling technology is adopted, and a digital phase-locked loop is introduced to realize accurate correction of a sampling clock. And performing multi-stage weighted fusion, time domain instantaneous power calculation and FFT frequency domain decomposition compensation on the acquired data, and finally accurately calculating the real power in a power grid period. According to the method, measurement errors caused by temperature excursion, phase deviation and harmonic interference in the prior art are effectively solved, the measurement precision and stability of the system are remarkably improved, and the method is suitable for high-precision power monitoring in a complex power grid environment.

The invention relates to the technical field of fluid measurement, in particular to a multimode signal fusion and self-adaptive processing ultrasonic flowmeter and a measuring method. The multimode signal fusion and self-adaptive processing ultrasonic flowmeter comprises an ultrasonic transducer, a signal generation driving module, a signal receiving and conditioning module, a control module, a signal processing module, a signal quality evaluation module and a sound velocity calculation and compensation module. According to the method, the time difference method and Doppler method signals are fused, the self-adaptive processing strategy is adopted to improve the measurement precision of the low-flow-velocity fluid and the impurity-containing fluid, the measurement precision of the low-flow-velocity fluid can be remarkably improved, the adaptability to complex fluid is enhanced, the overall measurement reliability is improved, the Doppler method precision is optimized, and the intelligent degree is high.

The invention relates to the technical field of ground resistance detection, in particular to a single-core cable ground resistance detection method capable of resisting strong power frequency interference. High-frequency signals are injected in a non-contact mode through a coupling type capacitor clamp, background voltage and current signals are collected firstly, and injection frequency far away from power frequency and harmonic waves is selected through Fourier analysis; cancelling background noise by adopting a normalized least mean square adaptive filter to generate an enhanced signal; the signal is down-converted to a base band through digital quadrature demodulation, a Kalman filter estimates the amplitude and the phase in real time, and the state and noise parameters are periodically calibrated through a compressed sensing algorithm; and finally, loop impedance is calculated according to the voltage and current amplitudes and the phase difference to obtain grounding resistance. The method has the advantages of being non-contact, high in safety, strong in anti-interference capability, high in measurement precision and the like, and is suitable for monitoring the grounding state of the cable in a complex electromagnetic environment.

The present invention provides an unmanned ship laser ranging optimization method and system based on dynamic environment perception, which relates to the field of navigation and obstacle avoidance technology of unmanned ships. The method includes: sensing the surrounding environment data in real time through sensors to obtain obstacle position, speed and heading information; based on the dynamic characteristics of the environment, using an adaptive algorithm to dynamically adjust the measurement frequency and angle of the laser rangefinder to optimize the measurement accuracy; combining the environmental data with the laser ranging results, using a path planning algorithm to optimize the obstacle avoidance route, and adjusting the heading in real time; adjusting the laser ranging parameters according to dynamic feedback information to ensure the stability of navigation and obstacle avoidance performance. The present invention can effectively improve the laser ranging accuracy of unmanned ships in complex dynamic environments, optimize navigation safety and obstacle avoidance capabilities, and has broad application prospects.

The invention discloses a pulse eddy current signal late period slope feature extraction method and system based on segmentation fitting, and belongs to the technical field of nondestructive testing. The method comprises the following steps: performing logarithmic transformation and filtering processing on a to-be-detected eddy current signal; intercepting a characteristic signal segment based on the filtering signal; dividing the feature signal segment into a plurality of sub-segments, performing piecewise linear fitting, determining a linear segment, and extracting a slope as a feature value; repeating the steps to obtain characteristic values of the test pieces with different thicknesses, performing curve fitting according to the characteristic values of the test pieces with different thicknesses and the corresponding thicknesses, and calculating a fitting error; and finally, iteratively optimizing the division number of the sub-segments by taking the minimum fitting error as a target. Through adaptive filtering, segmentation fitting and an intelligent optimization algorithm, the anti-interference performance, the linearity and the measurement precision of pulse eddy current signal feature extraction are remarkably improved, and efficient and reliable thickness detection of the high-temperature and high-pressure industrial pipeline under the condition that a heat preservation layer does not need to be disassembled is achieved.

The invention belongs to the technical field of PCB detection, and particularly relates to a probe tip deviation compensation method, system and equipment, and the method comprises the steps: building a reference coordinate system, controlling a probe swing arm to rotate to a vertical position and a horizontal position respectively, and employing a bonding pad combination on a special calibration plate to calibrate the probe tip deviation. An electric signal detection mode is adopted to accurately measure the deviation value of the needle point in the X-axis direction and the Y-axis direction, and the position of the probe is automatically compensated according to the deviation value. The system comprises a high-precision driving module, a visual positioning module and a signal acquisition module, and realizes a full-automatic calibration process. According to the method, a horizontal and vertical double-position detection mode is innovatively adopted, complex angle calculation is avoided, the calibration efficiency and precision are greatly improved, the problem of needle point position deviation caused by mechanical errors and long-term use in a traditional method is effectively solved, the measurement precision of PCB detection equipment is remarkably improved, and the detection precision of the PCB detection equipment is greatly improved. Meanwhile, the maintenance cost and the operation difficulty are reduced, and the method is suitable for the field of high-precision PCB detection.

The invention provides a multichannel gas ultrasonic flowmeter, which relates to the technical field of flow measurement and comprises a hardware layer and a software layer, the hardware layer comprises a pipeline, a connecting mechanism, a multichannel ultrasonic transducer, a pressure sensor, a temperature sensor, a wiring terminal box and a control box with an LCD display screen; the software layer comprises a data acquisition module, a preprocessing module, a multichannel speed measurement module, a data fusion module, a dynamic parameter compensation module, a flow calculation module, a man-machine interaction module, a communication module and a storage module. Pipeline section flow velocity information is collected through a multichannel ultrasonic transducer array, and a complex flow state is fitted in combination with a weighted fusion algorithm; the flow is dynamically compensated and corrected based on pressure and temperature; reliable operation of the system is guaranteed by means of hardware redundancy and a software verification diagnosis mechanism, the problems that a traditional flowmeter is low in measurement precision and poor in working condition adaptability are solved, and high-precision and stable gas flow measurement is achieved.

The invention discloses a slurry flow velocity measurement method, device and system for a slurry pump, and relates to the technical field of slurry flow velocity measurement, and the method comprises the steps: employing an ultrasonic transducer to transmit an ultrasonic signal to a slurry pipeline and receive a reflection signal, and obtaining ultrasonic propagation data; constructing a slurry flow velocity profile model according to the ultrasonic propagation data, and calculating slurry flow velocity and solid phase concentration distribution based on the slurry flow velocity profile model; and based on the slurry flow velocity and the solid-phase concentration distribution, rheological correction is conducted by combining the slurry flow state, and the actual slurry flow velocity of the slurry pump is obtained. According to the method, the non-Newtonian characteristic and the solid-phase migration effect of the slurry are considered in the measurement process, a rheological parameter dynamic correction mechanism based on the Reynolds number is established, and the measurement precision under the working conditions of high-sand-content and high-density slurry is improved compared with a traditional method.

The invention relates to the field of diameter measurement, in particular to a steel wire rope infrared laser diameter detection device and method, and the device comprises an installation seat which is connected with a measurement assembly used for measuring the diameter of a steel wire rope. According to the invention, through cooperation between the two mounting ring plates and the limiting rollers correspondingly limited on the two mounting ring plates, a steel wire rope to be measured is supported and limited, and then through cooperation between the laser emitting end and the laser receiving end correspondingly connected in the two mounting ring plates, the steel wire rope to be measured is measured. The steel wire rope diameter measuring device achieves the effect of measuring the diameter of a steel wire rope in a non-contact mode, effectively reduces friction and vibration during relative sliding of the steel wire rope and the shell through cooperation of a limiting roller and a buffer spring, and improves the measuring precision.

The invention relates to the technical field of electrical measurement, and discloses an electrical measurement instrument dynamic calibration error compensation method, which comprises the following steps: S1, multi-source data real-time acquisition: integrating a temperature sensor, a humidity sensor and an electromagnetic interference detection module in a measurement instrument, configuring voltage, current, frequency and other measurement channels, and carrying out multi-source data real-time acquisition at the frequency of not less than 100HZ; environmental parameters (temperature T, humidity H and electromagnetic interference intensity E) and measurement data (model characteristic parameters X1, X2,..., Xn such as voltage, current and frequency) are synchronously acquired. According to the electrical measuring instrument dynamic calibration error compensation method, through multi-source data real-time acquisition and composite error model construction, in combination with multiple linear regression and an improved BP neural network, environment and measurement signal changes are comprehensively captured, an error compensation value is accurately calculated, a measurement error can be effectively controlled within an extremely small range, and the error compensation accuracy is improved. Compared with a traditional method, the measurement precision is greatly improved.

The invention relates to the technical field of machine vision, in particular to a precision part size automatic detection method and system based on machine vision, precision part images are collected through a high-precision industrial camera, part positioning is carried out, sub-pixel-level topological feature mapping is carried out on interested area images, and precision part size automatic detection is carried out. Comprising the steps of gray histogram equalization, gray morphological processing, edge detection and edge chain code tracking, construction of an edge point topological feature space, execution of sub-pixel subdivision, obtaining of an edge line through contour analysis of a feature distance and a feature angle, and double-constraint geometric reconstruction based on the edge line. The characteristic distance and the characteristic angle are used for rotation matrix conversion and geometric dimension calculation, a relation model of the geometric dimension and the actual dimension of the part is established, precise part dimension measurement is achieved through dynamic error analysis and compensation, the measurement precision is remarkably improved, the risk caused by unreliability of a single characteristic is effectively reduced, and the measurement accuracy is improved. And the measurement stability is improved.

The invention provides a gas compressor moving blade tip clearance measuring method and device, and belongs to the field of aero-gas turbine gas compressors. The problems of low measurement precision, low measurement efficiency and small measurement range in the prior art are solved. The method comprises the following steps that an angle encoder is installed on a main shaft, and a three-dimensional laser profile measuring instrument is arranged on the blade tip side of a blade at intervals; the impeller is rotated, the three-dimensional laser profile measuring instrument scans the blade tip, and three-dimensional point cloud data of the whole circle of blade tip profile are obtained; after the casing and the impeller are assembled, a plurality of continuous blades on the impeller are detached, and the three-dimensional laser profile measuring instrument is arranged at the vacant position of the impeller; the impeller is rotated, the three-dimensional laser profile measuring instrument scans the inner wall of the casing, and three-dimensional point cloud data of the whole circle of the inner wall of the casing are obtained; processing data; registering the processed three-dimensional point cloud data of the blade tip contour and the processed three-dimensional point cloud data of the inner wall in the same coordinate system to form a registration model; and the blade tip clearance value of the whole circle is calculated. The method is mainly used for measuring the blade tip clearance.