400 results about "Force transducer" patented technology

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 invention relates to the technical field of intelligent manufacturing, in particular to an intelligent defect detecting and repairing method and system for a vacuum isothermal forging based on multi-mode sensing data. The method comprises the following steps: respectively acquiring image data, heat distribution data and stress monitoring data of the vacuum isothermal forging through a visual sensor, a thermal sensor and a stress sensor, and preprocessing the data to generate a time-space aligned multi-modal data set; performing fusion processing on the multi-modal data set, extracting multi-dimensional features of defects through a deep learning network, and generating a defect feature sequence; optimizing a repair path planning model based on the defect feature sequence in combination with the stress distribution features, and generating a repair task sequence; and inputting the repairing task sequence into the intelligent repairing equipment to execute repairing operation. According to the method, the multi-mode sensing technology and the deep learning algorithm are combined, high-precision detection, classification and repair of the defects of the vacuum isothermal forging are achieved, the production efficiency and the product quality are remarkably improved, and the defective rate and the repair cost are reduced.

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 relates to the technical field of water supply pipeline detection, and discloses an underground water supply pipeline health grade evaluation and risk prediction method, which comprises the following steps: sensor arrangement: arranging a flow sensor, a pressure sensor and a sonic sensor at key positions of an underground water supply pipeline; and data acquisition: acquiring signals of the sensor in real time through a data acquisition module, wherein the signals comprise flow, pressure and sound wave signals. Preprocessing the data: carrying out preprocessing such as denoising and normalization on the collected signals; and multi-source data fusion: inputting flow, pressure and sound wave signals into a deep neural network model, and performing feature extraction and fusion analysis. And health level assessment: assessing the health level of the pipeline based on the output result of the deep neural network model. And risk prediction: predicting abnormal working conditions possibly occurring in the future and risk levels of the abnormal working conditions by analyzing the current pipeline state and historical data. And abnormal positioning: accurately positioning an abnormal position in combination with the propagation time of the sensor signal and a positioning model of the deep neural network.

The invention relates to the technical field of data analysis, in particular to a dynamic mold pressure data analysis system for polyurethane pultrusion production, which comprises a mold pressure data capture module, a pressure gradient trend calculation module, a mold abnormal pressure identification module, a mold pressure adjustment data module and a multi-dimensional pressure state monitoring module. According to the invention, through data capture of the multi-node pressure sensor, high-precision real-time monitoring of internal pressure of the mold is realized, data integrity is enhanced, limitation of single data is avoided, pressure feature identification of different areas of the mold is realized, abnormality judgment accuracy is improved, normal fluctuation and abnormal accumulation are distinguished, and abnormal areas are accurately locked; temperature and ultrasonic signal analysis is introduced, curing abnormity and bubble aggregation are identified, the monitoring range is expanded, the data acquisition precision, the analysis depth and the regulation and control capability are improved, abnormity detection is more scientific, regulation and control are more intelligent, resin flowing is optimized, and the quality fluctuation risk is reduced.

The invention provides a sensor dynamic zero point correction method based on deep Kalman filtering, and relates to the technical field of sensor zero point tracking. The method comprises the following steps: acquiring voltage signal zero point output time sequence data of a sensor; the obtained data serve as input of a deep learning network model based on Kalman filtering, the model processes the data, noise and zero drift interference are removed from the output data, dynamic zero correction is achieved, and a real measurement value of the sensor is obtained. The deep learning network model based on Kalman filtering comprises an RNN recurrent neural network module, a Pyro probability programming module and a variational inference module. According to the invention, the external interference is simulated by using the environmental vibration to carry out the experiment, and the result shows that the deep Kalman filter model provides a new idea for the dynamic zero correction of the force transducer.

The invention relates to the technical field of digital twinning, in particular to a steel structure building construction whole process mechanical property evaluation method based on digital twinning, which comprises the following steps of: acquiring multi-source heterogeneous steel structure state data from a stress sensor, BIM model component information and a displacement monitoring point, comparing timestamps from all data sources, and determining the state of the multi-source heterogeneous steel structure according to the comparison result; and calculating a transmission delay value of each data source relative to the unified reference time, correcting the original data timestamps one by one, and establishing a steel structure state data stream with aligned time sequences. According to the method, the timestamps of the multi-source heterogeneous data are subjected to transmission delay correction through unified reference time, the timestamps of the original data are corrected one by one, the steel structure state data streams with the aligned time sequences are generated, the time deviation among the sensors, the BIM model and the monitoring points is eliminated, and the synchronism and coherence of dynamic changes of mechanical parameters are guaranteed.

The invention discloses a satellite antenna dynamic pointing calibration method and system based on satellite autonomous gradient optimization, relates to the technical field of satellite communication, and realizes closed-loop calibration without ground intervention by processing signal to noise ratio (SNR) data uploaded by a ground station on a satellite in real time and combining a multi-physical field coupling model of a temperature and stress sensor. And the pointing error in a dynamic environment is reduced from more than 2.0 degrees of a traditional scheme to less than 0.3 degrees.

The invention discloses a spring operating mechanism fault detection and optimization method and a related device, and the method comprises the steps: carrying out the real-time collection of key data of a spring operating mechanism through a stress sensor, a speed sensor and a vibration sensor; based on the collected key data, constructing a multi-dimensional data framework to obtain a multi-dimensional data set; fault feature extraction and data analysis are carried out on the obtained multi-dimensional data set, an adaptive fault model is constructed based on the extracted fault features, and then a real-time fault detection result is obtained through multi-modal data fusion; and optimizing a stress sensor, a speed sensor and a vibration sensor by utilizing automatic calibration and optimization of reinforcement learning according to the real-time fault detection result. Compared with a traditional fault detection method, high-precision real-time monitoring and fault prediction of the spring operating mechanism are achieved through the multi-modal data fusion and deep learning technology, and comprehensive and reliable technical support is provided for safe operation and maintenance optimization of equipment.

The invention discloses a coal mining rock burst prevention and early warning system which comprises a data acquisition system, and the data acquisition system comprises a sensor network, a self-adaptive sensor layout module, a signal sending module and a power supply module. The sensor network comprises a stress sensor, a displacement sensor and a vibration sensor which are arranged in a coal mine tunnel; the signal sending module is used for sending data acquired by the sensor; the power module is used for supplying power to the sensor network and the signal sending module. The coal mining rock burst prevention and early warning system is compatible with three kinds of sensing data of a stress sensor, a displacement sensor and a vibration sensor, and the positions and density of the sensors in a high-risk area are dynamically adjusted. And establishing a coal seam rock burst risk evaluation expert system by using the monitored result, and evaluating the early warning result. The sensor layout strategy of the coal mining rock burst prevention and early warning system is optimized, the monitoring capability of a high-risk area is improved, and the rock burst danger early warning level can be improved.

The invention discloses a self-adaptive settlement monitoring and compensation construction integrated system, and belongs to the technical field of foundation settlement monitoring and compensation integration. The system comprises a monitoring module, an intelligent control module, a compensation construction module and a digital twinning module. The monitoring module comprises a settlement sensor group, a stress sensor, a three-dimensional displacement sensor and a micro geological radar which are arranged according to a bionic root topology; the micro geological radar realizes layered scanning in an underground range by adopting a multi-band synthetic hole technology; the intelligent control module comprises an integrated settlement prediction algorithm, a multi-stage early warning unit and a seepage-stress coupling analysis model. The output end of the seepage-stress coupling analysis model and the compensation construction module form closed-loop control. The drainage efficiency is remarkably improved through intelligent association of the flow guide pipe and the pore water pressure, the digital twin module constructs a multi-source data interaction platform, dynamic mapping of a physical entity and a virtual model is achieved, the settlement control precision can be improved, and meanwhile the construction cost is reduced.

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 belongs to the field of ocean engineering hydrodynamic tests, and discloses a mooring model rigidity calibration device and a calibration measurement method.The calibration device comprises a fixed rack, a rack guide rail is installed on the fixed rack, a sliding rack is installed on the rack guide rail, a sliding table guide rail is installed on the sliding rack, and a sliding block is installed on the sliding table guide rail; the sliding block and the sliding table are fixedly connected and can move along the sliding table guide rail together. A laser displacement distance measuring sensor is installed on one side of the sliding table. A laser baffle is installed at one end of the sliding rack. The sliding table is also provided with a first tension sensor and a measuring rotating plate; a rope wheel mechanism corresponding to the measuring rotating plate is also mounted on the fixed rack; a second tension sensor and a tilt angle sensor are mounted on the measuring rotating plate; the laser displacement distance measuring sensor, the first tension sensor, the second tension sensor and the tilt angle sensor are all connected with a data collector through data lines, and the data collector is connected with a data processing control system. And continuous, two-way, automatic and accurate measurement can be realized.

The invention provides a novel multi-source information and damage coupled coal mine rock burst prediction method. The method comprises the following steps that rock mass fracture signals, a three-dimensional stress field and acoustic emission parameters are collected in real time through a micro-seismic monitoring array, an optical fiber stress sensor and a rock sound probe; an LSTM-attention fusion module is adopted to carry out spatio-temporal feature extraction on the collected multi-source data, an attention weight coefficient is generated, and a weighted fusion feature vector is output; calculating the rock mass damage degree based on a statistical damage mechanics Weibull distribution theory; based on the law of conservation of energy and the damage mechanics theory, a dynamic energy threshold function is constructed, the mining time effect and the rock mass damage state are incorporated into a quantitative evaluation system, and a dynamic energy accumulation rate threshold function is established by introducing a time accumulation effect and a damage coupling term; when the real-time energy accumulation rate is larger than or equal to the energy accumulation rate threshold value and the time derivative of the energy accumulation rate is larger than the sudden change threshold value, third-level early warning is triggered. According to the invention, advanced accurate early warning of the rock burst can be realized.

The invention belongs to the technical field of impact fatigue performance detection, and particularly relates to a Hopkinson rod three-point bending sample-based constant-amplitude impact fatigue device, which comprises a dynamic indentation system, an energy absorption system, a strain measurement system and a pressure data acquisition system, and is characterized in that the dynamic indentation system comprises kinetic energy application equipment, an impact rod, an incident rod and a three-point bending test bed; the strain measurement system comprises a strain gauge and a dynamic strain acquisition instrument which are electrically connected, the pressure data acquisition system comprises a force transducer and a data acquisition instrument which are electrically connected, and the energy absorption system comprises a flange, a sleeve and a mass block. The device depends on the Hopkinson rod technology, the momentum well design is ingeniously fused, the problem of secondary loading is effectively avoided, constant-amplitude impact fatigue loading is achieved, key parameters such as the yield point, the elastic limit and the breaking strength of the material are accurately measured, and the reliability and safety of the material are comprehensively evaluated.

The invention provides a self-adaptive fitting method and system for a substrate deformation measurement system based on a fiber bragg grating (FBG), and the method comprises the steps: reading an output signal of an FBG sensor network, respectively collecting the wavelength data of a grating sensor and the stress data of a stress sensor at the same position as the grating sensor, and constructing a stress-wavelength data set; fBG data points with most sensitive deformation response are automatically identified, and a dynamic sensitive point set is formed and then preprocessed; a set needing to be continuously monitored is analyzed and determined, a specific point is selected to execute an adaptive segmentation fitting algorithm, segmentation points and fitting polynomial coefficients of all subintervals are output, and a final fitting model is constructed; according to the sub-interval of the wavelength value measured by the FBG sensor, calling a sub-interval fitting model, calculating a corresponding stress value, and further obtaining the deformation quantity of the measured object. According to the invention, the contradiction between the monitoring efficiency and precision of the traditional uniform layout in a complex stress scene is solved, and the technical path and the application target have remarkable industry uniqueness.

The invention relates to an inhaul cable force data filling method for a cable force sensor fault and a storage medium. The data filling method comprises the steps that an inhaul cable with the sensor fault is selected as a target inhaul cable, and an adjacent inhaul cable without the fault serves as an input inhaul cable; extracting all stay cable force data before and after the fault, and respectively taking the data as a training set and a test set; preprocessing the cable force data, including deleting intermittent breakpoints in the data, performing downsampling processing and recombining the data; based on an extended dynamic mode decomposition principle, an observation function of input and target cable force is established, and a prediction operator is calculated; and predicting the target cable force of the test set by using the prediction operator, restoring the sampling frequency, and filling missing data. Compared with the prior art, the cable force data missing caused by sensor faults can be effectively and quickly filled, and the integrity and reliability of the data are improved.

The invention discloses a flexible pressure monitoring system for hip replacement surgery, and belongs to the technical field of biomedical instruments. The flexible pressure monitoring system comprises a flexible front-end signal acquisition module, a rear-end signal processing module and an upper computer system, the flexible front-end signal acquisition module is connected with the rear-end signal processing module, and the rear-end signal processing module is connected with the upper computer system; the flexible front-end signal acquisition module comprises a flexible pressure sensor, and the flexible pressure sensor is arranged at a hip joint; the flexible pressure sensor comprises a flexible substrate, an electrode layer, a spacing layer, a sensitive layer and a packaging layer. According to the flexible pressure monitoring system, the uncertainty that the operation effect is judged only according to experience in the hip joint replacement operation process is made up, clear pressure distribution at the hip joint in the operation process can be provided for surgeons, and objective mechanical data are provided for selection and adaptation of prostheses.

The invention relates to the technical field of fire fighting, in particular to an intelligent control method and system for a smoke exhaust fireproof valve, and the method comprises the steps of initial state setting, fire signal detection, smoke exhaust fireproof valve control and state monitoring and feedback. Compared with the prior art which only depends on temperature and particulate matter concentration data to carry out fire monitoring and control and has the defects of insufficient monitoring on internal air pressure change of the smoke exhaust fireproof valve and inflexible control response, the scheme is characterized in that an air pressure sensor is additionally arranged in a data acquisition module; an air pressure data processing step based on a sliding window average value method is introduced into the control module in a targeted manner, and the opening and closing degree of the smoke exhaust fireproof valve is adjusted by combining a proportion, integral and differential control algorithm, so that the scheme can monitor the air pressure change in the smoke exhaust fireproof valve in real time, improve the accuracy of fire early warning, and improve the safety of the fire. And opening and closing of the smoke exhaust fireproof valve can be dynamically adjusted according to air pressure changes, and the stability of smoke exhaust efficiency and the sensitivity of control response are ensured.

The invention relates to the field of air tightness testers, and discloses an automatic data calibration method and system for an air tightness tester, and the method comprises the steps: obtaining a temperature sensor value T, a pressure sensor value P and a humidity sensor value H from the air tightness tester; performing three-dimensional coordinate positioning in the three-dimensional coordinate space to obtain a coordinate position C1; mapping the coordinate position C1 to a distribution model for coordinate mapping by using a coordinate transformation matrix M; obtaining a compensation parameter set S1 based on the error characteristic value E and the compensation parameter combination S; adjusting the compensation weight of each environment parameter according to the compensation parameter set S1; fusing the adjusted compensation weight with the error characteristic value E and the compensation parameter combination S to obtain a comprehensive compensation coefficient Kc; and performing correction processing on the original measurement data by using the comprehensive compensation coefficient Kc. The method has the advantages that automatic extraction and dynamic adjustment of calibration parameters are achieved when the test environment changes.

The invention relates to the technical field of flexible electronic sensing, and particularly discloses a composite fiber membrane-based capacitive flexible pressure sensor integrated system and a preparation method thereof. The sensor is composed of a composite fiber membrane sensitive layer, an interlayer type electrode structure, a multi-channel signal acquisition module and an intelligent data processing system. Wherein the composite fiber membrane is prepared through an electrostatic spinning technology, polyvinylidene fluoride serves as a matrix, ionic liquid with the mass ratio of 40%-70% is evenly dispersed, a three-dimensional porous structure is formed, and a pressure signal is converted into capacitance change through the double-electric-layer capacitance effect; the signal acquisition module adopts a high-precision capacitance digital converter to cooperatively work with a microcontroller, 9-channel parallel data acquisition is realized, the resolution reaches 6aF, and data is transmitted through an anti-interference bus protocol; and the data processing system dynamically analyzes the pressure-capacitance relationship based on an exponential function model, suppresses noise to be below 0.1 aF RMS in combination with a filtering algorithm, and synchronously generates a visual pressure distribution map.

The invention relates to a real-time monitoring-based dynamic feedback system for tunnels in an earthquake-prone area. The system comprises a monitoring module, a data processing module, a feedback module and an execution module, and aims at collecting data such as surrounding rock deformation, vault settlement and earthquake vibration in tunnel construction in real time. The monitoring module obtains data through a stress sensor, an accelerometer, a displacement meter and other devices, and transmits the data to the data processing module through the wireless communication module. And the data processing module predicts the surrounding rock stability and generates a support optimization suggestion. And the feedback module generates a support optimization scheme according to the analysis result. And the execution module implements the optimization scheme to site construction, and dynamically adjusts support measures through automatic equipment. The system effectively improves the safety, stability and emergency response capability of tunnel construction through a real-time monitoring and dynamic feedback mechanism, is particularly suitable for tunnel construction under the conditions of frequent earthquakes and complex geological conditions, and has a wide application prospect.

The invention discloses valve performance test and diagnosis equipment and a method thereof, and belongs to the field of automatic diagnosis equipment. The data acquisition box DAU is used for providing a plug-in serial port of the sensor assembly, personalized configuration of the sensor assembly can be achieved, and valve physical quantity signals are acquired in real time and uploaded to the upper computer. Meanwhile, a signal control module and a data analysis module are constructed in the upper computer, the signal control module and the data analysis module can cooperate with each other, a change curve with jump information is constructed through data detected by a controller signal sensor, a displacement sensor and a driving stress sensor, and clamping stagnation fault recognition and diagnosis are executed based on information in jump signals. According to the valve performance test and diagnosis equipment, the advanced sensor, the data acquisition box and the upper computer system are integrated, automatic test and intelligent diagnosis of the valve can be achieved, and the valve performance test and diagnosis equipment has wide application prospects.

The invention relates to the technical field of wireless communication equipment, and discloses a self-adaptive dynamic adjustment slope stress monitoring device which comprises an anchor rod, a connecting sleeve, a pedestal, three stress sensors and three anchoring pipes, and the three stress sensors and the three anchoring pipes are sequentially connected. The anchoring pipe is provided with two-way prefabricated tongue plates with opposite openings and matched with boss nuts with opposite threads, a pedestal comprises a pressure release type supporting air cylinder and a sealing ring, when the device is used, the device is inserted into a drilled hole, an anchor rod is rotated to enable the prefabricated tongue plates to be clamped with a rock stratum, and grouting solidification is conducted through the anchor rod; the stress sensor monitors stress changes caused by rock stratum cracks in real time so as to accurately position the cracks, pressure is released for dynamic adjustment when the stress borne by the air cylinder exceeds a threshold value, the device can prevent the stress sensor from being interfered, overload damage is prevented, monitoring accuracy and self-adaptive protection are both considered, the slope monitoring reliability is greatly improved, and the service life of equipment is greatly prolonged.

The invention relates to the technical field of digital information transmission, in particular to an intelligent force transducer data remote transmission method and system based on the Internet of Things, and the method comprises the steps: obtaining the measurement data of a plurality of force transducers, calculating a multi-dimensional rate vector, and obtaining a multi-dimensional rate vector based on the multi-dimensional rate vector in a historical time window; calculating a differential entropy to determine an instantaneous fluctuation index, determining a predictive risk gradient in combination with the historical trend of the instantaneous fluctuation index, evaluating the effective throughput of the data transmission network online, and coupling the predictive risk gradient to determine a risk-aware transmission cost factor, fusing the predictive risk gradient with the transmission cost factor, and determining the risk-aware transmission cost factor. And jointly determining a dynamic transmission strategy level, and executing hierarchical adaptive data transmission operation according to the dynamic transmission strategy level. According to the method, intelligent balance of transmission efficiency and data reliability is realized.

The utility model discloses a recoverable impact type sounding system device, and belongs to the technical field of geological exploration equipment. The device is composed of a take-up and pay-off winch, a guide pulley, an ejection device, an impact sounding probe and a measurement and control cable. A winch is automatically controlled through a winch control unit, the take-up and pay-off speed is fed back and adjusted through a tension sensor, and dual-mode control is adopted for different operation water depths of 0-5 m and 5-50 m. The ejection device energizes the probe through the energy storage spring, and the locking mechanism achieves automatic locking and releasing. The impact sounding probe adopts a standard structure and is provided with various sensors, so that data can be stably acquired and wirelessly transmitted. The device can accurately control probe putting, is suitable for operation at different water depths, has good recoverability, effectively overcomes the defects of traditional sounding equipment, and improves the efficiency of geological exploration and the accuracy of data.

An acoustic source for use in a well or pipe includes a pulser piston disposed in an acoustic chamber, a linear actuator connected to one side of the pulser piston and a pressure compensator having a pressure outlet in fluid communication with the one side of the pulser piston. The pressure compensator has a sensor for measuring pressure in the well or pipe, a sensor for measuring compensation pressure on the one side of the piston, an hydraulic power source and a controller operatively connected to the hydraulic power source, the well or pipe pressure sensor and the compensation pressure sensor. The controller operates the hydraulic power source such that a predetermined pressure difference between the well or pipe pressure and the compensation pressure is maintained. The controller operates the linear actuator to move the pulser piston to generate acoustic waves having predetermined amplitude, phase, frequency, and waveform.

The invention relates to an ice water pool test simulation device and method for a submersible vehicle multi-attitude floating icebreaking process, and belongs to the technical field of low-temperature dragging ice water pool model tests. Comprising a lifting mechanism, an L-shaped extension arm, a supporting structure, a rotation angle sensor, a limiting cushion block, a cross beam base, a force measuring sensor, a buoyancy device and a camera, the L-shaped extension arm is connected with the lifting mechanism and the supporting structure, the L-shaped extension arm is connected with the cross beam base through the rotation angle sensor, the cross beam base is provided with the buoyancy device, and the supporting structure is provided with the limiting cushion block. The limiting cushion block is matched with the cross beam base, the cross beam base is connected with a submersible vehicle model through a force transducer, and cameras are arranged around the L-shaped extension arm. The device is suitable for different ice pool environments, the multi-attitude change in the contact ice breaking process of the underwater vehicle and the ice surface is truly represented, and important test data support is provided for design, performance evaluation and numerical simulation research of the underwater vehicle.

The invention discloses a marine propeller static balance detection device and a marine propeller static balance detection method. The propeller centering device comprises a bearing platform and a centering assembly, a suspension device is arranged in the middle of the lower portion of the bearing platform, the centering assembly comprises a centering disc and a plurality of clamping jaws which are arranged on the centering disc and can synchronously move inwards and outwards relative to the center of the positioning disc, and a propeller is directly located on the centering disc and is supported outwards from the interior of the centering disc through the clamping jaws for centering. The bearing platform is provided with a force measuring sensor, the centering assembly can suspend through the suspension device, and the force measuring sensor carries out data acquisition in the suspension state so as to carry out deviation detection. The device has the advantages that the working efficiency is greatly improved, the centering precision is also very high, and the accuracy of subsequent data detection is ensured; the service life is greatly prolonged; the centering device is simple in structure, good in parallelism and high in coaxiality, centering accuracy is guaranteed, the whole structural design is very simple, the number of parts is small, transmission links are small, reliability is high, detection data are accurate, and manufacturing cost is not low.

The invention relates to the technical field of micro-electro-mechanical system sensors, in particular to an MEMS pressure sensor which comprises a shell, an induction diaphragm and an ASIC signal processing unit, an induction mounting cavity and a signal processing cavity are formed in the shell, an air inlet is formed in the lower end face of the shell, a detection channel and a buffer cavity are formed in the shell, and the detection channel is communicated with the signal processing cavity. The buffer cavity is designed to be gradually expanded from bottom to top; pulse airflow firstly enters the detection channel through the air inlet, and direct disordered impact of the airflow is avoided; then the airflow enters the buffer cavity, the airflow speed and the pressure peak value are gradually reduced and the pulse energy is dispersed by utilizing the characteristic that the cross sectional area of the cavity is gradually increased, and the originally concentrated strong impact force is converted into gentle pressure transmission, so that the abrasion and damage risks caused by the fact that the sensing diaphragm frequently bears the violent pressure are reduced; the structure stability and the sensing sensitivity of the sensing diaphragm can be maintained, and the accuracy of pressure detection and the reliability of long-term work of the MEMS pressure sensor can be guaranteed.