4885results about "Fluid pressure measurement" patented technology

The invention provides a calibration method and system for measurement data of a pressure sensor, and the method comprises the steps: obtaining an original output signal of the pressure sensor and synchronous collection data of environment parameters, and carrying out the preprocessing, and obtaining multi-source sensing data and dynamic environment characteristics; based on multi-source sensing data and dynamic environment characteristics, a multi-error coupled comprehensive error model is constructed, and a dynamic compensation coefficient is generated through online parameter identification; according to the dynamic compensation coefficient and a preset confidence evaluation strategy, dynamic compensation calibration is carried out on the sensing data, a high-precision pressure value is generated, and the high-precision pressure value is used for representing a real environment pressure measurement value. By adopting the method, the accuracy and the reliability of the tester in the calibration of the pressure sensor in a multi-error coexistence and complex environment can be improved, and the precision and the stability of the measurement data calibration of the pressure sensor are improved.

The invention provides a pressure sensor data precision compensation method and system for industrial control, and the method comprises the steps: firstly obtaining an original pressure signal sequence outputted by a target pressure sensor in a preset collection period, the original pressure signal sequence containing a plurality of pressure signals arranged according to a timestamp; meanwhile, a real-time environment parameter set, covering temperature, humidity and mechanical vibration parameters in an acquisition period are detected, then the real-time environment parameter set is input into a pre-trained compensation parameter generation model, a corresponding dynamic compensation parameter set is generated, then each signal of an original pressure signal sequence is adjusted step by step according to the dynamic compensation parameter set, and a dynamic compensation parameter set is generated; and finally, the compensated pressure signal sequence is output to a signal processing module of an industrial control system to drive an execution mechanism, so that the data precision of the pressure sensor can be dynamically and accurately compensated by integrating multiple environmental factors, and the accuracy and stability of industrial control are improved.

The invention relates to the technical field of pressure transmitters, and discloses a high-precision self-adaptive pressure transmitter calibration method and system, and the method comprises the steps: carrying out the noise filtering processing of pressure signal data, obtaining standard signal data, carrying out the time-frequency domain joint analysis of the standard signal data, and obtaining a signal time-frequency joint representation; a dynamic compensation coefficient matrix of the target pressure transmitter is generated, and the response adaptation degree of the dynamic compensation coefficient matrix to the environment interference parameters is calculated; identifying a nonlinear error mode of the pressure transmitter, performing multi-dimensional parameter optimization on a calibration algorithm to obtain an optimal parameter, and extracting a key correction node parameter in a compensation function; adjusting factor distribution of each order of compensation item in the dynamic error correction model is analyzed, and a self-adaptive calibration instruction set of each order of compensation item in the dynamic error correction model is generated; and generating a multi-mode calibration scheme of the pressure transmitter. According to the invention, the calibration accuracy of the high-precision self-adaptive pressure transmitter can be improved.

The invention provides an intelligent pressure sensor temperature compensation system, and relates to the technical field of pressure sensors, and the system comprises a hardware sensing module which comprises an elastic sensitive element and is used for reducing the temperature drift magnitude of a pressure sensor; the environment data acquisition module comprises a flexible thermoelectric sensor array and is used for acquiring temperature and humidity data; the humidity correction module is used for integrating a dynamic humidity correction algorithm and establishing a cross-sensitive matrix model to correct the original signal to generate a first pressure correction signal; the temperature compensation module is used for carrying an incremental neural compensation network and constructing a compensation model to perform temperature compensation on the first pressure correction signal to generate a second pressure compensation signal; and the fault compensation module is used for triggering a digital twinborn compensation model to perform fault compensation on the second pressure compensation signal to generate a target pressure output signal when a fault of the single sensor is monitored, so that the pressure measurement error in the whole temperature range can be accurately controlled, and the environmental adaptability and the intelligent level of the system are improved.

The invention relates to the technical field of sensors, and discloses a temperature compensation method based on a silicon resonance pressure sensor. According to the method, real-time temperature drift data is collected through a sliding time window, and a temperature sensitive area and a temperature non-sensitive area are accurately identified; establishing a coupling model of zero drift and full scale drift in the temperature sensitive area; then, piecewise linearization processing is conducted on the coupling model through a dynamic weight distribution strategy, and high-precision temperature compensation parameters are generated; and finally, according to the environment temperature value detected in real time, automatically calling the temperature compensation parameter of the corresponding segment, and carrying out real-time dynamic correction on the original output value of the sensor. According to the method, through region identification and model coupling of temperature drift characteristics, fine division and adaptive matching of a compensation strategy are realized, and the measurement precision and long-term stability of the silicon resonance pressure sensor in a wide temperature range are improved.

The invention discloses a system and a method for automatically analyzing the abnormal state of a pressure gauge, and the method comprises the steps: learning a cooperation mode between a real-time flow velocity value sequence and a real-time pressure value sequence under a normal working condition through a cooperation model based on an auto-encoder, and reasoning an expected real-time pressure value sequence according to the real-time flow velocity value sequence. By calculating the residual error between the actual real-time pressure value sequence and the reasoning real-time pressure value sequence, the deviation degree of the cooperative relationship between the pressure and the flow velocity can be effectively quantified. And the residual error sequence and the time sequence characteristics of the residual error sequence are combined with the pressure time sequence characteristics of the target pressure gauge and are jointly input into the trained abnormal state diagnosis multi-classifier model, so that the accurate and robust diagnosis of the abnormal state of the pressure gauge is realized, and the pressure change caused by the fault of the pressure gauge or the abnormal system process is effectively distinguished.

The invention relates to the technical field of field data acquisition, in particular to an on-line temperature self-compensation calibration method and circuit for a force measurement transmitter. The calibration method comprises the steps that a working strain gauge and a temperature compensation gauge are synchronously excited through a two-way precision constant current source, the working strain gauge and the temperature compensation gauge are consistent in material parameter and are located in the same temperature field, and output current values of the two-way precision constant current source are equal and are controlled by a high-precision reference voltage source and a sampling resistor in a closed-loop mode. According to the invention, differential signals of the working strain gauge and the temperature compensation gauge are decoupled in real time through double-path precise constant-current source excitation and synchronous ADC acquisition technologies, gradient compensation is carried out on the temperature change rate in combination with a dynamic weighting algorithm, a lag error of traditional fixed coefficient compensation in a transient temperature field is effectively eliminated, and the accuracy of temperature compensation is improved. And online self-compensation of the temperature drift of the strain gauge is realized.

A gas detection device includes a casing, a detection unit, and a circuit board. The detection unit is electrically connected to the circuit board. The detection unit includes a detection casing and has an air chamber. The detection casing is located on the periphery of the air chamber and has a mating hole in communication with the air chamber. The casing has a ventilation hole. At least part of the detection unit is located inside the casing, and at least part of the circuit board is located inside the casing. The ventilation hole is in communication with the mating hole and also in communication with the outside of the gas detection device. The casing is one integral piece. This simplifies the manufacturing and installation process.

The invention relates to the technical field of control systems, in particular to an unmanned aerial vehicle flight control multi-sensor attitude confidence calculation method, which comprises the steps of multi-source sensor data acquisition, sensor independent attitude calculation, confidence coefficient dynamic evaluation, multi-modal data fusion, attitude error compensation and optimization and real-time verification and fault-tolerant processing. Compared with a fixed weight distribution scheme in the prior art, the method has the advantages that the attitude calculation precision is limited possibly, and particularly when the sensor data quality is influenced by environmental factors, the scheme adopts a strategy of checking the data quality in real time, judging the environmental state and dynamically distributing the weight; the validity of sensor data is effectively identified by verifying whether the acceleration modulus length is close to the gravitational acceleration or not and whether the magnetic field intensity is stable or not; meanwhile, the weight of each sensor is flexibly adjusted according to different environment states such as static, maneuvering or magnetic interference of the unmanned aerial vehicle, so that the self-adaptive capability and accuracy of attitude calculation are remarkably improved.

The invention discloses an intelligent monitoring method for an argon recovery system, particularly relates to the technical field of gas purification adsorbent state monitoring, and is used for solving the problem of adsorbent recessive failure early warning lag caused by dependence on tail gas average concentration monitoring of an existing argon recovery system. The method comprises the following steps: collecting regeneration tail gas concentration time sequence data in real time, and extracting a slope change rate of a desorption rate rising section and an area integral value of a desorption peak attenuation section; constructing an area integral value sequence and calculating a symmetric deviation degree; identifying a pressure pulse disturbance time period to obtain effective time period data; calculating the fluctuation abnormality of the slope change rate offset and the symmetry deviation degree based on the effective data; when the two regeneration periods simultaneously exceed the threshold value and three continuous regeneration periods meet the condition, an adsorbent replacement early warning signal is generated, and early-stage accurate early warning of adsorbent performance degradation is achieved.

The invention relates to a temperature drift compensation method for a pressure instrument, and belongs to the technical field of pressure instruments, and the method comprises the following steps: obtaining output signal values of a pressure sensor at different temperature points, and building a temperature-output signal data set; constructing a polynomial fitting model as a temperature drift compensation model, fitting a temperature coefficient through a least square method, and storing the coefficient into an instrument memory; original values of temperature and pressure are collected in real time and substituted into the model to calculate a compensated pressure value. The method also supports various strategies such as temperature sensor calibration, nonlinear error compensation, Kalman filtering noise reduction, dynamic temperature change rate compensation and neural network compensation, and has self-calibration and remote updating functions. According to the invention, the measurement precision and stability of the pressure instrument in a variable-temperature environment are significantly improved, and the method is suitable for high-precision industrial measurement and intelligent monitoring scenes of the Internet of Things.

The invention relates to a pressure sensor (1) for detecting a leakage in a first separating membrane (8), with - a process adapter (6) with a membrane system (7) comprising the first separation membrane (8) and a second separation membrane (9), which are arranged such that the first separation membrane (8) faces the medium (24) and the second separation membrane (9) faces away from the medium (24) and a first intermediate space (10) is enclosed between the first separation membrane (8) and the second separation membrane (9), which has a vacuum, - a sensor unit (14) with a carrier (15), a second pressure sensor (16) and a communication unit (17), wherein the sensor unit (14) is attached to the pressure sensor (1) in a pressure-tight manner by means of the carrier (15) and is arranged such that the second pressure sensor (16) monitors the vacuum in the first space (10), wherein the second pressure sensor (16) and the communication unit (17) are electrically connected to each other and are arranged on a surface of the carrier (15) facing the vacuum.

The invention discloses an enterprise safety supervision system and equipment based on data analysis, and relates to the technical field of data analysis. Comprising an initial sensitivity monitoring module, a vehicle state data extraction module, an intelligent feature analysis module, a vehicle state evaluation and classification module, a low-dynamic disturbance monitoring module and a high-dynamic disturbance sensitivity adjustment module, the change of brake hydraulic pressure is captured; and the vehicle state data extraction module is used for acquiring various data information of vehicle driving in real time in the abnormal recognition process. Through the high-dynamic disturbance sensitivity adjustment module and deep learning evaluation, the system dynamically reduces the sensitivity of the pressure sensor in a high-frequency disturbance state, filters noise, and accurately monitors real abnormity; the driving state is divided through intelligent feature analysis, sensitivity self-adaptive adjustment is achieved, and the monitoring precision and the system stability under the complex working condition are comprehensively improved.

The invention relates to an intelligent soft rock tunnel surrounding rock deformation automatic monitoring and early warning system, and belongs to the field of tunnel construction safety monitoring. According to the system, multi-source data of surrounding rocks are synchronously acquired through a micron-sized laser displacement sensor, a fiber grating strain sensor, a pore water pressure sensor and a three-dimensional micro-seismic sensor array which are distributed; the edge calculation node fuses the data in real time and calculates the displacement rate, the strain gradient and the osmotic pressure coupling coefficient, and local early warning is triggered in combination with a dynamic threshold value; the cloud early warning platform predicts a deformation trend based on an LSTM-Transform fusion model, generates a multi-stage early warning signal through a risk grading engine, and is linked with the supporting equipment to regulate and control pressure; and meanwhile, a self-calibration device, an explosion-proof shell and a piezoelectric-thermal energy self-powered system are integrated. According to the method, closed-loop control from millimeter-level deformation sensing to active supporting can be achieved, and tunnel construction safety is remarkably improved.

The embodiment of the invention provides a pipeline blockage monitoring method and system for wet metallurgy slurry conveying, and belongs to the technical field of pressure measurement and pipeline blockage monitoring. The method comprises the following steps: collecting multi-point pressure signals along a slurry pipeline, and extracting pressure pulsation amplitudes and phase characteristics in a pump fundamental frequency and frequency multiplication range based on the multi-point pressure signals so as to establish an on-way pulsation transmission sequence; determining equivalent on-way impedance based on comparison between the on-way pulse transmission sequence and a reference working condition, and outputting an initial judgment result for representing a blockage risk; flow temperature and viscosity estimation parameters are introduced based on the initial judgment result to carry out rheological correction on an impedance threshold value, and a high-frequency phase difference is extracted at an elbow section to update a candidate blockage position; and based on the updated candidate blockage position and the corrected impedance threshold, fusing a phase stability index, and generating and outputting a current blockage evaluation result. According to the scheme, early-stage accurate positioning and stable judgment of slurry pipeline blockage can be achieved under complex working conditions.

The invention discloses a pressure sensor fault state monitoring method and system based on artificial intelligence, and relates to the technical field of industrial equipment intelligent monitoring, and the method comprises the steps: S1, collecting an original output signal of a target pressure sensor and an associated environment temperature signal, and forming an original time sequence data stream; s2, performing sliding window segmentation processing on the original time sequence data stream to form standardized pressure signal segments, and extracting a current environment temperature value to form a temperature auxiliary signal; s3, generating a physical characteristic signal based on the pressure sensor physical mechanism model; s4, inputting the physical feature signal into a pre-trained lightweight deep feature extraction network, and fusing and outputting a deep feature signal; and S5, jointly inputting the depth characteristic signal and the temperature auxiliary signal into a multi-branch fault diagnosis network, and outputting a fault state code and a confidence evaluation signal after comprehensive judgment. According to the invention, the problem of high fault detection false alarm rate of the pressure sensor under complex working conditions can be solved.

The invention provides a sphygmomanometer automatic calibration inspection method and system. The method comprises the steps that a data interface of a sphygmomanometer is connected with external inspection equipment, and a cuff interface of the sphygmomanometer is connected with a programmable standard pressure source and a pressure sensor in the inspection equipment; the sphygmomanometer enters a calibration mode after being connected with the inspection equipment; obtaining the atmospheric pressure of the inspection equipment in the current detection environment, and determining whether the external air pressure fluctuation can influence the output of the inspection equipment or not based on the atmospheric pressure in the current detection environment; under the condition that the external air pressure fluctuation does not influence the output of the inspection equipment, applying pressure according to a preset pressure point, and respectively obtaining a high-precision reference pressure value in the inspection equipment and a measurement pressure value of the sphygmomanometer; dynamically calibrating and compensating the sphygmomanometer based on the error between the high-precision reference pressure value and the measured pressure value; wherein each sphygmomanometer corresponds to a unique identifier and is used for data binding and tracing management.

To provide an information collection device and a battery pack which improve the sealing performance of a signal collection device.SOLUTION: The present disclosure relates to the field of battery technologies, and provides an information collection device and a battery pack. The information collection device includes a casing, an air pressure sensor, and a sealing member. The casing has a first installation hole. The air pressure sensor is installed inside the casing, and at least a part of the air pressure sensor is snap-fitted into the first installation hole to acquire an air pressure parameter outside the casing. The sealing member seals the first installation hole, and the sealing member is used to allow gas to pass through and prevent liquid from passing through. Thereby, the information collection device can be arranged in a battery cell, and can collect information in an environment of electrolyte, thus capable of mitigating the technical problems of complex structure and insufficient reliability of a cover plate of the battery cell caused by external arrangement of the information collection device.SELECTED DRAWING: Figure 1

The invention discloses a wireless digital pressure gauge performance data monitoring management method based on the Internet of Things, and relates to the technical field of pressure gauge technical performance data monitoring, and the method comprises the following steps: building a historical behavior model and a neighborhood behavior joint model when a wireless digital pressure gauge is in an equipment address abnormal overlapping condition, fitting the uploaded performance data to obtain a first residual error and a second residual error, and generating a residual error coupling degree and a coupling degree change trend which are used for representing a transmission mapping chaos degree of the performance data based on the first residual error and the second residual error; and judging whether the uploaded performance data has an affiliation error problem or not according to the residual coupling degree and the transmission mapping confusion degree corresponding to the coupling degree change trend. According to the method, the problem of data affiliation errors of the wireless digital pressure gauge of the Internet of Things when the addresses are abnormally overlapped is solved, and intelligent identification, dynamic correction and trend modeling safety guarantee of data affiliation are realized.

The invention discloses an adaptive multi-angle elbow airtightness detection method, which comprises the following steps: arranging a flexible pressure sensor array and a micro inertial measurement unit on the inner wall of an elbow, collecting multi-point sealing pressure and attitude signals in real time, fusing geometric parameters and a spatial mapping relation, and completing denoising, normalization and multi-curvature region mapping of pressure data; a distributed pressure-attitude database is combined, a function model associated with sealing pressure and pipeline geometric parameters is established, inflation, exhaust and deformation of each node are dynamically adjusted through an intelligent closed-loop regulation and control algorithm, collaborative optimization of multi-node pressure and a fitting state is achieved, and the sealing performance of the pipeline is improved. According to the method, the accuracy and the self-adaptive adjusting capacity of sealing pressure distribution under a complex bent pipe structure are effectively improved, the tiny leakage real-time positioning and self-learning optimization capacity is achieved, and the method is suitable for sealing quality guarantee of various types of curved surface pipelines.

The invention belongs to the technical field of pressure sensors, and particularly relates to a wireless passive pressure sensor for detecting bolt pretightening force, which comprises a pressure-sensitive capacitor and an outer ring encapsulation ring, the voltage-sensitive capacitor comprises an inner ring basin cavity, and an upper insulation pad, an upper polar plate, an elastic cushion layer, a lower polar plate and a lower insulation pad which are sequentially arranged in the inner ring basin cavity from top to bottom, the bottom of the inner ring pelvic cavity, the upper insulating pad, the upper polar plate, the elastic cushion layer, the lower polar plate and the lower insulating pad are provided with concentric holes to form a central through hole of the voltage-sensitive capacitor; the outer ring potting ring wraps the outer ring of the inner ring basin cavity, and a circuit and an antenna are arranged in the outer ring potting ring; the circuit is a frequency conversion circuit which is connected with the upper polar plate and the lower polar plate; and the circuit is also connected with the antenna. The sensor realizes wireless passive real-time monitoring, is convenient to install, does not need direct current power supply, does not have a signal processing unit inside, only transmits frequency signals, and is high in response speed.

The invention relates to the technical field of MEMS microsensors, and discloses a resonant pressure sensor and a preparation method thereof, the resonant pressure sensor comprises a substrate layer and a resonant assembly, the substrate layer comprises a support substrate and a pressure sensitive film; the supporting substrate is located at the side part of the pressure sensitive film; the resonance assembly comprises a first resonance beam and a second resonance beam which are arranged in parallel, two ends of the first resonance beam are connected with the pressure sensitive film through a first anchor area and a second anchor area, and two ends of the second resonance beam are connected with the pressure sensitive film through a third anchor area and a fourth anchor area; the first resonant beam and the second resonant beam are coupled and connected together through the mass block and the spring; the resonance assembly further comprises a first driving electrode unit and a second driving electrode unit. The first driving electrode unit is positioned on one side of the first resonant beam; the second driving electrode unit is located on one side of the second resonant beam. Compared with the prior art, the detection sensitivity, precision and reliability of the sensor can be improved, the Q value is improved, and the measuring range of the sensor is increased.

The invention discloses an abnormity monitoring method and system for a digital pressure transmitter, and relates to the technical field of transmitter monitoring, and the method comprises the following steps: obtaining an original pressure response sequence in a high-frequency pressure pulsation environment, and synchronously recording a sampling clock pulse sequence in an acquisition process, establishing double-track mapping based on the original pressure response sequence and the sampling clock pulse sequence, and forming an input condition with a unified time baseline; and performing instantaneous phase difference extraction on the double-track mapping on the unified time base line. Through double-track mapping, phase difference extraction and nonlinear cross spectrum reconstruction, the stroboscopic aliasing risk is quantified and recognition in advance is realized, and the sensitivity and accuracy of abnormal monitoring of the digital pressure transmitter are improved; meanwhile, the multi-scale risk amplification and reversible time-frequency rearrangement technology is combined, covered high-frequency components are separated and recovered, a real pressure pulsation curve is output after dynamic correction, continuous and stable monitoring is guaranteed, and pressure measurement reliability and operation safety are improved.

The invention discloses a high-precision anti-interference pressure transmitter, and relates to the technical field of anti-interference pressure transmitters. Comprising a pressure data acquisition module, a data preprocessing and integration module, a pressure fluctuation feature extraction and quantification module, an intelligent evaluation and deep learning analysis module and a dynamic adaptive monitoring regulation and control module, the pressure transmitter firstly continuously detects the fluid pressure in the earth crust fracture according to a preset initial detection threshold value, and recorded and collected pressure data serve as the basis of all subsequent analysis. According to the method, deep learning analysis and dynamic threshold adjustment are combined, transient pressure fluctuation and magma rising premonition are intelligently distinguished, and the risk of false alarm and missing alarm is reduced. By improving the sampling frequency and optimizing data analysis, a complete pressure change track is formed, the volcano monitoring precision and the anti-interference capability are improved, and efficient technical support is provided for geological safety early warning.

The invention relates to the technical field of storage tank sampling, and discloses a sampling detection device for a low-temperature tank and a sampling method.The sampling detection device comprises a low-temperature tank body and a liquid storage tank, the feeding end of the low-temperature tank body is communicated with the discharging end of the liquid storage tank through a pipeline, and the discharging end of the low-temperature tank body is sequentially connected with a buffer cylinder and a circulation assembly; as water flows into the buffer cylinder from the low-temperature tank body, when the interior of the low-temperature tank body is in a high-pressure state, the speed of the water flowing into the buffer cylinder can be increased through strong pressure, the main conveying pipe cannot discharge all the water in time instantly, and at the moment, buoyancy of the water enables the semi-floating ball to support the valve plate to ascend; therefore, the communicating position of the pressure relief sampling pipe and the second cavity is opened, a small part of water can flow to the circulating assembly from the pressure relief sampling pipe, the diameter of the pressure relief sampling pipe is smaller than that of the main conveying pipe, impurities in water flow are concentrated accordingly, and the highly-concentrated impurity distribution state is beneficial for being captured by the detection assembly and detected.

The invention discloses a liquid cooling radiator cooling liquid leakage detection method and system, and relates to the technical field of equipment detection, and the method comprises the steps: obtaining the pressure reading of pressure measurement equipment; according to the pressure reading, the pressure change rate is calculated through differential operation; identifying a starting time point of a leakage event according to the pressure change rate; calculating an inherent response delay of the pressure measurement device; compensating the occurrence time sequence of the leakage event according to the inherent response delay to obtain a compensation time sequence; according to the starting time point and the compensation time sequence, the target leakage point position is determined, cooling liquid leakage detection is achieved, and accuracy is improved.

The invention discloses an active anti-floating drainage model test device and test method considering saturation change, and belongs to the technical field of active anti-floating of buildings. The test device comprises a boundary model box, a building model box, a plurality of pore pressure sensors, a plurality of dielectric constant sensors, a pressure limiting drainage pipe for simulating active anti-floating equipment in an actual building, a water head control device and a rainfall simulation device, and can simulate a seepage field of an underground space under the condition of active anti-floating measures during rainfall. The drainage condition of the underground space under the condition is reproduced; the pore pressure sensor and the dielectric constant sensor monitor the saturation change of the soil body in real time, the vacancy of the existing test device in the saturation change factor of the soil body is filled up, the drainage condition of the active anti-floating measure and the seepage law of the soil body in the unsaturated-saturated transition process of the soil body under different rainfall and different stratum conditions can be demonstrated, and the test device has a wide application prospect. Scientific basis and data support are provided for optimization application of active anti-floating measures under different saturation working conditions.

The invention provides a fault-tolerant diagnosis method adopting a dual-channel pressure sensor, and relates to the technical field of intelligent sensors, and the method comprises the steps: arranging the dual-channel pressure sensor on a target natural gas pipeline, and synchronously collecting and obtaining a first pressure signal sequence and a second pressure signal sequence; when any pressure signal reaches a preset pressure threshold value, signal deviation analysis is carried out, and a pressure signal deviation sequence is obtained; when the deviation value at any moment reaches a preset deviation threshold value, fault detection is carried out on the dual-channel pressure sensor, and a sensor detection result is obtained; when the deviation value reaching the preset deviation threshold value does not appear in the preset time interval, pipeline fault recognition and positioning are conducted, and a pipeline fault recognition result is obtained. The technical problems that in the prior art, pressure monitoring depends on a single sensor, effective fault diagnosis cannot be carried out or accurate data cannot be continuously provided when pressure abnormity occurs, pipeline faults cannot be found in time, and normal operation of a pipeline is affected are solved.

The invention relates to the technical field of mechanical vibration and fluid excitation coupling effect analysis, in particular to a runner crown modification pressure pulsation amplitude measurement method, which comprises the following steps of: extracting pressure gradient distribution and cavitation phase change characteristic parameters of a runner surface through fluid dynamics simulation; targeted arrangement of a high-frequency pressure sensor array in a vortex core area, a boundary layer separation critical position and a modification structure mutation area is guided, and the signal acquisition precision is improved by adopting an annular encryption and axial equal-interval arrangement strategy. And establishing a dynamic error feedback mechanism of actual measurement and simulation. And verifying an abnormal frequency band proportion through frequency domain kurtosis and analyzing envelope spectrum harmonic waves, and screening a modification parameter combination with the pressure pulsation amplitude decreasing to reach the standard and stable frequency band distribution. According to the method, the problem of measurement errors caused by multi-source high-frequency noise and effective signal frequency domain aliasing is solved, a high-precision quantification basis is provided for runner modification optimization, and the method is suitable for the field of mechanical system dynamic characteristic testing.

The invention relates to the technical field of leakage detection, and discloses an SF6 gas pressure early warning method, device and equipment, a storage medium and a program product.The SF6 gas pressure early warning method comprises the steps that for target electrical equipment, environment temperature data of the environment where the target electrical equipment is located is used for conducting environment compensation on measured pressure data of SF6 gas, and compensation pressure data is obtained; calculating a corrected pressure change rate based on the compensated pressure data at the plurality of moments; if the compensation pressure data at the current moment does not meet the pressure standard and / or the correction pressure change rate at the current moment does not meet the change rate standard, feature matching is carried out based on the data set at the current moment and the data set at the historical moment, and a target data set meeting the matching range is determined from the data set at the historical moment, taking the SF6 gas leakage condition at the historical moment corresponding to the target data set as the SF6 gas leakage condition at the current moment; and performing early warning based on the SF6 gas leakage condition at the current moment. According to the invention, the accuracy of SF6 gas early warning can be improved.