888 results about "Piezoelectric sensor" patented technology

The invention relates to the technical field of cable operation state detection, and particularly discloses a multi-source data driven cable operation state comprehensive evaluation method, which comprises the following steps of S1, adopting a layered distributed sensing network architecture, and deploying three types of core sensors at key nodes of a cable, through space-time calibration of the multi-source heterogeneous sensor, data consistency is improved, fusion deviation is eliminated, the problem of data islands of a traditional system is solved, and a precise evaluation foundation is laid; noise suppression and dynamic correlation modeling are adopted, environmental interference is stripped, a vibration and displacement coupling relation is quantified, limitation of a single parameter is broken through, heterogeneous fault features are captured, and evaluation comprehensiveness and sensitivity are improved; a self-adaptive threshold mechanism is constructed based on environment weight and historical data, the bottleneck of a fixed threshold is broken through, an evaluation standard is corrected along with equipment aging and environment change, misjudgment is avoided, and diagnosis robustness in different scenes is enhanced.

The invention relates to the technical field of grinding machining, and particularly discloses a crankshaft connecting rod grinding force dynamic error compensation method and system.The method comprises the steps that a prediction reference signal is collected; a grinding force signal of the grinding wheel spindle is collected based on a piezoelectric sensor; extracting spectrum characteristic parameters according to the predicted reference signal; predicting grinding force fluctuation information according to the spectrum characteristic parameters; a feedforward compensation instruction is generated according to the grinding force fluctuation information; generating a feedback compensation instruction according to the difference between the grinding force signal and the target grinding force of the current task; synthesizing the feedforward compensation instruction and the feedback compensation instruction to generate a compensation control instruction; according to the method, a control strategy combining feedforward and feedback is adopted, the response speed and compensation precision of a system to dynamic changes of grinding force are remarkably improved, accordingly, elastic deformation caused by fluctuation of the grinding force is effectively restrained, and finally the grinding machining precision and surface quality of key parts of the crankshaft connecting rod are improved.

A histotripsy therapy system configured for the treatment of brain tissue is provided, which may include any number of features. In one embodiment, the system includes an ultrasound therapy transducer, a drainage catheter, and a plurality of piezoelectric sensors disposed in the drainage catheter. The ultrasound therapy is configured to transmit ultrasound pulses into the brain to generate cavitation that liquefies a target tissue in the brain. The drainage catheter is configured to detect the ultrasound pulses. An aberration correction algorithm can be executed by the system based on the ultrasound pulses measured by the drainage catheter to automatically correct for an aberration effect caused by the ultrasound pulses passing through a skullcap of the patient.

The invention, which relates to the technical field of traffic management, discloses an intelligent detection system for a vehicle parking space in a passenger and goods mail fusion station, and the system comprises a multi-mode sensing module which is configured to collect vehicle data information, the collection mode comprises the steps that vehicle data information is collected through an enhanced geomagnetic array, an adjustable video monitoring set, a lateral laser radar and a piezoelectric sensor; and the edge computing node module is configured to integrate an AI chip, the AI chip comprises a vehicle classification model, an abnormal parking detection algorithm and a data fusion engine, and the collected data is computed and analyzed. The edge computing node is integrated with an AI chip, and data are analyzed and processed through a built-in algorithm; the hybrid communication network transmits data through an optical fiber backbone network and a specific redundant link, self-adaptive visual adjustment and intelligent algorithm optimization are performed, the problem of complex vehicle type detection in a passenger and goods mail fusion station is solved, and the parking space utilization rate and the operation efficiency are remarkably improved.

The invention discloses a sleep state real-time monitoring method and system, and belongs to the technical field of sleep monitoring, and the method specifically comprises the steps: collecting a heart rate variability signal, an electroencephalogram signal and body movement data of a user in real time through a non-invasive sleep pad integrating a piezoelectric sensor, a flexible dry electrode and a pressure sensor; based on the physiological data, whether the user reaches an autonomous sleep state or not is judged through a first algorithm model; if not, starting an active intervention program for playing the adjustable music, and dynamically adjusting the music volume, the playing speed or the track in combination with the physiological data feedback until the user enters an autonomous sleep state; after the user falls asleep, physiological data are continuously collected, and a sober period, a light sleep period, a deep sleep period and a rapid eye movement period are divided through a second algorithm model; if the staging result is a waking period, the autonomous sleep state judgment is executed again; according to the invention, non-intrusive monitoring and personalized intervention are combined, and the monitoring comfort and accuracy are improved.

The invention discloses intelligent bent pipe punch forming equipment and method, and relates to the technical field of pipe fitting punch forming, the intelligent bent pipe punch forming equipment comprises a machine body and a pipe blank, the machine body is provided with a die mechanism, a pushing mechanism and an elbow core rod provided with a first quick release assembly, and the die mechanism comprises an upper die and a lower die which are fixed to the machine body; the upper die and the lower die are respectively provided with forming runners which are matched with each other, and the tube blank is placed in the forming runner of the lower die. By arranging the pressure feedback mechanism and the lubricating oil spraying mechanism, the friction force between the pipe blank and the elbow core rod is converted into the pressure value change in the pressure detection cavity and transmitted to the piezoelectric sensor, the piezoelectric sensor feeds back the pressure value to the control unit, and the control unit can control the rotating speed of the oil pump according to the pressure value. The larger the friction force between the pipe blank and the elbow core rod is, the higher the rotating speed of the oil pump is, the more lubricating oil is sprayed out of the oil spraying holes, the intelligent degree of lubrication is improved, and the stamping effect is guaranteed.

The present invention discloses a multi-modal system for real-time plant hydration monitoring and irrigation management. The system comprises at least one acoustic sensor configured to emit controlled sound waves through plant tissues and detect corresponding vibrations and resonance frequencies using sensitive microphones or piezoelectric sensors to assess plant hydration. The system includes at least one bioelectrical sensor for monitoring bioelectrical signals. At least one nanotechnology-based sensor is configured to detect molecular changes in water content within plant cells through embedded or externally applied nanosensors. An aerial imaging device mounted on an unmanned aerial vehicle captures data related to canopy temperature, leaf color, and hydration indicators using infrared, multi-spectral, and thermal cameras. A central processing unit receives and analyzes data using predictive models, integrates the data via data fusion algorithm to generate a plant hydration profile, and controls water delivery through an irrigation management unit based on the hydration profile.

The invention discloses a rotating machine vibration protection method and system of an adaptive resonance neural network, and the method comprises the steps: collecting a millisecond vibration acceleration signal of a rotating machine through a distributed piezoelectric sensor array, obtaining the real-time working condition parameter of equipment, and generating a time-work synchronous vibration signal flow; inputting the time-work synchronous vibration signal flow into a resonance neural network, and dynamically generating a frequency domain-time varying adaptive threshold group in combination with the working condition parameters; extracting a weak impact resonance characteristic tensor by using a multi-scale resonance kernel of the resonance neural network; projecting a weak impact resonance characteristic tensor to an orthogonal fault subspace through a tensor decomposition algorithm, and separating out a decoupling fault characteristic matrix; and generating a real-time protection decision instruction set based on a comparison result of the decoupling fault feature matrix and the equipment operation historical database. According to the embodiment of the invention, the method can improve the detection sensitivity and positioning precision of a weak fault under an unsteady working condition, and achieves the real-time adaptive optimization of the vibration protection of the rotating machine.

The invention relates to the technical field of flexible piezoelectric sensors, and discloses a wide-working-condition multi-dimensional force representation flexible film piezoelectric sensor and a signal analysis method, after a pvdf piezoelectric film is cut in a paper-cut mode, regionalized electrode coating and covering are carried out, and multi-channel signal output is achieved. Therefore, characterization of multi-dimensional force can be realized on one film sensor, and meanwhile, the tension and conformal capability of the sensor are enhanced through the paper-cut design, so that the attachment requirement of a complex surface is met. A multi-layer composite structure is combined and comprises a flexible polymer protection layer and a flexible connection layer, and high sensitivity, excellent tensile property and mechanical durability are achieved through hot pressing and local ultrasonic welding. The sensing capability is enhanced, and the defect of poor tensile property of a traditional PVDF piezoelectric sensor is overcome. The preparation method is simple in process, low in cost and suitable for large-scale industrial production. In addition, the invention provides a deep learning analysis method for multi-channel signals, and classification and nonlinear fitting can be realized.

The invention provides a blasting engineering site safety risk real-time assessment and intelligent scheduling method. According to the method, a piezoelectric sensor array is arranged on a blasting engineering site to collect sound wave signals, and dynamic change information of fractures in a rock mass is captured; calculating sound wave propagation time difference data between adjacent nodes, and determining a new fracture space position and an existing fracture expansion trend according to time difference fluctuation characteristics; the fracture position, the expansion trend and the label of the current blasting operation stage are input into a fuzzy logic decision-making system, and a fracture risk distribution diagram reflecting the real-time stability of the rock mass is generated through collaborative analysis; determining a field safety risk level based on the graph, and quantifying the subsequent instability possibility of the rock mass; and a scheduling instruction is generated according to the risk level, the drilling position, the charging sequence and the detonation time sequence are dynamically adjusted, the operation process is optimized, and the instability risk is avoided. According to the method, the dynamic sensing precision and response speed of the blasting engineering field rock mass instability risk are improved.

The invention relates to the technical field of deep learning, in particular to a dialysis hypotension risk prediction system and method based on deep learning, and the system comprises a multi-point signal collection module, a signal processing module, a multi-scale causal expansion convolutional network prediction module, an osmotic pressure correction module and a dialysis plan automatic adjustment module. The method comprises the following steps: synchronously collecting physiological signals of a patient through a finger tip photoelectric volume sensor and a radial artery piezoelectric sensor array, carrying out band-pass filtering and morphological refinement processing on the signals, extracting features, and calculating pulse wave conduction time and a change rate thereof; inputting the characteristic parameters into a multi-scale causal expansion convolutional network to predict the hypotension risk in dialysis; dynamically correcting the prediction result according to electrolyte monitoring data; based on the corrected risk, a hierarchical response strategy is adopted to automatically adjust dialysis parameters, a multi-scale causal expansion convolutional network is adopted to capture physiological parameter changes on different time scales at the same time, and high-precision prediction of hypotension is achieved.

The invention relates to the technical field of vital sign measurement, in particular to a wearable underwater vital sign and environment monitoring system, which comprises a physiological signal acquisition module, a photoelectric volume pulse wave sensor, a bioelectrical impedance electrode, a piezoelectric sensor, a signal processing module, a signal processing module and a signal processing module, a wrist photoelectric volume pulse wave signal, a chest bioelectrical impedance signal and a neck piezoelectric signal are collected. According to the method, signal reconstruction is carried out based on energy proportion calculation, an electrocardiogram R wave peak value point position and an R-R interval time sequence are extracted, variability indexes are generated through frequency domain decomposition and frequency band energy statistics, time domain and frequency domain index values are calculated, weight distribution is carried out, and therefore comprehensive monitoring on the underwater physical sign state is achieved. The signal acquisition precision is improved by means of a multi-source signal acquisition mode, noise interference is eliminated through signal track matrix decomposition operation, and the signal reconstruction quality is ensured through feature vector energy proportion calculation.

The invention discloses a button switch adaptive optimization method and a storage medium. The method comprises the following steps: acquiring a tactile signal through a high-density piezoelectric sensor, and extracting pressure distribution, gradient change rate and energy concentration degree characteristics in combination with a space-time convolution kernel and a dynamic baseline calibration algorithm; integrating time-frequency domain analysis of the historical operation sequence and neural differential equation modeling, predicting an operation probability and marking an anomaly; and an anti-interference control instruction is generated by fusing environmental parameters, and multi-source data are dynamically weighted by adopting a gating attention mechanism. The system constructs a multi-stage reliability protection mechanism, and fault immunity is realized through feature drift detection, digital twin residual verification and hybrid control switching. And responding to a real-time demand, dynamically optimizing heterogeneous computing resource allocation, executing three-dimensional storage reconstruction and precision bit width switching, and forming a closed-loop cognitive evolution link.

In aspects of rollable screen device with piezoelectric sensing, a mobile device includes a rollable display screen configurable in one of multiple display states corresponding to respective device form factors. The mobile device has one or more piezoelectric sensors that detect forces applied to the rollable display screen of the mobile device. The mobile device implements a selection manager that activates one or more parameters (e.g., volume, call acceptance, call decline) of the mobile device based on the forces detected by the one or more piezoelectric sensors.

The invention relates to the field of flexible sensing, and discloses a flexible dual-mode sensor with a foot arch and motion detection function, the flexible dual-mode sensor comprises an upper substrate, a lower substrate, an electrode layer, a conductive pin, a PVDF doped BTO-NPs nanofiber film and a PVDF doped ionic salt solution nanofiber film, the upper substrate and the lower substrate are polyimide films (PI), the electrode layer is an immersion gold (Au) pad, and the conductive pin is arranged on the electrode layer. The conductive pin is formed by fixing a copper wire on the electrode plate through silver paste, the nanofiber membrane is obtained by PVDF doped BTO-NPs and PVDF doped ionic salt electrostatic spinning, the gold immersion (Au) bonding pad membrane is designed on the PI substrate to form polar plates and electrodes of the capacitive sensor and the piezoelectric sensor, and the electrode plate is led out through the copper wire to serve as the conductive pin. According to the flexible dual-mode sensor, the flexible PI in a specific shape is prepared to serve as the upper substrate and the lower substrate of the flexible dual-mode sensor, and the gold immersion (Au) bonding pad films are designed on the PI substrates, so that the flexible sensor has flexibility and ductility and is more attached to surfaces with different curvatures.

Systems and methods include a sensor device for detecting passing valves. The sensor device includes a housing including a first side configured to contact a wall of a pipe in a pipe system. A cover plate is coupled to a second side of the housing opposite the first side. A piezoelectric sensor is disposed in the housing and configured to detect acoustic emissions from a valve in the pipe system. A sensor holder is disposed within the housing to maintain a position of the piezoelectric sensor. A spring is positioned around a portion of the sensor holder and configured to bias the sensor holder away from the cover plate and toward the first side of the housing. A computer system is mounted to the housing and configured to determine that a valve is a passing valve based on acoustic emissions detected by the piezoelectric sensor.

The embodiment of the invention discloses a flexible piezoelectric sensor packaged by a fish scale microstructure elastomer and a preparation method thereof, the flexible piezoelectric sensor is provided with a flexible main body structure, the flexible main body structure comprises a first packaging layer, a piezoelectric layer, an electrode layer and a second packaging layer, the central area of the first packaging layer is provided with a rectangular notch, and the piezoelectric layer is arranged in the rectangular notch; a rectangular notch is formed in the first packaging layer, an elastomer packaging layer covers the rectangular notch, the elastomer packaging layer comprises a substrate and a fish scale microstructure, and the stress distribution effect of the elastomer packaging layer is optimized through the fish scale microstructure, so that the composite packaging structure of the first packaging layer and the elastomer packaging layer can guide stress to be concentrated in a specific area; the flexible piezoelectric sensor has the advantages that the flexible piezoelectric sensor is provided with the fish scale microstructure, local strain capacity is enhanced, energy dissipation is reduced, the fish scale microstructure comprises a plurality of fish scale microstructure units, the fish scale microstructure units are arranged in an array mode, and sensitivity and response speed of the flexible piezoelectric sensor under the low-pressure or low-frequency condition are further improved.

The invention discloses an engineering structure performance state inversion method, a safety early warning method and a safety early warning system based on engineering skin. The inversion method comprises the following steps: acquiring multi-source data acquired by multiple types of sensors arranged on a to-be-monitored engineering structure; preprocessing the multi-source data; fusing the multi-source data by adopting multi-rate Kalman filtering based on a neural network to obtain multi-source data with a unified time step; taking the data of the plurality of flexible piezoelectric sensors after the unified time step as model input, inputting the data into a trained neural network-based key point engineering demand parameter inversion model, and performing inversion to obtain engineering demand parameters of a plurality of key points of the engineering structure; and correcting an inversion result by using a Bayesian algorithm in combination with data of corresponding time steps of the external source sensor. According to the method, the key point engineering demand parameters can be quickly inverted, the inversion efficiency is high, and the precision is high.

The invention discloses a double-layer piezoelectric sensor and an application and method of the double-layer piezoelectric sensor in representing beta-phase polyvinylidene fluoride membrane adsorptive pollution, a piezoelectric beta-phase polyvinylidene fluoride membrane is a porous membrane formed by a blending system of polyvinylidene fluoride and ionic liquid and has a beta-phase crystal structure and a piezoelectric response characteristic, and the piezoelectric beta-phase polyvinylidene fluoride membrane is prepared by spin-coating a PVDF solution on a chip. The double-layer piezoelectric sensor containing the beta-phase polyvinylidene fluoride membrane is obtained, and QCM-D detection is carried out to characterize the adsorptive pollution condition of the beta-phase polyvinylidene fluoride membrane. Adsorption and desorption behaviors of organic matters with different dissolvability and mixtures thereof on the beta-phase PVDF membrane layer are represented, the adsorption result is matched with the hole blocking resistance in the actual membrane pollution process, and the hole blocking resistance is calculated by monitoring the fifth overtone of the piezoelectric quartz sensor. And the quality of soluble organic matters adsorbed on the PVDF surface and the property of an adsorption layer can be evaluated by using a frequency change value and a dissipation value, and a scheme is provided for researching the pollution behavior of the beta-phase polyvinylidene fluoride membrane.

The invention relates to a construction method for a roadbed penetrating through a V-shaped valley area, and belongs to the technical field of foundation engineering and foundation treatment. The problems of low foundation drainage efficiency, filling side slope instability and differential settlement control in V-shaped valley roadbed construction are solved. According to the technical scheme, a groove is dug along the bottom of a valley, a gravel drainage blind ditch wrapped by permeable geotextile is laid, and a foundation drainage system is formed; during layered filling, a vibratory roller with a piezoelectric sensor embedded into a steel wheel is adopted; after every two layers are filled, one-way geogrids are laid along the slope and vertically anchored into the compaction layer through U-shaped anchoring parts; a transverse drainage pipe is pre-buried when filling is conducted to a foundation bearing capacity sudden change point threshold value; and after filling is completed, a settlement monitoring array is arranged. According to the method, through system integration of foundation drainage structure optimization, filling body intelligent compaction and differential settlement dynamic treatment, the bearing stability of the fill roadbed under the complex terrain is remarkably improved, and the method is suitable for foundation construction and disaster prevention and control of the V-shaped canyon section of the mountain road.

The invention belongs to the technical field of cutting processing, and particularly discloses a vibration cutting device monitoring and control system based on a flexible piezoelectric sensor, comprising a cutting module, a signal detection module, a signal processing module and a feedback control module: the cutting module is used for cutting according to an elliptical motion track based on a preset vibration signal; the output end of the signal detection module is connected with the input end of the signal processing module and used for detecting vibration signals of the cutting module in real time. The output end of the signal processing module is connected with the input end of the feedback control module, and the signal processing module is used for analyzing and processing the vibration signals and identifying abnormal changes and interference factors in the vibration signals; and the output end of the feedback control module is connected with the input end of the cutting module, and the feedback control module is used for predicting a vibration signal of the cutting module at a future moment based on the abnormal change and the interference factor, generating a compensation signal based on an error between the predicted vibration signal and a preset target vibration parameter, and adjusting the vibration signal of the cutting module in real time.

The invention discloses a micro-seismic monitoring piezoelectric acceleration sensor optimization method based on an NSGA-II algorithm, provides a piezoelectric sensor based on a triangular shear structure, and relates to the technical field of piezoelectric acceleration sensors. According to the micro-seismic monitoring piezoelectric acceleration sensor optimization method based on the NSGA-II algorithm, the NSGA-II genetic algorithm is adopted to optimize the structural size of the designed sensor, and an optimal structural parameter combination is obtained, that is, when the height of a mass block is 10.6 mm, the thickness of a piezoelectric patch is 3.29 mm, the height of the piezoelectric patch is 8.1 mm and the height of a central column is 19 mm, the sensor design is optimal, and the optimal structural parameter combination is obtained. The working frequency of the optimized sensor is improved by 2.68%, and the voltage sensitivity is improved by 8.96%. And finally, respectively carrying out a calibration experiment and a micro-seismic signal test on the designed sensor by building an experiment platform. Experimental results show that the working frequency range of the designed sensor is 0.1-2123 Hz, and the voltage sensitivity is 173.49 mv / g.

A piezoelectric sensor (e.g., for use in a piezoelectric MEMS microphone) includes a substrate and a cantilever beam attached to the substrate. The cantilever beam has a proximal portion attached to the substrate and extending to an unsupported distal end. An electrode is disposed on or in the proximal portion of the beam and has an outer boundary with a shape substantially corresponding to a contour line of a strain distribution plot for the cantilever beam resulting from a force applied to the cantilever beam.

Some embodiments relate to an energy transduction device or apparatus. An example device or apparatus includes: a piezoelectric transducer; electrical conductors electrically coupled to the piezoelectric transducer; and an axially aligned magnet assembly arranged to apply static compressive force to the piezoelectric transducer, the magnet assembly being coupled to a base at one end and having a free opposite end. The magnet assembly is coaxial with the piezoelectric transducer and at least part of the magnet assembly is concentric with the piezoelectric transducer. The magnet assembly defines a gap between axially adjacent parts of the magnet assembly, wherein the gap is dimensioned to be sufficiently small that the magnet assembly applies a static compressive force to the piezoelectric transducer while being sufficiently large to allow for axial movement of the piezoelectric transducer without closing the gap.

The invention discloses a fuzzy theory fused tongue diagnosis characteristic quantitative analysis method and system, and relates to the technical field of traditional Chinese medicine tongue diagnos.The method comprises the steps that a micro piezoelectric sensor array and a hyperspectral imaging module are integrated, tongue surface Young modulus distribution data and hyperspectral reflectivity data are synchronously collected, and a multi-mode tongue picture fusion data set is generated; further performing crack region segmentation and super-resolution reconstruction through a neural network model, outputting a crack network diagram and a tongue papilla form entropy, generating topological fingerprints in combination with continuous homology analysis, identifying a mechanical gradient mutation region and extracting a metabolic index, constructing a mechanical-metabolic associated feature set, and obtaining a mechanical-metabolic associated feature set; topological fingerprints and mechanical-metabolic characteristics are fused in a three-dimensional space-time coordinate system, a dynamic intuitionistic fuzzy decision field is constructed, finally, tongue picture pathology evolution risk indexes and a visual early warning report are output through a pathology prediction model, and the system provides quantifiable decision support for'prevention before illness' in traditional Chinese medicine.

The invention provides a low-frequency measurement amplifying circuit for suppressing direct-current bias voltage and noise. The low-frequency measurement amplifying circuit is mainly used for reducing the direct-current bias voltage and suppressing interference of low-frequency and high-frequency noise of the circuit. The scheme of the invention comprises a low-pass filtering module, a charge conversion module, a multi-gear gain adjustment module and an output signal protection module. High-frequency noise of weak charge signals generated by the piezoelectric sensor is filtered out through the low-pass filtering module, then the charge signals are converted into voltage signals through the charge conversion module, the voltage signals are amplified according to different proportions through the multi-gear gain adjusting module, and finally the converted and amplified voltage signals are output through the output signal protection module. Compared with the prior art, the low lower limit cut-off frequency is achieved, meanwhile, the direct current bias voltage and noise generated by the circuit are reduced, a band elimination filter is formed through circuit design, the influence of low-frequency and high-frequency interference signals is restrained, and the quality of output signals is improved.

The utility model belongs to the technical field of structural health monitoring, and particularly relates to a clamp for a piezoelectric sensor bonding process. The clamp is characterized in that a force application rod mounting part is arranged on a fixed bracket; one end of the telescopic support frame is connected with the fixed bracket, and the other end of the telescopic support frame is connected with a structural member of a piezoelectric sensor to be bonded through a fixed sucker; the force application rod is mounted on the force application rod mounting part, a force application handle is mounted at one end of the force application rod, and a force sensor is mounted at the other end of the force application rod; the piezoelectric sensor bonding head is mounted on the force sensor, and a piezoelectric sensor is bonded in the piezoelectric sensor bonding head; the sensor output display device is used for displaying and recording measurement data of the force sensor. According to the invention, standardization and uniformity of the installation technology can be realized, difference caused by manual bonding is eliminated, and the bonding performance of the sensor is improved.

The invention relates to the technical field of nuclear reactors, and provides a nuclear reactor piezoelectric sensor sensitive material optimization method and device and a medium, and the method comprises the steps: 1, determining an initial sensitive material sample based on a sensitive material template and an initial element doping scheme; 2, performing an irradiation experiment on the initial sensitive material sample, and determining irradiation parameters corresponding to the initial sensitive material sample based on an experiment result; 3, determining the average parameter change rate of the sample based on the irradiation parameters corresponding to the plurality of initial sensitive material samples and the high-temperature performance parameters corresponding to the plurality of initial sensitive material samples subjected to the irradiation experiment, and judging whether the average parameter change rate of the sample is smaller than a preset threshold value or not; if yes, determining the initial sensitive material sample as a target optimization sensitive material; and if not, adjusting the initial element doping scheme, and returning to the step 1. According to the embodiment, the piezoelectric coefficient of the piezoelectric sensitive material in a high-temperature nuclear radiation environment is improved, and the fault monitoring precision of key equipment of a nuclear reactor is improved.

The invention discloses a passive wireless bolt axial force measuring method and equipment, the bolt axial force measuring equipment comprises a pulse transmitting unit, a transmitting end transmitting coil, a transmitting end receiving coil, an electric signal detection unit, a receiving end coil, a piezoelectric sensor and an ultrasonic probe, the pulse transmitting unit can generate an electric pulse signal with the pulse width of 100-0.01 us, and the receiving end coil can generate an electric pulse signal with the pulse width of 100-0.01 us; the electric pulse signal is received by the transmitting end transmitting coil to generate an induction pulse electromagnetic field, the induction pulse electromagnetic field is received by the receiving end coil to be transmitted to the piezoelectric sensor, the piezoelectric sensor generates ultrasonic waves, the ultrasonic waves act on the bolt and then are reflected, and the reflected ultrasonic signal outputs an electric signal through the piezoelectric sensor; after the electric signal detection unit receives the electric signal through the transmitting end receiving coil, the bolt axial force is calculated based on the ultrasonic propagation sound time when the ultrasonic propagation sound time is measured.

The invention discloses an intelligent pruning system and method for vine crops. The intelligent pruning system comprises a multi-foot moving platform, a two-stage visual positioning module, an obstacle avoidance module, a multi-mode cutting module and a control module. The multi-foot mobile platform adapts to complex terrains, multiple sets of bionic mechanical arms are symmetrically arranged on the top, and collision is avoided through anti-interference cooperation; in the two-stage visual positioning, the coarse positioning identifies a bud flower area based on an HSV color space and transfer learning, and the fine positioning adopts macro vision and an improved YOLOv5 model to realize the pose compensation of the mechanical arm; the obstacle avoidance module generates a three-dimensional point cloud through laser radar scanning, and plans a collision-free path in combination with an adaptive step RRT algorithm. The multi-mode cutting module integrates a piezoelectric sensor, a near infrared spectrum and the like, and a pneumatic cutting tool, a mechanical cutting tool or a laser cutting tool is dynamically switched. The control module coordinates the whole-process operation and supports the shearing and vine swinging modes; the system realizes high-precision identification, self-adaptive cutting and low damage rate, and is suitable for automatic management of vine crops such as grapes and watermelons.