240 results about "Distributed acoustic sensing" patented technology

The invention discloses a planning method and system of a power distribution communication access network, particularly relates to the technical field of power distribution communication network dynamic topology management, and is used for solving the problems of fault misjudgment and inaccurate positioning caused by topology update delay in the prior art. A dynamic topological data set is generated by dynamically monitoring the operation state of each optical fiber node and a link transmission signal, a real-time topological view with a dynamic version identifier is generated based on a preset topological planning strategy, and a network change area is quickly locked by combining a topological difference identification technology of an alarm moment and a historical view. Candidate fault links are screened through the conflict relation between link switching frequency and service priority, and the vibration characteristics of the construction machinery are further analyzed by using distributed acoustic sensing data and external force damage interference is eliminated; and finally, optical cable breakage faults are confirmed through optical power interruption verification, heartbeat signal loss detection and redundant optical fiber phase mirror symmetry verification. And multi-dimensional accurate positioning of the topological data fault root cause is realized.

In some embodiments, a system for producing fluid from a well can include an electrical submersible pump (ESP) disposed in a wellbore of the well and configured to pump the fluid. The system may further include a distributed acoustic sensing (DAS) system, for example having an interrogator unit and a fiber optic cable extending downhole in the wellbore. An end of the fiber optic cable can be disposed downhole relative to the ESP. In embodiments, the system may further include a controller configured to receive data from the DAS system, process the data to detect a slug, determine a parameter of the detected slug, and alter operation of the ESP in response to determining that the parameter exceeds a threshold.

A fiber optic distributed sensing system and method. The fiber optic distributed sensing system includes: an optical fiber extending through an underwater gas field; an interrogator connected to the optical fiber so that light transmitted through the optical fiber is capable of being sensed by the interrogator; and a computer system configured to obtain sensor data captured by the interrogator and determine an amount or a characteristic of gas within the underwater gas field based on the sensor data. The method includes: capturing sensor data using a fiber optic distributed sensor extending through an acoustic field; performing a wavelet transform on the sensor data in order to obtain spatiotemporal data; and matching the spatiotemporal data to an event template of a predetermined set of event templates in order to identify a spatiotemporal event.

The invention relates to the technical field of audio processing, and discloses an intelligent control system and method for a wireless microphone, and the method comprises the steps: collecting multi-point acoustic data through a distributed microphone network, and constructing a spatial acoustic topology model; based on a topological analysis result, constructing an adaptive notch filter bank to realize howling suppression; environment changes are monitored in real time through a distributed acoustic sensor network, and suppression parameters are dynamically optimized; integrating a lightweight convolutional neural network on microphone equipment to identify acoustic events; low-delay acoustic event processing and howling prevention are realized by adopting a layered edge computing architecture; according to the invention, the technical problems of unstable howling suppression, weak environmental adaptability and lack of spatial perception in a complex environment are effectively solved.

Disclosed are systems and methods that employ distributed fiber optic sensing (DFOS) / distributed acoustic sensing (DAS) to monitor and provide real-time estimation of ice thickness on fiber optic communications facilities, and which integrate DSA data with a hybrid processing technique that combines frequency domain decomposition (FDD) and stochastic subspace identification (SSI). Aspects of our innovative systems and methods include: i) Hybrid Signal Processing Techniques; ii) Real-time, Continuous Ice Monitoring; iii) Enhanced Noise Robustness and Non-linear Dynamics Handling; and iv) Adaptability and Scalability.

Methods and systems for managing operation of a well are disclosed. The method may include obtaining distributed acoustic sensing (DAS) data based on a measurement made using a DAS sensing element positioned in the well. A qualification process for the DAS data may be performed to identify whether any portion of the DAS sensing element was acoustically coupled to a structure of the well during the measurement in a manner that introduced at least one artifact to the DAS data. If at least one portion of the DAS sensing element was coupled in such a manner, a remediation process may be performed to manage impacts of the at least one artifact on downstream use of the DAS data.

Disclosed are systems and methods employing distributed fiber optic sensing (DFOS) / distributed acoustic sensing (DAS) that continuously monitor the buried / exposed status of undersea power cables for offshore wind farms. Our DAS systems and methods continuously monitor dynamic conditions characterizing undersea power cables and advantageously detect dynamic strain of an optical fiber that may be part of a composite cable with the power cable. By measuring and monitoring these dynamic conditions, a change in status from buried to exposed is determined and service personnel deployed before damage occurs to the power cable.

The invention relates to the technical field of industrial safety monitoring, in particular to a fallen object accurate identification FOD calculation method based on a fixed tower and application of the fallen object accurate identification FOD calculation method. Comprising the following steps: synchronously acquiring multi-source heterogeneous sensing data; carrying out multi-modal data preprocessing and feature extraction; performing cross-modal feature fusion and representation construction; modeling and reasoning a time-space diagram neural network; and performing multi-dimensional threat quantification and decision output. According to the design of the invention, multi-modal sensor groups are deployed at the tower bottom, the tower middle and the tower top of a fixed tower in a layered manner, and a high-definition multispectral camera, a high-density laser radar and a distributed acoustic sensor are integrated, so that 7 * 24-hour full-automatic data acquisition is realized; according to the design, the time and environment limitation of manual inspection is eliminated, and the complex weather detection capability is improved by 80%; meanwhile, the sensor synchronously triggers the mechanism and the grading detection process, the single-frame data processing delay is less than or equal to 50ms, and the real-time monitoring requirement of an aircraft take-off and landing high-frequency scene is met.

Distributed fiber optic sensing (DFOS) / distributed acoustic sensing (DAS) that illustrate inventive techniques—applicable to all embedded systems—that deliver high-bandwidth traffic from a DFOS system to a cloud or other processing resources in real-time, employ firmware that operates at a register-transfer level and writes data repeatedly into the embedded host memory directly—without software intervention after initial configuration. This technique advantageously enables the use of the relatively large host memory to compensate for any software jitter. Preferably configured, the firmware employs only a small buffer to compensate for a transaction and host-memory arbitration latency. A second dedicated thread sends out data from the user space buffer to a cloud, or a connected server. Remote procedures that are executed on a remote system (a computer, network of computers, or cloud), receive data transmitted from the embedded system, and perform further processing as necessary.

The invention discloses a city toughness real-time determination method and system based on distributed sound wave sensing, and the method comprises the steps: carrying out the optical cable distribution of a target region, carrying out the connection with a data channel, and carrying out the channel number mapping; acquiring a strain rate signal of each channel of the optical cable; caching the acquired DAS data; detecting, screening and judging the signal quality of each channel; if the SNR value and the DR value of one channel are lower than 80% of the whole channel, the coupling is abnormal; performing multi-domain feature extraction on the data; rendering the evolution trend of the activity intensity, the disturbance duration and the regional synchronization index along with time and space; constructing a multi-index fusion matrix; different indexes are mapped to color depth and saturation, an abnormal region track is identified, and high-intensity cooperative event prompting and recording are triggered; and obtaining a regional risk evolution situation. The system comprises a sensing optical fiber unit, a DAS demodulation unit, a data storage unit, a data processing and analysis unit, a toughness collaborative analysis unit and a toughness evolution visualization unit. The method is low in cost, wide in space coverage, high in timeliness and friendly in privacy.

A hydraulic fracturing system and method uses a model trained with external pressure gauge data and LFDAS sensor data to identify pressure communication events based on LFDAS sensor data. One or more monitoring wells are established in proximity to a well undergoing well stimulation, each monitoring well including one or more LFDAS sensors. LFDAS sensor data is received from the LFDAS sensors of the one or more monitoring wells, the received LFDAS sensor data including data received after start of a well stimulation operation. Occurrences of pressure communication events at each monitoring well may then be identified based on the model and on the received LFDAS sensor data.

The present invention relates to the field of audio processing technology, and discloses a wireless microphone intelligent control system and method, wherein a wireless microphone intelligent control method includes: collecting multi-point acoustic data through a distributed microphone network to construct a spatial acoustic topology model; constructing an adaptive notch filter group to achieve howling suppression based on the topology analysis results; monitoring environmental changes in real time through a distributed acoustic sensor network to dynamically optimize suppression parameters; integrating a lightweight convolutional neural network on the microphone device to identify acoustic events; and adopting a layered edge computing architecture to achieve low-latency acoustic event processing and howling prevention. The present invention effectively solves the technical problems of unstable howling suppression, weak environmental adaptability and lack of spatial perception in complex environments.

The invention discloses a method and system for monitoring the abnormal state of a belt conveyor based on deep learning, and the method comprises the steps: laying sensing optical fibers along the line of a rack of the belt conveyor, and collecting the operation sound signals of a plurality of spatial point locations along the line through the sensing optical fibers by a distributed acoustic sensing DAS device; the method comprises the following steps: in a normal operation state of a belt conveyor, collecting normal sound signals of each point location, preprocessing the signals, and constructing a normal sample data set; for a normal sample of each spatial point location, training a corresponding unsupervised learning model; in real-time monitoring, sound signals collected at each point location are input into a corresponding unsupervised learning model, a reconstruction error is calculated, and the reconstruction error is compared with a dynamic threshold value based on normal sample statistical characteristics to obtain an abnormal result; and performing comprehensive judgment on an abnormal result based on statistical logic of the time window, and triggering an alarm if an abnormal proportion in the window exceeds a set value. High-accuracy abnormity early warning is realized, and system deployment is convenient.

The present invention relates to systems and methods for monitoring microseismic activity in a geothermal well system using fiber optic sensing technology. The system includes fiber optic cables installed in multiple wells of the geothermal well system. The fiber optic cables enable simultaneous collection of distributed acoustic sensing (DAS) data, strain measurements, and temperature data. By detecting and localizing microseismic events during stimulation and operation of the geothermal well system, seismic activity is maintained within safety thresholds, providing for safe and effective extraction from the geothermal well system.

The invention relates to the technical field of building construction, and discloses a BIM (Building Information Modeling) deepening-based steel reinforced concrete composite column ultra-large-span corridor construction method, which comprises the following steps of: constructing a multi-modal sensing building information model, and integrating a fiber bragg grating and a distributed acoustic sensor on a steel member to form an intelligent member; establishing a data link between the intelligent component and the sensing BIM center and calibrating the data link; dynamic optimization control based on strain feedback is carried out on collaborative hoisting, and internal quality monitoring based on multi-modal sensing fusion is carried out on concrete pouring; after construction is completed, digital twin baseline calibration is carried out, and a data packet containing a structure initial state vector is generated. According to the method, the multi-modal sensing system and the BIM are deeply fused, and the whole construction process is penetrated, so that real-time, closed-loop and quantitative control of key procedures is realized, the safety, accuracy and quality of super-large complex structure construction are remarkably improved, and a high-fidelity digital twinning baseline is established for structural health monitoring of the whole life cycle of a building.

The invention discloses a dry hot rock reservoir horizontal well fracturing fiber breakage early warning method based on DAS monitoring, which comprises the following steps: firstly, collecting a vibration signal in a shaft through a DAS (Distributed Acoustic Wave Sensing) system, and carrying out wavelet threshold denoising, data segmentation and normalization processing to obtain preprocessed signal data; secondly, performing time-frequency analysis on the signal by adopting a short-time Fourier transform analysis method so as to identify energy distribution of different frequency bands and visualize a high-energy region, thereby identifying an abnormal broadband; then, phase wrapping detection is carried out, whether the signals exceed a dynamic range or not is verified, and the strain rate and histogram features of the phase signals are calculated; and finally, the standard deviation of the strain rate is evaluated through normal distribution modeling and maximum likelihood estimation, and once the standard deviation exceeds a set threshold value, fiber breakage risk early warning information is sent out. According to the method, the signal processing technology and the statistical analysis technology are effectively integrated, the safety of fracturing operation is improved, and meanwhile reliable technical support is provided for efficient development of the hot dry rock reservoir.

Methods for geothermal well planning and development are provided. This includes: installing fiber optic cables that extend within a plurality of shallow wells, wherein the fiber optic cables support both DTS measurements and DAS measurements; connecting DTS interrogators to the fiber optic cables and configuring the DTS interrogators to measure temperature profiles in the plurality of shallow wells over time; determining planned location of one or more geothermal wells that access a geothermal reservoir from the measured temperature profiles; selecting at least one shallow well to be used for DAS measurements; at each selected shallow well, disconnecting the DTS interrogator from the fiber optic cable at the shallow well and connecting a DAS interrogator to the fiber optic cable at the shallow well; and configuring the DAS interrogator at each selected shallow well to measure an acoustic profile in the selected shallow well over time.

The invention relates to a distributed acoustic sensing system environment noise monitoring and event recognition method and system and a medium, and the method comprises the following steps: obtaining real-time environment sound signals f (t) at different distances from a distributed acoustic sensing system; obtaining a frequency domain signal # imgabs0 # in the sound signal through Fourier transform, wherein the frequency domain signal # imgabs0 # is called S for short; based on the frequency domain signal, extracting a characteristic value corresponding to each event by adopting a double-domain self-adaptive signal peak value extraction method based on dynamic morphological coupling; classifying sound signal features through convolutional neural network machine learning, and judging corresponding events; according to the method and the device, diversified noise types can be effectively processed, and real-time monitoring of key infrastructures is realized.

This application relates to a Rayleigh scattering noise suppression method and system for a distributed acoustic wave detection system. The method includes: performing optical phase sinusoidal modulation on a high-coherence continuous laser output from a narrow-linewidth laser in an FBG-based distributed acoustic detection system according to a set modulation scheme using an optical phase modulator; the set modulation scheme is Csin(2πf m t), C is the phase modulation amplitude, f m The phase modulation frequency and satisfying f m τ = k, where τ is the time difference between two adjacent reflected light pulses being detected, t is time, and k is an integer. A highly coherent continuous laser beam with sinusoidal phase modulation is passed through an unbalanced interferometer to generate dual light pulses. These dual light pulses are then injected into an FBG array for distributed acoustic wave detection. This achieves low-noise distributed acoustic wave detection and effectively improves the detection performance of FBG-based distributed acoustic wave detection.

The application relates to an environment noise monitoring and event identification method, system and medium of a distributed acoustic sensing system, which comprises the following steps: obtaining real-time environment sound signals f(t) at different distances from the distributed acoustic sensing system; obtaining a frequency domain signal S in the sound signal through Fourier transform; extracting characteristic values corresponding to each event based on the frequency domain signal by adopting a dual-domain adaptive signal peak extraction method based on dynamic morphological coupling; classifying the sound signal characteristics through a convolutional neural network machine learning and determining the corresponding event; and reporting the noise determination result. The application can effectively process diversified noise types and realize real-time monitoring of key infrastructures.

Methods and apparatus for estimating a position of a boundary of a queue of traffic are disclosed, the queue extending along a roadway. Distributed acoustic sensing is used to generate, as a function of time and of position along the roadway, a signal representing acoustic vibration at a sensing optical fibre that extends along the roadway. A queue signature is detected in the signal of either the slowing down of a plurality of vehicles as they approach the boundary of the queue, or speeding up of a plurality of vehicles as they advance from the departed boundary of the queue. A position of the boundary of the queue is then estimated from the detected queue signature. Methods and apparatus are also disclosed for controlling one or more road traffic signals by using distributed acoustic sensing to detect acoustic vibration at one or more sensing optical fibers disposed along a roadway, as a function of time and of position along a roadway, and controlling the one or more road traffic signals responsive to the detected acoustic vibration.

The invention discloses a distributed acoustic sensing earthquake monitoring data stream processing method and system, and belongs to the technical field of earthquake monitoring and data processing. The method comprises the following steps: after preprocessing original seismic monitoring data, slicing the original seismic monitoring data by adopting a sliding processing time window to obtain data fragments suitable for real-time detection; designing a self-adaptive short-time average / long-time average detection algorithm, detecting data segments, and dynamically adjusting self-adaptive parameters in the algorithm according to data characteristics; and finally, multi-channel fusion detection is performed on the initial candidate list of the seismic events, so that a final detection list of the seismic events is generated. The method is based on a distributed streaming data processing architecture, combines the innovation advantages of a self-adaptive earthquake detection algorithm, can improve the earthquake detection precision, guarantees the real-time performance of a detection result, and can provide efficient and reliable technical support for a large-scale earthquake monitoring task.

A radio-controlled, two-way acoustic modem for operating with a distributed fiber optic sensing (DFOS) system including circuitry that receives radio signals including configuration information, configures the modem to operate according to the configuration information, and generate acoustic signals that are detected by the DFOS system. The acoustic modem includes one or more sensors that detect environmental information that is encoded in the acoustic signals for further reception by the DFOS system. The received configuration information may change the operating times, sensors or other operating aspects of the modem as desired an such information may be transmitted from a fixed location or a mobile vehicle.

A computer-implemented method is disclosed for monitoring traffic using a distributed acoustic sensing (DAS) model trained with video input. The method includes receiving DAS training data representing strain or strain rate along a fiber optic cable and video training data captured from a segment of road covered by the same cable. A machine learning-based object detection model (e.g., YOLOv11) is applied to the video data to generate vehicle attribute data labels, which are aligned with the DAS training data. A neural network model (e.g., UNet) is trained using the aligned data to associate DAS signal patterns with vehicle classification outcomes. The trained DAS model is stored in memory and subsequently applied to operational DAS data to detect and classify vehicles in real time, producing model output such as synthetic strain maps or detection maps. Once trained, the model functions without requiring operational video data.

The application discloses a kind of rock mechanics test in the collection device of acoustic emission signal, including computer, measurement and control and signal processing equipment, distributed acoustic wave sensing equipment and collection probe: the collection probe is composed of single-mode optical fiber and probe skeleton, single-mode optical fiber is fixed around probe skeleton, when testing, collection probe is fixed on the surface of rock sample for testing;The measurement and control and signal processing equipment include: radio frequency amplifier, digital-to-analog conversion module, analog-to-digital conversion module, filter amplifier, field programmable logic gate array and CPU-GPU data processing module;The distributed acoustic sensing equipment includes narrow linewidth laser, fiber coupler, acoustooptic modulator, erbium-doped fiber amplifier, circulator, polarization diversity receiver, first balanced photodetector and second balanced photodetector;Collection signal band is wide, can be conveniently installed on any rock sample.Collecting main frequency is lower, collection probe is connected closely with rock sample, coupling is good, without additional smearing coupling agent.

A method includes: outputting optical signals to a first optical fiber via a first interrogator, the first interrogator located at a topside / onshore location, the first interrogator configured to collect distributed acoustic sensor (DAS) and / or distributed temperature sensor (DTS) measurements; outputting optical signals to a second optical fiber via a second interrogator, the second interrogator located subsea, the second interrogator configured to collect DAS and / or DTS measurements; receiving optical signals from the second optical fiber via the first interrogator; receiving optical signals from the first optical fiber via the second interrogator; providing acoustic, temperature, and / or vibration sensing along a portion of the second optical fiber via the first interrogator based on the optical signals received from the second optical fiber; and providing acoustic, temperature, and / or vibration sensing along a portion of the first optical fiber via the second interrogator based on the optical signals received from the first optical fiber.

Techniques for extending distributed acoustic sensing (DAS) range in undersea optical cables are provided. For example, DAS range can be extended by transmitting and amplifying a DAS signal along multiple spans of a first optical fiber, routing or bypassing the DAS signal from the first optical fiber to a second optical fiber different from the first fiber via a high-loss loopback architecture, and returning and amplifying the DAS signal along the same multiple spans back to a DAS device. The DAS device may then receive and process the DAS signal to detect any changes in the DAS environment. The loopback configuration may be based on different types of loopback architecture.

A system can include a distributed acoustic sensing (DAS) system and a computing device coupled with the DAS system. The DAS system can include a pulse generator and a sensing fiber that can be positioned in a wellbore. The system can generate a light pulse to be transmitted into the sensing fiber to make one or more measurements relating to a wellbore operation involving the wellbore. The system can receive an initial pulse that includes a reflection of the light pulse prior to the light pulse entering the sensing fiber. The system can apply a cross-correlation filter to one or more subsequently received pulse reflections originating from the sensing fiber. The cross-correlation filter can include the initial pulse reflection or synthetic initial pulse. The system can generate, based on applying the cross-correlation filter, an output signal that can be used to control the wellbore operation.

The invention discloses a distributed acoustic sensing road cavity detection method based on an active excitation source. The method is based on distributed acoustic sensing (DAS), and comprises the following steps of: firstly, acquiring a DAS signal sampling data sequence to be processed; preprocessing the data of each DAS channel; calculating a short-time zero-crossing rate to remove channels with abnormal data records; then, signal space-time positioning is carried out through sliding window detection, signal envelopes in a signal area are extracted, and space-time distribution information of signals is obtained; and finally, extracting spatial correlation features and energy distribution features of the signals, and realizing automatic detection of the road cavity based on feature judgment. According to the method, all-weather sensing and high-resolution precision characteristics of the DAS array are fully utilized, accurate estimation of road cavity detection is achieved with small calculation amount, large-range sensing can be achieved, and the method is suitable for real-time engineering application occasions.