Image-based mine flood sensing alarm system

Abstract

The invention relates to the related technical field of mine flood treatment, in particular to an image-based mine flood sensing alarm system, which comprises an image acquisition module, a data processing module, a communication module and an alarm module. According to the image-based mine flood sensing and alarming system, visual information in a mine is acquired through the image acquisition module, the most direct and basic original data is provided for subsequent flood recognition and analysis, and according to scene records, when a flood occurs, analysis of a flood spreading path is facilitated, and personnel are helped to evacuate through an optimal channel in time, so that the flood sensing and alarming efficiency is improved. According to data extraction and processing, the change of the water level is accurately fed back, prediction can be carried out in advance according to daily data, preprocessing and flood prevention can be conveniently carried out, and the system can achieve accurate sensing and quick response.

Description

Technical Field

[0001] The present invention relates to the technical field related to mine flood treatment, and in particular to an image-based mine flood perception and alarm system. Background Art

[0002] A mine is a shaft and tunnel engineering facility that forms an underground mining space. Due to the particularity of mines, during the mining process, in the rainy season, a large amount of rainfall or snowmelt in mountainous areas may flow directly into the mine through surface collapse areas and cracks. During the mining process, if the groundwater approaches or penetrates the aquifer, it will flow into the mine due to the pressure difference. Insufficient geological exploration and mining technology problems may also cause mine flooding. Therefore, mine flood monitoring is of great significance, which is related to the safe production of mines, personnel safety, and the economic benefits of enterprises. Therefore, an image-based mine flood perception and alarm system is needed.

[0003] Existing image-based mine flood perception and alarm systems may result in inaccurate information transmission due to the complex underground water level conditions. This makes it impossible to effectively judge flood conditions and predictions based on accurate data, resulting in the inability to take reasonable emergency measures for emergencies and floods, which can easily lead to loss of control and casualties. Summary of the Invention

[0004] The purpose of the present invention is to provide an image-based mine flood perception and alarm system to solve the problem of the existing image-based mine flood perception and alarm system proposed in the above background technology. Due to the complex underground water level situation, the information transmission may be inaccurate, and it is impossible to effectively judge the flood situation and prediction based on accurate data, resulting in the inability to take reasonable emergency measures for emergencies and floods, which may easily cause loss of control and casualties.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: an image-based mine flood perception and alarm system, comprising:

[0006] Image acquisition module: The image acquisition module includes a mounting bracket, an explosion-proof camera, an auxiliary light source and a power supply system. The mounting bracket and the explosion-proof camera are fixedly connected and are used to collect visual information and scene records in the mine;

[0007] Data processing module: The data processing module includes image preprocessing, water level recognition, target recognition and analysis, and data post-processing parts. The image preprocessing is used to process the image data collected by the image acquisition module, reduce noise and enhance the image data, retain image details, and observe water level characteristics. The image preprocessing provides clear image details for the water level recognition. The water level recognition determines the outline of the water level through shape feature extraction to provide a basis for water level height calculation and shape analysis, and then accurately identifies the water level area through texture feature extraction. The water level recognition provides a basis for water level calculation and model establishment for the target recognition and analysis. The target recognition and analysis calculates the water level height through geometric relationships and predicts the trend and specific value of water level changes through model calculation. The target recognition and analysis provides a basis for data processing for the data post-processing part. The data post-processing part is used to establish a model, perform data statistics and advance estimation, calculate the mean and standard deviation of water level data, and use water level changes to determine whether the data is an abnormal value;

[0008] Communication module: The communication module includes industrial Ethernet, downhole switches, wireless communication modules and video servers for connecting communications and information transmission, and is used for image data transmission, equipment interconnection, sharing and interaction, remote monitoring and timely alarm notification;

[0009] Alarm module: The alarm module includes a control submodule, an audible and visual alarm, a monitoring center, and a broadcasting device, and is used to issue alarm information in a timely manner, guide personnel to evacuate safely, and record and analyze accidents.

[0010] Preferably, the fixed bracket fixes multiple groups of explosion-proof cameras on the side walls and roof of the mine tunnel, the explosion-proof cameras are installed adjacent to the auxiliary light source, the image information of the explosion-proof cameras is transmitted to the monitoring center via industrial Ethernet, the explosion-proof cameras and auxiliary light sources are powered by a power supply system, and the power supply system adopts an explosion-proof power supply.

[0011] Preferably, the image preprocessing is provided with a denoising submodule and an enhancement submodule. The denoising submodule adaptively adjusts the filtering parameters according to the noise characteristics of the local area of the image to retain the image details. The enhancement submodule increases the contrast and brightness adjustment to make the water level significantly different from the surrounding environment, which is used to collect and observe water level characteristics.

[0012] Preferably, the water level recognition includes shape feature extraction, and the shape feature extraction uses edge detection and contour analysis to perform texture feature extraction.

[0013] Preferably, the target recognition and analysis includes a classification recognition submodule and a water level calculation submodule. The classification recognition submodule uses classifiers such as vector machines and decision trees to classify the extracted features to determine whether the area in the image is a water level area. The water level calculation submodule establishes a mathematical model of water level changes based on the classification submodule, and predicts the changing trend of the water level based on the changes in the shape, area and other characteristics of the water level area in the image, combined with the time series analysis method, and calculates the specific value of the water level.

[0014] Preferably, the data post-processing part includes a data smoothing submodule and an outlier processing submodule. The data smoothing submodule performs moving average filtering on the water level data obtained by continuous collection and processing, removes short-term fluctuations in the data, and calculates the mean of the water level. The outlier processing submodule calculates the mean and standard deviation of the water level data based on the data smoothing submodule, and treats data that deviates from the mean by a certain multiple of the standard deviation as outliers for processing.

[0015] Preferably, the industrial Ethernet in the communication module is used to connect to the downhole switch, supporting the transmission of video data and control signals, and the wireless communication module is used for remote and local data transmission.

[0016] Preferably, the alarm module is provided with a monitoring center, which is used to receive data and send signals to the sound and light alarm and broadcasting equipment through the control submodule.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] 1. The image acquisition module collects visual information inside the mine, providing the most direct and basic raw data for subsequent flood identification and analysis. Based on scene records, when a flood occurs, it helps to analyze the path of flood spread and help personnel evacuate through the optimal channel in a timely manner.

[0019] 2. The data acquisition module converts raw images into actionable decision-making information. Based on data extraction and processing, it provides accurate feedback on water level changes. It can also make predictions in advance based on daily data, facilitating pre-processing and flood prevention, enabling the system to achieve accurate perception and rapid response.

[0020] 3. Through the communication module and the alarm module, data is transmitted to complete the equipment interconnection and data sharing and interaction, and the alarm signal is transmitted in time. Then, the alarm information is issued in time through the sound and light alarm and broadcasting equipment in the alarm module to guide personnel to evacuate safely. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a schematic diagram of the mine flood sensing and alarm system of the present invention;

[0022] Figure 2Schematic diagram of the image acquisition module of the present invention;

[0023] Figure 3 Schematic diagram of the data processing module of the present invention;

[0024] Figure 4 This is a schematic diagram of the communication module of the present invention;

[0025] Figure 5 Schematic diagram of the alarm module of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] See also Figure 1-5 The present invention provides a technical solution: an image-based mine flood perception and alarm system, comprising:

[0028] Image acquisition module: The image acquisition module includes a mounting bracket, an explosion-proof camera, an auxiliary light source and a power supply system. The mounting bracket and the explosion-proof camera are fixedly connected and are used to collect visual information and scene records in the mine;

[0029] Data processing module: The data processing module includes image preprocessing, water level recognition, target recognition and analysis, and data post-processing parts. The image preprocessing is used to process the image data collected by the image acquisition module, reduce noise and enhance the image data, retain image details, and observe water level characteristics. The image preprocessing provides clear image details for the water level recognition. The water level recognition determines the outline of the water level through shape feature extraction to provide a basis for water level height calculation and shape analysis, and then accurately identifies the water level area through texture feature extraction. The water level recognition provides a basis for water level calculation and model establishment for the target recognition and analysis. The target recognition and analysis calculates the water level height through geometric relationships and predicts the trend and specific value of water level changes through model calculation. The target recognition and analysis provides a basis for data processing for the data post-processing part. The data post-processing part is used to establish a model, perform data statistics and advance estimation, calculate the mean and standard deviation of water level data, and use water level changes to determine whether the data is an abnormal value;

[0030] Communication module: The communication module includes industrial Ethernet, downhole switches, wireless communication modules and video servers for connecting communications and information transmission, and is used for image data transmission, equipment interconnection, sharing and interaction, remote monitoring and timely alarm notification;

[0031] Alarm module: The alarm module includes a control submodule, an audible and visual alarm, a monitoring center, and a broadcasting device, and is used to issue alarm information in a timely manner, guide personnel to evacuate safely, and record and analyze accidents.

[0032] Furthermore, the fixed bracket fixes multiple groups of explosion-proof cameras on the side walls and roof of the mine tunnel, and the explosion-proof cameras are installed adjacent to the auxiliary light source. The image information of the explosion-proof cameras is transmitted to the monitoring center via industrial Ethernet. The explosion-proof cameras and auxiliary light sources are powered by a power supply system, and the power supply system adopts an explosion-proof power supply.

[0033] Furthermore, explosion-proof cameras are fixed with mounting brackets in tunnels and side walls at a height of more than two meters, and an explosion-proof camera is installed every 50-100 meters to avoid collisions and cover the monitoring range. The explosion-proof cameras are selected with a resolution of 1080P or above, a frame rate of 15-30 frames / second and a larger dynamic range.

[0034] Furthermore, the image preprocessing is provided with a denoising submodule and an enhancement submodule. The denoising submodule adaptively adjusts the filtering parameters according to the noise characteristics of the local area of the image to retain the image details. The enhancement submodule increases the contrast and brightness adjustment to make the water level significantly different from the surrounding environment, which is used to collect and observe water level characteristics.

[0035] Furthermore, the denoising submodule uses algorithms such as median filtering and Gaussian filtering to remove the noise generated during the image acquisition process, and cooperates with adaptive filtering to better retain image details while removing noise. The enhancement submodule improves the contrast of the image through methods such as histogram equalization, and appropriately adjusts the brightness of the image according to the overall brightness of the image.

[0036] Furthermore, the water level recognition includes shape feature extraction, and the shape feature extraction uses edge detection and contour analysis to perform texture feature extraction.

[0037] Furthermore, edge detection can determine the outline of the water level, obtain the contour curve of the water level through the contour tracking algorithm, and then calculate the perimeter, area, shape factor and other features of the contour. These features help to distinguish the water level area from other areas of similar shape. Through texture feature extraction, the grayscale co-occurrence matrix of the image is calculated, and texture feature parameters such as contrast, entropy, energy and correlation are extracted from it. The texture characteristics of the water flow are significantly different from those of the surrounding solid areas such as coal walls and equipment. These texture features can be used to more accurately identify the water level area.

[0038] Furthermore, the target recognition and analysis includes a classification recognition submodule and a water level calculation submodule. The classification recognition submodule uses classifiers such as vector machines and decision trees to classify the extracted features to determine whether the area in the image is a water level area. The water level calculation submodule establishes a mathematical model of water level changes based on the classification submodule, and predicts the changing trend of the water level based on the changes in the shape, area and other features of the water level area in the image, combined with the time series analysis method, and calculates the specific value of the water level.

[0039] Furthermore, the data post-processing part includes a data smoothing submodule and an outlier processing submodule. The data smoothing submodule performs moving average filtering on the water level data obtained by continuous collection and processing, removes short-term fluctuations in the data, and calculates the mean of the water level. The outlier processing submodule calculates the mean and standard deviation of the water level data based on the data smoothing submodule, and treats data that deviates from the mean by a certain multiple of the standard deviation as outliers for processing.

[0040] Furthermore, the water level values h1, h2, ..., h collected in chronological order n , after using the moving average filter with a window size of m, the new water level value is as follows:

[0041]

[0042] and

[0043]

[0044] The outlier processing submodule adopts the 3σ principle. If a data point x satisfies (x-μ)>3σ (where μ is the mean and σ is the standard deviation), then x is considered an outlier.

[0045] Furthermore, the industrial Ethernet in the communication module is used to connect to the underground switch, supporting the transmission of video data and control signals, and the wireless communication module is used for remote and local data transmission.

[0046] Furthermore, the alarm module is provided with a monitoring center, which is used to receive data and send signals to the sound and light alarm and broadcasting equipment through the control submodule.

[0047] Furthermore, an alarm signal is generated based on the image analysis structure. When a sudden and continuous water flow is detected, the image data is processed by the core processor, the early warning condition is triggered, and the alarm information is sent to the monitoring center. The sound and light alarm is linked with the monitoring terminal, and an alarm is issued through strong light and high-decibel sound to remind on-site personnel to evacuate urgently. Secondly, the voice broadcast is automatically played through the broadcasting equipment, including the location of the sudden water, escape route and emergency instructions, covering all areas underground. At the same time, the monitoring center is connected to the video server to obtain real-time on-site images and display alarm information to assist ground personnel in decision-making. The escape route is dynamically planned according to the location of the flood, and the route information is updated in real time through electronic displays or broadcasts. The control sub-module is linked with the underground drainage system and ventilation equipment. When the alarm is triggered, the drainage pump is automatically started or the waterproof gate is closed. At the same time, a text message notification is sent to the ground emergency command center to coordinate rescue resources.

[0048] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An image-based mine flood perception and alarm system, characterized by: include: Image acquisition module: The image acquisition module includes a mounting bracket, an explosion-proof camera, an auxiliary light source and a power supply system. The mounting bracket and the explosion-proof camera are fixedly connected and are used to collect visual information and scene records in the mine; Data processing module: The data processing module includes image preprocessing, water level recognition, target recognition and analysis, and data post-processing parts. The image preprocessing is used to process the image data collected by the image acquisition module, reduce noise and enhance the image data, retain image details, and observe water level characteristics. The image preprocessing provides clear image details for the water level recognition. The water level recognition determines the outline of the water level through shape feature extraction to provide a basis for water level height calculation and shape analysis, and then accurately identifies the water level area through texture feature extraction. The water level recognition provides a basis for water level calculation and model establishment for the target recognition and analysis. The target recognition and analysis calculates the water level height through geometric relationships and predicts the trend and specific value of water level changes through model calculation. The target recognition and analysis provides a basis for data processing for the data post-processing part. The data post-processing part is used to establish a model, perform data statistics and advance estimation, calculate the mean and standard deviation of water level data, and use water level changes to determine whether the data is an abnormal value; Communication module: The communication module includes industrial Ethernet, downhole switches, wireless communication modules and video servers for connecting communications and information transmission, and is used for image data transmission, equipment interconnection, sharing and interaction, remote monitoring and timely alarm notification; Alarm module: The alarm module includes a control submodule, an audible and visual alarm, a monitoring center, and a broadcasting device, and is used to issue alarm information in a timely manner, guide personnel to evacuate safely, and record and analyze accidents.

2. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The fixed bracket fixes multiple groups of explosion-proof cameras on the side walls and roof of the mine tunnel. The explosion-proof cameras are installed adjacent to the auxiliary light sources. The image information of the explosion-proof cameras is transmitted to the monitoring center via industrial Ethernet. The explosion-proof cameras and auxiliary light sources are powered by a power supply system, and the power supply system adopts an explosion-proof power supply.

3. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The image preprocessing is provided with a denoising submodule and an enhancement submodule. The denoising submodule adaptively adjusts the filtering parameters according to the noise characteristics of the local area of the image to retain the image details. The enhancement submodule increases the contrast and brightness adjustment to make the water level significantly different from the surrounding environment, which is used to collect and observe water level characteristics.

4. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The water level recognition includes shape feature extraction, and the shape feature extraction uses edge detection and contour analysis to perform texture feature extraction.

5. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The target recognition and analysis includes a classification recognition submodule and a water level calculation submodule. The classification recognition submodule uses classifiers such as vector machines and decision trees to classify the extracted features and determine whether the area in the image is a water level area. The water level calculation submodule establishes a mathematical model of water level changes based on the classification submodule, and predicts the changing trend of the water level based on the changes in the shape, area and other features of the water level area in the image, combined with the time series analysis method, and calculates the specific value of the water level.

6. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The data post-processing part includes a data smoothing submodule and an outlier processing submodule. The data smoothing submodule performs moving average filtering on the water level data obtained by continuous collection and processing, removes short-term fluctuations in the data, and calculates the mean of the water level. The outlier processing submodule calculates the mean and standard deviation of the water level data based on the data smoothing submodule, and treats data that deviates from the mean by a certain multiple of the standard deviation as outliers for processing.

7. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The industrial Ethernet in the communication module is used to connect to the underground switch and supports the transmission of video data and control signals. The wireless communication module is used for remote and local data transmission.

8. The image-based mine flood perception and alarm system according to claim 1, characterized in that: The alarm module is provided with a monitoring center, which is used to receive data and send signals to the sound and light alarm and broadcasting equipment through the control submodule.

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