1426 results about "Vibration sensor" patented technology

The invention relates to the technical field of energy storage cabinet safety monitoring, in particular to an energy storage cabinet multi-parameter intelligent monitoring device based on an MEMS sensor array, a sensor array unit in the energy storage cabinet multi-parameter intelligent monitoring device comprises distributed MEMS temperature and vibration sensors, the temperature sensors are installed in a non-vertical mode, detection deviation caused by direct blowing of airflow is avoided, and the energy storage cabinet multi-parameter intelligent monitoring device based on the MEMS sensor array is obtained. The airflow disturbance correction unit corrects temperature original data in real time and eliminates interference of airflow on module body temperature detection by means of a heat dissipation airflow vector field dynamic model and a compensation algorithm, and the multi-parameter coupling analysis unit processes vibration and temperature signals in a double-channel mode, extracts tab loosening high-frequency micro-vibration characteristics and correlates the temperature rising rate. Early fault logic is triggered through two-stage judgment, the fault decision and output unit fuses the correction temperature, the coupling strength coefficient and the speed-up ratio, graded early warning is generated through a fault tree model and transmitted to an external monitoring system, and accurate monitoring of early faults of the energy storage cabinet is achieved.

The disclosure relates to a blade transport vehicle, a monitoring system, a monitoring method and an electronic device, the blade transport vehicle comprising: a trailer having a length direction, a width direction and a height direction; the blades are fixed on the trailer through a mounting assembly; the vibration sensor is arranged on the trailer or the installation assembly, the vibration sensor is provided with at least one detection direction, and the at least one detection direction is parallel to at least one of the length direction, the width direction and the height direction of the trailer. According to the technical scheme, the possibility that the blades are damaged can be reduced, and the installation quality of the wind power blades is guaranteed.

The invention discloses a wind turbine generator impeller anomaly detection method and system based on sound vibration signal identification. According to the method, firstly, impeller response is collected through a microphone / vibration sensor, and a Mel spectrogram is generated; then, a Teager-Kaiser energy operator and self-correlation analysis are utilized, and under the condition of not depending on a rotating speed signal, the rotating period of the impeller is recognized, and frequency spectrum segmentation is carried out; calculating a cross-period Mel frequency spectrum dynamic deviation, and normalizing the cross-period Mel frequency spectrum dynamic deviation through an amplitude correction coefficient related to the rotating speed; generating a periodic coherent energy diagram by adopting an improved structural similarity algorithm; performing filtering enhancement by using a harmonic resonance template, performing morphological deconstruction and parameterization on an abnormal region in the graph, and extracting geometric features; and finally, calculating a comprehensive abnormal score based on the multi-dimensional features and realizing automatic early warning. According to the method, the problems of variable working condition interference and rotating speed dependence are effectively solved, and accurate and stable detection of early abnormality of the impeller can be realized.

The invention discloses a metal mine production big data intelligent analysis method and device and a medium, and relates to the technical field of intelligent mine information, and the device comprises an acquisition and modeling module, an analysis module, a prediction and optimization module and a visualization module; the data acquisition unit is provided with a vibration sensor, a temperature sensor and a geological pressure sensor, and is used for acquiring mine equipment operation parameters, mineral processing process indexes and geological environment parameters in real time to obtain multi-source data; the data preprocessing unit is used for performing timestamp alignment, missing value compensation, noise elimination and unit normalization processing on the multi-source data to obtain standardized multi-source data; the feature extraction unit adopts a multi-head Transform network, performs space-time modeling and semantic feature fusion on standardized multi-source data, and outputs a tensor embedding vector, the risk identification result is converted into an executable process adjustment strategy, the crossing from passive early warning to active optimization is realized, and the efficiency and the intelligent level are enhanced.

The invention discloses a sound barrier sound insulation characteristic evaluation method suitable for a real ship complex sound field, and belongs to the technical field of real ship sound barriers, and the method comprises the steps: arranging hydrophone arrays at acoustic mirror symmetry positions at two sides of a real ship fairing sound barrier to form an in-situ measurement pair; controlling the ship to sail at a plurality of navigational speeds, and synchronously acquiring sound pressure time domain signals on two sides; carrying out preprocessing and time-frequency analysis on the signals, and calculating sound pressure levels of a sound facing surface and a sound backing surface to obtain an in-situ sound pressure level difference; and based on the sound pressure level difference at different navigational speeds, analyzing the change rule of the sound insulation performance along with the frequency and the navigational speed, and carrying out comprehensive evaluation. In addition, by arranging a vibration sensor and a turbulence measuring device, path separation of structural sound and flow-induced noise is achieved, spatial coherence weighted average is introduced, and the accuracy and representativeness of evaluation under a complex sound field are improved. The method overcomes the limitations of laboratory test environment distortion and single working condition, and can truly and comprehensively reflect the actual sound insulation efficiency of the sound baffle in the dynamic navigation of a real ship.

The invention discloses an elevator internal device fault intelligent inspection management system and management method. The system comprises a sensing layer, a transmission layer, a platform layer and an application layer which communicate in sequence. The sensing layer collects operation data of devices such as an elevator traction machine and a portal crane system through special sensors such as a vibration sensor and a temperature sensor and a camera. The transmission layer encrypts transmission data in a mixed transmission mode after edge calculation preprocessing; the platform layer adopts double databases to store data, and fusion analysis is performed through a convolutional neural network model and a long-short-term memory network model; the application layer provides exclusive functions for multiple subjects. The management method forms a closed loop through data acquisition, processing, diagnosis, operation and maintenance. According to the method, the fault identification accuracy is over 96 percent, the response time is shortened to be within 30 minutes, 45 percent of sudden faults are reduced, accurate decision is supported, the safety is improved, the operation and maintenance cost is reduced, and the applicability is high.

The invention discloses a vibrating screen control system based on a cloud platform. The vibrating screen control system comprises a data acquisition layer, an edge computing layer, a cloud analysis layer and an execution control layer. The data acquisition layer comprises a plurality of sensor groups, and each sensor group comprises a vibration sensor, a temperature sensor and an audio sensor which are arranged on a vibrating screen so as to acquire a vibration signal, a temperature signal and an audio signal in real time. And the edge calculation layer preprocesses the vibration signal, the temperature signal and the audio signal. And the cloud analysis layer executes a fault prediction and diagnosis step and outputs a fault result according to the preprocessed vibration signal, temperature signal and audio signal. And the execution control layer controls the vibrating screen based on the fault result of the cloud analysis layer. According to the method, the fault detection accuracy, the system robustness, the equipment safety and the operation and maintenance efficiency are comprehensively improved through multi-mode fusion sensing, cloud-side cooperative computing and intelligent control modes, and the defects of an existing vibrating screen monitoring and control technology are remarkably overcome.

The invention discloses an intelligent dynamic regulation and control method for compaction quality of a high-liquid-limit fly ash roadbed, which comprises the following steps of: establishing a mapping relation among high-spectral characteristics of high-liquid-limit fly ash, a specific surface area index, a total hydroxyl content and a water content through a first neural network model, and establishing an optimal water content prediction model through a second neural network model; the third to fifth neural network models construct the correlation of the compactness, the dielectric constant, the rigidity and the water content; two-stage water content regulation and control of a storage yard and a paving layer are realized through hyperspectral imaging of an optical fiber probe and an unmanned aerial vehicle, and pre-humidification and secondary precise regulation and control are performed in combination with an intelligent spraying system; in the compaction stage, data are collected in real time through a multi-frequency ground penetrating radar and a vibration sensor, compaction degree distribution is inverted, layered evaluation is conducted, and rolling parameters are dynamically adjusted. According to the invention, a hyperspectral technology, multi-source sensing and deep learning are fused, intelligent management of compaction quality is realized, and construction uniformity and quality stability of the fly ash roadbed are significantly improved.

The invention discloses an electric power aerial patrol operation data mining method, and belongs to the technical field of intelligent patrol. Coordinate values and temperature data of target equipment are synchronously collected through an infrared thermal imager, a visible light camera and a vibration sensor carried by power equipment, infrared coordinates and visible light coordinates are projected to the same geographic coordinate system through affine transformation, space registration is achieved, continuous wavelet transformation is conducted on collected vibration signals, and the temperature of the target equipment is obtained. The method comprises the following steps: extracting vibration feature vectors including global vibration intensity, wavelet energy spectrum and wavelet entropy, calculating the weight of each feature through image quality, carrying out weighted fusion to calculate a state index representing the health state of equipment, judging the state index according to a dynamic threshold value, judging that the equipment is abnormal if the state index exceeds the threshold value, and judging that the equipment is abnormal if the state index does not exceed the threshold value. And a feedback mechanism is triggered to collect data again to monitor the trend, otherwise, the data is stored for subsequent analysis. According to the invention, the precision and reliability of abnormal state identification in electric power aerial patrol operation and the robustness to a complex field environment are significantly improved.

The invention discloses a robot joint torque control system and method, and the system comprises a joint torque sensor which is used for detecting the actual output torque of a joint; the joint driver is used for driving robot joints to move according to the control instruction; the bearing pre-tightening mechanism is used for applying pre-tightening force to the joint bearing; the multi-source environment sensing module comprises a temperature sensor used for detecting the temperature of the bearing, a vibration sensor used for detecting the mechanical vibration frequency and amplitude, and an electromagnetic interference detector used for detecting the electromagnetic interference intensity; the intelligent compensation module is integrated in the controller and comprises a thermal deformation compensation unit, the input end of the thermal deformation compensation unit is connected with the temperature sensor, and the thermal deformation compensation unit is used for generating the first torque compensation amount. According to the method, high-stability control over the robot joint torque is achieved, the influence of various kinds of interference and uncertainty on the torque control effect is reduced, the reliability under the complex working condition is remarkably improved, and the higher-precision robot joint torque control requirement is met.

The invention relates to a vertical high-speed motor active and passive vibration reduction system, which comprises a motor body, a motor base, a controller, a vibration sensor and an integrated active and passive pneumatic damping actuator, and is characterized in that the actuator is arranged between the motor body and the motor base; the vibration sensor is in signal connection with the motor body; the input end of the controller is in signal connection with the vibration sensor, and the output end of the controller is in signal connection with the high-speed switch pneumatic servo valve. According to the vertical high-speed motor active and passive vibration reduction system and vibration reduction method, a controller, a high-speed switch pneumatic servo valve and other components form an active damping system; and the damping pore plate and the auxiliary air chamber jointly form a built-in passive damping system. The passive damping system processes broadband vibration, and active control burden is reduced; and the active damping system achieves accurate suppression, and the overall energy efficiency ratio is increased. The active damping system and the passive damping system work in cooperation to jointly solve the vibration problem, so that the vibration problem of the vertical high-speed motor is rapidly and effectively suppressed.

A system and method are disclosed for advanced multimodal-sensor systems integrating various sensing characteristics for machine condition monitoring, including thermal imaging cameras, ultrasonic, vibration, temperature, magnetic sensors, high-band microphones, electro-magnetic emission detectors and others. The system's architecture comprises edge computing capabilities for real-time anomaly detection and operational feedback, utilizing edge machine learning (ML) models trained in the cloud. The system supports flexible configuration and calibration to optimize measurements based on machine requirements, while a cloud-based analysis framework enables robust data fusion, training and condition assessment. The method comprises performing automated diagnostic workflows enabled by models at the edge, reducing or eliminating human intervention, and significantly enhancing operational performance, maintenance and efficiency across multiple machines in an industrial setting.

The invention relates to the technical field of industrial equipment control, and discloses a dynamic maintenance management method and system based on the full life cycle of test equipment, and the method comprises the steps: obtaining a time domain vibration signal and torque current data during the operation of the equipment through a high-frequency vibration sensor and a current loop feedback interface; calculating an accumulated damage gradient parameter representing the physical recession degree of the mechanical transmission chain; the parameters are input into a preset damage stress coupling model to solve the maximum radial impact force allowed to be borne by the damaged part, and the impact force is mapped into a dynamic capability boundary for carrying out logic constraint on the motion planning instruction; and the motion controller reconstructs an ideal speed curve by using the boundary in an interpolation period, and reshapes a torque load spectrum output to a servo motor by reducing the jump of acceleration and deceleration sections. The problem that an existing static control strategy is mismatched with the dynamic aging characteristic of equipment is solved.

The invention relates to a shield tunneling machine tunneling construction method for stratums with different sand contents, which comprises the following steps of: S1, investigating characteristic parameters, including types, sand contents and mechanical parameters, of stratums to be tunneled; s2, installing an ultrasonic-assisted hob system integrated with an ultrasonic excitation module; s3, ultrasonic parameters and shield tunneling parameters are set according to the characteristic parameters of the stratum; and S4, shield tunneling is started, ultrasonic parameters and shield tunneling parameters are adjusted in real time through the cooperative control module, vibration, hob abrasion and mud cake forming conditions in the construction process are monitored, and in the tunneling process, the operation mode of the cooperative control module is that on the basis of multi-dimensional monitoring data collected by a vibration sensor, an abrasion detection device and a slag sample analysis sensor, the ultrasonic parameters and the shield tunneling parameters are adjusted in real time. Parameters are dynamically adjusted according to stratum types and sensitive area requirements, the single adjustment amplitude and adjacent adjustment intervals of the parameters are controlled, the adjustment effect is verified in real time through a sensor, and closed-loop control over parameter adjustment and monitoring is formed.

The invention relates to the technical field of equipment control, in particular to a vibration control method and system for drilling equipment. The method comprises the following steps that vibration information collected by a vibration sensor on drilling equipment and drill bit damage state information of the drilling equipment in the cutting process are obtained; confirming a vibration characteristic fingerprint mode based on the vibration information and the drill bit damage state information; based on the vibration characteristic fingerprint mode and a preset vibration suppression library, obtaining a vibration suppression mode corresponding to the vibration characteristic fingerprint mode; and based on the vibration suppression mode, driving control is conducted on an active vibration reduction actuator, so that vibration control is conducted on the drilling equipment. The vibration control method aims at solving the problem that when an existing vibration control method for the drilling equipment is under the non-standard operation condition or is used for treating heterogeneous composite materials, complex vibration modes are difficult to effectively deal with, and consequently the drilling equipment cannot be effectively controlled.

The invention discloses an early warning system and method for looseness of a wiring terminal of a distribution box, and relates to the technical field of power equipment monitoring, and the system comprises a miniature vibration sensor module which is installed in the center of a polished rod section of a connecting bolt of a target wiring terminal in an embedded manner, and is used for collecting a micro-amplitude mechanical vibration signal; the non-contact infrared temperature measurement module is over against the surface of the wiring terminal and is used for monitoring the temperature and calculating the temperature rise rate; the edge calculation unit, the vibration sensor module and the infrared temperature measurement module are in communication connection, synchronously acquire data, extract vibration spectrum characteristics and temperature rise rate, and perform fault judgment based on a preset coupling criterion; and the wireless communication module uploads the early warning event to a remote monitoring platform. The method has the advantages that data are acquired through cooperation of the rigidly coupled miniature vibration sensor and the multi-angle infrared temperature measurement module, real looseness and load fluctuation interference are effectively distinguished by combining a dynamic threshold value and a multi-physics coupling criterion, the weak looseness characteristic signal acquisition sensitivity is improved, and the multi-physics coupling criterion is accurately identified.

The invention belongs to the technical field of shock absorption of building structure engineering, and provides an adjustable resonance suppression method for a floorboard, and the method comprises the steps: deploying a vibration sensor on the floorboard, obtaining a vibration signal in real time, and carrying out the analysis, so as to precisely recognize a dominant excitation frequency, a transmission path of vibration energy, and the contribution degree of the transmission path; the contribution degree of a transmission path and the vibration amplitude of a floor plate are taken as optimization targets, meanwhile, the parameter constraint space of the adjustable steel support is taken into consideration, and it is ensured that the generated tuning parameter combination meets the suppression requirement and meanwhile adapts to the structural bearing capacity of the adjustable steel support; driving the adjustable steel support to perform grading adjustment, obtaining feedback data after grading adjustment, and recalculating the contribution variation of the transmission path and the amplitude attenuation rate of the floor plate; and when the regulation and control effect does not reach the standard, the solution parameter of the optimization function and the analysis parameter of the vibration signal are correspondingly adjusted, so that the suppression method is ensured to have good dynamic adaptability, and the stable resonance suppression effect can be continuously maintained.

The invention relates to the technical field of power equipment state monitoring, and provides a switch cabinet state intelligent detection method and system based on multi-sensor fusion, and the method comprises the steps: obtaining state data corresponding to a switch cabinet through a temperature sensor, a vibration sensor, a partial discharge sensor, a current sensor and a voltage sensor which are disposed in the switch cabinet; inputting the obtained state data into a preset data preprocessing module, performing denoising processing and normalization processing on the state data, obtaining preprocessed multi-source data, and generating a multi-dimensional feature vector; inputting the multi-dimensional feature vector into a preset hierarchical fusion model, carrying out feature layer fusion on the multi-dimensional feature vector to obtain an intermediate fusion feature, combining historical operation data and historical fault data of the switch cabinet, carrying out decision-making layer weighted fusion on the intermediate fusion feature to generate a comprehensive state feature vector, and outputting the comprehensive state feature vector. And triggering a corresponding early warning system or a fault alarm system.

The invention discloses a rail fastener loosening fault diagnosis and identification method and system. The method comprises the steps that at least one steel rail vibration signal in a preset time period is acquired based on a preset improved vibration sensor; carrying out improved symplectic geometric mode decomposition on the at least one steel rail vibration signal to respectively obtain a steel rail vibration reconstruction signal corresponding to the at least one steel rail vibration signal; carrying out feature selection on each steel rail vibration reconstruction signal according to a preset Leloine feature screening strategy, and constructing a feature matrix corresponding to each steel rail vibration reconstruction signal based on the selected features; and inputting each feature matrix into a preset improved bidirectional gating loop unit network, and performing iterative training on the improved bidirectional gating loop unit network to obtain a fastener loosening fault analysis model. The accuracy of track fastener loosening fault degree recognition and the classification precision are improved, and track faults can be checked easily.

The invention provides an avalanche real-time monitoring and early-warning system, and the system comprises avalanche monitoring stations which are installed at multiple points in the avalanche advancing direction, and each avalanche monitoring station is composed of a vibration sensor, a remote wireless alarm signal transmitter, a solar power supply system, and a monitoring rod. The acousto-optic alarm station is arranged on a road, a mining area, a pasturing area, a tourist area and a personnel residential area and is composed of a remote wireless alarm signal receiver, a signal processor, a flashing light, a high-power loudspeaker, a solar power supply system and a monitoring rod. The environment monitoring station is composed of an infrasound sensor, an earth sound sensor, a rainfall and snowfall sensor, a temperature and humidity sensor, a wind direction and wind speed sensor, a solar power supply system, an LORA radio transceiver and a monitoring rod. And the intelligent telemetering control terminal consists of an intelligent telemetering terminal, a solar power supply system and a monitoring rod. The system is helpful for timely sending dangerous case alarms to the masses in a threat area before and just when an avalanche disaster occurs, so as to avoid or reduce casualties and property loss.

The invention provides a conveyor state monitoring device and method based on machine vision, and the device comprises a monitoring cabin which can autonomously reciprocate along a rigid guide rail at one side of a conveyor, automatic charging piles are arranged at the two ends of the guide rail, and the monitoring cabin is integrated with an infrared thermal imager, a visual camera and a sound sensor. A vibration sensor and an incremental photoelectric encoder are arranged along the line. A processor is arranged in the monitoring cabin, and time alignment, feature extraction, fusion of a multi-scale feature fusion model and three-level decision judgment are carried out on infrared signals, visual signals, sound signals and vibration signals on the basis of encoder timestamps. According to the method, fault diagnosis and false alarm filtering are achieved by controlling inspection of a monitoring cabin, multi-source data preprocessing, confrontation feature fusion network processing and three-level progressive judgment, and accurate positioning is achieved based on the mapping relation between encoder pulses and support numbers. According to the invention, the monitoring coverage range is expanded, the endurance continuity is improved, the data transmission stability is improved, and the false alarm rate is reduced.

Vibration sensors are provided. The vibration sensor may include: a vibration assembly, the vibration assembly including a mass element and an elastic element, and the mass element being connected to the elastic element; a first acoustic cavity, the elastic element constituting one of sidewalls of the first acoustic cavity, and the vibration assembly vibrating to make a volume of the first acoustic cavity change in response to an external vibration signal; an acoustic transducer, the acoustic transducer being in communication with the first acoustic cavity and the acoustic transducer generating an electrical signal in response to a volume change of the first acoustic cavity; and a buffer, the buffer limiting a vibration amplitude of the vibration assembly, wherein the acoustic transducer has a first resonance frequency, the vibration assembly has a second resonance frequency, and the second resonance frequency of the vibration assembly is smaller than the first resonance frequency.

The invention discloses an oil liquid quality evaluation system based on big data, and relates to the technical field of multi-source sensing and Internet of Things, and the system comprises a data collection module which collects full-dimensional data through a heterogeneous sensing array of an oil-containing liquid multi-parameter integrated sensor and a high-frequency vibration sensor in combination with a timestamp synchronous triggering mechanism; the space-time calibration module adopts a dynamic time warping-interpolation collaborative algorithm to align the vibration signal and the oil data, and the information loss is controlled to be lower than a preset threshold value; the feature fusion module generates enhanced fusion features through a pre-trained embedded model and a double-stage attention mechanism; the intelligent evaluation model outputs oil quality grade and fault early warning based on a deep neural network, and the federated learning optimization unit guarantees data privacy; and the visual output module visually displays the result. The system improves the evaluation precision and the data utilization rate, adapts to industrial predictive maintenance, and reduces the shutdown loss of equipment.

The invention relates to an oxygen supply device and an intelligent oxygen supply amount adjusting method, belongs to the technical field of medical equipment, and solves the problems of low resource utilization rate and poor individual comfort caused by extensive oxygen supply in the prior art. The oxygen supply device comprises a vibration sensor used for collecting weak vibration signals of a human body; the signal processing platform is used for extracting a respiration signal, a heart impact signal and related characteristics of the respiration signal and the heart impact signal in the human body weak vibration signals and calculating the blood oxygen saturation degree; regulating and controlling the oxygen supply amount and generating a corresponding regulation and control command by monitoring the change of the oxyhemoglobin saturation and the breathing signal; and the oxygen supply output device is used for adjusting the state of a valve to carry out oxygen supply output according to the regulation and control command of the signal processing platform. Through undisturbed non-intrusive real-time monitoring of vital signs, real-time intelligent adjustment of oxygen supply is achieved, the comfort of oxygen supply is improved, and energy consumption and resource waste are reduced.

The invention relates to the technical field of rail transit equipment safety, and discloses a rail transit vehicle domestic chip door controller fault diagnosis method based on deep learning, which comprises the following steps: step 1, through a vibration sensor, a temperature and humidity sensor and a door control system working state sensor which are deployed in a rail transit vehicle door control system, a fault diagnosis result is obtained; collecting operation data, environment data and external disturbance factor data of the door controller in real time; step 2, starting a data preprocessing module, performing cleaning and formatting operation on the data collected in real time in the step 1, and integrating the data from different sensors by adopting a multi-dimensional data fusion technology; according to the technical scheme, the deep learning model is adopted to analyze multi-source sensor data in real time, the technical effects of rapid fault recognition and early warning are achieved, compared with a traditional relay control mode applied in the prior art, the defects that response is slow and faults are not found in time are overcome, and the safety of passengers getting on and off the bus is improved.

The invention discloses a self-adaptive precision polishing control system and method based on multi-modal perception and artificial intelligence decision. According to the system, a multi-mode sensing network is constructed through an acoustic emission sensor, a force / torque sensor, a vibration sensor, a visual sensor and a temperature sensor, and physical signals in the polishing process are collected in real time. The system adopts a deep learning model to carry out feature fusion and space-time analysis on multi-source sensing data, realizes accurate estimation of the material removal rate and comprehensive scoring of the surface quality, further integrates a reinforcement learning optimization engine, takes a process state as input, takes control parameter adjustment as action, and takes a multi-target reward function as guidance, and realizes comprehensive evaluation of the surface quality. And the autonomous optimization decision of the polishing parameters is realized. The invention further comprises a digital twinning system for offline training and online verification, and a transfer learning-based small sample rapid adaptation mechanism, so that the polishing quality consistency, the processing efficiency and the process autonomy can be remarkably improved.

The invention discloses a municipal pipe network leakage position identification method, and belongs to the technical field of municipal water supply engineering. Vibration sensors are arranged in a pipe network to collect leakage signals, multiple sub-band signals are obtained through band-pass filtering and wavelet packet decomposition, self-adaptive weights are calculated based on coherence coefficients of all sub-bands, and cross-correlation functions are subjected to weighted fusion to estimate time delay. Frequency domain phase compensation is applied to each sub-band according to the physical parameters of the pipeline to eliminate the dispersion effect, and then the correction time delay is recalculated, and then a pipe network topological graph is established, and a target function is constructed by using the time delay information of the multiple sensor pairs to perform global optimization to obtain a positioning result. And finally calculating a confidence index and a spatial uncertainty index to evaluate the positioning reliability. According to the method, the time delay estimation precision under a low signal-to-noise ratio is improved, systematic deviation caused by dispersion of a non-metal pipeline is eliminated, the problem of multi-solution positioning in a complex pipe network is solved, and quantitative reliable reference is provided for engineering decision making.

The utility model discloses a Bluetooth NFC integrated multi-mode unlocking locomotive intelligent lock which comprises a Bluetooth NFC controller, an intelligent lock assembly, a remote controller, a mobile phone BLE unit and an NFC card, and an MCU main control unit is arranged in the Bluetooth NFC controller and electrically connected with an RF internal receiving module, an NFC driving module, a Bluetooth BLE module, a vibration sensor and an acousto-optic prompting module. According to the intelligent lock, five-in-one unlocking of remote control, Bluetooth induction, an NFC entity card, a mobile phone simulation card and a mechanical key is achieved, and the functions of automatic fortification, graded vibration alarm, riding anti-robbing reminding, parameter graded adjustment, multi-device management and OTA upgrading are integrated; the problems that a traditional locomotive lock is single in unlocking, poor in anti-theft performance and weak in adaptability are solved, the using convenience and safety of a locomotive are improved, and the anti-theft lock is suitable for anti-theft control over two-wheel locomotives and electric vehicles.

The invention relates to an intelligent warning pile for preventing external damage of a power transmission line and a monitoring method. The intelligent warning pile comprises a warning pile body, an intelligent control mainboard, a communication module, visual monitoring equipment, sensing equipment and warning equipment, the sensing equipment comprises an infrared sensor and a vibration sensor and continuously works when the warning pile is in a monitoring state; the intelligent control mainboard is awakened according to a monitoring signal of the sensor; the visual monitoring equipment is used for capturing and identifying images; the intelligent control mainboard is further configured to control the alarm device to give an alarm and / or control the communication module to send an alarm signal only when it is judged that the ground breaking construction behavior exists according to the recognition result of the visual monitoring device. According to the invention, through a cooperative control mechanism of sensor normally-open, mainboard dormancy, accurate wakeup and visual review, the alarm accuracy is greatly improved while long-term reliable duty under extremely low power consumption is realized, so that an efficient, economic and maintenance-free intelligent protection solution is provided for the power transmission line.

The utility model discloses an adjustable carbon steel cable bracket for a ship, and relates to the technical field of cable brackets. The cable bracket comprises the main body, the fixing block is arranged in the main body, one side of the fixing block is fixedly connected with the V-shaped seat, the second threaded rod and the third threaded rod are arranged, so that the upper clamping plate can be finely adjusted according to cables with different diameters, the adaptability of the bracket to the cables is improved, and the cable bracket is convenient to use. The risk that the cable is loosened or falls off due to vibration or external force impact is reduced, when the vibration sensor detects abnormal vibration, the warning lamp is immediately triggered to be turned on through an electric signal, warning information is sent to an external control console at the same time, the timely warning mechanism can quickly attract the attention of sailors and operators, and the safety of the sailors and the operators is improved. The warning lamp is turned on, so that sailors and operators are reminded to pay attention to the state of the cable and carry out fixed-point maintenance, and the effect of warning passersby is also achieved.