100 results about "Triaxial accelerometer" patented technology

A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device. A learning module continuously improves system performance using reinforcement learning based on historical outcomes. The system supports predictive diagnostics, robotic repair, and automated optimization for long-term structural integrity.

The invention relates to the technical field of machining, and discloses a lathe tool wear self-inspection alarm system which comprises a multi-source sensing module, an intelligent analysis module, a dynamic response module, an interactive display module and a self-adaptive energy supply module. The multi-source sensing module synchronously acquires the surface abrasion loss, the vibration spectrum and the acoustic emission signal of the cutter through an optical sensor, a capacitive sensor and an MEMS triaxial accelerometer, and outputs the surface abrasion loss, the vibration spectrum and the acoustic emission signal to the intelligent analysis module; and the intelligent analysis module performs fusion analysis on the multi-source data by adopting a mixed feature extraction and double-model decision mechanism. High-precision monitoring and dynamic evaluation of lathe tool wear are realized through optical, vibration and acoustic emission sensors of the multi-source sensing module in combination with mixed feature extraction and a double-model decision mechanism of the intelligent analysis module. By means of the mode of combining multi-dimensional monitoring and intelligent analysis, machining defects and equipment failure risks caused by tool abrasion can be reduced.

The invention relates to the technical field of strip mine side slope slippage trend early warning, and particularly discloses a strip mine side slope slippage trend early warning system based on active micro-vibration excitation, which comprises the following components: an excitation unit which is composed of a frequency-adjustable micro-vibration exciter which periodically applies low-amplitude controllable mechanical disturbance signals to a side slope rock mass, the rock-soil medium structure response is excited, and the early warning sensitivity is improved; the sensing unit comprises a three-axis acceleration sensor, a displacement meter, a GNSS (Global Navigation Satellite System) sensor and a ground acoustic wave sensor, and is used for recording response change in a vibration disturbance signal propagation process and obtaining data; the analysis unit comprises an edge intelligent terminal, a slippage trend identification model built in the edge intelligent terminal and a lightweight neural network, and the slippage trend identification model performs sensing processing on the data and outputs a slippage trend label; and the communication control unit is used for ensuring that the data streams of the units are stable and cooperatively run with the modules.

The invention discloses a spatial sound effect test method and system for a sound system. The method comprises the following steps: S1, synchronously acquiring multi-modal sensing data of a test environment in a preset stage; s2, generating a three-dimensional sound pressure distribution thermodynamic diagram, and constructing an initial sound field model based on the three-dimensional sound pressure distribution thermodynamic diagram; s3, generating a corrected sound field model, and synchronously recording vibration data acquired by the triaxial accelerometer; s4, generating a sound image positioning trajectory diagram, and calculating a deviation angle between an actual sound image position and a theoretical position; and S5, determining the sound effect quality score of each test stage. According to the method, a closed-loop test framework of physical environment perception, sound field real-time modeling, man-machine interaction analysis and fault linkage traceability is constructed, a full-process test solution covering a hardware state, acoustic characteristics and human factor perception is provided for an immersive audio system, and the spatial sound effect reliability of digital playing equipment is remarkably improved.

The invention relates to the technical field of security and protection equipment, and discloses a portable multi-mode intelligent alarm terminal based on Beidou positioning, which comprises a Beidou third-generation positioning module, a multi-mode communication module, a dual-mode power supply system, a physical key assembly, a central processing unit and a sensor array, the Beidou third-generation positioning module supports BDS / GPS / GLONASS multimode fusion positioning, the positioning precision is less than or equal to 1m (in an outdoor enhancement mode), and the multimode communication module integrates 4G / 5G data communication, Beidou short message transmission and Bluetooth LE near field communication functions. According to the invention, through Beidou third-generation / GPS / GLONASS multimode fusion positioning, the Kalman filtering algorithm and the signal-to-noise ratio dynamic weighting technology are combined, and the outdoor positioning precision of less than or equal to 1m is realized. When a satellite signal is shielded, an inertial navigation mode is automatically switched to, a trajectory is corrected by utilizing data of a triaxial accelerometer, and an accumulative error is controlled within 5m / min. Through actual measurement, the positioning success rate in the urban canyon environment reaches 98% and is improved by 40% compared with that of a traditional single-mode GPS terminal, and it is ensured that rescue force quickly and accurately arrives at the site.

The invention discloses an intelligent livestock and poultry ear tag device based on edge calculation and lightweight reasoning, and the device comprises a dynamic sampling module which collects the motion behavior data of livestock and poultry through a three-axis acceleration sensor based on a low-power-consumption sampling mechanism. The local processing module carries out local real-time processing on the collected data by adopting feature screening and a light-weight behavior recognition algorithm based on a TinyML model, and the low-power-consumption transmission module processes the collected data based on a bitmap compression coding form to carry out internal communication transmission, so that wireless data transmission is carried out by a low-power-consumption transmission mechanism based on AI edge calculation; according to the method, a low-power-consumption sampling mechanism and a lightweight algorithm based on a TinyML model are matched with feature screening, so that the power consumption and the calculation amount can be greatly reduced; an AI edge computing architecture is utilized, only key events and features are uploaded, the wireless transmission frequency is reduced, the communication power consumption is reduced, and local intelligent operation in a network disconnection scene is supported.

The invention provides a substation settlement monitoring method and system, and relates to the technical field of settlement monitoring, and the method comprises the steps: deploying a bionic root system mesh array sensor network which comprises a plurality of monitoring nodes; collecting current phase data of a transformer substation bus in real time to calculate magnetic field interference, and performing inverse compensation on an original displacement signal of the magnetostrictive displacement sensor; carrying out vibration monitoring through a triaxial accelerometer, and carrying out data weight adjustment on a plurality of monitoring nodes; and performing settlement prediction on the transformer substation according to the displacement compensation data in combination with the weight parameters of the plurality of nodes, performing backtracking calibration on the bionic root system mesh array sensor network, and performing closed-loop monitoring on the settlement of the transformer substation according to a calibration result. The technical problem of inaccurate settlement monitoring caused by interference in a high-intensity magnetic field environment of the transformer substation in the prior art is solved, and accurate prediction and closed-loop monitoring of settlement of the transformer substation are realized by deploying a plurality of intelligent sensors and performing magnetic field interference compensation.

The invention provides an automobile fault identification method and a detection system. The method comprises the following steps: acquiring running state data of the automobile seat through a multi-mode sensor network; wherein the multi-mode sensor network comprises a current sensor, a temperature sensor, a triaxial accelerometer and a displacement sensor, and the operation state data at least comprises a current signal, a vibration signal, a temperature signal and a displacement signal; generating a seat state mapping matrix based on the multi-modal data; inputting the seat state mapping matrix into a preset hybrid diagnosis model to execute fault recognition; and according to a fault identification result output by the hybrid diagnosis model, carrying out fault early warning and generating a fault risk quantification report. Through the method provided by the invention, the fault of the automobile seat can be effectively identified.

The invention relates to a dual-mass-block three-axis acceleration sensor and a processing method thereof. The sensor comprises an X-axis and a Y-axis which are arranged on a first mass block, and a Z-axis which is independently arranged on a second mass block. The X-axis movable comb tooth structure and the Y-axis movable comb tooth structure are arranged outside the first mass block; the movable comb tooth structure of the Z axis is arranged in a central area between the first mass block and the second mass block, and an included angle of 135 degrees or 45 degrees is formed between the extension direction of the movable comb tooth structure of the Z axis and the extension directions of the movable comb tooth structures of the X axis and the Y axis; the first elastic supporting piece is connected to the first mass block and the substrate and used for sensing the X-axis acceleration and the Y-axis acceleration. The second elastic supporting piece is connected to the second mass block and the substrate and used for sensing the Z-axis acceleration. The fixed comb tooth structures of the X axis, the Y axis and the Z axis are fixed to the substrate through anchor points and arranged in a staggered mode with the movable comb tooth structures. The X-axis, the Y-axis and the Z-axis are arranged on different mass blocks, the comb tooth structure forms an included angle, the cross-axis sensitivity is reduced, and the size is reduced.

The invention provides a backpack multi-sensor data fusion-based motion attitude anomaly real-time detection method, which comprises the following steps of: acquiring multi-channel original data through a backpack-type integrated triaxial accelerometer, a gyroscope, a magnetometer and a barometer, implementing synchronous sampling and time-space alignment, and constructing a standardized time sequence data stream through wavelet denoising and multi-dimensional normalization preprocessing; high-dimensional features representing motion differences are extracted, nonlinear dimensionality reduction is achieved through principal component and Laplacian feature mapping, and a motion mode prototype library is generated; according to the method, a new motion situation can be continuously and adaptively learned, and the motion recognition accuracy, the system robustness and the attitude anomaly detection capability in a complex scene are effectively improved.

The invention discloses a uterine contraction detection method based on multi-modal signal fusion reconstruction, which comprises the following steps of: 1, synchronously acquiring an abdominal surface uterine electromyographic signal in real time through a high-density electrode array, acquiring a uterine contraction pressure signal in cooperation with a fundus pressure sensor, synchronizing a triaxial accelerometer signal to acquire a maternal motion signal, and preprocessing; 2, performing time sequence alignment and resampling on the data, and constructing a quality mask to form a multi-mode uterine contraction signal data set; 3, constructing a reconstruction network based on multi-modal feature fusion; 4, constructing a total loss function of the multi-modal feature fusion reconstruction network; and 5, training a reconstruction network of multi-modal feature fusion, wherein the reconstruction network is used for fusion reconstruction of the multi-modal uterine contraction data. According to the invention, through multi-modal signal fusion and deep feature correlation analysis, accurate monitoring and prediction of uterine contraction and premature delivery risks in the pregnant and birth period can be realized.

The invention discloses an urban and rural pavement maintenance monitoring system based on intelligent well lid data linkage, and the system comprises a data collection module which detects the acceleration data, angular motion data and inclination angle change data of a well lid in real time through a three-axis acceleration sensor, a gyroscope and an inclination angle sensor which are disposed on the well lid; the edge calculation module is used for calculating a vibration value of the well lid according to the acceleration data, the angular motion data and the inclination angle change data of the well lid and correcting the vibration value; the cloud data center obtains a risk index of a road surface where the well lid is located through a pre-constructed association model according to the corrected vibration value and the position of the well lid corresponding to the vibration value; and the maintenance decision terminal module performs maintenance decision on the road surface where the well lid is located according to the risk index of the road surface where the well lid is located. According to the invention, the well lid on the road surface is taken as the basis of data acquisition, and the maintenance condition of urban and rural road surfaces is detected in real time by acquiring the data on the well lid, so that the maintenance condition can be accurately obtained in real time.

The invention provides an angle calculation method and system based on a triaxial accelerometer, and relates to the technical field of inertial navigation, and the method comprises the steps: obtaining an acceleration signal and preprocessing the acceleration signal to obtain an effective acceleration component, constructing a nonlinear error feature vector, carrying out the real-time parameter identification through a recursive least square method, and building a nonlinear error compensation model. And performing dynamic correction by adopting a self-adaptive sliding time window, and finally calculating a pitch angle and a roll angle. The non-linear error of the accelerometer can be effectively inhibited, the angle calculation precision is improved, and the method has the characteristics of good real-time performance and strong adaptability.

The invention relates to intelligent wearable bioelectronic equipment for monitoring and treating temporal muscle and masseter dysfunction and a control method, and belongs to the technical field of medical equipment. The device comprises a circuit board, a core processing unit MCU is arranged on the circuit board, the core processing unit MCU is respectively connected with an ACC triaxial accelerometer, a digital isolator and an NFC wireless communication and charging patch, the ACC triaxial accelerometer is connected with a surface myoelectricity electrode patch through an analog front end, the digital isolator is connected with a stimulation electrode patch through an electrical stimulation driving module, and the NFC wireless communication and charging patch is connected with an NFC wireless communication and charging module. And the NFC wireless communication and charging patch is connected with a reference electrode patch. According to the invention, efficient, safe and comfortable treatment of functional TMD is realized.

The invention relates to the technical field of brain-computer interfaces, and discloses a multi-channel EEG-based personalized model training and common feature extraction system, which comprises a three-channel EEG sensor electrode, a triaxial accelerometer, an electro-oculogram auxiliary electrode, a signal conditioning and acquisition circuit module, a local processing unit, a wireless communication module and a power management module. The invention also provides a tag generation method of the multi-channel EEG-based personalized model training and common feature extraction system, and the method comprises the following steps: S1, multi-modal signal synchronous collection: through cooperation of all parts, bio-electricity signals and behavior signals of a user in different states can be monitored and captured in real time, and the multi-modal signal synchronous collection is realized; in addition, the local model can actively align cross-user feature distribution while optimizing task performance, inter-domain differences are effectively reduced, and the generalization ability of the global model is improved.

This invention discloses a near-bit engineering parameter measuring device and method. The measuring device includes a novel drill bit and an engineering parameter measuring mechanism connected to each other. The novel drill bit includes a drill bit body, a drill pressure strain gauge, a torque strain gauge, and a data transmission system, accurately measuring operating parameters such as torque and thrust at the drill bit during drilling. The engineering parameter measuring mechanism includes an outer cylinder, an inner cylinder, a triaxial accelerometer, a signal processing module, a ground signal receiving device, and a battery module. The engineering parameter measuring mechanism is a double-layer, double-cylinder structure that uses the principle of magnetoelectricity to generate current and power the measuring system. The magnitude of the current generated when the inner cylinder rotates relative to the outer cylinder provides feedback on the relative rotational speed of the drill bit. Simultaneously, a triaxial accelerometer is arranged on the outer cylinder to acquire the angular acceleration information of the outer cylinder, calculate the rotational speed of the outer cylinder, and sum the velocities to obtain the actual rotational speed at the drill bit, thus achieving accurate measurement of the drill bit rotational speed.

A laryngeal pacemaker is configured for external placement on skin of a patient to produce respiration stimulation signals. An implantable stimulation electrode delivers the respiration stimulation signals to adjacent target neural tissue for vocal fold abduction during respiration of the recipient patient. A triaxial accelerometer produces a body motion signal reflecting energy expenditure of the recipient patient. A respiration sensor includes a flexible skin-transferrable printed tattoo electrode having a tetrapolar configuration for impedance pneumography measurement to produce a sensed respiration signal for the laryngeal pacemaker. The respiration sensor is configured for transfer and release by guided placement from a sensor applicator to the skin at the angulus sterni of the recipient patient. And the laryngeal pacemaker is configured to interpret the body motion signal and the sensed respiration signal to make a real time determination of respiratory phase and frequency for adaptively adjusting the respiration stimulation signals accordingly.

The invention belongs to the field of embedded device security design, and particularly relates to a security starting system and method based on dynamic environment binding and heterogeneous inspection. A safe starting framework is constructed through a triaxial accelerometer, a main control chip and a verification module, wherein the main control chip integrates an annular oscillator array, a temperature sensor and a hardware hash engine, and the verification module comprises an AI coprocessor and a block chain communication module. The system firstly collects three-dimensional acceleration and environment temperature data, combines dynamic physical signals generated by an annular oscillator array, and generates a dynamic decryption key through fusion of a hardware hash engine; and then heterogeneous dual-channel verification is formed through the AI coprocessor and the block chain communication module, so that the key validity is ensured. According to the method, a static key is replaced by a dynamic trust root, the bottleneck of a single chain is broken through heterogeneous verification, protection is enhanced through environmental data binding, security and light weight are considered, a real-time industrial control scene with limited adaptive resources is adapted, and attacks such as physical detection and environmental simulation are effectively resisted.

This invention discloses a real-time detection method and system for steel slag flow based on a triaxial accelerometer, belonging to the field of steel metallurgical process detection technology. It acquires triaxial vibration data to fully capture the impact energy of steel slag in any direction in three-dimensional space, overcoming the signal loss problem caused by the mismatch between the installation direction and the impact direction of traditional single-axis sensors. Based on this, a dynamic threshold pre-screening mechanism is adopted, requiring only the calculation of a few core features to quickly determine the slag-free state. For suspected slag-containing periods, a CNN-LSTM hybrid model is further used for fine identification. The model automatically extracts the nonlinear combinations and temporal dependencies between feature dimensions, achieving accurate classification of four states: initial flow, stable slag flow, and impact of large slag pieces. This invention integrates comprehensive perception, efficient prediction, and intelligent identification, providing a safe, reliable, and low-cost online detection and classification control solution for steel slag flow in the steelmaking process.

The invention provides a medical flatcar with spine maintaining and anti-seismic functions, and belongs to the technical field of medical instruments, the flatcar absorbs vertical oscillation and horizontal jolt in the transfer process through a multi-stage damping structure (buffer springs, air cushions and buffer pads); pavement pre-judgment and self-adaptive damping adjustment are realized through an intelligent sensing system (a laser ranging sensor / laser obstacle avoidance radar, a triaxial accelerometer and a central controller); an ergonomic protection structure (including a spine fixing system, a protection plate and a back cushion) is matched to guarantee the body position safety of the patient; and the equipment management efficiency is improved through a bottom drawing type storage structure. Transfer jolt is remarkably reduced, the device is particularly suitable for patients with spinal injury, cerebral hemorrhage, organ rupture and the like, head displacement is reduced according to clinical actual measurement, and the discomfort rate of the patients is decreased.

A testing method and system for lithium battery protection boards is disclosed. The method includes: sampling the resonant frequency of a connector structure using an acoustic resonant sensing unit to obtain an acoustic baseline signal indicating the mechanical connection state of the connector; real-time acquisition of environmental vibration intensity and impact event time using a triaxial accelerometer and an impact sensor, and time alignment with the acoustic baseline signal; applying excitation pulses of a predetermined frequency to the connector at a preset cycle, and acquiring the real-time resonant response curve of the connector to the excitation pulses using the acoustic resonant sensing unit to calculate the baseline profile offset; comparing the baseline profile offset with a preset safety threshold to convert the acoustic offset into a loosening risk indicator based on the comparison result; and performing a load switching test of a predetermined amplitude in response to the loosening risk indicator to determine whether the connector is abnormal. This invention can promptly detect poor contact caused by changes in connector gaps due to vibration, ensuring the accuracy of the alarm.

The utility model relates to the technical field of laser surveying and mapping, in particular to a laser surveying and mapping positioning device which comprises a laser surveying and mapping instrument and an installation cover connected to the laser surveying and mapping instrument in a threaded and sleeved mode, an optical lens is fixedly installed on the laser surveying and mapping instrument, and a protection mechanism is arranged on the installation cover. The protection mechanism comprises a triaxial accelerometer, a wireless communication module and a microcontroller, a mounting ring is rotatably mounted in the mounting cover, a gear ring sleeves the mounting ring, multiple groups of annularly distributed closing plates are arranged in the mounting cover, the multiple groups of closing plates are rotatably connected with the mounting cover through handles, and fourth gears sleeve the multiple groups of handles. Through the protection mechanism, when the optical lens is not used, a plurality of groups of closing plates are in a closed state and are matched with the mounting cover to enable the optical lens to be in a covering closed state, so that the optical lens is prevented from being collided and damaged.

The invention provides an intelligent wearable health monitoring system, and relates to the technical field of sports biomechanics, and the method comprises the steps: collecting original sensing data streams of a triaxial accelerometer and a gyroscope in real time, and converting the original sensing data streams to a human skeleton coordinate system through a rotation matrix; calculating the Euler angle of the limb joint based on the converted data, and extracting gait phase parameters in combination with the curvature features of the motion trail; calculating a real-time stride frequency according to the gait phase parameter; when a plurality of continuous stride frequency sampling values exceed a preset medium-high intensity motion threshold value, generating a medium-high intensity motion state identifier; synchronously executing according to the medium-high intensity motion state identification, constructing a blood glucose dynamic evaluation window based on a continuous sampling sequence of a blood glucose sensor, calculating a time sequence gradient of blood glucose reading in the window, and generating a dynamic compensation coefficient according to the time sequence gradient. According to the invention, dynamic and accurate health monitoring and risk early warning in a motion scene are realized.

This invention provides a triaxial accelerometer based on a four-degree-of-freedom weakly coupled resonator, comprising an upper and lower double-layer structure. The upper layer is a micromechanical sensing element constructed from silicon, and the lower layer is a glass substrate made of silicon dioxide, which provides mechanical support and electrical isolation. The micromechanical sensing element performs signal conversion; the lower glass substrate, formed by wet etching and metal sputtering processes, is used for signal output. This invention, based on the collaborative design of an orthogonally distributed resonant unit array and a mechanical amplification mechanism, combined with electrostatic drive and amplitude ratio detection, achieves synchronous and accurate sensing of Y-axis, X-axis, and Z-axis acceleration using a single sensing element. This overcomes the technical limitations of traditional single-axis detection modes, reduces the complexity of back-end signal processing circuitry, and improves device space utilization.

The utility model discloses a real-time monitoring system for baseball motion parameters. The real-time monitoring system comprises a nine-axis inertial measurement unit, a dynamic integral reset processing unit, a data preprocessing unit, a wireless transmission module, a wireless charging receiving module for supplying power, a wireless receiving module, a data processing unit and a user side, the nine-axis inertial measurement unit, the dynamic integral reset processing unit, the data preprocessing unit, the wireless transmission module and the wireless charging receiving module are arranged in the baseball; the nine-axis inertial measurement unit comprises a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer and is used for acquiring the acceleration, the angular velocity and the magnetic field intensity of the baseball; the dynamic integral reset processing unit is connected with the nine-axis inertial measurement unit; the nine-axis inertial measurement unit, the data preprocessing unit and the wireless transmission module are connected in sequence; the wireless receiving module is respectively connected with the wireless transmission module and the data processing unit; and the user side is connected with the data processing unit.

The invention relates to a top-rushing and bottom-falling prevention protection device for an elevator, and belongs to the technical field of elevators. The system comprises an intelligent sensing trigger module, a multi-stage buffer execution module and a system linkage control module, the intelligent sensing trigger module comprises a three-axis acceleration sensor, a laser range finder and a steel wire rope tension detection unit, and the multi-stage buffer execution module comprises a plurality of single-stage buffer execution assemblies. One single-stage buffering execution assembly is arranged on each 1-3 layers of elevator shafts, each single-stage buffering execution assembly comprises two sets of buffering units, the buffering units are symmetrically arranged on the elevator shaft walls on the two sides of a lift car, each buffering unit comprises a buffering steel plate and a buffering driving part, and the buffering driving parts drive the buffering steel plates to move between two stations inside and outside a lift car operation area. And the system linkage control module receives a signal sent by the intelligent sensing trigger module and a position signal of a car in the elevator and controls the multi-stage buffer execution module. The multi-protection elevator has the multi-protection effect in the abnormal operation state of the elevator.

This application relates to the field of multi-condition bellows dynamic characteristic testing technology, and in particular to a multi-condition bellows dynamic characteristic testing device. The device excites and tests bellows under combined working conditions using a vibrator or hammer. It measures the vibration acceleration parameters of triaxial accelerometers at both ends of the bellows, and after calculation, accurately obtains the vibration isolation performance parameters of the bellows under combined working conditions, achieving higher testing accuracy. By selecting the vibrator or hammer according to the bellows' mass and diameter, the influence of the vibrator's added mass and stiffness on measurement accuracy can be avoided. Furthermore, it can simulate the environment, more closely resembling real service conditions. By applying different working conditions and combined working conditions such as high temperature, pressure load, axial or lateral displacement, it realistically simulates the actual working conditions of the bellows, accurately obtaining the vibration isolation performance parameters of the bellows.

A structural-health-monitoring system is disclosed for real-time detection and autonomous maintenance of physical structures. The system includes a sensor network comprising at least one strain gauge and one tri-axial accelerometer mounted on the structure to generate real-time sensor signals. A perception module filters and normalizes the signals and extracts numerical features such as peak amplitude and dominant frequency. A digital-twin module maintains a finite-element model updated in response to the extracted features. A data-driven surrogate model predicts sensor behavior and refines itself using machine-learning techniques. An anomaly-detection module computes an anomaly score from model residuals or classifier outputs. Upon exceeding a threshold, a maintenance module initiates a maintenance action, including generating an inspection schedule or issuing a control signal to an autonomous inspection or repair device. A learning module continuously improves system performance using reinforcement learning based on historical outcomes. The system supports predictive diagnostics, robotic repair, and automated optimization for long-term structural integrity.

A device for orienting core samples relative to their position in the subsoil before extraction, attaching to a core bit during drilling features a robust tubular body with a detector to identify core sample breakage and orientation using triaxial accelerometers and gyroscopes, measuring orientation by the gravity vector or true north. An electronic control unit stores, timestamps, and transmits data wirelessly via BLUETOOTH®, ensuring data reliability without removing the device. The device includes adapters for different pipe diameters, minimizing the need for disassembly and reducing user fatigue, while maintaining pump functionality with a bypass valve if needed.

The invention relates to the technical field of underground pipeline protection identification, in particular to an underground pipeline protection identification device for monitoring geological deformation, and the device comprises an underground pipeline protection identification column which comprises a base part and a warning part; a triaxial accelerometer is arranged in the base part; a noise monitoring module; the filtering module is used for determining a filtering mode according to the amplitude of the noise and determining the position of the noise according to the characteristic parameters of the noise; the control module is used for determining an estimated geological state according to geological structure parameters, and determining whether to start the filtering module or not according to the estimated geological state and the noise position; the warning part is provided with a lamp strip used for displaying the geological deformation state, the lamp strip comprises a plurality of indicator lamps with different light colors, and the indicator lamps with the corresponding light colors are turned on according to different distances between maintenance personnel and the underground pipeline protection identification column. The accuracy of monitoring the geological deformation around the pipeline by the identification device is improved, and the energy consumption of the identification device is reduced.