Intelligent operation control system and data processing method thereof

Abstract

The invention discloses an intelligent operation control system and a data processing method thereof, and the system comprises a monitoring module, a data analysis module, a data collection module, and an alarm module. The monitoring module comprises a video data acquisition device arranged in the pipe gallery; the data acquisition module comprises a pipeline vibration acquisition sensor and a ground vibration acquisition sensor; the data analysis module is used for constructing vibration waveform image data of the pipeline and ground vibration waveform image data; and the alarm module sends an alarm signal. By means of the system, the situation of the pipeline can be monitored in real time, pipeline vibration data and ground vibration data are monitored, the data are processed through the data analysis module, and whether the abnormal situation exists in the pipeline or not is judged. Once the system detects that the pipeline is abnormal, the alarm module can send out an alarm signal in time to help an operator to quickly respond, so that the possibility of accidents is reduced, and safe and stable operation of the pipeline system is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the field of operation and maintenance technology, and specifically relates to an intelligent operation and control system and a data processing method thereof. Background Art

[0002] Smart operation and maintenance is an operation and maintenance management model based on digital, automated and intelligent technologies. It uses technologies such as the Internet of Things, artificial intelligence and big data analysis to achieve real-time monitoring of equipment, fault prediction, optimized scheduling, etc., to improve operation and maintenance efficiency and equipment reliability. Big data technology can process and analyze large-scale and complex data sets. It includes technical means for data collection, storage, processing and analysis, which can be used to discover patterns, trends, and correlations in the data, and obtain valuable information and insights from them.

[0003] In the prior art, for example, the technical solution described in the patent with publication number: CN112883802A: a method for identifying monitoring specific events, obtaining real-time signals of soil vibration around the pipeline through optical fiber, and identifying the real-time signals after analyzing and processing the signals to determine whether destructive events occur around the pipeline.

[0004] In the prior art, sensors are usually directly installed on the pipeline to detect pipeline vibration. When using pipeline vibration signals to detect natural gas pipeline leaks, part of the pipeline may be affected by the surrounding environment, resulting in the key features in the vibration signal being masked. This may reduce the detection accuracy and even lead to misjudgment. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent operation and control system and a data processing method thereof, so as to solve the problem in the prior art proposed in the background technology that when detecting natural gas pipeline leakage through pipeline vibration signals, some pipeline sections are affected by the environment, which may cause key features in the pipeline vibration signals to be covered, thereby reducing the detection accuracy or causing false detection.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] Intelligent operation and control system, including monitoring module, data analysis module, data acquisition module and alarm module;

[0008] A monitoring module, which includes several video data acquisition devices arranged in the pipe gallery and is used to monitor the pipeline;

[0009] The data acquisition module includes a plurality of pipeline vibration acquisition sensors arranged on the pipeline, the pipeline vibration acquisition sensors are used to collect pipeline vibration data, and a ground vibration acquisition sensor arranged directly below the pipeline for collecting ground vibration data;

[0010] The data analysis module is connected to the monitoring module and the data acquisition module respectively; the data analysis module is used to construct the pipeline vibration waveform image data and the ground vibration waveform image data; and judge whether the pipeline is abnormal according to the pipeline vibration waveform image and the ground vibration waveform image;

[0011] The alarm module is connected to the data analysis module and sends out an alarm signal according to the results of the data analysis module.

[0012] The data processing method of the intelligent operation control system includes the following steps:

[0013] Step S1, data collection, collecting the vibration data of the pipeline during operation through the data collection module, the collected data including the intensity and frequency of ground vibration; and calculating the environmental parameters of pipeline vibration through the collected data;

[0014] Step S2, judging according to the environmental parameters calculated in step S1, if the environmental parameters are less than the set environmental parameter threshold, it is considered that there is no interference, and if the environmental parameters are greater than the set environmental parameter threshold, it is considered that there is interference;

[0015] Step S3, establishing a corresponding detection model according to the interference type determined in step S2, and determining whether the pipeline is abnormal;

[0016] Step S4: When the data analysis module determines that there is an abnormality in the pipeline vibration signal, the alarm module sends an alarm signal, and the monitoring module collects video data of the abnormal position of the pipeline.

[0017] According to the above technical solution, in step S1, the parameters affecting the external environment of the pipeline are calculated as follows:

[0018]

[0019] Where A represents the external environment impact parameter of the pipeline, I represents the ground vibration intensity, and I x represents the preset threshold of ground vibration intensity; α represents the weight coefficient of ground vibration intensity; F represents the ground vibration frequency, F x It represents the preset threshold value of ground vibration frequency, and β represents the weight coefficient of surface vibration frequency.

[0020] According to the above technical solution, in step S3, the corresponding detection model is established according to the interference type as follows:

[0021] If there is no interference, the vibration data of the pipeline is collected by a plurality of pipeline vibration collection sensors arranged on the pipeline, and the vibration waveform image data of the pipeline is constructed by a data analysis module, and the vibration waveform image data of the pipeline is compared with the vibration waveform image data of the adjacent pipeline to determine whether the sudden change difference between the vibration waveform image data of the pipeline and the vibration waveform image data of the adjacent pipeline is greater than a predetermined threshold value. If so, the data analysis module determines that the vibration waveform image data of the pipeline is sudden change waveform image data;

[0022] If there is interference, it is considered that the interference caused by environmental vibration has an impact on the pipeline, and it is necessary to collect pipeline vibration data and ground vibration data through pipeline vibration collection sensors and ground vibration collection sensors respectively. The data analysis module constructs pipeline vibration waveform data images and ground vibration waveform data images based on the collected pipeline vibration data and ground vibration data;

[0023] The characteristic amplitude is determined according to the amplitude of the wave peak in the ground vibration waveform data image, and the pipeline vibration waveform data image is screened according to the characteristic amplitude to determine whether the vibration signal of the pipeline vibration waveform image is abnormal.

[0024] According to the above technical solution, the sudden difference between the vibration waveform image data of the pipeline and the vibration waveform image data of the adjacent pipeline is specifically calculated as:

[0025] Mutation difference = |vibration frequency of adjacent pipelines - vibration frequency of pipelines| / average vibration frequency of pipelines+|vibration amplitude of adjacent pipelines - vibration amplitude of pipelines| / average vibration amplitude of pipelines.

[0026] According to the above technical solution, the characteristic amplitude is determined according to the amplitude of the peak in the ground vibration waveform data image:

[0027] First, the average peak amplitude C of the ground vibration in the ground vibration waveform data image is calculated. The average peak amplitude plus or minus the fluctuation value of the amplitude is the characteristic amplitude, that is, C∈[C+m,Cm]; m represents the fluctuation value;

[0028] After obtaining the characteristic amplitude, the pipeline vibration waveform data image is screened by the characteristic amplitude. If the amplitude of the pipeline vibration waveform data image is within the characteristic amplitude range, it is considered that the pipeline vibration is within the normal range. If not, the pipeline vibration data is considered abnormal.

[0029] According to the above technical solution, the position of the vibration source needs to be determined in step S4, specifically:

[0030] First, determine whether the vibration is generated in the pipeline or caused by an external vibration source; specifically: collect vibration data through the pipeline vibration collection sensor and the ground vibration collection sensor respectively, sort the collected vibration data in the order of collection, and find the vibration point with the highest vibration amplitude; define this point as X1; X1 is the point closest to the vibration source; if the X1 collected by the pipeline vibration collection sensor and the ground vibration collection sensor are on the same straight line, it is considered that the vibration source is inside the pipeline, and the alarm module prompts that a vibration source appears inside the pipeline; if not, the vibration source needs to be defined as X0;

[0031] Find an adjacent detection point X on the optical fiber i , X i The distance from X1 is d; determine the location of the vibration source, specifically:

[0032]

[0033] Where L represents the distance between the vibration source and the optical fiber sensor, and d represents the distance between X1 and X i v represents the propagation speed of the vibration signal in the soil, △t represents the distance between the vibration source and X1. i time difference.

[0034] According to the above technical solution, the surroundings are scanned within a certain range with the vibration point X1 as the center to determine whether there are other vibration sources within the range; if there are other vibration sources within the scanning range, the vibration point with the highest vibration amplitude is recorded as X2, and the scanned vibration point X2 is taken as the center, and the scanning is continued within a certain range, and the next vibration point Xn is recorded until no new vibration source is scanned; if there are no other vibration sources within the scanning range, the scanning is terminated.

[0035] According to the above technical solution, based on the vibration points obtained by scanning, it is determined whether the spacing between adjacent vibration points is the same. If they are the same, it means that the vibration amplitude between adjacent vibration sources has not changed. It is only necessary to determine the vibration value of one of the vibration sources to confirm whether it exceeds the preset value.

[0036] If they are not the same, it is necessary to judge the vibration values ​​of all vibration sources to confirm whether they exceed the preset values.

[0037] According to the above technical solution, if the number of vibration points is single, it is determined whether the vibration parameter value of the single vibration point exceeds the preset value. When it is determined that the vibration parameter value of the single vibration point exceeds the preset value, the alarm module issues an alarm message indicating that the position of the vibration point in the pipeline is abnormal, and monitors the position of the vibration point through the monitoring module.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] Through the system of the present invention, the pipeline conditions can be monitored in real time, including monitoring pipeline vibration data and ground vibration data. These data can be processed by the data analysis module to determine whether there are abnormal conditions in the pipeline. Once the system detects an abnormality in the pipeline, the alarm module will send out an alarm signal in time to help operators respond quickly, reduce the possibility of accidents, and ensure the safe and stable operation of the pipeline system. Overall, the intelligent operation and control system can improve the reliability and safety of pipeline operation and reduce operational risks. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Embodiment 1

[0042] Intelligent operation and control system, including monitoring module, data analysis module, data acquisition module and alarm module;

[0043] A monitoring module, which includes several video data acquisition devices arranged in the pipe gallery and is used to monitor the pipeline;

[0044] The data acquisition module includes a plurality of pipeline vibration acquisition sensors arranged on the pipeline, the pipeline vibration acquisition sensors are used to collect pipeline vibration data, and a ground vibration acquisition sensor arranged directly below the pipeline for collecting ground vibration data;

[0045] The data analysis module is connected to the monitoring module and the data acquisition module respectively; the data analysis module is used to construct the pipeline vibration waveform image data and the ground vibration waveform image data; and judge whether the pipeline is abnormal according to the pipeline vibration waveform image and the ground vibration waveform image;

[0046] The alarm module is connected to the data analysis module and sends out an alarm signal according to the results of the data analysis module.

[0047] Through the system of the present invention, the pipeline conditions can be monitored in real time, including monitoring pipeline vibration data and ground vibration data. These data can be processed by the data analysis module to determine whether there are abnormal conditions in the pipeline. Once the system detects an abnormality in the pipeline, the alarm module will send out an alarm signal in time to help operators respond quickly, reduce the possibility of accidents, and ensure the safe and stable operation of the pipeline system. Overall, the intelligent operation and control system can improve the reliability and safety of pipeline operation and reduce operational risks.

[0048] In this embodiment, the data processing method of the intelligent operation control system includes the following steps:

[0049] Step S1, data collection, collecting the vibration data of the pipeline during operation through the data collection module, the collected data including the intensity and frequency of ground vibration; and calculating the environmental parameters of pipeline vibration through the collected data;

[0050] Step S2, judging according to the environmental parameters calculated in step S1, if the environmental parameters are less than the set environmental parameter threshold, it is considered that there is no interference, and if the environmental parameters are greater than the set environmental parameter threshold, it is considered that there is interference;

[0051] When the interference in the environment is transmitted to the pipeline, since the pipeline vibration collection sensor is directly installed on the pipeline, if the interference in the environment is not judged, the vibration generated in the environment will be superimposed on the pipeline, resulting in misjudgment of the vibration.

[0052] Step S3, establishing a corresponding detection model according to the interference type determined in step S2, and determining whether the pipeline is abnormal;

[0053] Step S4: When the data analysis module determines that there is an abnormality in the pipeline vibration signal, the alarm module sends an alarm signal, and the monitoring module collects video data of the abnormal position of the pipeline.

[0054] In step S1, the parameters affecting the external environment of the pipeline are calculated as follows:

[0055]

[0056] Where A represents the external environment impact parameter of the pipeline, I represents the ground vibration intensity, and I x represents the preset threshold of ground vibration intensity; α represents the weight coefficient of ground vibration intensity; F represents the ground vibration frequency, F x It represents the preset threshold value of ground vibration frequency, and β represents the weight coefficient of surface vibration frequency.

[0057] In this embodiment, the value of α is set to 0.1 to 0.3, preferably, α=0.2; the value of β is set to 0.35 to 0.55, preferably, β=0.4.

[0058] In step S3, the corresponding detection model is established according to the interference type:

[0059] If there is no interference, the vibration data of the pipeline is collected by a plurality of pipeline vibration collection sensors arranged on the pipeline, and the vibration waveform image data of the pipeline is constructed by a data analysis module, and the vibration waveform image data of the pipeline is compared with the vibration waveform image data of the adjacent pipeline to determine whether the sudden change difference between the vibration waveform image data of the pipeline and the vibration waveform image data of the adjacent pipeline is greater than a predetermined threshold value. If so, the data analysis module determines that the vibration waveform image data of the pipeline is sudden change waveform image data;

[0060] If there is interference, it is considered that the interference caused by environmental vibration has an impact on the pipeline, and it is necessary to collect pipeline vibration data and ground vibration data through pipeline vibration collection sensors and ground vibration collection sensors respectively. The data analysis module constructs pipeline vibration waveform data images and ground vibration waveform data images based on the collected pipeline vibration data and ground vibration data;

[0061] The characteristic amplitude is determined according to the amplitude of the wave peak in the ground vibration waveform data image, and the pipeline vibration waveform data image is screened according to the characteristic amplitude to determine whether the vibration signal of the pipeline vibration waveform image is abnormal.

[0062] The specific calculation of the sudden difference between the vibration waveform image data of the pipeline and the vibration waveform image data of the adjacent pipeline is:

[0063] Mutation difference = |vibration frequency of adjacent pipelines - vibration frequency of pipelines| / average vibration frequency of pipelines+|vibration amplitude of adjacent pipelines - vibration amplitude of pipelines| / average vibration amplitude of pipelines.

[0064] The characteristic amplitude is determined according to the amplitude of the peak in the ground vibration waveform data image:

[0065] First, the average peak amplitude C of the ground vibration in the ground vibration waveform data image is calculated. The average peak amplitude plus or minus the fluctuation value of the amplitude is the characteristic amplitude, that is, C∈[C+m,Cm]; m represents the fluctuation value;

[0066] In this embodiment, the fluctuation value m is set to 1 / 8C to 1 / 12C.

[0067] After obtaining the characteristic amplitude, the pipeline vibration waveform data image is screened by the characteristic amplitude. If the amplitude of the pipeline vibration waveform data image is within the characteristic amplitude range, it is considered that the pipeline vibration is within the normal range. If not, the pipeline vibration data is considered abnormal.

[0068] In this embodiment, since it has been determined whether there is an abnormality in the pipeline, when there is abnormal vibration in the pipeline, it is necessary to further determine the vibration source, so that the monitoring module can monitor the abnormal point and realize key monitoring of the pipeline, thereby improving the utilization rate of pipeline monitoring and thus improving the monitoring effect.

[0069] In step S4, the position of the vibration source needs to be determined, specifically:

[0070] First, determine whether the vibration is generated in the pipeline or caused by an external vibration source; specifically: collect vibration data through the pipeline vibration collection sensor and the ground vibration collection sensor respectively, sort the collected vibration data in the order of collection, and find the vibration point with the highest vibration amplitude; define this point as X1; X1 is the point closest to the vibration source; if the X1 collected by the pipeline vibration collection sensor and the ground vibration collection sensor are on the same straight line, it is considered that the vibration source is inside the pipeline, and the alarm module prompts that a vibration source appears inside the pipeline; if not, the vibration source needs to be defined as X0;

[0071] Find an adjacent detection point X on the optical fiber i , X i The distance from X1 is d; determine the location of the vibration source, specifically:

[0072]

[0073] Where L represents the distance between the vibration source and the optical fiber sensor, and d represents the distance between X1 and X i v represents the propagation speed of the vibration signal in the soil, △t represents the distance between the vibration source and X1. i time difference.

[0074] Scan the surroundings within a certain range with the vibration point X1 as the center to determine whether there are other vibration sources within the range; if there are other vibration sources within the scanning range, record the vibration point with the highest vibration amplitude as X2, and continue scanning within a certain range with the scanned vibration point X2 as the center, and record the next vibration point Xn until no new vibration source is scanned; if there are no other vibration sources within the scanning range, end the scan.

[0075] According to the vibration points obtained by scanning, it is determined whether the spacing between adjacent vibration points is the same. If the spacing is the same, it means that the vibration amplitude between adjacent vibration sources has not changed. It is only necessary to determine the vibration value of one of the vibration sources to confirm whether it exceeds the preset value.

[0076] If they are not the same, it is necessary to judge the vibration values ​​of all vibration sources to confirm whether they exceed the preset values.

[0077] If the number of vibration points is single, it is determined whether the vibration parameter value of the single vibration point exceeds the preset value. When it is determined that the vibration parameter value of the single vibration point exceeds the preset value, the alarm module issues an alarm message indicating that the position of the vibration point in the pipeline is abnormal, and monitors the position of the vibration point through the monitoring module.

[0078] The data processing of the present invention further comprises the following steps:

[0079] 1. Data processing. The collected data must be a real-time data stream with diverse formats and huge volume. In the data processing stage, it needs to be processed by the data processing framework in the big data ecosystem, such as Spark and Storm. The main purpose of this stage is to deduplicate, format, and process the data, and finally form useful data in a unified format.

[0080] 2. Formatting: Data formatting refers to unifying the format of collected data to facilitate subsequent processing. For example, JSON format is a more common format at present. Most API query results are returned in JSON format, and most collection tools, such as Logstash, can also easily convert the format.

[0081] filter{

[0082] json{

[0083] source=>"message"}

[0084] }

[0085] As mentioned above, you can easily convert the format into JSON by adding a few lines of code to the Logstash filter plugin.

[0086] 3. Processing: After data formatting, it is necessary to process the data. For example, common timestamps and version information. If this information is retained, each piece of data will be unique, and subsequent deduplication work will not be possible. Therefore, this information must be removed.

[0087] By adding the above code to the filter plug-in, the timestamp and version information can be removed. If there is other information that will affect the deduplication work, it can also be removed at this stage. The formatted and processed data is temporarily stored in Elasticsearch.

[0088] 4. Deduplication: The processed data is sent to Spark or Storm for deduplication. The purpose of deduplication is to reduce the amount of data output in the end. Data collection tools continuously collect data from various places. If deduplication is not done, a large amount of duplicate and useless information will be stored in the system. There are many ways to deduplicate, and the common methods are:

[0089] 1) Use a third-party database to remove duplicates.

[0090] 2) Perform MD5 or HASH operation on the data and save it, and determine whether the data is repeated by calculating the MD5 value or HASH value.

[0091] 3) BitMap method: Create a BitSet and map each URL to a certain bit through a hash function.

[0092] Since the collected data has been converted into JSON format during the formatting and processing stage, the streaming processing framework can be integrated with the third-party database Redis to complete deduplication.

[0093] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0094] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. Intelligent operation and control system, characterized by: Including monitoring module, data analysis module, data acquisition module and alarm module; A monitoring module, which includes several video data acquisition devices arranged in the pipe gallery and is used to monitor the pipeline; The data acquisition module includes a plurality of pipeline vibration acquisition sensors arranged on the pipeline, the pipeline vibration acquisition sensors are used to acquire pipeline vibration data, and a ground vibration acquisition sensor is arranged directly below the pipeline to acquire ground vibration data; The data analysis module is connected to the monitoring module and the data acquisition module respectively; the data analysis module is used to construct the pipeline vibration waveform image data and the ground vibration waveform image data; and judge whether the pipeline is abnormal according to the pipeline vibration waveform image and the ground vibration waveform image; The alarm module is connected with the data analysis module and sends out an alarm signal according to the result of the data analysis module.

2. A data processing method for an intelligent operation and control system, characterized in that: Using the intelligent operation and control system described in claim 1, the data processing method of the intelligent operation and control system comprises the following steps: Step S1, data collection, collecting the vibration data of the pipeline during operation through the data collection module, the collected data including the intensity and frequency of ground vibration; and calculating the environmental parameters of pipeline vibration through the collected data; Step S2, judging according to the environmental parameters calculated in step S1, if the environmental parameters are less than the set environmental parameter threshold, it is considered that there is no interference, and if the environmental parameters are greater than the set environmental parameter threshold, it is considered that there is interference; Step S3, establishing a corresponding detection model according to the interference type determined in step S2, and determining whether the pipeline is abnormal; Step S4: When the data analysis module determines that there is an abnormality in the pipeline vibration signal, the alarm module sends an alarm signal, and the monitoring module collects video data of the abnormal position of the pipeline.

3. The data processing method of the intelligent operation control system according to claim 2, characterized in that: In step S1, the parameters affecting the external environment of the pipeline are calculated as follows: Where A represents the external environment impact parameter of the pipeline, I represents the ground vibration intensity, and I x represents the preset threshold of ground vibration intensity; α represents the weight coefficient of ground vibration intensity; F represents the ground vibration frequency, F x It represents the preset threshold value of the ground vibration frequency, and β represents the weight coefficient of the surface vibration frequency.

4. The data processing method of the intelligent operation control system according to claim 2, characterized in that: In step S3, the corresponding detection model is established according to the interference type: If there is no interference, the vibration data of the pipeline is collected by a plurality of pipeline vibration collection sensors arranged on the pipeline, and the vibration waveform image data of the pipeline is constructed by a data analysis module, and the vibration waveform image data of the pipeline is compared with the vibration waveform image data of the adjacent pipeline to determine whether the sudden change difference between the vibration waveform image data of the pipeline and the vibration waveform image data of the adjacent pipeline is greater than a predetermined threshold value. If so, the data analysis module determines that the vibration waveform image data of the pipeline is sudden change waveform image data; If there is interference, it is considered that the interference caused by environmental vibration has an impact on the pipeline, and it is necessary to collect pipeline vibration data and ground vibration data through pipeline vibration collection sensors and ground vibration collection sensors respectively. The data analysis module constructs pipeline vibration waveform data images and ground vibration waveform data images based on the collected pipeline vibration data and ground vibration data; The characteristic amplitude is determined according to the amplitude of the wave peak in the ground vibration waveform data image, and the pipeline vibration waveform data image is screened according to the characteristic amplitude to determine whether the vibration signal of the pipeline vibration waveform image is abnormal.

5. The data processing method of the intelligent operation control system according to claim 4, characterized in that: The specific calculation of the sudden difference between the vibration waveform image data of the pipeline and the vibration waveform image data of the adjacent pipeline is: Mutation difference = |vibration frequency of adjacent pipelines - vibration frequency of pipelines| / average vibration frequency of pipelines+|vibration amplitude of adjacent pipelines - vibration amplitude of pipelines| / average vibration amplitude of pipelines.

6. The data processing method of the intelligent operation control system according to claim 4, characterized in that: The characteristic amplitude is determined according to the amplitude of the peak in the ground vibration waveform data image: First, the average peak amplitude C of the ground vibration in the ground vibration waveform data image is calculated. The average peak amplitude plus or minus the fluctuation value of the amplitude is the characteristic amplitude, that is, C∈[C+m,Cm]; m represents the fluctuation value; After obtaining the characteristic amplitude, the pipeline vibration waveform data image is screened by the characteristic amplitude. If the amplitude of the pipeline vibration waveform data image is within the characteristic amplitude range, it is considered that the pipeline vibration is within the normal range. If not, the pipeline vibration data is considered abnormal.

7. The data processing method of the intelligent operation control system according to claim 2, characterized in that: In step S4, the position of the vibration source needs to be determined, specifically: First, determine whether the vibration is generated in the pipeline or caused by an external vibration source; specifically: collect vibration data through the pipeline vibration collection sensor and the ground vibration collection sensor respectively, sort the collected vibration data in the order of collection, and find the vibration point with the highest vibration amplitude; define this point as X1; X1 is the point closest to the vibration source; if the X1 collected by the pipeline vibration collection sensor and the ground vibration collection sensor are on the same straight line, it is considered that the vibration source is inside the pipeline, and the alarm module prompts that a vibration source appears inside the pipeline; if not, the vibration source needs to be defined as X0; Find an adjacent detection point X on the optical fiber i , X i The distance from X1 is d; determine the location of the vibration source, specifically: Where L represents the distance between the vibration source and the optical fiber sensor, and d represents the distance between X1 and X i v represents the propagation speed of the vibration signal in the soil, △t represents the distance between the vibration source and X1. i time difference.

8. The data processing method of the intelligent operation control system according to claim 7, characterized in that: Scan the surroundings within a certain range with the vibration point X1 as the center to determine whether there are other vibration sources within the range; if there are other vibration sources within the scanning range, record the vibration point with the highest vibration amplitude as X2, and continue scanning within a certain range with the scanned vibration point X2 as the center, and record the next vibration point Xn until no new vibration source is scanned; if there are no other vibration sources within the scanning range, end the scan.

9. The data processing method of the intelligent operation control system according to claim 8, characterized in that: According to the vibration points obtained by scanning, it is determined whether the spacing between adjacent vibration points is the same. If the spacing is the same, it means that the vibration amplitude between adjacent vibration sources has not changed. It is only necessary to determine the vibration value of one of the vibration sources to confirm whether it exceeds the preset value. If they are not the same, it is necessary to judge the vibration values ​​of all vibration sources to confirm whether they exceed the preset values.

10. The data processing method of the intelligent operation control system according to claim 9, characterized in that: If the number of vibration points is single, it is determined whether the vibration parameter value of the single vibration point exceeds the preset value. When it is determined that the vibration parameter value of the single vibration point exceeds the preset value, the alarm module issues an alarm message indicating that the position of the vibration point in the pipeline is abnormal, and monitors the position of the vibration point through the monitoring module.

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