67 results about "Three axis accelerometer" patented technology

The invention discloses an inclinometer magnetic interference error compensation method, system and device and a medium, and relates to the technical field of measurement while drilling, the method comprises the following steps: obtaining triaxial accelerometer data and triaxial magnetometer data collected by a plurality of preset azimuth angles of an inclinometer; performing magnetic interference preliminary correction on the data of the three-axis magnetometer by using a multi-measuring-point analysis method to obtain a preliminary correction azimuth angle; inputting the triaxial accelerometer data and the triaxial magnetometer data into a pre-trained error compensation model ICGO-RELM, and outputting a magnetic interference error compensation value; and compensating the initial correction azimuth angle based on the error compensation value to obtain final azimuth angle data. And the solving precision of the underground azimuth angle is improved.

The present disclosure provides a kind of inertial motion measurement double-axis rotation excitation enhancement method and system based on observability analysis.First, the system state space model of introducing double-axis rotation mechanism is constructed, the normalized observability analytical expression of sensor error under zero speed condition is derived based on Gramian matrix eigenvalue decomposition;Accordingly, the attitude condition of error observability maximization is determined, and the optimal rotation excitation strategy including a series of optimal observation positions is set;In the process of inertial navigation positioning assisted by zero speed update ZUPT, in non-zero speed interval, based on the optimal rotation excitation strategy, the IMU is sequentially guided to each optimal observation position by controlling double-axis rotation mechanism, to solve the problem of low error state observability caused by single carrier attitude in zero speed correction.The present application can realize full state high-precision estimation of three-axis accelerometer bias and gyroscope zero bias, effectively improve the precision and robustness of autonomous motion measurement in complex environment.

The invention relates to the technical field of hoisting machinery safety monitoring and control, and particularly discloses a portal crane moment limit protection method and system based on current verification. Real-time detection signals of a hoisting mechanism are obtained through a moment sensor, and a three-axis accelerometer is arranged at the connecting position of a steel wire rope to obtain swing signals; analyzing a jitter interference factor based on the steel wire rope jitter displacement, and judging the accuracy of a detection signal; on the premise that the signal is accurate, operation state detection of primary mechanical power calculation is carried out, then secondary operation state detection is carried out by combining the rated working current of the lifting frequency converter calculated by the detection signal and the real-time working current collected by the PLC, and the lifting mechanism is controlled to operate according to the detection result. Through multi-dimensional signal fusion and secondary verification, the detection precision and the overload judgment reliability are improved, the overload operation of equipment can be effectively prevented, and the operation safety of the crane and the service life of the equipment are guaranteed.

The intelligent positioning and tracking device comprises a cap body, a three-axis magnetometer is fixedly connected to the front end of the left side of the cap body, a positioner is fixedly connected to the rear end of the left side of the cap body, and a three-axis accelerometer is fixedly connected to the front end of the right side of the cap body. And the rear end of the right side of the cap body is fixedly connected with a three-axis gyroscope. A worker wears the helmet body on the head, the first binding belt and the second binding belt can be firmly connected under the cooperation of the nylon velvet belt and the nylon hook belt, the three-axis accelerometer, the three-axis magnetometer, the three-axis gyroscope and the positioner are arranged, the position information of the worker can be positioned in real time, and the working efficiency is improved. A methane sensor, a carbon monoxide sensor, an oxygen concentration sensor, a temperature and humidity sensor, a dust concentration sensor and a microseismic monitoring sensor are arranged, and the methane concentration, the carbon monoxide concentration, the oxygen concentration, the temperature and humidity information, the dust concentration and the vibration condition in the environment can be detected respectively.

The present application relates to a kind of pedestrian collaborative navigation method based on distance and angle, the collaborative navigation method includes: S1, by MIMU output each pedestrian respective three-axis accelerometer and three-axis gyroscope data, and carry out strapdown inertial navigation solution, again by the state of zero speed detection to the data of inertial navigation solution is carried out zero speed correction by extended Kalman filtering;S2, by UWB ranging angle measurement obtains the relative distance and angle between pedestrians as observation, then with the position information and heading angle information of N pedestrians as state quantity, carries out Kalman filtering, obtains the correction data of the position information and heading angle information of each pedestrian;S3, according to the position information and heading angle information of each pedestrian after correction collaborative navigation is carried out.The present application uses distance and angle as observation to correct pedestrian navigation after ZUPT auxiliary, solves the current pedestrian navigation heading angle drift and the problem of large amount of calculation of centralized filtering.

The application relates to an angle calibration solution method and system of a tilt sensor. Compared with the prior art, the method comprises the following steps: 1) collecting three-axis original acceleration data output by a three-axis accelerometer and performing filtering processing; 2) adopting a six-position calibration method to perform calibration; and 3) adopting a segmented combination angle solution method to calculate the included angle between the X axis and the Y axis of the tilt sensor relative to a horizontal plane. The application has the advantages of high accuracy and high precision in full-range measurement, smooth angle output, high calibration efficiency and the like.

The application discloses a building construction site data acquisition system based on Internet of Things and relates to the technical field of building engineering. The system is provided with a sound wave acquisition module, three-dimensional space is laid out with acquisition points in underground pouring structures, and an excitation source position is set in combination with the position of a pre-buried anchoring support, so that sound wave reverberation signals generated by wideband vibration signals are used to realize high-density and high-time-efficiency data acquisition. The MEMS three-axis accelerometer arranged in the acquisition point can collect the sound wave decay time Tdec and the reverberation residual energy peak value Ares of each acquisition point in real time, form a standard vibration sound wave energy data set, and provide a data basis for subsequent structure integrity judgment. Compared with traditional manual detection, image recognition and external detection methods, the system has the advantages of not needing to be damaged and not needing to additionally lay out ultrasonic equipment, and can realize early warning of internal interlayers, cavities and cold joints and real-time visualization of structure states in the construction process.

This invention belongs to the field of inertial measurement technology, specifically an inertial measurement unit and its linear-angular coupling motion calibration method. It includes constructing a non-contact inertial measurement unit linear-angular motion synchronous measurement system. Through a reference cubic prism, a three-dimensional laser vibrometer, a first dual-axis autocollimator, a second dual-axis autocollimator, and a data acquisition module, an attitude transformation matrix is ​​established from the cubic mirror coordinate system to the inertial measurement unit coordinate system. By synchronously triggering the inertial measurement unit, based on the outputs of a three-axis gyroscope and a three-axis accelerometer, the three-axis acceleration measured by the three-dimensional laser vibrometer in the inertial measurement unit coordinate system, and the three-axis angular velocity of the inertial measurement unit measured by the dual-axis autocollimator, the linear-angular coupling motion of the inertial measurement unit is calibrated. This invention avoids the influence of vibration on the accuracy of the measurement system and solves the problem of difficulty in dynamically tracking and monitoring the actual motion of the inertial measurement unit during vibration.

The application discloses a MEMS three-axis accelerometer calibration method based on a simulated annealing particle swarm optimization algorithm, adopts a centrifuge to calibrate a MEMS three-axis accelerometer, uses angular velocity generated by the centrifuge as specific force input of the MEMS three-axis accelerometer, applies the simulated annealing particle swarm optimization algorithm to a nonlinear model for solving to-be-calibrated parameters of the MEMS three-axis accelerometer, and identifies corresponding parameters; in the calibration process, firstly, six-position tumbling method is used to determine scale factors and zero offset values of the three-axis accelerometer, and initial values of particle swarm iteration are determined, so that the convergence speed and stability of the algorithm are improved. By rotating a slave shaft on which the accelerometer is installed by 180 degrees, the influence of centrifuge system error on parameter identification is reduced. The method effectively excites high-order coefficients of the MEMS three-axis accelerometer, significantly reduces the uncertainty of unknown parameters of the MEMS three-axis accelerometer, and greatly improves the calibration precision.

The present application relates to the field of measurement while drilling technology, and more particularly to a method, system and electronic device for improving the measurement accuracy of data while drilling, the method comprising: obtaining the attitude angle of the drill string at the current time by using a MEMS three-axis accelerometer and a MEMS three-axis gyroscope, wherein the MEMS three-axis accelerometer and the MEMS three-axis gyroscope are both installed on the drill string; calculating the error compensation value corresponding to the attitude angle of the drill string at the current time; and compensating the attitude angle of the drill string at the current time by using the error compensation value corresponding to the attitude angle of the drill string at the current time, to obtain the final attitude angle of the drill string at the current time. The installation error of the MEMS three-axis accelerometer and the MEMS three-axis gyroscope installed on the drill string, the angle random walk error and the zero drift error can be reduced, and the measurement accuracy of the data while drilling, i.e. the attitude angle of the drill string, can be improved.

The invention discloses an electronic equipment falling protection system based on multi-dimensional sensing. The system comprises a multi-dimensional sensing array, an edge calculation unit, a self-adaptive magnetic field control system and a continuous learning unit, the multi-dimensional sensor array is integrated with a triaxial accelerometer, a gyroscope, a barometer and a magnetometer, and the edge calculation unit adopts a low-power-consumption FPGA and a customized neural network processor to execute a time sequence feature extraction and trajectory prediction algorithm. According to the invention, the problem of insufficient identification precision of a traditional single sensor method under insufficient illumination or complex scenes is overcome; a 5kHz high-frequency sampling rate is adopted, and a multi-stage assembly line parallel processing architecture is combined, so that efficient extraction and trajectory prediction of time sequence characteristics are realized, and the response speed of the system is greatly improved; according to the method, the system power consumption is effectively reduced, and meanwhile, the real-time performance and accuracy of the model are ensured; the multiple electronic devices are controlled to cooperatively generate the dynamic magnetic field network, accurate magnetic suspension track control is provided for the falling device, and the device damage risk is effectively reduced.

The invention relates to the technical field of intelligent gyroscopes, in particular to an intelligent gyroscope system and method.The intelligent gyroscope system comprises a gyroscope body, a motion detection module, a data processing module, a wireless communication module, a power module and a mobile terminal application, a sealed containing cavity is formed in the gyroscope body, and the gyroscope body is of a low-gravity-center structure; the motion detection module is arranged in the accommodating cavity, and the motion detection module comprises a six-axis inertial measurement unit, an integrated three-axis gyroscope and a three-axis accelerometer and is used for collecting rotation motion data of the gyroscope in real time; the data processing module is connected with the motion detection module and is used for filtering the collected original motion data and calculating the real-time rotation speed and rotation duration of the gyroscope; according to the invention, accurate quantification and objective recording of motion parameters are realized, and the competitive property and interestingness of the toy are improved.

The invention relates to the technical field of welding gun clamping, and discloses a welding gun clamping device which comprises a robot and a rotating arm, a miniature photoelectric encoder is arranged in an upper joint hemisphere, and a lower joint hemisphere is arranged at one end of the upper joint hemisphere. The upper joint hemisphere and the lower joint hemisphere are elastically connected through a plurality of belleville spring sets, a copper ring is embedded in a groove formed in the lower joint hemisphere, an integrated circuit board is arranged in the lower joint hemisphere, and a three-axis MEMS accelerometer is arranged at one end of the integrated circuit board. Passive compliance is achieved through the belleville spring set, active stabilization is achieved through the enameled wire coil-copper circular ring eddy current damper based on ACRI intelligent decision, the belleville spring set and the copper circular ring eddy current damper are connected in parallel and cooperate, and the contradiction that in a traditional scheme, the response speed and stability cannot be achieved at the same time is solved. And the efficiency and the reliability of automatic production can be greatly improved while complete functions are ensured.

The application relates to a MEMS accelerometer-based rocker arm inclination angle detection method, three three-axis MEMS accelerometers a, b and c are respectively installed in an electric control box and left and right rocker arms of a coal mining machine, the y detection axes of the accelerometers b and c are respectively parallel to swing axes of the left and right rocker arms, the z detection axes of the accelerometers b and c are vertically upward, the x detection axes of the accelerometers b and c are horizontally extended and far away from the swing axes of the respective rocker arms when the electric control box and the left and right rocker arms are in a horizontal state, the corresponding detection axes of the accelerometers a and c are parallel, then original acceleration vectors output by the MEMS accelerometers a, b and c are respectively acquired, the original acceleration vectors are subjected to filtering processing to obtain filtered acceleration vectors, inclination angle values of the filtered acceleration vectors relative to a horizontal plane are respectively calculated, and the included angles of the left and right rocker arms relative to the electric control box are respectively calculated. Compared with a traditional method, the application has the advantages of small sensor volume, simple installation and low cost.

An implantable medical device that includes an inflatable member, a fluid reservoir, a first pressure sensor connected to the fluid reservoir, a second pressure sensor connected to the inflatable member, an accelerometer configured to detect an acceleration of the implantable medical device along three orthogonal directions, and an electronic pump device. The electronic pump device includes a controller that is configured to execute operations that include receiving a first signal with pressure readings from the first pressure sensor and computing an ambient pressure value based on the pressure readings. The operations further include detecting an inflation pressure of the inflatable member using the second pressure sensor, receiving a second signal with acceleration data from the accelerometer, computing a gauge pressure based on the ambient pressure, the acceleration data, and the inflation pressure, and controlling inflation or deflation of the inflatable member based on the gauge pressure.

A system for acquiring ultrasound images of internal organs of a human body, includes a scanner and at least a minimum number of components in, or associated therewith including: i) an ultrasound probe head; ii) the at least one IMU, which comprises a three-axis accelerometer and a three-axis gyroscope; iii) electronic components for wired or wireless communication with remote terminals, and iv) a power source, wherein the 3-axis gyroscopes and 3-axis accelerometers of the IMU are calibrated by the manufacturer for offset, scale-factor, cross-axis sensitivity and initial orientation; and MEMS IMUs are calibrated by the user.

The application belongs to the field of sign language recognition, and provides a sign language recognition method based on wearable computing, and a sign language recognition system based on wearable computing, which comprises a pair of inertial data gloves, a routing device and a human-computer interaction platform. Each inertial data glove comprises sixteen inertial sensors and a wireless transmission module, wherein the inertial sensors comprise a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and the wireless transmission module completes interaction with the human-computer interaction platform through the transmission control protocol with the routing device as the hub. The human-computer interaction module can operate the sign language recognition system, and is integrated with a trained Bi-LSTM model, hand data uploaded by the inertial data gloves is input into the Bi-LSTM model for sign language recognition, and the recognized sign language information is displayed. The system can recognize 20 kinds of Chinese dynamic sign languages, and has the characteristics of high precision, low power consumption, small device size and easy deployment and recognition.

The application relates to the technical field of monitoring, and particularly discloses a self-sensing and early-warning seamless expansion joint based on a flexible MEMS sensing array, which comprises a flexible sensing array module and a data concentrator; the flexible sensing array module is composed of a high-performance elastomer base body, a MEMS sensor array embedded in the base body and a flexible printed circuit; the MEMS sensor array is composed of a plurality of sensing nodes distributed in a grid-shaped dot matrix form, each sensing node is integrated with a three-axis MEMS accelerometer, a MEMS temperature sensor, a MEMS strain gauge and a MEMS microphone; the application endows the seamless expansion joint with real-time, multi-dimensional and self-diagnostic intelligent monitoring capability through the cooperation of hardware integration and algorithm innovation; the integrated module of the flexible base body and the multi-parameter MEMS sensing array solves the problem of long-term reliable cooperative work of the sensor and the flexible deformation body, and realizes the synchronous intensive sensing of multiple physical fields such as temperature, strain, vibration and sound.

The application discloses a drilling tool axial impact signal filtering method based on jerk filtering. The method does not need the intervention of prior knowledge, and first uses the Z-axis of the three-axis accelerometer coupled with the drilling tool to obtain the drilling tool axial acceleration signal, and obtains the jerk value of the sampling signal, so as to greatly increase the amplitude of the sampling signal. Then, the characteristics of the short-time energy of the impact acceleration are used to define the jerk peak value, set the jerk peak value condition, and determine the number of the jerk peak value. The jerk impact threshold value is set, the threshold value sampling method (TVS-threshold-value sampling) is used to screen out the jerk impact value meeting the condition, and then the energy interpolation principle (EIP-energy interpolation principle) is used to restore the sampling point number. Finally, the measurement signal of the drilling tool after the axial impact acceleration is filtered is obtained through the operation of adjacent time.

The invention particularly relates to a one-stop service method and system for intelligent hospital logistics management, and relates to the technical field of intelligent hospital logistics management. And asset characteristic data including motion state characteristics, space attitude characteristics and base in-place state characteristics are obtained. According to the invention, the three-axis accelerometer, the magnetic induction sensor and the positioning unit are integrated in the end-side intelligent tag, and a mixed acquisition strategy combining event-driven triggering and periodic heartbeat reporting is adopted, so that the multi-dimensional synchronous sensing of the medical asset position, the motion state, the spatial attitude and the base in-place state is realized, and the sensing dimension is expanded; and meanwhile, the sensor component enters the low-power-consumption sleep mode in the time period when no event is triggered and the heartbeat reporting moment is not reached, so that the continuous power consumption of the terminal is reduced.

The utility model relates to the technical field of fiber-optic gyroscope IMU (Inertial Measurement Unit), in particular to a fiber-optic gyroscope IMU structure which comprises a shell, and a plurality of mounting grooves are formed in the side wall of the shell; the mounting grooves in the side wall of the shell comprise an upper mounting groove, a rear mounting groove, a left mounting groove and a lower mounting groove, the left mounting groove, the rear mounting groove and the lower mounting groove are each provided with an optical fiber assembly, and the axes of the optical fiber assemblies are spatially orthogonal in pairs; a mounting boss is arranged in the upper mounting groove and used for mounting the navigation plate, a triaxial accelerometer, a storage module and a temperature sensor are mounted in the upper mounting groove, and a certain distance is kept between the upper mounting groove and the bottom surface of the navigation plate, so that interference is avoided. A common square structural design is adopted, so that production, processing and manufacturing are facilitated; the layout of electronic components and optical devices is very reasonable, for example, the upper mounting groove is mainly provided with related structures such as an accelerometer, the lower mounting groove is mainly provided with related structures such as a fiber-optic gyroscope, and a light source is arranged in an independent cavity, so that electromagnetic interference isolation and heat source isolation are realized.

The invention relates to the technical field of biomedical electronic engineering and physiological signal processing, and discloses a special MEMS sensor for heart sound, which comprises an MEMS sensor shell, a silicon substrate is fixedly connected to the inner bottom of the MEMS sensor shell, and a central acoustic unit and a peripheral inertial unit are integrated on the silicon substrate in a monolithic manner; the central acoustic unit is used for collecting sound pressure signals; the central acoustic unit is arranged in the MEMS sensor shell, the peripheral inertial unit is arranged around the central acoustic unit and is used for collecting three-axis acceleration signals, a processor is arranged in the MEMS sensor shell and is electrically connected with the central acoustic unit and the peripheral inertial unit, the central acoustic unit is of a capacitive MEMS microphone structure, and the central acoustic unit and the peripheral inertial unit are arranged in the MEMS sensor shell. The peripheral inertia unit is of a three-axis MEMS accelerometer structure. Through multi-modal signal fusion and closed-loop adaptive adjustment, the problems that traditional heart sound collection is low in signal-to-noise ratio, unstable in signal and lack of comparability are solved.

The invention discloses a psychological stress pre-judgment method and device based on motion features. The method comprises the following steps: acquiring user motion original data comprising X-axis acceleration data, Y-axis acceleration data and Z-axis acceleration data at a sampling frequency of 10-50Hz through a three-axis EMS accelerometer, and converting the user motion original data into a step number sequence with a timestamp; preprocessing the step number sequence to obtain a dynamic motion signal matrix; extracting micro tremor features, action mode features and behavior rhythm features from the dynamic motion signal matrix to form a 6-dimensional feature vector; collecting normal step number data of a preset number of days of a user to establish an initial individual datum line, and updating the individual datum line in a rolling manner based on the newly generated normal step number data; and inputting the six-dimensional feature vector into a stress assessment model constructed by an improved random forest algorithm, and outputting a real-time psychological stress value by comparing the deviation between the six-dimensional feature vector and an individual datum line and combining a preset interference elimination mechanism. According to the scheme, the psychological stress can be quantified through the step number features, detection misjudgment is reduced, and the detection accuracy is improved.

This invention belongs to the field of electronic device control technology, specifically a multi-scenario adaptive headphone control system, including a multimodal sensing module, a state fusion and recognition module, a scene adaptive decision-making module, and a dynamic audio control module. By integrating a pressure sensor array, an infrared proximity sensor, a three-axis accelerometer, and a microphone array to form the multimodal sensing module, it can capture subtle state changes of the headphones from multiple dimensions such as pressure distribution, physical distance, motion posture, and acoustic environment. The state fusion and recognition module adopts a classification model based on a multilayer perceptron to deeply fuse and intelligently recognize data from multiple heterogeneous sensors, achieving high-precision and high-reliability differentiation of various physical states such as removal / placement, loose wearing, and tight wearing, fundamentally avoiding control mis-triggering problems caused by state misjudgment.

Smart shoe comprising a flexible antenna metal network integrated into the upper, a waterproof encapsulated electronic unit in the sole or heel containing a microcontroller, a WLAN / Mesh / Bluetooth chip, a battery, and a motion-based energy harvesting generator in the form of a threaded magnetic coil, a temperature-controlled heating function integrated under the insole, and sensors for movement via a three-axis accelerometer, for position via a gyroscope, for temperature, humidity, and pulse, as well as a GPS module and other health and safety parameters.

The present invention relates to a fishing rod which transmits a detection signal according to a bite pattern, the fishing rod comprising: a body part connected by multiple tubular bodies and adjustable in length; and a grip part coupled to one end of the body part. The grip part includes: a first body portion that surrounds an end of the body part and is coupled thereto; and a second body portion detachably coupled to the first body portion. The second body portion includes: half-shell cases coupled in a cylindrical shape; three-axis accelerometers that are installed inside the cases and measure a vibration pattern transmitted via the body part; PCBs that are installed inside the cases and equipped with CPUs for comparing the vibration pattern measured by the three-axis accelerometers with a bite pattern of a target fish to determine whether the patterns match; and a lamp module configured to emit light when the CPUs determine that the vibration pattern matches the bite pattern of the target fish.

A kind of liquid level measurement method and system of guided wave radar liquid level meter, to solve the problem that the accuracy of actual liquid level measurement result is not high when guided wave radar liquid level meter measures the liquid level of asphalt reaction kettle due to installation or steam and temperature in the reaction kettle, the echo signal of guided wave radar liquid level meter is smoothed and filtered;Generate echo signal-time curve, obtain peak information of reflected echo;Select the shortest transmission time of reflected echo peak segment and its coordinate position;Measure the temperature at a certain time in the reaction kettle, calculate the original liquid level distance using the relative speed of electromagnetic wave and coordinate position;Assume that the force is gravity, calculate the inclination angle of the top of guided wave radar liquid level meter and liquid level horizontal plane by three-axis acceleration;Obtain the actual liquid level distance by using trigonometric function;Obtain the function relationship of temperature, inclination angle and actual liquid level measurement value in the reaction kettle by using MATLAB software to calculate the actual measurement distance.

The application relates to the technical field of intelligent hardware control, and discloses an intelligent flat plate support control method and system based on MCU, wherein the intelligent flat plate support control method based on MCU comprises the following steps: synchronously reading signals of a three-axis accelerometer, a gyroscope, a magnetometer and a charging detection circuit; performing coarse classification through a voltage threshold value and fine identification through a current change rate; dynamically adjusting filter parameters and correcting electromagnetic interference through an interference compensation parameter table; adopting a priority preemption type task scheduling strategy, avoiding task conflicts and resource competition through a time slice rotation and a resource mutual exclusion lock mechanism; adopting a segmented motor control strategy for a task scheduling scheme to obtain a head control position control instruction; dynamically adjusting charging power; and adopting state caching and incremental updating technology to obtain an updated control instruction; through hierarchical charging state detection technology, the system can accurately identify different charging stages, and dynamically adjusts head control parameters according to the charging state.

This invention concerns an innovative method and device for recording and analyzing road surface smoothness, implemented via a telematics device-main unit (1) installed on a transport vehicle [e.g., truck, bus, etc.] (7) performing independent tasks, such as waste collection, goods transportation, passenger transport, or surveillance. The telematics device - main unit (1) records acceleration [vertical - longitudinal - lateral] (8) and angular velocity through the integrated three-axis accelerometer (2), gyroscope (3), and GPS receiver. Subsequently, the processor-controller (6) correlates the data with geographic coordinates and transmits them via the cellular communication module (5) to the cloud-based computing platform (9), where data is visualized on a GIS map with color-coded smoothness indicators, alert algorithm output, and administrative classification [Municipality, Region, Highway] (10). The device automatically calculates the vertical axis when the vehicle is stationary, regardless of the mounting orientation. It further applies corrections in cases of high longitudinal or lateral acceleration by filtering out vibrations unrelated to road surface degradation. The platform displays the latest measurements for each point, maintains historical records, and activates alerts only when new wear or damage is detected. The data is categorized into geographic units (municipalities, regions, highways), enabling the production of statistical and comparative reports per area, thereby supporting evidence-based planning and prioritization of maintenance interventions.

This utility model belongs to the field of unmanned aerial vehicle (UAV) technology and relates to a fiber optic integrated navigation device. The device includes a housing, within which an inertial measurement unit (IMU) is housed. The IMU comprises a three-axis embedded fiber optic gyroscope assembly, which is detachably connected to the housing. A three-axis accelerometer is connected to the bottom of the three-axis embedded fiber optic gyroscope assembly. This utility model adopts a three-axis integrated structure, highly integrating the fiber optic gyroscope assembly, accelerometer, satellite navigation module, and processing circuitry into a compact housing. The components are modularly assembled through detachable connections, significantly reducing size and weight, and adapting to installation requirements in space-constrained scenarios such as aircraft center of gravity. Through miniaturization, high integration, multi-source fusion, and environmental adaptability, this device overcomes the limitations of traditional fiber optic inertial navigation, providing high-precision, high-reliability, and low-cost fiber optic inertial navigation for aviation, maritime, and other fields.