429 results about "Vibration sensing" patented technology

The invention relates to the technical field of optical cable line external force damage monitoring, and discloses an optical cable external force damage intelligent identification system. The system comprises an optical fiber vibration sensing module, a multi-source feature fusion analysis module, an abnormal event association positioning module and an intelligent checking strategy generation module. The optical fiber vibration sensing module constructs a model based on historical data and outputs a reference vibration characteristic value; the multi-source feature fusion analysis module performs three-dimensional fusion analysis of time domain, frequency domain and phase on the reference value and the measured value to generate a feature difference matrix; the abnormal event association positioning module is used for generating an abnormal probability distribution cloud picture and positioning an abnormal area in combination with the topological parameters and the environment information; and the intelligent checking strategy generation module configures checking parameters according to the cloud picture, starts high-frequency acquisition for a high-probability region, and applies an environment disturbance test to adjacent lines. The system can accurately identify and position optical cable external force damage, and the monitoring efficiency is improved.

The invention discloses a polarization-state-based optical fiber vibration sensing system and application, and relates to the technical field of optical fiber sensing, and the polarization-state-based optical fiber vibration sensing system mainly comprises a transmitting end and a receiving end. The transmitting end comprises a laser diode, a first erbium-doped optical fiber amplifier, a first circulator, a polarization scrambler, a single-mode optical fiber link, a second circulator and a second erbium-doped optical fiber amplifier which are connected in sequence; and the receiving end comprises a polarization beam splitter, a first shunt module, a second shunt module, an optical mixer, a first balanced photoelectric detector, a second balanced photoelectric detector, a third balanced photoelectric detector and a polarization analysis module. According to the optical fiber vibration sensing system based on the polarization state and the application, the vibration monitoring performance and reliability in a long-distance and high-noise environment can be improved.

The invention relates to the technical field of automatic control, and discloses a cable winding and unwinding speed self-adaptive control system under a dynamic working condition, which comprises an endogenous vibration sensing module configured on a cable reel supporting bearing and a system state decoding module, and the decoding module can decode a single original electric signal from a single original electric signal converted by the endogenous vibration sensing module. According to the invention, the core bearing structure of the reel is converted into an information source of a self-state, and multi-dimensional state information of real-time tension, overall rotational inertia of the system, abrupt change of friction and the like after temperature self-calibration is decoded in parallel, so that the self-adaptive control module is driven to match and execute a corresponding speed control strategy. Signal delay and system vulnerability caused by traditional multi-sensor layout are avoided, a control decision is made according to information reflecting the current system state, and the system further has the functions of optimizing a control strategy and compensating temperature influence according to historical data.

The invention belongs to the technical field of distributed optical fiber sensing and low-altitude security and protection, and particularly relates to an unmanned aerial vehicle long-distance tracking method based on distributed optical fiber vibration sensing. The invention relates to an unmanned aerial vehicle vibration / electromagnetic fusion multi-mode identification method, a special installation formation design, a dispersion compensation and amplitude phase error compensation design, an unmanned aerial vehicle target vibration / electromagnetic fusion multi-mode identification design, a detection capability calculation method of an unmanned aerial vehicle vibration sound pressure-space attenuation law-distributed optical fiber processing equipment detection capability coupling model, a long-distance sensing optical cable and an electromagnetic monitoring node. According to the tracking method, a special optical fiber installation mode, dispersion compensation and phase error compensation of an original phase signal, a vibration / electromagnetic fusion multi-mode identification method, an unmanned aerial vehicle vibration sound pressure-space attenuation model-distributed optical fiber processing equipment detection capability corresponding method and other innovative work are adopted; a mature distributed optical fiber vibration sensing system is utilized to realize long-distance passive detection and target tracking of the low-slow-small unmanned aerial vehicle.

The invention provides a highway subgrade void recognition method, device and system and a storage medium, and belongs to the technical field of signal processing, and the method comprises the steps: obtaining corresponding original time domain vibration signals generated when a current vehicle passes through a plurality of grating measurement points in a grating array vibration sensing optical cable arranged below a highway surface layer; extracting dominant frequency features corresponding to each grating measuring point from the original time domain vibration signal; determining a signal fluctuation characteristic value of an area where the plurality of grating measuring points are located based on the dominant frequency characteristic corresponding to each grating measuring point; and determining a roadbed void identification result of an area where the plurality of grating measuring points are located based on the signal fluctuation characteristic values. The void identification is carried out according to the quantized data of the signal energy fluctuation between the grating measuring points, the identification mode is simple and rapid, and the fluctuation value of the dominant frequency characteristic is used as an identification index, so that the high-sensitivity discrimination of the abnormal state in the roadbed structure is realized, and the accuracy and efficiency of the void identification of the highway roadbed are improved.

The invention relates to the technical field of hydraulic control one-way valve testing, and discloses a hydraulic control one-way valve testing method which is used for solving the problem that the real performance of a hydraulic control one-way valve under actual complex working conditions is difficult to comprehensively reflect due to the fact that an existing testing method is single in working condition, insufficient in data acquisition dimension and lack of dynamic modeling capacity. A programmable working condition loading module is introduced, a hydraulic test environment with dynamic characteristics is constructed according to a pressure and flow change curve in practical application, and high-precision and multi-dimensional synchronous acquisition of the whole opening and closing process of the hydraulic control one-way valve is realized by combining a high-frequency displacement sensor, a micro-flow sensor and a vibration sensing unit; according to the scheme, the defect that a traditional testing method is difficult to restore the real dynamic working condition is effectively overcome, the authenticity of valve performance testing and the detail integrity of response data are remarkably improved, and powerful support is provided for accurately evaluating the dynamic behavior of the hydraulic control one-way valve under the complex working condition.

The invention discloses a rock slope sliding interface identification and degradation monitoring method based on distributed sound wave sensing. The monitoring method comprises the steps that a plurality of vibration sensing optical cables are vertically arranged in a rock slope along a drill hole, multi-channel vibration time sequence data are obtained through a distributed sound wave sensing demodulator, and the multi-channel vibration time sequence data are obtained through detrending and noise suppression of a data preprocessing unit, space-time consistency filtering of apparent velocity constraint and phase weighted stacking. STA / LTA triggering and DBSCAN clustering are utilized to realize single-cable event merging, and unique pairing and three-dimensional positioning of cross-cable events are completed in combination with geometric matching degree and waveform form correlation degree; the sliding interface inversion unit adopts a deep learning model to classify abnormal events, constructs an event density field and an energy intensity field for sliding related events, forms a sliding interface evidence field, and optimizes an inversion sliding interface in a limited solution domain; the degradation state monitoring unit identifies a hot spot area on a sliding interface, tracks intensity and scale evolution, constructs a degradation index, and can realize early warning in combination with multi-source information such as earth surface displacement.

The invention relates to the field of buried facility monitoring, and discloses a piezoelectric cantilever vibration sensing and super capacitor self-powered energy closed-loop operation method and system, and the method comprises the steps: building a star array composed of a master pile and a slave pile, and configuring a TDMA time slot and an uplink message length; the slave pile collects a vibration signal through a piezoelectric cantilever, the vibration signal is rectified by a piezoelectric rectification energy taking module and then charges a super capacitor, and the voltage state of the two ends of the super capacitor is obtained; when the voltage state reaches a preset upper threshold, the boosting module supplies power to the processing circuit and the transmitting circuit of the slave pile, and the processing circuit generates a four-byte feature code; the slave piles send four-byte feature codes in a magnetic induction link according to TDMA time slots, the master pile receives and aggregates the four-byte feature codes sent by the multiple slave piles, completes positioning and fusion according to the arrival time difference, and returns the four-byte feature codes to the platform through LoRa and 4G, and the platform completes storage and output according to the four-byte feature codes and a positioning result. According to the invention, end-side cloud connection and replicable deployment can be realized, and low-frequency vibration acquisition and buried communication are adapted.

The invention discloses a solder paste defect detection method based on machine vision, relates to the technical field of printed circuit board detection, and aims at the challenge of solder paste printing quality detection in superfine-pitch high-reliability manufacturing, high-precision three-dimensional point cloud data is collected and an attitude matrix is marked through laser triangle-grating interference dual-mode imaging and board micro-vibration sensing; constructing an adaptive reference surface based on the point cloud and real-time fitting warping curved surface parameters, executing local height remapping, and eliminating the influence of micro warping; calculating a warping composite slope index and a glare texture robust index by using the height matrix, and adjusting a confidence threshold of the boundary enhanced convolutional network to realize real contour segmentation of adjacent pads; dynamically updating imaging parameters, accumulating real scene samples, and optimizing the adaptive ability of the model; and cross-shift knowledge reuse is realized through the shared model library. According to the invention, the volume measurement consistency and the first pass yield of the ultra-fine pitch bonding pad can be improved, and the process debugging time is shortened.

The invention discloses a 3D (three-dimensional) perimeter security system and an operation method thereof, the system comprises a server terminal, a front-end sensing system, a data transmission system and a central control system, the front-end sensing system is networked in multiple groups of partitions, and each group of partitions of the front-end sensing system is provided with a nine-axis sensor, an edge computing all-in-one machine and a switch; and lighting, wind and rain sensor, broadcasting, microwave radar and camera equipment. The data transmission system transmits data; the central control system comprises an application server and a data server. The system forms a first defense line for active detection of the microwave radar and the camera and a second defense line for vibration sensing of the nine-axis sensor, and a monitoring blind area is eliminated through three-dimensional data fusion. The operation method comprises four groups of subsystem modules. According to the method, 'sky-ground-fence 'dead-corner-free monitoring is realized, the false alarm rate is reduced by combining multi-modal data fusion with an intelligent algorithm, self-evolution is realized by edge-cloud federal learning, and threat disposal efficiency is improved by automatic linkage response.

The invention belongs to the technical field of engineering machinery intelligence and construction quality detection, and provides an intelligent compaction degree detection system and method integrated on a road roller. The detection system comprises a multi-mode sensing unit which comprises a vibration sensing module, a machine vision module, an inertia measurement positioning module and a flatness detection module; the detection method comprises the following steps: S1, synchronously collecting data; s2, vibration signal processing and compaction index calculation; s3, image analysis and apparent feature extraction; s4, a multi-source data fusion and machine learning model; s5, positioning and drawing; in conclusion, the invention provides the intelligent compaction degree detection system and method integrated on the road roller. The method is reasonable in design and simple to operate, can realize real-time, comprehensive, lossless and high-precision detection of the compaction degree, and can evaluate the construction apparent quality at the same time, so that the method is suitable for industrial popularization.

The invention discloses a phi-OTDR (Optical Time Domain Reflectometer) vibration signal classification method based on multi-scale residual convolution and a bidirectional long-short-term memory network, relates to the technical field of phase-sensitive optical time domain reflectometer vibration sensing, and solves the problems of insufficient feature extraction, single model fusion mechanism, poor system real-time performance and the like of an existing phi-OTDR vibration signal classification method. The method is realized through the steps of a multi-scale deep convolutional network, a bidirectional long-short term memory network, a cross attention fusion module, a learnable gating mechanism and the like. A cross attention fusion module is adopted, association between spatial features and time sequence features is dynamically established in a double-path network, feature interaction and information coupling are deepened, and the sensing ability of the model to key information is remarkably improved. Meanwhile, the fusion proportion of the multi-path features is adaptively adjusted according to the actual distribution of the input features, background noise interference is effectively suppressed, and the robustness and discrimination performance of the model are enhanced. Accurate identification and classification of external vibration signals are realized.

The invention relates to the technical field of friction power generation, in particular to an energy collection and vibration sensing device and system for a transmission line, which comprises a shell, a vibration sensor arranged in an inner cavity of the shell, and energy collectors arranged at the upper end and the lower end of the vibration sensor respectively. The vibration sensor comprises a balancing weight, and elastic pieces are arranged between the upper end and the lower end of the balancing weight and the adjacent energy collectors respectively. A positive friction piece is installed on the outer ring of the balancing weight, and a negative friction piece is installed on the inner wall of the shell. The positive friction piece can move up and down along with the balancing weight and make contact with the negative friction piece so as to generate electric signals. The energy collector comprises a positive electrode power generation membrane group and a negative electrode power generation membrane group which are oppositely arranged up and down and can make contact with each other and achieve friction power generation, one of the positive electrode power generation membrane group and the negative electrode power generation membrane group abuts against the shell, and the other abuts against the end, away from the balancing weight, of the elastic piece.

The invention discloses a lightweight optical fiber vibration intrusion event identification method and system for perimeter security and protection, and belongs to the technical field of optical fiber sensing technology and mode identification, and the method comprises the steps: collecting an original vibration signal of a perimeter monitoring region through a distributed optical fiber vibration sensing system; performing wavelet threshold de-noising preprocessing on the original vibration signal to obtain a de-noised signal; performing feature extraction on the denoised signal, and constructing a high-dimensional feature vector; performing dimension reduction processing on the high-dimensional feature vector by using a linear discriminant analysis method to obtain a low-dimensional classification feature vector; and inputting the low-dimensional classification feature vector into a pre-trained lightweight convolutional neural network model for classification and identification, and outputting a corresponding intrusion event category. According to the method, through cooperation of front-end LDA dimension reduction and a rear-end lightweight network, the model parameter quantity and calculation overhead are greatly reduced while high recognition precision is guaranteed, efficient real-time deployment on edge equipment is achieved, and the method is suitable for intrusion detection in perimeter security and protection.

An electronic system includes a first vibration sensing device, a second vibration sensing device, a database, and a processor. The first vibration sensing device is arranged on the surface of the first equipment and detects a first time domain vibration signal when the first equipment operates. The second vibration sensing device is arranged on the surface of the second equipment and detects a second time domain vibration signal when the second equipment operates. The database stores a process parameter associated with at least one of the first device and the second device. The processor trains a predictive model based on the first time-domain vibration signal, the second time-domain vibration signal, and the process parameter. The predictive model is used to diagnose a health condition of the first device.

The invention provides a packaging-level integrated optical fiber micro-vibration sensing device which comprises a photoelectric function cavity and a micro-bend sensing optical fiber with a long-period fiber grating structure, a light source assembly and a signal processing device are arranged in the photoelectric function cavity at intervals, the light source assembly is optically connected with the input end of the micro-bend sensing optical fiber, and the signal processing device is electrically connected with the input end of the micro-bend sensing optical fiber. The signal processing device is optically connected with the output end of the micro-bend sensing optical fiber, the signal processing device is used for converting an optical signal of the output end into an electric signal and restoring an original vibration signal, and the optical fiber micro-vibration sensing device further comprises micro-bend sensing cavities which are integrally packaged with the photoelectric functional cavity and are arranged at intervals; an oscillation block and a flexible material layer covering the oscillation block are arranged in the microbend sensing cavity, and the long-period fiber grating structure is embedded in the flexible material layer and penetrates through the oscillation block. According to the optical fiber micro-vibration sensing device, extra insertion loss can be reduced, the mechanical stability, the sensing sensitivity and the response speed are improved, and the anti-interference capability and the adaptability to fine scenes are enhanced.

The invention discloses a road surface state recognition method based on machine vision and force feedback. The method comprises the following steps: S1, continuously shooting a front road surface image flow by using a vehicle front-end image acquisition device; s2, automatically segmenting a road surface abnormal region by adopting an arbitrary target segmentation model; s3, arranging a piezoelectric film vibration sensing unit in the contact surface of the vehicle tire and the road surface to collect tiny vibration signals in real time; s4, extracting time domain and frequency domain features of the vibration signals; s5, performing vision and force feedback feature multi-scale coding; s6, dynamically adjusting the weights of the two modal features, and generating fusion decision features; and S7, outputting a road surface state recognition result. The method is used for improving automatic driving safety.

The invention discloses a fusion type distributed optical fiber vibration sensing system with broadband response, which is suitable for high-precision acoustic signal measurement and spatial position positioning. The system comprises an acoustic measurement unit, a position measurement unit and a data acquisition synchronous control module which are respectively used for acquiring high-frequency vibration information and positioning low-frequency signals, has the sensing capabilities of wide band, high resolution and high signal-to-noise ratio, and realizes signal synchronization by adopting phase-locked control and high-sampling-rate data acquisition, so that the accuracy of signal synchronization is improved. And the signal stability and the signal-to-noise ratio are improved through polarization control and filtering design. The method supports frequency feature extraction, accurate identification and spatial positioning of the vibration event, and is suitable for pipeline structure monitoring, fault diagnosis and other engineering application scenes in a complex environment.

The embodiment of the utility model discloses a vibration sensing circuit, a piezoelectric sensing assembly and a vehicle-mounted sensing system. The vibration sensing circuit comprises at least one sensing sub-circuit; the input end of each sensing sub-circuit in the at least one sensing sub-circuit can be connected with the piezoelectric vibrator sensor, the output end of each sensing sub-circuit can be connected with the controller, and each sensing sub-circuit comprises an amplifying circuit and a controlled switch; the first input end of the amplifying circuit serves as the input end of each sensing sub-circuit to be connected with the piezoelectric vibrator sensor, the second input end of the amplifying circuit is grounded, the output end of the amplifying circuit is connected with the control end of the controlled switch, and the first end of the controlled switch serves as the output end of each sensing sub-circuit to be connected with the controller. The second end of the controlled switch is grounded.

The invention relates to a vibration sensing device based on cantilever beam structure sensitization and a control method and a manufacturing method thereof. The device comprises a laser generator, a fiber bragg grating vibration sensor, a circulator and a photoelectric detector, the fiber bragg grating vibration sensor comprises a base, a cantilever beam, a fiber bragg grating and a load bearing assembly, the bottom surface of the base is fixed on the surface of a vibration source, the cantilever beam comprises a fixed part and two extension parts with the same length, and one end of the fiber bragg grating is connected with a central point at the upper end of the fixed part; the other end of the fiber bragg grating is connected with a central point at the upper end of the load-bearing assembly; the circulator is used for transmitting the laser signal generated by the laser generator to the fiber bragg grating vibration sensor and transmitting the laser signal reflected by the fiber bragg grating vibration sensor to the photoelectric detector; and the photoelectric detector is used for converting the laser signal into a voltage signal. The device is high in anti-electromagnetic interference capability, high in sensitivity, good in insulating property and relatively high in durability.

The invention relates to a pipeline surrounding event pattern recognition method based on an improved sparrow search algorithm optimization support vector machine, and solves the problem that the working efficiency and prediction precision of pipeline monitoring are reduced due to the fact that an existing pipeline monitoring recognition model is easy to fall into local optimum and relatively slow in convergence speed. The method comprises the following steps: firstly, acquiring pipeline peripheral vibration data acquired by a distributed optical fiber vibration sensing system, preprocessing, performing feature extraction to obtain a feature vector, dividing the feature vector into a training set and a test set, and taking the training set as input to obtain a test set; and searching the penalty factor of the support vector machine model and the optimal value of the kernel parameter by using an improved sparrow search algorithm to obtain an ISSA-SVM identification and classification model, and testing the ISSA-SVM identification and classification model by using the test set. According to the method, the support vector machine is optimized based on the improved sparrow search algorithm, different types of vibration events can be accurately recognized, the real-time performance is high, the accuracy is high, and the pipeline monitoring efficiency is greatly improved.

The invention relates to the technical field of optical fiber sensing, and provides an improved moving average method applied to a distributed optical fiber vibration sensing system, and the method comprises the steps: continuously collecting a plurality of backward Rayleigh scattering curves; setting a plurality of different moving average window widths, and performing moving average processing on the plurality of backward Rayleigh scattering curves based on each moving average window width to obtain a plurality of scattering curves after moving average processing corresponding to each moving average window width; for each moving average window width, calculating the variance of the scattering curve after moving average processing at the same time point, and obtaining a variance sequence corresponding to the moving average window width; according to the variance sequence corresponding to each moving average window width, determining the corresponding moving average window width when the variance change tends to be stable, and taking the moving average window width as a target window width; and moving average processing is carried out on a plurality of acquired backward Rayleigh scattering curves by using a target window width, and a disturbance event on the optical fiber is positioned.

The invention discloses a flow-state concrete pouring quality monitoring method based on vibration sensing and ultrasonic fusion, and belongs to the technical field of concrete construction quality control, the technical scheme is that the method comprises the following steps: deploying a vibration sensing module and an ultrasonic detection module for collecting vibration signals in a pouring area; vibration signals and ultrasonic signals are synchronously collected and preprocessed in the concrete vibration process; extracting compactness characteristics used for representing the compact state of concrete from the vibration signals, and extracting ultrasonic characteristics used for representing aggregate distribution and defects from the ultrasonic signals; the compactness features and the ultrasonic features are input into a fusion judgment model, and concrete internal defect types, position coordinates and compactness and aggregate uniformity judgment results are obtained; and performing pouring quality judgment based on a judgment result, and outputting a quality state and a vibration adjustment instruction at a visual terminal. The flow-state concrete pouring quality monitoring method based on vibration sensing and ultrasonic fusion has the beneficial effect that the flow-state concrete pouring quality monitoring method based on vibration sensing and ultrasonic fusion is provided.

The invention discloses a ship internal combustion engine fault monitoring instrument and system based on the AI technology, and relates to the technical field of fault monitoring, the ship internal combustion engine fault monitoring instrument comprises a multi-source sensing cluster, an edge AI processor and a ship-borne monitor, the edge AI processor is fixedly installed at the top end of the outer wall of the multi-source sensing cluster, and the ship-borne monitor is fixedly installed on the surface of an internal combustion engine cylinder body. The edge AI processor is connected with the multi-source sensing cluster through a data line to establish a bidirectional data channel; a vibration sensing substrate and a temperature conduction copper pipe are arranged in the shipborne monitor, a piezoelectric ceramic array is arranged at the top end of the outer wall of the vibration sensing substrate, and the piezoelectric ceramic array is embedded into the inner wall of the shipborne monitor in an equilateral triangle mode. Through the multi-source sensing cluster, the multi-dimensional data synchronous acquisition function of the ship internal combustion engine is realized, the problems that the monitoring means is single and fault features cannot be comprehensively captured are solved, and the internal combustion engine fault is predicted more early and accurately.

The invention discloses a building engineering damping control method and system based on an intelligent monitoring device, and relates to the technical field of intelligent control. The method comprises the steps that a target building framework is acquired, and a universal damping mode and a flexible damping mode are divided according to a vibration scene; according to an intelligent monitoring network deployed by a target building, vibration sensing and edge side pulse verification are carried out, a vibration space is reconstructed, and an edge side executes a universal damping decision to determine a first vibration control strategy; returning the vibration space to the building industrial control system, and assisting the flexible decision module to determine a second vibration control strategy; according to the first vibration control strategy and the second vibration control strategy, a damping device is directionally driven to conduct damping regulation and control on the target building. The technical problem that in the prior art, a damping strategy is difficult to flexibly adjust according to the real-time vibration condition, and consequently the damping effect is poor is solved, and the damping effect of the target building under different vibration conditions is improved.

The utility model discloses a backflow cable anti-theft detection device, which is applied to a backflow cable and comprises a vibration sensing optical cable device arranged on the backflow cable along the backflow cable and used for detecting a first alarm signal; the plurality of point location type vibration sensing devices are distributed on the backflow cable along the backflow cable, and each point location type vibration sensing device is used for detecting a second alarm signal of the corresponding detection point; the overall distribution length of the point location type vibration sensing devices is smaller than or equal to the length of the vibration sensing optical cable device. And the control device is electrically connected with the vibration sensing optical cable device and the plurality of point location type vibration sensing devices, and the control device is used for transmitting the first alarm signal and the plurality of second alarm signals to a monitoring platform so as to realize anti-theft monitoring of the backflow cable. The anti-theft detection device can improve the accuracy of anti-theft detection of the backflow cable.

The invention discloses an automatic leveling and height adjusting device for a 3D printer and a control circuit thereof.The automatic leveling and height adjusting device comprises a hot bed, springs are arranged below the four corners of the hot bed, a piezoelectric sensor is arranged below the hot bed, and the piezoelectric sensor is connected with an input channel of a main control panel; the piezoelectric sensor is provided with a vibration sensing mechanism or a pressure sensing mechanism. The invention belongs to the field of FDM 3D printing, and particularly relates to an automatic leveling and height adjusting device of a 3D printer and a control circuit of the automatic leveling and height adjusting device. A plurality of piezoelectric ceramic vibration sensing modules are arranged between a bearing base on a machine body and a printing platform, a control panel receives signals of a plurality of sensors for comprehensive analysis and comparison through vibration or pressure generated instantly when a printing nozzle touches the printing platform, and the signals are fed back to a printer mainboard to generate net bed compensation; and meanwhile, automatic height alignment of the full-breadth spray head is achieved, the mainboard controls the motor to automatically ascend and descend to compensate the height of the net bed according to detection data during printing, and the automatic leveling function is achieved.

This invention relates to the field of cable technology and discloses a safety early warning cable with temperature sensing. The cable includes a wrapping layer containing multiple insulated power wire cores, a protective layer outside the wrapping layer, a first vibration sensing element within the protective layer, and an isolation layer between the wrapping layer and the protective layer. By incorporating a spiral metal sheath within each conductor, with thermally conductive silicone grease filling the space between the sheath's inner wall and the temperature-sensing optical fiber, rapid and direct monitoring of the conductor's core temperature is achieved. Simultaneously, heat is transferred through the conductor's copper wires in the spiral microgrooves, the thermally conductive metal strip on the surface of the insulation layer, and the thermally conductive material in the filling layer to the multimode optical fiber core in the multi-core sensing cable, forming redundant temperature measurement channels. When the temperature of a conductor is abnormal, the corresponding temperature-sensing optical fiber and the multimode optical fiber core can be cross-verified, effectively avoiding false alarms caused by single-point faults or poor local contact, significantly improving temperature measurement reliability and response speed.

The invention discloses a mine earthquake monitoring device for deep well layout, and relates to the technical field of monitoring devices, the mine earthquake monitoring device comprises a shell, and a mounting rack is fixed in the shell; the measuring assembly comprises a vibration sensing module and an orientation sensing module which are coaxially fixed on the mounting frame, the vibration sensing module is used for monitoring a vibration signal, and the orientation sensing module is used for acquiring orientation deflection information of the vibration sensing module in real time; the signal processing module is in communication connection with the vibration sensing module and the direction sensing module, and performs direction correction on the vibration signals acquired by the vibration sensing module based on the direction deflection information so as to eliminate monitoring and positioning errors caused by direction deflection; a vibration sensing module and a direction sensing module are coaxially fixed on a rigid mounting frame to form a composite measurement unit with unified internal direction reference; when the device is arranged in a deep well and randomly deflects due to uncontrollable factors, the azimuth sensing module can sense the azimuth change in real time.

The invention relates to the technical field of pronunciation control, and provides a non-contact Hall drumhead vibration sensing and intelligent pronunciation control method and system, and the method comprises the steps: collecting an original Hall sensing electric signal generated when a user knocks a drumhead through a Hall sensor array in a drumhead, carrying out the signal preprocessing of the original Hall sensing electric signal, and obtaining a pre-processed signal; a standard Hall sensing electric signal is obtained, physical characteristic parameters are extracted, and a first tympanic membrane tension parameter, a damping coefficient and a striking position are obtained; obtaining an initial tympanic membrane tension parameter through a tympanic membrane stress sensor, carrying out the comparative analysis of the first tympanic membrane tension parameter and the initial tympanic membrane tension parameter, obtaining a tension decay value, and obtaining a pitch parameter based on a pre-constructed tension decay value-pitch mapping relation. According to the invention, through signal preprocessing and physical characteristic parameter extraction, key quantities reflecting the physical state of the tympanic membrane, such as a tympanic membrane tension parameter, a damping coefficient and a striking position, are systematically extracted, and a real and accurate physical basis is provided for sound generation.