Intelligent fiber grating sensor network with edge calculation function

Abstract

The invention discloses an intelligent fiber bragg grating sensor network system with an edge calculation function, which consists of distributed fiber bragg grating sensors, an edge calculation unit and a central control system, and can analyze, process and transmit data acquired by the sensors in real time; the delay of data transmission and the network load are reduced through the edge computing technology, and the response speed and the intelligent level of the sensor network are improved.

Description

Technical Field

[0001] The present invention relates to the field of optical fiber sensing and edge computing technology, specifically to an intelligent optical fiber grating sensor network with edge computing function, which is applied to the fields of structural health monitoring, environmental monitoring, energy pipeline monitoring, etc. Background Art

[0002] Infrastructure is the cornerstone of urban and social development, and its planning, design, construction, operation and maintenance are all crucial. Traditional management methods often have problems such as inaccurate data, imprecise model construction, and low management efficiency, which cannot meet the needs of modern infrastructure management. Therefore, a more efficient and accurate management method is needed to improve the management level of infrastructure.

[0003] Fiber Bragg grating sensors are widely used in monitoring physical quantities such as temperature, stress and vibration due to their high sensitivity and strong resistance to electromagnetic interference. However, the traditional centralized data processing architecture faces the following problems: Delay problem: The centralized processing architecture causes data processing delays, making it difficult to meet real-time monitoring needs.

[0004] Energy consumption problem: Large amounts of raw data transmission consume high bandwidth, leading to increased energy consumption and communication costs.

[0005] Scalability issues: Centralized systems are difficult to adapt to the dynamic expansion requirements of sensor networks.

[0006] In order to solve the above problems, fiber Bragg grating sensor networks combined with edge computing technology have become a research hotspot. Edge computing significantly improves system response speed and optimizes data processing efficiency by performing real-time data processing at the edge close to the data source. Summary of the invention

[0007] The present invention aims to overcome the problems of high data delay, high energy consumption and poor scalability of traditional fiber grating sensor networks, and proposes an intelligent fiber grating sensor network combined with edge computing function, which has real-time data analysis, optimized transmission and intelligent decision support functions.

[0008] To achieve the above objectives, the present invention provides the following technical solutions: First, the overall structure Fiber Bragg grating sensor node: collects physical quantity data of the target monitoring area.

[0009] Demodulation module: converts the optical signal collected by the sensor into an electrical signal and extracts the measurement data.

[0010] Edge computing unit: performs real-time analysis on the data output by the demodulation module, including feature extraction, anomaly detection, and data compression.

[0011] Data transmission module: efficiently transmit optimized data to the central control system.

[0012] Central control system: Centrally store data and conduct in-depth analysis and visual display.

[0013] Second, the innovation of edge computing unit Modular design: The edge computing unit includes data acquisition module, signal processing module and communication module.

[0014] Intelligent algorithm: The signal processing module implements feature extraction and anomaly detection based on deep learning and machine learning algorithms.

[0015] Efficient communication: Use optimized data compression algorithms to reduce communication bandwidth requirements and energy consumption.

[0016] Third, system advantages Real-time: Data processing delay is reduced to less than 50 milliseconds.

[0017] Low energy consumption: transmission traffic is reduced by about 70%.

[0018] High scalability: supports dynamic expansion of sensor networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Attached Figure 1 :Schematic diagram of the overall system architecture The figure shows the overall architecture of the intelligent fiber Bragg grating sensor network, including the relationship between the fiber Bragg grating sensor node, demodulation module, edge computing unit, data transmission module and central control system. The fiber Bragg grating sensor node is responsible for data acquisition, the demodulation module is responsible for signal conversion, the edge computing unit performs real-time data processing, and the data transmission module sends the optimized data to the central control system for in-depth analysis and display.

[0020] Attached Figure 2 :Edge computing unit structure diagram This figure shows the internal module structure and functions of the edge computing unit. The edge computing unit includes a data acquisition module, a signal processing module, and a communication module. The data acquisition module receives the signal from the sensor node, the signal processing module performs feature extraction and anomaly detection on the data, and the communication module transmits the processed data to the central control system.

[0021] Attached Figure 3 :Signal processing flow chart The figure shows the complete process from data acquisition to signal processing and data transmission. First, the fiber grating sensor node collects data, the demodulation module converts the optical signal into an electrical signal, the edge computing unit performs data processing (including feature extraction, data compression and anomaly detection), and finally, the optimized data is uploaded to the central control system through the data transmission module.

[0022] Attached Figure 4 :Application scenario diagram This figure shows the layout and data flow of the intelligent fiber Bragg grating sensor network in different application scenarios. The scenarios include bridge health monitoring, oil and gas pipeline monitoring, and environmental monitoring. Different types of monitoring data are collected through fiber Bragg grating sensor nodes, and the edge computing unit processes them in real time and uploads the results to the central control system for display and analysis. DETAILED DESCRIPTION

[0023] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0024] Example 1: Bridge Health Monitoring System Fiber Bragg grating sensor nodes are deployed at key locations on the bridge to collect temperature, stress and vibration data of the bridge. The data collected by the sensor is converted into electrical signals by the demodulation module and transmitted to the edge computing unit for real-time processing. The edge computing unit uses fast Fourier transform (FFT) to extract dynamic features and combines deep learning algorithms (such as convolutional neural network CNN) to detect anomalies in the data and identify potential structural problems.

[0025] Optimize data transfer: Through wireless communication modules (such as LoRa or NB-IoT), the optimized data is uploaded to the central control system.

[0026] Health Assessment Report: In the central control system, the data undergoes in-depth analysis and health assessment to generate monitoring reports and provide real-time bridge health status.

[0027] Example 2: Oil and gas pipeline monitoring system Fiber Bragg grating sensors are installed on the surface of oil and gas pipelines to monitor the pressure and temperature of the pipelines. After data collection, the edge computing unit analyzes the sensor data in real time and identifies whether there are abnormal conditions (such as excessive pipeline pressure or high temperature). Through low-power communication protocols (such as NB-IoT), abnormal information is transmitted to the central control system in a timely manner for alarm and risk warning.

[0028] Quick response and alarm: The central control system analyzes the uploaded data and issues alarm information in a timely manner to ensure a quick response to potential risks.

[0029] Example 3: Intelligent environment monitoring system Fiber Bragg grating sensors are placed on the surface of oil and gas pipelines to monitor data such as ambient temperature, humidity, and gas concentration. The edge computing unit processes data in real time and uses deep learning algorithms to perform intelligent analysis of the data to identify trends and anomalies in environmental changes.

[0030] Intelligent early warning: The system can issue early warning information when abnormal environmental changes occur, and transmit it to the central control system through a low-power communication protocol for further processing and display.

[0031] The intelligent fiber grating sensor network system with edge computing function provided by the present invention combines real-time data processing, optimized transmission and intelligent decision support functions, significantly improving the response speed and intelligence level of the system. This technology is particularly suitable for bridge health monitoring, oil and gas pipeline monitoring and environmental monitoring, and can effectively reduce data transmission delays, optimize data processing efficiency, and improve system performance and reliability.

Claims

1. Intelligent fiber grating sensor network with edge computing function, including: Fiber Bragg grating sensor nodes are used to collect physical quantity data in the target area; A demodulation module, connected to the fiber grating sensor node, for converting the optical signal into an electrical signal and extracting sensing data; An edge computing unit, connected to the demodulation module, for real-time processing of sensor data, including feature extraction, data compression and anomaly detection; A data transmission module, connected to the edge computing unit, for transmitting the processed optimized data to a central control system; Central control system, used to receive, store, and transmit data, and to perform in-depth analysis and display of the data; Characterized in that: the edge computing unit comprises: A data acquisition module, used for receiving sensor data from the demodulation module; Signal processing module, used for feature extraction, anomaly detection and data compression of collected data; The communication module is used to send the processed optimization data to the central control system.

2. The intelligent fiber grating sensor network according to claim 1, characterized in that: The signal processing module completes intelligent analysis and processing of data based on deep learning or machine learning algorithms, including prediction and analysis of changes in environmental parameters.

3. The intelligent fiber grating sensor network according to claim 1, characterized in that: The edge computing unit further includes a power management module for dynamically optimizing the energy consumption of the edge computing unit to ensure long-term stable operation of the system.

4. The intelligent fiber grating sensor network according to claim 1, characterized in that: The central control system further comprises: A data fusion module for integrating data from multiple edge computing units; Visualization module, used to display monitoring results in real time and generate trend analysis and health assessment reports.

5. The intelligent fiber grating sensor network according to claim 1, characterized in that: The data transmission module adopts wireless communication protocol and supports multiple communication modes, including but not limited to LoRa, NB-IoT and Wi-Fi.

6. The intelligent fiber grating sensor network according to claim 1, characterized in that: The fiber grating sensor node has multifunctional integration capability and is used to simultaneously monitor physical quantities such as temperature, stress and vibration.

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