2602results about "Using subsonic/sonic/ultrasonic vibration means" patented technology

The invention discloses a glass ceramic thickness detection method and a related device, and the method comprises the steps: obtaining a vibration signal generated in a glass ceramic thinning and grinding process, and extracting a vibration dominant frequency, a frequency spectrum centroid frequency and a frequency band energy distribution ratio as thickness characteristic parameters through fast Fourier transform processing; three-dimensional position coordinates of the grinding head are obtained, space mapping and weighted average processing are conducted on the thickness characteristic parameters, and space distribution of the thickness characteristic parameters is obtained; performing process interference compensation and sliding window time sequence smoothing processing according to the grinding process parameters to obtain stable thickness characteristic distribution; based on the stable thickness feature distribution and the current grinding process, final thickness distribution is predicted, and a thickness qualification pre-judgment result is obtained; and extracting a time sequence change characteristic of the thickness characteristic parameter as a vibration evolution index, and performing comprehensive quality evaluation in combination with a thickness eligibility pre-judgment result. According to the scheme, the thickness can be detected in real time in the thinning and grinding process of the microcrystalline glass, and the production efficiency is improved.

Disclosed in the present invention is a bridge scour curved surface morphological feature reconstruction method based on three-dimensional sonar point clouds, comprising the following steps: collecting point cloud data of a three-dimensional morphology of an underwater riverbed terrain near a bridge foundation, and acquiring original point cloud data of a complete morphology of an underwater riverbed; performing denoising and ball pivoting reconstruction preprocessing on the collected original point cloud data to complete preliminary reconstruction of point clouds; on the basis of the point cloud data having undergone preliminary reconstruction, performing point cloud binarization-based scour morphology recognition on the basis of a computer vision principle, calculating scour pit element classification values of all the point clouds, and recognizing scour pit point clouds; on the basis of the recognized scour pit point clouds, using a K-means clustering algorithm for clustering, and calculating the maximum depth of each pier scour pit; and on the basis of the obtained scour pit element classification values of all the point clouds, providing a curved surface reconstruction method based on scour recognition to perform high-precision curved surface reconstruction on the scour pits. The present invention can achieve high-precision scour pit morphology reconstruction.

The invention discloses an electromagnetic ultrasonic thickness detection method and system based on a miniaturized low-power-consumption internet of things, and the method comprises the steps: carrying out the parameter optimization processing through a pulse coding excitation algorithm according to the electromagnetic characteristic parameters of a target material and a preset detection precision requirement, and outputting a low-power-consumption excitation parameter set; driving an electromagnetic ultrasonic transducer to generate a detection signal based on the low-power-consumption excitation parameter set, and outputting a compressed echo signal; performing multi-scale intrinsic mode decomposition on the compressed echo signal, and outputting a thickness correlation characteristic parameter set; inputting the thickness correlation characteristic parameter set into a depth residual error-attention network model, and outputting a thickness prediction result; and performing multi-node data fusion on the thickness prediction result based on an Internet of Things cloud platform to generate a final thickness detection report. According to the embodiment of the invention, high-precision and traceable thickness detection can be realized based on the miniaturized low-power-consumption Internet of Things.

The invention discloses a pan-tilt-free dynamic compensation water flow velocity measurement system used in a vibration environment. The pan-tilt-free dynamic compensation water flow velocity measurement system comprises a multi-source sensor module, a dynamic motion compensation module, a self-adaptive Kalman filter bank and a data credibility evaluation module, the multi-source sensor module is used for collecting platform attitude information, water flow original speed and platform height. The dynamic motion compensation module comprises an attitude solution sub-module and an error calculation sub-module and is used for realizing flow velocity dynamic compensation under the condition of no holder structure; the adaptive Kalman filter bank comprises an angular velocity filter and a flow velocity filter, the angular velocity filter dynamically adjusts filtering parameters according to the angular motion intensity of the platform, and the flow velocity filter dynamically switches processing strategies according to the effectiveness of a water flow signal measured by the radar; and the data credibility evaluation module is used for carrying out stability judgment based on a sliding window variance-trend joint detection algorithm. According to the invention, attitude calculation and motion compensation are fused, and accurate measurement of the water flow velocity of the holder-free platform in a vibration environment is realized.

The invention discloses a tower foundation landslide monitoring method, system and device and a medium. The method comprises the steps that InSAR data and GNSS data are fused to conduct wide-area deformation monitoring, a quadratic fitting model is established to conduct error dynamic correction on InSAR observation values, and a potential landslide hidden danger area is recognized; the method comprises the following steps: performing multi-dimensional cooperative monitoring on a potential landslide hidden danger area through an unmanned aerial vehicle carrying a sensor, and fusing multi-source data by utilizing edge computing equipment to generate a landslide risk thermodynamic diagram; an active waveguide acoustic emission system is adopted to capture landslide deep deformation signals, and early warning is achieved through ringing counting and acoustic emissivity parameters. According to the invention, the InSAR and GNSS technologies are fused, and the Kalman filtering algorithm is combined, so that the precision of surface deformation monitoring is improved; the InSAR observation value is constrained and corrected through the GNSS observation value, so that the deformation monitoring precision is improved; more accurate data support is provided for landslide monitoring through the unmanned aerial vehicle carrying sensor equipment; powerful support is provided for early warning of landslide disasters through an active waveguide acoustic emission technology.

A system for providing an interactive inspection map of an inspection surface inspected by an inspection robot includes an inspection circuit structured to interpret inspection data of the inspection surface from the inspection robot and a user interaction circuit structured to interpret a user focus value from a user device. The user focus value includes an activation state value. The system further includes an inspection visualization circuit structured to provide the interactive inspection map to the user device in response to the user focus value. The interactive inspection map is based on the inspection data. Also, the system includes an inspection data validation circuit that determines an inspection data validity description of the inspection data. The inspection data validity description is provided as a display layer on the interactive inspection map to indicate whether the inspection data is valid.

The invention discloses an ultrasonic enhanced tactile sensor system, a sensor and a sensing method. The tactile sensor system comprises a multi-mode sensing unit and a processing unit. The multi-mode sensing unit integrates an ultrasonic module and a visual tactile sensing module, ultrasonic acoustic impedance matching and optical imaging transmission are achieved through an acousto-optic matching structure, and ultrasonic echo signals and tactile deformation images can be synchronously collected. In the processing unit, an event triggering module detects a contact event based on a tactile image and generates a switching signal, and a self-adaptive processing module dynamically controls an ultrasonic mode, distance measurement during non-contact, and switching to object internal imaging or material property identification during contact according to the switching signal. And the three-level fusion processing module outputs a multi-modal sensing result through signal-level synchronous acquisition, feature-level cross-modal fusion and decision-level task switching. According to the system, multi-dimensional perception of proximity sense, surface texture and deep information is realized, and the pre-judgment and accurate operation capability of the robot in a complex scene is improved.

The invention discloses a method and a system for estimating the pile length of an engineering pile. The method comprises the following steps: acquiring a multi-source detection signal reflecting the striking response of a pile hammer and stratum prior information; on the basis of stratum prior information, carrying out physically-driven adaptive analysis on sound wave components in the multi-source detection signals, and extracting preliminary sound wave reflection features; performing correlation verification on the preliminary sound wave reflection characteristics by using vibration components in the multi-source detection signals to generate corrected reflection characteristics; and the signal quality of the corrected reflection characteristics is evaluated, an intelligent hammering control instruction is generated according to the signal quality so as to execute closed-loop enhanced signal excitation, finally, multi-modal information before and after enhancement is fused, and a final pile length estimated value is obtained through calculation. Through sound and vibration coupling verification and intelligent active excitation, the accuracy, reliability and detection depth of pile length estimation under the conditions of strong noise, complex stratum and large depth are improved.

The invention relates to the technical field of detection, and provides a non-contact thickness measurement detection method and detection equipment, a set of multi-dimensional, high-precision and self-adaptive thickness measurement system is constructed by fusing two non-contact detection technologies of laser and ultrasonic, a complete closed loop is formed from signal acquisition and processing to result fusion compensation, and the thickness measurement accuracy is improved. The method effectively breaks through the thickness measurement limitation of a single technology, adapts to complex and variable industrial measurement scenes, realizes accurate and stable measurement of the thickness of a measured object, gives consideration to dynamic compensation and environment adaptation, provides reliable technical support for the fields of high-end manufacturing, precision detection and the like, assists in improving the product quality control level, and has a wide application prospect. And the non-contact thickness measurement technology is promoted to develop to intelligence and high precision.

The invention provides an efficient crack detection and intelligent risk assessment system, belongs to the technical field of structural health monitoring, and is particularly suitable for crack detection in buildings, bridges, tunnels and industrial equipment. According to the system, comprehensive detection on the surface and the interior of a crack is realized by combining an optical imaging sensor, a laser scanning sensor and an ultrasonic sensor through a multi-mode sensor fusion technology. The system comprises a data acquisition unit, a data processing unit, a multi-modal data fusion module, a three-dimensional modeling module and an intelligent decision support module. Through an adaptive learning algorithm and a deep learning technology, the system can dynamically optimize a detection model and provide a high-precision detection result. Meanwhile, the system supports three-dimensional reconstruction and visual display of the crack, carries out real-time assessment on the crack risk through an intelligent decision support module, automatically generates a health assessment report and gives out an early warning. Compared with traditional manual detection, the system has the advantages that the comprehensiveness, the automation degree and the efficiency of detection are greatly improved, and the system is suitable for structural health monitoring in various complex scenes.

The invention discloses a bridge engineering-oriented foundation pile quality detection system, which relates to the technical field of engineering quality detection, and comprises a data acquisition module configured to acquire detection data including foundation pile construction parameters, geological environment data, stress wave signals and geometric dimension parameters, the wave velocity correction module is configured to correct a standard wave velocity through a dynamic coupling algorithm, the defect depth calculation module is configured to calculate the defect depth of a foundation pile defect, and the credibility evaluation module is configured to output a credibility correction coefficient and feed back the credibility correction coefficient to the wave velocity correction module by quantifying errors of detection data; according to the method, through multi-physical field wave velocity correction, pile diameter-defect depth double correction and credibility quantitative iteration, a high-precision, objective and traceable integrated solution is systematically provided for bridge engineering foundation pile quality detection.

The invention relates to the technical field of environmental pollution monitoring, in particular to an on-line environmental pollution monitoring method and system.The method comprises the steps that original acoustic signals of the inner side wall and the outer side wall of a curve are collected in real time in a high-risk monitoring area, propagation path compensation is conducted, and an inner side acoustic characteristic parameter set and an outer side acoustic characteristic parameter set are obtained; analyzing to obtain thickness values and adhesion strength values of biological membranes on the inner side and the outer side of the curve; inner and outer side falling risk factors are obtained through calculation, and a comprehensive falling risk value of the inner and outer side falling risk factors is calculated; when the comprehensive shedding risk value exceeds a preset shedding risk threshold value, generating biological membrane shedding risk early warning information; the monitoring problem of spatial distribution heterogeneity of the biological membrane at the pipe network bend is effectively solved, and accurate early warning of the falling risk of the biological membrane in the bend area is achieved.

The invention belongs to the field of ultrasonic oil film thickness measurement, and discloses a minimum oil film thickness calibration method considering different friction pair shape structures, which utilizes an ultrasonic oil film thickness calibration platform capable of designing a corresponding calibration test piece according to different structure shapes of a measured friction pair, and aims at the shape structure characteristics of different friction pairs. The minimum oil film thicknesses of friction pairs with different shapes and structures are accurately controlled, ultrasonic reflection signals under the different minimum oil film thicknesses are collected and subjected to frequency domain analysis processing, and on the basis, polynomial fitting is conducted on the minimum oil film thicknesses and reflection coefficients in combination with a film thickness calculation model; and the ultrasonic minimum oil film thickness calibration under a special friction pair structure is realized.

The invention discloses a method and system for measuring the ultrasonic proportionality coefficient of the thickness of a lubricating film of a sliding bearing, and the method comprises the steps: firstly, obtaining the comprehensive response coefficient of sound waves in a transition combination layer of a substrate and a lining through calculating the proportionality coefficient of a reflection echo signal of a bearing bush in an air medium and a reflection echo signal of a substrate-lining interface; characterizing the propagation rule of sound waves in a base body and lining combination layer; secondly, a proportionality coefficient is constructed based on a lubricating film reflection echo signal and a matrix-lining interface reflection echo signal, a lubricating film reflection coefficient is calculated in combination with a comprehensive response coefficient of sound waves in a matrix-lining transition combination layer, and finally the thickness of the lubricating film is solved through a resonance model method or a composite model method. According to the invention, the influence of the change of the binding force between the sensor and the substrate and the unstable voltage of ultrasonic pulse emission equipment on the reference signal can be avoided, the robustness is high, and the long-term reliable monitoring of the thickness of the lubricating film of the sliding bearing is facilitated.

The invention discloses a hydropower station diversion tunnel longitudinal crack depth detection method, which comprises the following steps: arranging ultrasonic measuring points above and below a diversion tunnel longitudinal crack to obtain a reinforced concrete sound velocity representative value; arranging ultrasonic measuring points within the length range of the crack; performing ultrasonic detection, and judging the depth of the crack through ultrasonic waves; adjusting the position of the ultrasonic measuring point according to the depth of the fracture until the ultrasonic shape is in a suitable state; and calculating the depth of each detection point of the longitudinal crack. According to the technical scheme, by means of the method for detecting the longitudinal crack depth of the reinforced concrete in the diversion tunnel of the hydropower station through the ultrasonic waves, crack depth detection and calculation of the circular tunnel are completed, and in order to judge the development condition and the stability state of the crack, the crack depth can be regularly detected in the overhaul period of a hydropower station generator set; therefore, monitoring of longitudinal crack expansion and extension is realized.

The invention relates to the technical field of industrial laser precision measurement, in particular to a laser centering device for a coupler and a using method of the laser centering device for the coupler. Light spot displacement signals and environment vibration signals are synchronously collected through a laser transmitter and an optical sensor array, and a frequency domain feature decoupling module is adopted to separate a shafting displacement component and an interference component; the time domain correlation verification module is used for calculating signal time sequence correlation and generating a deviation vector, and finally the adaptive compensation decision module is used for analyzing the deviation vector and outputting an adjustment instruction. According to the invention, effective separation of real misalignment and transient noise in a dynamic environment is realized, the technical problem of measurement misalignment of an existing laser centering device in a complex industrial environment is solved, and the coupling installation precision and the equipment operation stability are improved.

The invention relates to the technical field of rolling technology and equipment detection, in particular to a method, a system and equipment for detecting deviation of a roll gap of a rolling mill, and the method comprises the steps: constructing a vibration detection center line parallel to a roll axis of a working roll according to a to-be-processed copper material, and according to the vibration detection center line, roller vibration characteristics are acquired by taking each working roller as a unit, a vibration characteristic matrix is generated according to the machining time of the corresponding working roller, and vibration deviation comparison is performed on the vibration characteristic matrix corresponding to each working roller by establishing a reference vibration deviation model, so that a roller gap deviation detection result is obtained. The problem that weak vibration changes under high-speed and high-load working conditions are difficult to capture in roll gap deviation is effectively solved, a reference vibration deviation model is established through dynamic monitoring and analysis based on vibration signals, efficient and accurate roll gap deviation detection is achieved, and the stability of the production process is guaranteed.

The invention discloses a real-time monitoring, regulating and controlling method for concrete pouring cracks of a high-rise building, and the method comprises the steps: arranging a distributed optical fiber sensor array and an ultrasonic detector in a concrete pouring region of the high-rise building, and collecting the data of a temperature field and a strain field in concrete in real time based on the distributed optical fiber sensor array; the collected data parameters are transmitted to a data processing terminal, and a crack early warning model is established in combination with concrete material characteristic parameters; analyzing the received data by using a crack early warning model, and judging whether the concrete has cracks and the development trend of the cracks; and when the crack is monitored or the crack development risk exists, the regulation and control system is started. The system has the beneficial effects that all-directional real-time monitoring of the internal state of concrete is realized through combination of distributed optical fibers and ultrasonic detection, the coverage range is wider, and data is more comprehensive. A crack early warning model constructed based on multiple parameters is combined with a deep learning architecture, so that the precision of crack identification and trend prediction is greatly improved.

The invention discloses an electromagnetic ultrasonic resonance thickness measuring method capable of adaptively regulating and controlling sweep frequency step length, which comprises the following steps of: exciting a continuous sweep frequency signal of a certain frequency band by an electromagnetic ultrasonic probe at a variable frequency step length, forming ultrasonic waves on the surface of a workpiece, penetrating the workpiece, and reflecting on the other surface of the workpiece to measure the thickness of the workpiece. The electromagnetic ultrasonic probe receives the reflected time domain signal, time-frequency conversion is conducted on the time domain signal based on the Fourier transform principle, a spectrogram is obtained, and wall thickness information of the current measuring point is calculated according to the frequency difference. However, due to the fact that the processes of frequency sweeping excitation, ultrasonic wave receiving and data processing of a series of waveforms are slow, the real-time performance of measurement can be affected, according to the electromagnetic ultrasonic resonance thickness measurement method oriented to ultrathin wall thickness measurement, frequency domain segmentation is achieved based on signal amplitude recognition, the frequency sweeping step length is shortened near the resonance frequency, and the measurement accuracy is improved. The step length is increased in other frequency bands, full-band equal-step-length frequency sweeping is replaced by variable-step-length frequency sweeping, the frequency sweeping step number is reduced, and therefore the measurement efficiency is improved.

The invention relates to the technical field of glassware detection, and discloses a glassware thickness detection device and method.The glassware thickness detection device comprises a discharging plate fixed to a conveying line and used for fixing glassware and a detection head used for thickness detection, and a liftable positioning plate is arranged above the glassware; a rotating shaft is rotationally arranged below the positioning plate, a rotating seat is fixed to the bottom end of the rotating shaft, a first sliding groove is formed in the rotating seat, a liquid injection pipe used for coating the surface of the glassware with a coupling agent is arranged in the first sliding groove in a sliding mode, and a transmission rod is fixed to the end of the liquid injection pipe; the circumference of the rotating shaft is sleeved with a disc, and an annular wave groove for the transmission rod to slide is formed in the lower surface of the disc. According to the technical scheme, when a coupling agent is coated, the liquid injection pipe rotates to drive the transmission rod to slide along the annular wave groove, so that the liquid injection pipe can swing back and forth while rotating, and the coating effect of the coupling agent is better.

The invention discloses an MGPCC fracture damage monitoring method based on AE and DIC, and relates to the technical field of building material fracture damage monitoring, the method comprises the following steps: preparing an MGPCC fracture test piece, arranging an acoustic emission probe, installing the test piece on a 3-P-B fracture test device, carrying out displacement control loading, collecting AE signals and shooting images in real time during loading, and determining the fracture damage of the MGPCC. Then analyzing characteristic parameters, images and the like to determine FPZ related conditions, and finally establishing a fracture damage evolution model in combination with a monitoring result. Spatial distribution and characteristic parameters of a damage source are monitored in real time through the AE technology, a strain cloud picture and a displacement field are accurately obtained in combination with the DIC technology, microcrack propagation and FPZ formation and evolution laws in the MGPCC fracture process are revealed, multi-dimensional quantitative characterization of the fracture damage process is achieved, and the method is suitable for mass production. A more comprehensive and accurate technical means is provided for building material fracture damage monitoring, and the blank of MGPCC multi-scale crack resistance and damage evolution research is filled.

A method of monitoring both liner wear and charge impact in an industrial mill uses a sensor mounted on an elongated element deployed through a shell into a liner of the mill. The elongated element wears at a same rate as the liner under conditions within the shell. Liner wear is related to a reduction in length of the elongated element as measured by travel time of an ultrasound wave, while location and strength of charge impact is related to change in amplitude of vibrations caused by the charge impact. Liner wear measurement can be improved by using shear ultrasound waves instead of conventional longitudinal ultrasound waves. A mill monitoring apparatus has a means for acquiring ultrasonic waves and audible sound waves using the same digitizer; a means for determining the angular position of the monitoring apparatus; and a means for supplying electric power to the apparatus.

The invention relates to the technical field of image processing, in particular to an intelligent detection method and system for support turning. The method comprises the steps that sensor signals of the support in the turning machining process are obtained in real time; constructing a sensor topological graph; extracting real-time time sequence process features reflecting the dynamic response of the tool-workpiece-machine tool system in the sensor topological graph; inputting the real-time time sequence process features into a trained multi-task prediction model, and outputting prediction deviation values of a plurality of geometric dimensions of the support and a prediction surface defect mask pattern; and if all the predicted deviation values are within the corresponding tolerance threshold values and the ratio of the defect area of the predicted surface defect mask pattern to the total area of the bracket is smaller than a set area threshold value, judging that the expected quality state of the bracket is qualified. According to the scheme, the expected quality state of the support product can be comprehensively judged in real time.

The invention provides a building curtain wall deformation degree detection method and system, and relates to the technical field of intelligent building monitoring, and the method comprises the steps: obtaining multi-modal curtain wall data of a target building curtain wall based on a multi-modal data collection network; constructing a curtain wall deformation detection model, inputting the multi-modal curtain wall data into the curtain wall deformation detection model, and generating a curtain wall deformation detection result; based on a three-level alarm response mechanism, triggering an alarm response of a corresponding level according to a curtain wall deformation detection result; based on a model closed-loop optimization mechanism, parameters of the curtain wall deformation detection model are correspondingly adjusted, so that comprehensive, accurate and real-time detection and early warning can be performed on the deformation degree of the building curtain wall, the requirement of manual intervention is greatly reduced, the curtain wall detection efficiency is improved, meanwhile, the continuous operation capability and the immediate response characteristic of a detection system are guaranteed, and the detection accuracy is improved. And the safety and the reliability of the building curtain wall are improved.

The invention discloses a method for jointly detecting corrosion defects of a pressure pipeline by utilizing multiple guided wave modes, relates to an ultrasonic non-destructive testing technology, and is used for solving the problem that the accuracy is relatively low when a single guided wave mode is used for detecting. The method for detecting the corrosion defect of the pressure pipeline comprises the following steps: calculating ultrasonic guided wave dispersion data of the pressure pipeline, and determining the center frequency of a transducer according to the dispersion data; the method comprises the following steps: arranging ultrasonic transducer annular arrays on two sides of a to-be-detected pressure pipeline, and acquiring ultrasonic guided wave data detected by the pressure pipeline in an L (0, 1) mode and a T (0, 2) mode; preprocessing the array waveform data to obtain detection data which can be used for guided wave imaging; according to the L (0, 1) mode guided wave data, a full waveform inversion method is adopted to invert the wall thickness of the pipeline corrosion defect; judging whether the pipeline defect exceeds the detection depth range of the T (0, 2) mode, and if the pipeline defect exceeds the detection depth range, ending; and if not, inverting the wall thickness of the pipeline corrosion defect by adopting a full-waveform inversion method according to the T (0, 2) mode guided wave data.

The invention relates to the technical field of material thickness detection, and discloses a multilayer material thickness detection system and method based on a TM sensor, electronic equipment and a storage medium, and the system comprises an ultrasonic detection module which is internally provided with a transmitting unit and a receiving unit; the feature extraction module is configured to obtain the ultrasonic signals and perform feature extraction on the ultrasonic signals; the control module is electrically connected with the ultrasonic detection module and the feature extraction module, and the control module comprises an acquisition unit, an algorithm generation unit, an analysis unit, an adjustment unit and a storage unit; the acquisition unit is configured to acquire amplitude characteristic data, waveform characteristic data and spectrum characteristic data; and the algorithm generation unit is configured to generate a layered measurement algorithm by taking the amplitude characteristic data, the waveform characteristic data and the frequency spectrum characteristic data as input signals, and calculate the measurement thickness of each layer of material according to the layered measurement algorithm. The measurement algorithm can be automatically adjusted, and the accuracy and reliability of the measurement result are ensured.

Disclosed in the present invention is an aerial manipulator system for measuring the depth of cracks in the substructure of a reinforced concrete bridge, the system comprising a main human-computer interface device, an aerial manipulator, and an end effector, wherein the main human-computer interface device comprises a remote controller and a control computer; the aerial manipulator comprises a drone and a single-degree-of-freedom robotic arm; and the end effector comprises an ultrasonic crack depth measurement mechanism, a shock absorber and a force sensor. In the present invention, the aerial manipulator system is designed to be able to stably contact the substructure of a reinforced concrete bridge and automatically complete crack depth measurement procedures, thereby reducing the high-altitude operation risk and workload of bridge inspectors, and improving the efficiency of crack depth measurement operations.

The invention belongs to the technical field of oil film inspection and detection, and particularly discloses a device for measuring the thickness of an oil film in a piston rod, the device is located in the piston rod and comprises a measuring unit and an adjusting unit, and the measuring unit and the adjusting unit are connected through a T-shaped sleeve, the adjusting unit is used for adjusting the acoustic coupling state of the measuring unit and the inner wall of the piston rod; the measuring unit is used for measuring the oil film thickness of the inner wall of the piston rod when the measuring unit and the inner wall of the piston rod are in an acoustic coupling state. Stable contact between the ultrasonic probe and the inner wall of the piston rod can be ensured, so that the measurement precision and stability are improved.

The invention specifically relates to the technical field of digital twinning, and discloses a seamless steel tube size parameter detection and deviation correction system based on digital twinning, which comprises a multi-dimensional data acquisition module, a digital twinning model construction module, a deviation quantitative evaluation module, a correction scheme generation module, a correction scheme iteration module and a knowledge model optimization module, a real-time transmission mechanism of data acquisition-deviation analysis-correction decision is constructed, full-dimensional parameters of the seamless steel pipe are acquired in real time through a multi-dimensional data acquisition module, a digital model of the steel pipe is synchronously input, and a quantitative model driven by full-process data is constructed, so that the full-dimensional parameters of the seamless steel pipe are obtained. The size deviation degree and the surface quality score are accurately calculated through a deviation quantitative evaluation model, comprehensive deviation grades are divided, an initial correction scheme is generated based on deviation types and grades, parameters are quantified and adjusted through an iterative optimization correction scheme, an iterative correction-case precipitation-model optimization closed-loop structure is constructed, continuous evolution of the system is achieved, and the system quality is improved. The production efficiency is improved.

The invention relates to the technical field of pipeline monitoring, and discloses an underwater pipeline wall thickness monitoring processing method and system, electronic equipment and a storage medium, and the method comprises the steps: measuring a measurement point through a WAND sensor, and obtaining original wall thickness data; after noise processing is conducted on the original wall thickness data, environment parameters are collected, the original wall thickness data are corrected according to the environment parameters, and corrected wall thickness data are obtained; performing data fusion on the corrected wall thickness data of each measurement point to obtain fused wall thickness data, and marking abnormal points according to the historical wall thickness data, the nominal wall thickness data and the fused wall thickness data; performing wall thickness trend analysis on the wall thickness of the pipeline based on the historical wall thickness data to obtain predicted wall thickness data; and finally, determining that the measurement point is a high-risk area or an area with a damage risk. According to the invention, through noise processing, environmental parameter correction and data fusion, the effectiveness of a measurement result is ensured, a high-risk area and a potential damage risk are identified, and the overall safety is improved.