CN-122019895-A - PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system

CN122019895ACN 122019895 ACN122019895 ACN 122019895ACN-122019895-A

Abstract

The invention discloses a PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system, which belongs to the technical fields of optical fiber sensing, seismic data processing, traffic monitoring and signal processing, and comprises a data access module, a user interface module, a data conversion module, a basic processing module and a high-level analysis module, wherein the data access module is used for acquiring data, the user interface module is used for performing visualization operation, the invention relates to a data conversion module, which is used for realizing the uniform format of acoustic wave sensing data with different formats, and a basic processing module and an advanced analysis module are used for jointly realizing the processing and the visualization of distributed acoustic wave sensing data.

Inventors

HONG HETING

Assignees

合肥达斯纤觉科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260127

Claims (8)

1. The PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system is characterized by comprising a data processing platform for optical fiber distributed acoustic wave sensing data, wherein the data processing platform provides a visualization function and comprises the following modules: The data access module is used for directly accessing the standby fiber cores of the existing communication optical fibers or automatically arranging special sensing optical cables along a monitoring path, converting the corresponding optical fibers into a continuous distributed auditory perception array, setting a distributed acoustic wave sensing demodulator to be directly connected with the optical fibers, and then demodulating vibration data of the optical cables to obtain DAS data in different formats; The user interface module is used for receiving an operation instruction input by a user, providing a visual interface, realizing related picture display, waveform and spectrum analysis by the visual interface, integrating Matplotlib drawing tools and supporting image derivation and custom resolution setting; the data conversion module reads the distributed acoustic wave sensing data with different formats, and converts the distributed acoustic wave sensing data with different formats into standardized DAS data bodies and structured metadata; The basic processing module is used for preprocessing data and pushing the processed data to the user interface module for content display; And the advanced analysis module is used for analyzing the data subjected to the nondestructive processing by the basic processing module, analyzing by using the interactive pickup sub-module and the vehicle tracking sub-module, and displaying the analysis result through the user interface module.
2. The PyQt-based fiber optic distributed acoustic sensor data visualization processing system of claim 1, wherein the user interface module is developed using a PyQt5 framework, and wherein the user interface module is configured using a three-region layout comprising: The data area is used for loading distributed acoustic wave sensing data in different formats and integrating an operation log and a display component of file attributes; the image display area is used for displaying a two-dimensional waterfall diagram of the distributed acoustic wave sensing data, providing a single-channel time sequence and a spectrogram and realizing interactive operation; and the signal processing control area is used for regulating and controlling the running states of the basic processing module and the advanced analysis module and processing the distributed acoustic wave sensing data.
3. The PyQt-based fiber optic distributed acoustic sensor data visualization processing system of claim 2, wherein: Loading distributed acoustic wave sensing data in a plurality of main stream file formats, wherein the data of the distributed acoustic wave sensing data is vibration data, the data format is a two-dimensional array, the two-dimensional array is listed as a channel and the behavior time, the initial access process is simplified, an operation log and a display component of file attributes can provide instant feedback and key metadata information for a user, and the key metadata information comprises the starting time, the sampling rate, the scale distance, the equipment type and the track distance and is realized by adopting a DASPy reader; The image display area has the specific contents that the transverse and longitudinal axes of the two-dimensional waterfall diagram are respectively time and channel numbers, and can display the space-time evolution characteristics of the DAS data of the optical fiber distributed acoustic wave sensing technology along the optical fiber; The basic processing module is used for realizing the space coordinate calibration, the data downsampling, the data extraction, the data conversion and the common mode noise removal of the standardized DAS data body and the structured metadata; The advanced analysis module includes phase pickup and vehicle trajectory identification, and the signal processing techniques described above are selectively applied by the user interface module.
4. The visual processing system of the optical fiber distributed acoustic wave sensing data based on PyQt of claim 1, wherein the data conversion module is used for reading data based on DASPy libraries, supporting loading of distributed acoustic wave sensing data in different formats, converting the data into NumPy arrays through NumPy modules to achieve data standardization, analyzing metadata synchronously through a dictionary structure of Python, wherein the metadata comprises data source information, acquisition parameters and file attributes, and outputting standardized DAS data volumes and structured metadata.
5. The PyQt-based optical fiber distributed acoustic sensor data visualization processing system of claim 1, wherein the basic processing module receives the standardized DAS data body and the structured metadata for preprocessing, and specifically comprises the following steps: Space coordinate calibration, namely realizing accurate mapping of channel numbers and physical space coordinates; data downsampling, namely reducing the data volume through a decimation algorithm; Data extraction, namely supporting bandpass and lowpass filtering and customizing a frequency range; data conversion, namely realizing bidirectional conversion of data between strain and strain rate; common mode noise removal, attenuating spatially correlated noise common to all channels.
6. The visual processing system of the optical fiber distributed acoustic wave sensing data based on the PyQt is characterized in that a high-level analysis module receives data processed by a basic processing module, the high-level analysis module comprises an interactive pickup sub-module and a vehicle tracking sub-module, special analysis is carried out through the two sub-modules, an analysis result is passed through a user interface module, and a vehicle track graph with the number of channels as a horizontal axis and time as a vertical axis is generated.
7. The PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system of claim 6, wherein the interaction pickup sub-module provides manual pickup and event marking functions at the time of phase arrival and supports the derivation of results of manual pickup and event marking; the vehicle tracking submodule realizes automatic extraction of vehicle track and motion parameter estimation based on Kalman filtering and smoothing algorithm, and the motion parameter estimation comprises speed and direction of the vehicle.
8. The PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system is characterized in that the specific implementation process of the Kalman filtering and smoothing algorithm in the vehicle tracking sub-module comprises the following steps of signal preprocessing, extracting 0.01-1Hz low-frequency quasi-static strain signals and detecting the remarkable peak value of each channel signal; Defining a state vector, definition No State vector of individual channels The method comprises the following steps: ; Wherein, the To the first vehicle The time of the individual channels is chosen to be, For time derivative, superscript Representing a transpose of the matrix; state evolution describes the state change of a vehicle between successive channels: ; ; Wherein, the For the distance between the channels, Performing observation modeling, namely taking candidate arrival time obtained by channel peak detection as an observation value, and establishing an observation relation through the following model: ; ; Wherein, the In order to observe the time of arrival, Is observation noise; Track optimization, namely recursively estimating the state of the vehicle through a Kalman filter, optimizing the track by combining a Lach-Tong-Style bell smoother, generating the track, drawing the whole vehicle track by generating the smooth vehicle position marked by each channel, and identifying a plurality of obvious vehicle tracks from the initial track.

Description

PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system Technical Field The invention relates to the technical fields of optical fiber sensing, seismic data processing, traffic monitoring and signal processing, in particular to an optical fiber distributed acoustic wave sensing data visualization processing system based on PyQt. Background The optical fiber distributed acoustic wave sensing (DAS) technology is an advanced monitoring technology using optical fibers as a continuous distributed sensor, and the DAS technology has been widely applied to a plurality of fields such as seismic detection, environmental noise imaging, pipeline leakage detection, traffic flow monitoring, structural health monitoring, urban underground imaging and the like by virtue of high spatial resolution, large sampling density, wide monitoring range and cost effectiveness. However, DAS data has the characteristics of massive mass, ultra-dense sampling and format heterogeneity, has essential differences from traditional seismic records, and brings great challenges to data visualization and signal processing. The traditional DAS data processing tool has the following defects that (1) the traditional tool is mainly programmed based on command lines or scripts, the threshold for non-programming professionals is high, (2) an open source DAS data processing library (such as DASPy, DASCore, xdas and the like) is not available, but an integrated and interactive graphical interface is lacking, the requirements of quick data exploration and visualization are difficult to meet, (3) the compatibility of data formats is limited, the heterogeneity of data formats generated by different manufacturer devices is high, the difficulty of data interoperation is increased, and (4) special advanced analysis functions aiming at DAS data characteristics such as integrated support of automatic vehicle track extraction, long-term traffic statistics and accurate seismic phase pickup are lacking. Disclosure of Invention The invention aims to provide an optical fiber distributed acoustic wave sensing data visualization processing system based on PyQt to solve the problems in the background art, wherein in order to reduce the technical threshold of DAS data processing and improve the data processing efficiency and user experience, the system integrates the functions of data loading, visualization, signal processing and advanced analysis through a graphical interface and supports multi-field application. In order to achieve the above purpose, the invention provides a PyQt-based optical fiber distributed acoustic wave sensing data visualization processing system, which comprises a data processing platform of optical fiber distributed acoustic wave sensing data, wherein the data processing platform provides a visualization function, and the modules are as follows: The data access module is used for directly accessing the standby fiber cores of the existing communication optical fibers or automatically arranging special sensing optical cables along a monitoring path, converting the corresponding optical fibers into a continuous distributed auditory perception array, setting a distributed acoustic wave sensing demodulator to be directly connected with the optical fibers, and then demodulating vibration data of the optical cables to obtain DAS data in different formats; The user interface module is used for receiving an operation instruction input by a user, providing a visual interface, realizing related picture display, waveform and spectrum analysis by the visual interface, integrating Matplotlib drawing tools and supporting image derivation and custom resolution setting; the data conversion module reads the distributed acoustic wave sensing data with different formats, and converts the distributed acoustic wave sensing data with different formats into standardized DAS data bodies and structured metadata; The basic processing module is used for preprocessing data and pushing the processed data to the user interface module for content display; And the advanced analysis module is used for analyzing the data subjected to the nondestructive processing by the basic processing module, analyzing by using the interactive pickup sub-module and the vehicle tracking sub-module, and displaying the analysis result through the user interface module. Preferably, the user interface module is developed by using a PyQt5 framework, and the user interface module adopts a three-region layout, wherein the three-region layout comprises: The data area is used for loading distributed acoustic wave sensing data in different formats and integrating an operation log and a display component of file attributes; the image display area is used for displaying a two-dimensional waterfall diagram of the distributed acoustic wave sensing data, providing a single-channel time sequence and a spectrogram and realizing interactive operation; and the signal proce