Monitoring system for preventing large excavation damage of gas pipeline based on vibration signal feature extraction

Abstract

The invention discloses a monitoring system for preventing large excavation damage of a gas pipeline based on vibration signal feature extraction, and relates to the technical field of safety monitoring of gas conveying pipelines. The monitoring system is based on vibration signal feature recognition of a large-scale operation machine. Comprising four technical modules, namely a multi-sensor hardware circuit system taking vibration acceleration measurement as a main part, a software algorithm for identifying the characteristic frequency spectrum of large-scale operation mechanical equipment, a master-slave network structure for large-scale communication networking along a gas pipeline, and a self-energy-supply column type mechanical supporting structure. The system is convenient to install and debug, does not need external energy supply, can perform large-scale monitoring on large-scale excavation events on a gas pipeline in a field environment, can perform early warning and image evidence obtaining on damage behaviors of large-scale excavation operation machinery, and improves the gas supply safety of a gas conveying main pipeline.

Description

Technical Field

[0001] The present invention belongs to the technical field of gas transmission pipeline safety monitoring, and more specifically, relates to a gas pipeline monitoring system for preventing large-scale excavation damage based on vibration signal feature extraction. Background Art

[0002] Gas pipeline transmission has become the preferred mode of gas transportation due to its advantages of low cost, safety and airtightness, large transportation volume, and easy control and management. However, gas is flammable and explosive. Once a pipeline leakage accident occurs, it may cause a series of disasters such as explosion, fire, poisoning, and environmental pollution. The main causes of gas pipeline leakage include external force damage, corrosion and aging of materials and equipment, illegal operation, and natural disasters. Large-scale excavation equipment is often used in the construction of bridges and roads in the field, which is likely to cause damage to the main gas transmission pipeline, causing gas leakage and leading to major safety accidents. Therefore, when large-scale excavators are operating, safety monitoring of the main gas transmission roads that may be affected is a problem that technicians need to solve. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide a monitoring system for preventing gas pipelines from being damaged by large-scale excavation based on vibration signal feature extraction. The system is easy to install and debug, does not require external energy supply, can implement large-scale monitoring of large-scale excavation events on gas pipelines in a wilderness environment, and provide early warnings and image evidence collection for the destructive behavior of large-scale excavation machinery, thereby improving the gas delivery safety of the gas transmission trunk pipeline.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: a monitoring system for preventing large-scale excavation damage to gas pipelines based on vibration signal feature extraction, comprising: The multi-sensor hardware circuit system is composed of multiple sensor modules, a main circuit board designed based on the stm32f103 single-chip microcomputer, and a sub-circuit board connected to each sensor; the main circuit board and the sub-circuit board are connected by a flat cable, and the flat cable contains an I / O interface and a serial communication interface; the multiple sensor modules include a three-axis accelerometer sensor module, a methane concentration sensor module, a noise decibel sensor module, and a camera; The master-slave network structure of large-scale communication networking along the gas pipeline adopts a one-master and four-slave LORA communication network structure. Each monitoring point contains a LORA communication module and is networked along the direction of the gas pipeline; the LORA host is deployed in the middle position, and two LORA slaves are deployed on both sides of it, with an interval of 200 meters between monitoring points; the host communicates with the four slaves in a polling manner to query the status of the four monitoring points; the 4G communication module is deployed on the host to send monitoring data to the cloud background; The mechanical support structure of the self-powered column includes a solar panel, a column, a fixing plate, and an installation box. The installation box is fixedly connected to the column. The fixing plate is fixedly connected to the bottom of the column and connected to the soil above the gas pipeline through bolts. The solar panel is fixedly connected to the top of the column. The battery power supply line of the solar panel is connected to the power interface of the installation box. The hardware circuit and sensor of the monitoring point are encapsulated in the installation box. The pan / tilt and camera are installed on the upper part of the column, and the lens is installed along the direction of the gas pipeline. The software algorithm for identifying the characteristic spectrum of vibration signals of large-scale operating machinery and equipment is mainly used for identifying the vibration spectrum of large-scale excavating machinery and equipment, and adopts the fast Fourier spectrum analysis method; when the spectrum signal is collected multiple times and the operating spectrum characteristics of large-scale excavating machinery and equipment exist in the multiple analysis results, it is determined that a large-scale excavating operating machinery is operating on the pipeline; after the above judgment, the camera is turned on to collect on-site picture information and save the picture.

[0005] Preferably, the main circuit board includes a 4G communication module to send the monitoring information of the networked monitoring points to the cloud background; the three-axis accelerometer sensor module is connected through the SPI bus to collect acceleration data for spectrum analysis under the condition of meeting the noise threshold; the 10-pin wiring interface leads to the sensor power enable port, serial communication interface, 485 communication interface, and overflow bit I / O port on the secondary circuit board.

[0006] Preferably, the auxiliary circuit board includes a voltage conversion circuit that converts the solar cell output 12V into 24V, 5V, a LORA communication module power enable circuit, a methane sensor and a noise sensor power enable circuit, a voice broadcast module power enable circuit, and a pan / tilt and camera power enable circuit; in the 10-pin wiring connected to the main circuit board, the pan / tilt, camera and noise sensor are mounted on the 485 bus, the serial port bus is connected to the LORA communication module, an I / O line reads the methane concentration value, an I / O line controls the voice module broadcast, an I / O line detects the solar voltage value, and other I / O leads control each power enable.

[0007] Preferably, the installation box consists of a base plate and a box cover, the base plate is provided with a card slot and a mounting column, the card slot is used to install the LORA module, and the protruding mounting column fixes the main circuit board and the auxiliary circuit board by screws; the three-axis accelerometer is installed in close contact with the base plate to sense vibration signals; the box cover is respectively provided with fixing holes for the methane sensor, the noise sensor and the voice module, and the fixing holes are facing the ground during installation.

[0008] Preferably, the large-scale operation machinery equipment vibration signal characteristic spectrum recognition software algorithm is mainly to periodically sample sensor signals and make judgments, and the specific steps are: S1: Start the timer, turn on the methane and noise sensors within the sampling period, read the methane concentration value and noise decibel value N times, and take the average value; S2: If the methane concentration or the average noise decibel exceeds the set threshold, it is considered that there are large-scale operating machinery and equipment around the current monitoring station, and the process goes to step S3, otherwise it returns to step S1; S3: Start reading the vibration signal of the triaxial accelerometer for N times for M seconds, define three static arrays in the program to store the vibration signal data, and input the fast Fourier analysis function after the data is read to obtain the main frequency value of the vibration signal; S4: If there are multiple vibration signal main frequency values ​​matching the spectrum signal characteristics of a large excavator in the analysis results, it is considered that there is a large excavator working on the gas pipeline, and the program goes to step S5, otherwise it returns to step S1; S5: The MCU turns on the PTZ and camera enable switches and the voice broadcast switch, broadcasts warning information, and sends an image acquisition command to the camera to store the current image information; S6: If the site where the excavator is currently operating is determined to be a slave site, upon receiving the host polling signal, the image information is sent to the host via LORA; the slave returns to step S1; S7: If the host monitors the excavator operation information, or receives the excavator operation information from the slave, the host will package the monitoring point number, time, longitude and latitude, and image information, and transmit the data back to the background cloud through the 4G module; after the transmission is completed, the host returns to step S1.

[0009] Preferably, the method for the host to poll the slave is: P1: The host defines the polling data frame according to the station numbers of the four slaves. When the slave receives the polling data frame that matches it, it returns the binary keyword 0000 or 0001. 0000 indicates normal and 0001 indicates abnormal. P2: When the host receives abnormal information from a slave, after polling the four slave monitoring points, it communicates with the abnormal monitoring point separately to read back the image information; P3: When a slave detects abnormal information, it will stop the sampling cycle described above and wait for the host to finish reading the image information before starting the sampling cycle.

[0010] The beneficial effects of adopting the above technical solution are: 1. The present invention adopts a one-master and four-slave LORA communication network structure. A LORA communication module is set at each monitoring point. The LORA host is deployed in the middle position, and two LORA slaves are deployed on both sides. The two monitoring points are 200 meters apart and networked along the direction of the gas pipeline. The gas trunk pipeline can be monitored over a large area.

[0011] 2. The present invention uses a software algorithm for identifying the characteristic spectrum of vibration signals of large-scale operating mechanical equipment, adopts a three-axis accelerometer to collect vibration signals, collects noise signals through a noise decibel sensor, comprehensively determines whether there is a large excavator working on the pipeline, and determines whether there is a natural gas leak in the pipeline through a methane concentration sensor. The camera then collects image information, which can be used to conduct construction and safety monitoring and evidence collection on large-scale excavation events on the gas pipeline, thereby improving the gas delivery safety of the gas pipeline.

[0012] 3. The present invention uses solar panels to provide power to the monitoring system, and does not require external power supply, which is suitable for working in wilderness environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a schematic diagram of the host workflow; Figure 2 This is a schematic diagram of the slave machine’s working process; Figure 3 It is the circuit diagram of the auxiliary circuit board; Figure 4 It is a schematic diagram of the installation box structure; Figure 5 It is a structural schematic diagram of a self-powered column mechanical support structure; In the figure: 1. Box cover; 2. Mounting column; 3. Three-axis accelerometer slot; 4. Voice module mounting hole; 5. Auxiliary circuit board; 6. Base; 7. Methane sensor; 8. Noise module mounting hole; 9. LORA antenna lead-out hole; 10. Power lead-in hole; 11. LORA module; 12. Main circuit board; 13. Solar panel; 14. Mounting box; 15. Column; 16. Fixing plate; 17. Pan / tilt; 18. Camera. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0015] The monitoring system is based on the vibration signal feature recognition of large-scale operating machinery, including four technical modules: a multi-sensor hardware circuit system based on vibration acceleration measurement, a software algorithm for characteristic spectrum recognition of large-scale operating machinery and equipment, a master-slave network structure for large-scale communication networking along gas pipelines, and a self-powered column-type mechanical support structure.

[0016] The multi-sensor hardware circuit system includes a main circuit board 12 designed based on the stm32f103 single-chip microcomputer, a sub-circuit board 5 connected to each sensor, and multiple sensor modules. The main circuit board 12 and the sub-circuit board 5 are connected by a flat cable, which includes an I / O interface and a serial communication interface. The multiple sensor modules include a three-axis accelerometer, a methane concentration sensor, a noise decibel sensor, a camera, etc.

[0017] Specifically, the main circuit board is based on stm32f103, including a 4G communication module, which sends the monitoring information of the networked monitoring points to the cloud backend. The three-axis accelerometer sensor module is connected via the SPI bus to collect acceleration data for spectrum analysis under the condition of meeting the noise threshold. The 10-pin cable interface leads to the sensor power enable port, serial communication interface, 485 communication interface, overflow bit I / O port, etc. on the auxiliary circuit board.

[0018] like Figure 3 As shown, the auxiliary circuit board 5 connected to each sensor includes a voltage conversion circuit that converts the solar cell output 12V into 24V and 5V, a LORA communication module power enabling circuit, a methane sensor and a noise sensor power enabling circuit, a voice broadcast module power enabling circuit, and a pan / tilt and camera power enabling circuit. In the 10-pin wiring connected to the main circuit board, the pan / tilt, camera and noise sensor are mounted on the 485 bus, the serial bus is connected to the LORA communication module, an I / O line reads the methane concentration value, an I / O line controls the voice module broadcast, an I / O line detects the solar voltage value, and other I / O leads control each power enable.

[0019] like Figure 4-5 As shown, the self-powered column mechanical support structure includes a mounting box 14, a column 15, and a fixing plate 16. The mounting box 14 is fixed to the column 15 by bolts or clamps, and the fixing plate 16 is welded to the bottom of the column 15. The fixing plate 16 is installed on the soil above the gas pipeline by expansion bolts. The solar panel 13 is fixed on the top of the column 15 to provide power for various components, and its battery power supply line is connected to the power interface of the mounting box 14.

[0020] The main circuit board 12, the auxiliary circuit board 5 and each sensor are installed in the installation box 14. The installation box 14 consists of a base plate and a box cover 1. The card slot on the base plate is used to install the LORA module, and the protruding mounting column 2 fixes the main circuit board 12 and the auxiliary circuit board 5 by screws; the three-axis accelerometer is installed in the three-axis accelerometer card slot 3 and fits with the base plate to better sense the vibration signal; the box cover 1 is provided with fixing holes for the methane sensor 7, the noise sensor and the voice module. The fixing holes are facing the bottom surface during installation to prevent rainwater from leaking into the box cover 1. The pan / tilt 17 and the camera 18 are installed above the column 15, and the lens is installed along the direction of the gas pipeline.

[0021] The master-slave network structure of large-scale communication networking along the gas pipeline adopts a master-four-slave LORA communication network structure. Each monitoring point contains a LORA communication module, which is networked along the direction of the gas pipeline. The LORA host is deployed in the middle position, and two LORA slaves are deployed on both sides of it. The interval between monitoring points is about 200 meters. The host communicates with the four slaves in a polling manner to query the status of the four monitoring points. The 4G communication module is deployed on the host to send monitoring data to the cloud background.

[0022] The software algorithm for identifying the characteristic spectrum of vibration signals of large-scale operating machinery and equipment is based on the principle of multi-sensor threshold detection, and each sensor is turned on step by step to achieve monitoring. Figure 1-2 As shown, the recognition algorithm is mainly used for vibration spectrum recognition of large-scale excavating machinery and equipment. The fast Fourier spectrum analysis method is used. When the spectrum signal is collected multiple times and the spectrum characteristics of large-scale excavating machinery and equipment are present in the multiple analysis results, it is determined that a large-scale excavating machinery is operating on the pipeline. After the above judgment, the camera is turned on to collect on-site picture information and save the picture.

[0023] The software algorithm for identifying the characteristic spectrum of vibration signals of large-scale operating machinery and equipment is to periodically sample sensor signals and make judgments, specifically: S1: Start the timer, turn on the methane and noise sensors within the sampling period, read the methane concentration value and noise decibel value N times, and take the average value.

[0024] S2: If the methane concentration or the average noise decibel exceeds the set threshold, it is considered that there are large-scale operating machinery and equipment around the current monitoring station, and the process goes to step S3, otherwise it returns to step S1.

[0025] S3: Start reading the vibration signal of the triaxial accelerometer for N times and M seconds. Define three static arrays in the program to store the vibration signal data. After the data is read, input the fast Fourier analysis function to obtain the main frequency value of the vibration signal.

[0026] S4: If there are multiple vibration signal main frequency values ​​matching the spectrum signal characteristics of a large excavator in the analysis results, it is considered that there is a large excavator working on the gas pipeline in the surrounding area, and the program enters step S5, otherwise it returns to step S1.

[0027] S5: The MCU turns on the pan / tilt and camera enable switches and the voice broadcast switch, broadcasts a warning message, sends an image acquisition command to the camera, and stores the current image information.

[0028] S6: If the site currently determined to have an excavator operation is a slave site, upon receiving the host polling signal, the slave sends the image information to the host via LORA. The slave returns to step S1.

[0029] S7: If the host monitors the excavator operation information, or receives the excavator operation information from the slave, the host will package the monitoring point number, time, longitude and latitude, and image information, and transmit the data back to the backend cloud through the 4G module. After the transmission is completed, the host returns to step S1.

[0030] Specifically, the working steps of the host polling the slave are as follows: P1: The host defines the polling data frame according to the station numbers of the four slaves. When the slave receives the polling data frame that matches it, it returns the binary keyword 0000 or 0001. 0000 indicates normal and 0001 indicates abnormal.

[0031] P2: When the host receives abnormal information from a slave, after polling the four slave monitoring points, it communicates with the abnormal monitoring point separately to read back the image information.

[0032] P3: When a slave detects abnormal information, it will stop the sampling cycle described in claim 5 and wait for the host to finish reading the image information before starting the sampling cycle.

[0033] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A monitoring system for preventing gas pipelines from being damaged by large-scale excavation based on vibration signal feature extraction, characterized in that: include: The multi-sensor hardware circuit system is composed of multiple sensor modules, a main circuit board designed based on the stm32f103 single-chip microcomputer, and a sub-circuit board connected to each sensor; the main circuit board and the sub-circuit board are connected by a flat cable, and the flat cable contains an I / O interface and a serial communication interface; the multiple sensor modules include a three-axis accelerometer sensor module, a methane concentration sensor module, a noise decibel sensor module, and a camera; The master-slave network structure of large-scale communication networking along the gas pipeline adopts a one-master and four-slave LORA communication network structure. Each monitoring point contains a LORA communication module and is networked along the direction of the gas pipeline; the LORA host is deployed in the middle position, and two LORA slaves are deployed on both sides of it, with an interval of 200 meters between monitoring points; the host communicates with the four slaves in a polling manner to query the status of the four monitoring points; the 4G communication module is deployed on the host to send monitoring data to the cloud background; The mechanical support structure of the self-powered column includes a solar panel, a column, a fixing plate, and an installation box. The installation box is fixedly connected to the column. The fixing plate is fixedly connected to the bottom of the column and connected to the soil above the gas pipeline through bolts. The solar panel is fixedly connected to the top of the column. The battery power supply line of the solar panel is connected to the power interface of the installation box. The hardware circuit and sensor of the monitoring point are encapsulated in the installation box. The pan / tilt and camera are installed on the upper part of the column, and the lens is installed along the direction of the gas pipeline. The software algorithm for identifying the characteristic spectrum of vibration signals of large-scale operating machinery and equipment is mainly used for identifying the vibration spectrum of large-scale excavating machinery and equipment, and adopts the fast Fourier spectrum analysis method; when the spectrum signal is collected multiple times and the operating spectrum characteristics of large-scale excavating machinery and equipment exist in the multiple analysis results, it is determined that a large-scale excavating operating machinery is operating on the pipeline; after the above judgment, the camera is turned on to collect on-site picture information and save the picture.

2. According to claim 1, a gas pipeline monitoring system for preventing large-scale excavation damage based on vibration signal feature extraction is characterized in that: The main circuit board includes a 4G communication module, which sends the monitoring information of the networked monitoring points to the cloud background; the three-axis accelerometer sensor module is connected through the SPI bus to collect acceleration data for spectrum analysis under the condition of meeting the noise threshold; the 10-pin wiring interface leads to the sensor power enable port, serial communication interface, 485 communication interface, and overflow bit I / O port on the auxiliary circuit board.

3. According to claim 1, a monitoring system for preventing gas pipelines from being damaged by large-scale excavation based on vibration signal feature extraction is characterized in that: The auxiliary circuit board includes a voltage conversion circuit that converts the solar cell output 12V into 24V and 5V, a LORA communication module power enable circuit, a methane sensor and a noise sensor power enable circuit, a voice broadcast module power enable circuit, and a pan / tilt and camera power enable circuit; in the 10-pin wiring connected to the main circuit board, the pan / tilt, camera and noise sensor are mounted on the 485 bus, the serial port bus is connected to the LORA communication module, an I / O line reads the methane concentration value, an I / O line controls the voice module broadcast, an I / O line detects the solar voltage value, and other I / O leads control each power enable.

4. A monitoring system for preventing gas pipelines from being damaged by large-scale excavation based on vibration signal feature extraction according to claim 1, characterized in that: The installation box consists of a base plate and a box cover. The base plate is provided with a slot and a mounting column. The slot is used to install the LORA module, and the protruding mounting column fixes the main circuit board and the auxiliary circuit board by screws. The three-axis accelerometer is installed in contact with the base plate to sense vibration signals. The box cover is respectively provided with fixing holes for the methane sensor, the noise sensor and the voice module, and the fixing holes face the ground during installation.

5. The gas pipeline monitoring system for preventing large-scale excavation damage based on vibration signal feature extraction according to claim 1 is characterized in that: The software algorithm for identifying the characteristic spectrum of vibration signals of large-scale mechanical equipment is mainly to periodically sample sensor signals and make judgments. The specific steps are as follows: S1: Start the timer, turn on the methane and noise sensors within the sampling period, read the methane concentration value and noise decibel value N times, and take the average value; S2: If the methane concentration or the average noise decibel exceeds the set threshold, it is considered that there are large-scale operating machinery and equipment around the current monitoring station, and the process goes to step S3, otherwise it returns to step S1; S3: Start reading the vibration signal of the triaxial accelerometer for N times for M seconds, define three static arrays in the program to store the vibration signal data, and input the fast Fourier analysis function after the data is read to obtain the main frequency value of the vibration signal; S4: If there are multiple vibration signal main frequency values ​​matching the spectrum signal characteristics of a large excavator in the analysis results, it is considered that there is a large excavator working on the gas pipeline, and the program goes to step S5, otherwise it returns to step S1; S5: The MCU turns on the PTZ and camera enable switches and the voice broadcast switch, broadcasts warning information, and sends an image acquisition command to the camera to store the current image information; S6: If the site where the excavator is currently operating is determined to be a slave site, upon receiving the host polling signal, the image information is sent to the host via LORA; the slave returns to step S1; S7: If the host monitors the excavator operation information, or receives the excavator operation information from the slave, the host will package the monitoring point number, time, longitude and latitude, and image information, and transmit the data back to the background cloud through the 4G module; after the transmission is completed, the host returns to step S1.

6. A monitoring system for preventing gas pipelines from being damaged by large-scale excavation based on vibration signal feature extraction according to claim 1, characterized in that: The method for the host to poll the slave is: P1: The host defines the polling data frame according to the station numbers of the four slaves. When the slave receives the polling data frame that matches it, it returns the binary keyword 0000 or 0001. 0000 indicates normal and 0001 indicates abnormal. P2: When the host receives abnormal information from a slave, after polling the four slave monitoring points, it communicates with the abnormal monitoring point separately to read back the image information; P3: When a slave detects abnormal information, it will stop the sampling cycle and wait for the host to finish reading the image information before starting the sampling cycle.

Images