181results about "Acoustic presence detection" patented technology

A method for monitoring an infrastructure of interest, the method comprising: providing a distributed acoustic sensor, an analysis module, and optical fibre cable adjacent to the infrastructure wherein the optical fibre cable is divided into one or more sections, and the distributed acoustic sensor generates DAS sensor data from the one or more sections; providing a processing module comprising one or more processors and a memory, wherein the memory comprises at least two or more processing algorithms, wherein the one or more processors are configured to execute the processing algorithms with the DAS sensor data as input, wherein each processing algorithm is configured to provide an output state for each section of the optical fibre cable adjacent to the infrastructure of interest.

The invention relates to the technical field of high-speed rail platform safety monitoring, and discloses a high-speed rail platform area intrusion detection and early warning alarm system, which comprises an acoustic and vibration sensor network deployed in a platform area and used for collecting environment signals in real time, the edge calculation unit extracts signal features and compares the signal features with a dynamically maintained environmental rhythm feature baseline to generate a detuning event mark, and the detuning mode analysis device identifies an abnormal mode through space-time correlation and triggers an alarm. According to the method, early perception of subtle anomalies is realized by constructing a multi-modal environment rhythm baseline, active perturbation injection and differential response analysis technologies are combined, the recognition capability of a silent target is remarkably improved, meanwhile, the monitoring continuity under an extreme working condition is ensured by using an elastic baseline adaptive mechanism, and the detection accuracy is improved. And a closed-loop security and protection system from passive sensing to active discrimination is formed.

Disclosed embodiments provide techniques for automated passive acoustic monitoring with machine learning. An acoustic sensor is accessed. The acoustic sensor includes an embedded acoustic controller which hosts a machine learning model. The acoustic sensor is coupled to one or more hydrophones. The acoustic sensor is deployed in a body of water and is submerged. The acoustic sensor can enter a sleep mode. The hydrophones receive an underwater audio signal. The audio signal can be associated with an acoustic pressure. The acoustic sensor can be woken from sleep when the acoustic pressure is above a pressure threshold. The machine learning model classifies a predicted source of the underwater audio signal. The classifying can be based on filtering the underwater audio signal for a first frequency band associated with a source of interest. The predicted source is reported to a user using a communications device.

The invention belongs to the technical field of signal processing, and more specifically relates to an intrusion monitoring identification and event positioning device and method based on a DAS system. According to the invention, mode identification and accurate positioning are carried out on various vibration sources around by using sensing optical cables laid in a large range based on an optical fiber distributed sound wave vibration sensing technology. According to the method, respective advantages of a direct detection method and a coherent detection method are exerted, the vibration position can be quickly demodulated by using the direct detection method, the dynamic process of vibration change can be obtained by using a digital coherent method, and then vibration event identification is realized. The method has the advantages of being wide in monitoring area range, high in recognition accuracy, high in real-time performance, high in stability and the like.

The invention discloses an automatic processing device and method for PCB lamination, and the method comprises the steps: depositing an erodable film on a lamination material layer and arranging a cavity concentric with a through hole array before the lamination of a PCB, and collecting acoustic resonance frequency data to obtain a reference matrix; dynamic dot frequency tracking processing is carried out on the multi-point acoustic time sequence signals in the pressing heating stage, and a through hole instantaneous acoustic track library is obtained; performing coupling judgment on time-temperature-pressure ternary working condition data according to the trajectory library to obtain a blockage risk matrix; carrying out time delay and gradient adjustment on a pressing temperature and pressure curve based on the risk matrix; and carrying out three-dimensional inversion processing on the whole board broadband acoustic spectrum collected before cooling, calculating through hole filling rate distribution and judging the quality of the board. According to the scheme, the resin filling state of the micro through hole can be monitored in real time in the PCB pressing process, an acoustic detection channel is constructed through the erodable film and the cavity structure, early warning and active intervention of the blocking risk are achieved, and the pressing quality is ensured.

The subject matter of the invention is a system for earthquake predictions and forecasts. The system comprises a data collection module, where the data collection module contains at least one data channel. The system comprises further an integrated AI and forecast module, where the integrated AI and forecast module contains at least one autoencoder and a predictor. The second subject matter of the invention is a method for earthquake predictions and forecasts, which is conducted in the system according to the invention.

The invention belongs to the technical field of side slope micro-seismic signal analysis and identification, and relates to an automatic side slope rolling stone micro-seismic signal detection method, which comprises the following steps: acquiring signals by using a node seismograph, and establishing a database; acquiring a time-frequency diagram by adopting continuous wavelet transform; building a convolutional neural network introducing a double-attention mechanism, and obtaining a network weight parameter with a loss value small enough by training a loss value reduction function; carrying out abnormal signal pickup on the data detected in real time by using a de-noised MER-AIC method; and taking a pickup signal as the input of the convolutional neural network after continuous wavelet transform, and giving an identification result by a trained model to realize automatic detection. According to the method, abnormal signals can be fully automatically and accurately picked up and side slope rolling stone micro-seismic signals can be detected in data which are collected in real time in a rock side slope and mixed with various kinds of noise, intelligence and automation of real-time detection work of rolling stone events are achieved, dependence on manpower is reduced, and the recognition efficiency is improved.

The invention provides a sector-shaped slope crack monitoring system and a monitoring method thereof, and relates to the technical field of crack monitoring, and the sector-shaped slope crack monitoring system comprises an ultrasonic detector which is used for generating and receiving a required sound wave frequency; the sensing network is used for collecting crack data in the sector area; the data acquisition unit is used for acquiring data of the sensing network and sound wave frequency data of the ultrasonic detector and preprocessing the data; the communication module is used for transmitting the data acquired by the data acquisition unit to the central processing platform; and the central processing platform is used for analyzing and processing the collected data, generating a report and sending out an alarm notification according to a preset threshold value, can realize omnibearing coverage of slope cracks by combining underground crack monitoring and earth surface crack monitoring, and can realize comprehensive coverage of the slope cracks based on analysis of the monitoring data. Continuous innovation and perfection of related monitoring technologies and early warning systems can be promoted, and the automation and intelligence level of geological disaster monitoring and early warning is improved.

The invention discloses a multi-physical-field joint target detection method based on underwater low-frequency seismic wave field and sound field signals. The method comprises the following steps: acquiring underwater low-frequency seismic signals x1 (t) and sound field signals x2 (t) through a sensor; performing cross-correlation spectrum calculation on the seismic wave signal and the sound field signal in the fixed time window t0 to obtain a frequency spectrum Xm; removing a direct current component in the frequency spectrum Xm to obtain a direct current component-removed FFT sequence XFFT; the XFFT data of the direct-current component FFT sequence in the third step are preprocessed; the detection threshold value Xt of # imgabs0 # is calculated; comparing # imgabs1 # with Xt, and judging a suspected target line spectrum frequency point according to a difference value T of # imgabs1 # and Xt: performing time integration on the difference value T, and judging that a suspected target appears if the maximum frequency Q of the suspected line spectrum frequency point in a time window is greater than a set value R; if the suspected target appears within a plurality of continuous seconds, judging that a target signal appears; suspected targets can be eliminated and the targets can be quickly locked under complex environment interference, and a basis is provided for underwater weapon development and underwater multi-physics field target recognition.

The invention provides a lightning monitoring method and device, and the method comprises the steps: integrating an electromagnetic sensor, a thunder detection device and a camera, and monitoring the electromagnetic, acoustic and optical signals of lightning in real time. When any signal is triggered, the camera executes video backtracking: if the three signals respond, backtracking is carried out by taking the first signal as a reference; if the two responses, the video is traced back and verified; and backtracking and verifying according to a preset time length when the single sensor is triggered. The confirmed lightning video is output and saved. According to the technology, multiple monitoring sources are fused, and the accuracy and efficiency of lightning detection are remarkably improved through cooperation of sensors.

The invention relates to the technical field of vehicle safe driving, in particular to an alcohol detection and vehicle control system for safe driving of a driver, which comprises an alcohol detection system, a core control system and an application monitoring system, the alcohol detection system comprises an air pressure detection sensor, a sound recognition sensor, a passive alcohol detection sensor, an active alcohol detection sensor, an infrared body temperature sensor, a camera, an NFC module and a fingerprint recognition module; the core control system comprises an ignition switch control circuit, a 4G communication module, a positioning module, a power supply circuit, a voice module, an automobile CAN bus module and a master control core system. The application monitoring system is connected with the cloud application system through the Internet, and the collected local data and the detection result are reported to the server application monitoring system, so that the risk of alcohol in the body of the driver to safe driving can be reduced.

The invention discloses a buried PE pipeline depth detection method. The method comprises the steps that the basic trend of a pipeline is determined; a plurality of horizontal plane measuring lines are arranged according to the basic trend, each plane measuring line is provided with a plane measuring point, and a plane positioning line of the pipeline is determined according to a signal value obtained by a signal receiving device at the plane measuring point; a vertical point location is arranged according to the plane positioning line of the pipeline, a depth measuring line is downwards arranged at the vertical point location perpendicular to the ground, a depth measuring point is arranged on the depth measuring line, and the depth position of the pipeline is determined according to a signal value obtained by a signal receiving device at the depth measuring point. According to the detection method, the depth position of the buried gas PE pipeline is detected through a direct method, more test environments are met, and the test accuracy can be effectively improved; and a more accurate test result can be provided for actual engineering, so that the safety risk during pipe network transformation is effectively reduced.

The invention relates to the technical field of communication early warning, in particular to a building vibration real-time monitoring and early warning method based on a communication optical fiber, and the method comprises the steps: selecting the communication optical fiber, knocking a building at each branch point of the communication optical fiber, collecting a vibration signal generated by the knocking of each branch point, and carrying out the early warning of the building vibration. Recording the vibration time and the vibration place of each branch point, and establishing a preliminary calibration relationship between the optical fiber signals and the vibration places through time synchronization and feature comparison of the optical fiber signals and the vibration signals; correcting the initial calibration relationship between the optical fiber signal and the vibration place through delay attenuation hybrid positioning, and confirming the final calibration relationship between the optical fiber signal and the vibration place; and monitoring optical fiber signals in the building in real time, analyzing whether the optical fiber signals are abnormal optical fiber signals or not, positioning the vibration place corresponding to the abnormal optical fiber signals based on the final calibration relationship between the optical fiber signals and the vibration place, and performing early warning. According to the invention, possible illegal decoration behaviors can be identified in time, so that potential safety hazards of buildings can be effectively prevented.

Described herein in is an acoustic system and method for tracking and identifying trends or behavioural characteristics or properties of multiple sound producing targets or objects across a geographical area. The method and system may be used independently of or as a supplement to bespoke tracking technology associated with such objects or targets. The acoustic method includes repeatedly transmitting, at multiple instants, interrogating optical signals into each of one or more optical fibres distributed across the geographical area and forming at least part of an installed fibre- optic communications network. Next the method includes receiving, during an observation period following each of the multiple instants, returning optical signals scattered in a distributed manner over distance along the one or more of optical fibres, the scattering influenced by acoustic disturbances caused by the multiple objects within the observation period. The acoustic data is then demodulated from the optical signals and the acoustic data is processed to identify tracks made by the objects over a period of time across the area. Further, one or more characteristics of the tracks or tracked features, including start and end points, are analysed to identify relationship links between the dynamic objects and their locations or between the dynamic objects and other static or dynamic objects or fixtures or events in the geographic area for real time, historic or predictive analysis.

The invention discloses a fusion feature vector construction mode determination and construction method for sealing electronic equipment redundancy positioning and a redundancy positioning method, and belongs to the technical field of sealing electronic equipment redundancy detection. The objective of the invention is to solve the problem that the classification effect of sealing electronic equipment redundancy positioning is limited by the obtained feature vector due to the fact that the existing signal for sealing electronic equipment redundancy positioning is constructed by taking a sound sensor as a unit. According to the method, channels and features are respectively used as basic construction units, and are arranged according to a channel and feature numbering sequence or a random disordered row; randomly disrupting features and channel numbers of each basic construction unit, or randomly disrupting features and channel numbers of each basic construction unit and arranging features of feature vectors according to an incompletely identical rule to obtain a fusion feature vector; screening based on the positioning identification accuracy to obtain a fusion feature vector construction mode; and feature vectors are constructed based on a feature vector construction method and are used for redundant object positioning.

The invention relates to a detection system (1) comprising N detection devices (10) distributed throughout an area to be monitored (Z), each device comprising an acoustic sensor and a processing unit; - a second operating mode in which the sounds captured by the detection device are processed, the second operating mode corresponding to a second level of power consumption higher than the first level; each detection device (10) operates by default in a first mode that corresponds to a first very low level of power consumption of the device in which the first analysis on the electrical signal delivered by the acoustic sensor is performed by the processing block, and in which the electrical signal is not permitted to be recorded; and, as soon as the first analysis detects a predefined acoustic phenomenon, the detection device (10) alerts the N-1 other detection devices (10) of the system; upon receiving the alert, each of the N-1 other detection devices (10) then switches to a second mode that triggers: - a step of transmitting, to a recording unit, the electrical signal delivered by its acoustic sensor after receiving the alert; - a step of recording, by the recording unit, the transmitted electrical signal; and - a second analysis step of analysing the recorded electrical signal in order to detect acoustic phenomena, the second analysis step implementing algorithmic processing that corresponds to a second level of power consumption higher than the first level.

Elbow erosion monitoring is of great significance to the safety of pipeline systems and maintenance personnel. A percussion method is used to monitor pipe erosion. Under different erosion degrees, the mass reduction of the elbow is measured by high-precision electronic scale and the residual thickness of the elbow is detected by telescoping gauge. Machine learning algorithm, the K- Nearest Neighbor and recurrent network method are employed to identify the different wall thickness level and erosion mass level.

The invention relates to the field of vibration monitoring, in particular to an intelligent vibration monitoring and adaptive optimization device based on a neural network, which is provided with a vibration monitoring unit, a data storage unit, an analysis and determination unit, a vibration verification unit and an optimization unit, the data storage unit is used for recording a timestamp of each wake-up moment and storing the timestamp in a data list, and the analysis and determination unit is used for determining a submission state of the data, performing feature extraction on the original vibration data to calculate a vibration trigger characterization coefficient, identifying a vibration trigger source and sending the vibration trigger characterization coefficient to the data storage unit. The vibration verification unit is used for calculating vibration comparison similarity so as to determine the recognition accuracy of the analysis and determination unit, and the optimization unit is used for continuously collecting new vibration samples and integrating the vibration samples into an existing model so as to improve the accuracy of the model and the sensitivity of vibration monitoring.

This disclosure describes systems, methods and workflows; computer-implemented methods; computer software products; and ML models for real-time monitoring of the infrastructures in modern cities, including bridges, road tunnels, airports, buildings, and wind turbine towers, utilizing seismic data. The monitoring is not restricted solely to the recorded seismic data. This disclosure also emphasizes the importance of monitoring various critical infrastructures using seismic sensors, including security sites and manufacturing facilities, to enhance safety and security, detect infrastructure health, and prevent unauthorized intrusions. Additionally, seismic sensors can be used to monitor indoor human activity. Bridge monitoring involves continuous assessments to ensure structural integrity and longevity, while road tunnel monitoring focuses on optimizing traffic conditions and monitoring structural images. Monitoring at airports improves runway safety and ensures optimal performance of the aviation infrastructure, minimizing potential risks and enhancing overall safety and efficiency in air travel. Deploying seismic sensors to monitor a building's infrastructure enables the detection and location of potential risks to the building structures. Monitoring wind turbine towers is crucial for optimizing green energy production and ensuring the structural health of the turbines. Security and manufacturing sites are monitored to ensure the safety and security of the facilities and prevent unauthorized intrusions. By monitoring and analyzing seismic data of human activities in rooms, one can identify different types of activities and detect instances of walking and falling. By employing seismic sensors and real-time processing of the seismic data, these monitoring systems collectively contribute to the safety, security, resilience and reliability of vital infrastructures in various domains.

The invention belongs to the technical field of aerial sonic boom target positioning, and discloses a system for positioning an aerial sonic boom target by using an earthquake monitoring station net, the system comprises stations for collecting signals, the stations are arranged in a circle with the theoretical drop point of the aerial sonic boom target as the circle center and the radius of 10km, and the stations are used for collecting the signals. A monitoring station time service uses an NTP server to carry out unified time service on stations, the stations transmit signals to a monitoring processing center in real time, the monitoring processing center transmits the collected real-time signals to a flow positioning system to carry out spectrum analysis, positioning is carried out by using a simulated annealing method after analysis, and thus the falling point position of an aerial sonic boom target is judged. According to the system, the falling point position of the air sonic boom target can be accurately judged, and the deviation precision is smaller than 50 m; therefore, the air sonic boom target drop point can be quickly judged, a decision basis is provided for quickly studying and judging drop area safety, and the method is suitable for air sonic boom target drop point judgment.

A system and a method for monitoring and detecting an illegal sump pump in a sewer system is used to accurately detect and locate sump pumps that are illegally connected to the sewer system. Actual audio profiles are collected and timestamped with audio-recording devices. The actual audio profiles from the audio-recording devices are relayed to the remote server. The remote server compares each actual audio profile to a baseline audio profile to identify at least one matching audio profile. If the matching audio profile is identified amongst the actual audio profiles, the remote server geolocates a potential location for an illegal sump pump based on the sewer location of the corresponding audio-recording device for the matching audio profile. The remote server compiles the potential location of an illegal sump pump into a summarization report. The sewer system is continuously monitored by executing several iterations of the overall process.

A nondestructive evaluation system and method are provided for detecting the material type and leakage of an underground service line. An impactor applies a controlled impact to an instrumented rod in contact or proximity with the service line, inducing stress waves that propagate into the service line and surrounding soil. Sensors on the rod and / or on the ground surface detect the resulting waveforms. A processing unit analyzes time and frequency domain characteristics such as wave speed, attenuation, and vibration response to determine service line material and identify anomalies associated with leakage. The system enables accurate, real-time diagnostics of buried pipelines without excavation or fluid interruption.

The present invention discloses a drilling recyclable microseismic sensor installation method, comprising the following steps: S1: making a sensor installation base and a hole protection steel pipe; S2: drilling a hole in the rock mass of the monitoring area; S3: assembling the microseismic sensor, the installation base, and the hole protection steel pipe and placing them in the borehole; S4: sealing the borehole and grouting; S5: connecting a collector and performing microseismic monitoring; S6: recovering the microseismic sensor. The present invention aims at the problems of high ground stress, soft and broken rock mass, and large mining impact in underground engineering, realizes the protection, recovery and recycling of microseismic sensors, and improves the coupling effect of drilling installation of microseismic sensors and the quality of signal acquisition.

This measurement device (1) comprises an imaging control unit (21) for causing an imaging unit (14) to image a prescribed object of interest in the water and a vibration measurement unit (23) for measuring sound waves in the water by measuring the vibration frequency of the object of interest on the basis of images that were made to be captured by the imaging control unit (21).

Generator (1) of acoustic waves for submarine environments, wherein a hollow body (10) is developed along an axis (AX) and delimited by a first closed end (100) and by a second end (102) provided with an acoustic diffuser member (1020); the hollow body (10) presenting a first cylindrical portion (104) delimited by the first end (100) and housing a first piston (20) and a second cylindrical portion (106) delimited by the second end (102) and housing a second piston (22) in a freely axially sliding manner; the second piston (22) being mechanically free from the first piston (20) and presenting a face (220) facing the said diffuser member (1020); an impulsive actuating means (30) being associated with the first piston (20) to move it towards the second piston (22); adjusting means (40) of a longitudinal motion of the second piston (22) being arranged between the first piston (20) and second piston (22).

The invention belongs to the field of underwater information detection, and particularly relates to a bottom-supported underwater multi-physics-field information detection device, which comprises a mounting rack, an information detection module, a buoyancy module and an information integration module, and is characterized in that the mounting rack comprises an open top-layer three-dimensional frame, a middle-layer three-dimensional frame and a bottom-layer three-dimensional frame, and the top-layer three-dimensional frame is provided with a sound releaser; an anchor block base is movably arranged at the bottom of the bottom-layer three-dimensional frame and is connected with an execution end of the sound releaser, an information detection module of the sound releaser is located on the top-layer three-dimensional frame, and the top-layer three-dimensional frame is of a fully-open and unshielded structure and has higher perceptibility to the outside, so that underwater information can be monitored more easily in an omnibearing and more sensitive manner; however, most of existing similar devices are of semi-closed or closed structures, signal sources received by information detection modules are unidirectional, and if information needs to be monitored in all directions, the information detection modules need to be arranged in multiple directions.

The present application relates to a detection method and system for marine metal detection, belonging to the field of metal detection technology. The method includes obtaining a required detection area and a device docking position; performing metal detection at the device docking position to obtain local detection conditions; obtaining the current ocean current direction after determining the local detection conditions, determining a single detection area according to the device docking position and the detection radius, and determining a waiting detection area according to the required detection area and the single detection area; determining a downstream travel path according to the current ocean current direction and the device docking position, and generating detection points on the downstream travel path according to the waiting detection area; controlling the unmanned ship to move along the detection points and continuously updating the device docking position until a detection completion signal is output when the waiting detection area is empty. The present application has the effect of facilitating the intelligent detection operation of the unmanned ship for marine metals.

A method, apparatus, and processor-readable medium for detecting a physical change in an environment are provided, the method comprising: acquiring a first set of sound frames representing sound waves reflected in the environment; applying frequency filtering to extract from the first set of sound frames a corresponding first set of filtered frames limited to a predefined frequency band, the predefined frequency band corresponding to a frequency band of a predefined cyclic acoustic detection signal; calculating an instantaneous amplitude of the filtered frame in the first set of filtered frames; evaluating whether the first set of sound frames is indicative of a physical change in the environment based on the calculated instantaneous amplitude and a predefined reference parameter corresponding to a reference state of the environment; when the evaluation indicates the physical change, a predefined operation is caused to be performed.

The present disclosure relates to systems and techniques for identifying collisions, such as relatively low-energy impact collisions involving autonomous vehicles. Sensor data from a first sensor modality in a first array can be used to determine a first estimated collision location, and second sensor data from a second sensor modality in a second array can be used to determine a second estimated collision location. A low-energy collision event can be constituted when the first estimated collision location corresponds to the second estimated collision location.

Various examples are directed to apparatus and methods for acoustic pest detection, to provide enhanced pest detection and enhanced battery life for a power supply of a pest detection device. The pest detection device includes an acoustic or vibration sensor and a controller connected to the acoustic or vibration sensor. The controller is configured to detect, identify, or detect and identify one or more pests based at least in part on comparing one or more signals received from the acoustic or vibration sensor with a predetermined sound or vibration profile of the one or more pests.