Pipeline integrity monitoring device and method

Abstract

The invention provides a pipeline integrity monitoring device and method.The monitoring device comprises a data collection module, a data processing module, a communication module and a monitoring algorithm module, the data collection module sends collected data to the data processing module, and the data processing module is electrically connected with the communication module; the data processing module sends processed data to the monitoring algorithm module through the communication module, an algorithm model is established in the monitoring algorithm module through the AI technology, the received data are imported into the established algorithm model, stress data are obtained and compared with a normal value, and whether the pipeline is complete or not is judged. Based on the learning capability of the AI algorithm, monitoring precision and reliability are continuously optimized and improved in actual operation, the position of a leakage point and the size of a leakage problem can be rapidly fed back, a pipeline leakage event can be timely found and controlled, loss is reduced to the minimum, maintenance personnel can rapidly adopt a proper maintenance scheme, and the maintenance efficiency is improved. And the problem of the pipeline is timely and effectively fed back.

Description

Technical Field

[0001] The present invention belongs to the technical field of pipeline monitoring, and in particular relates to a pipeline integrity monitoring device and method. Background Art

[0003] The existing patent (Announcement No.: CN108679455A) pipeline leakage monitoring device and pipeline leakage monitoring method, this patent has two adjacent leakage detection components arranged at equal intervals, which can detect the leakage of the pipeline being tested between them outside the pipeline without destroying the internal structure of the pipeline. When a leak occurs, the detection range can be effectively reduced. The setting of the management device makes the signal transmission more convenient and faster, and can timely obtain the leakage situation and the landfill depth information, pipe diameter information, longitude and latitude information of the pipeline being tested. The power-off unit cuts off the power supply of the leakage detection component after the alarm unit sends an alarm signal, which can prevent safety accidents caused by fluid leakage to a greater extent. However, in the face of mixed transportation of oil and gas in the pipeline, and when the pipeline has a large elevation difference and is not fully transported, the leakage situation cannot be effectively fed back, and the leakage location cannot be quickly inferred, which has the problem of limited applicable working conditions for pipeline management. Summary of the invention

[0004] The purpose of the present invention is to provide a pipeline integrity monitoring device to overcome the above technical problems existing in the prior art.

[0005] Another object of the present invention is to provide a pipeline integrity monitoring method, which is based on the learning ability of the AI ​​algorithm, is continuously optimized in actual operation, and continuously improves the monitoring accuracy and reliability. It can quickly feedback the location of the leakage point and the size of the leakage problem, which is conducive to maintenance personnel to quickly adopt appropriate maintenance plans, timely and effectively feedback pipeline problems, and timely discover and control pipeline leakage incidents, thereby minimizing losses.

[0006] To this end, the technical solution provided by the present invention is as follows: A pipeline integrity monitoring device comprises a data acquisition module, a data processing module, a communication module and a monitoring algorithm module, wherein the data acquisition module sends the collected data to the data processing module, the data processing module is electrically connected to the communication module, the data processing module sends the processed data to the monitoring algorithm module through the communication module, the monitoring algorithm module adopts AI technology to establish an algorithm model, imports the received data into the established algorithm model, obtains stress data and compares it with normal values, and judges whether the pipeline is intact. The data acquisition module includes a displacement detection module, a pump frequency detection module, a pressure detection module, a flow meter and a pressure transmitter.

[0007] The displacement detection module is a turbine displacement detector, and the displacement detection modules are respectively installed at the head and tail ends of the pipeline.

[0008] A pump body is installed at both the first and second ends of the pipeline. The pump frequency detection module is arranged in the pump body. The pump frequency detection module is a multimeter electrically connected to the pump body.

[0009] The pressure detection module tube is a pipeline air pressure sensor, and a plurality of pipeline air pressure sensors are arranged at equal intervals in the pipeline.

[0010] The flow meter is installed at the beginning and end and the middle of the pipeline. The flow meter is used to detect the total amount of fluid in the pipeline in a certain time interval. The flow meter detects the total amount of fluid in the pipeline in a certain time interval to form flow data.

[0011] The pressure transmitter is installed at the beginning, end and middle of the pipeline, and converts the pressure parameters of the liquid in the pipeline into a standard electrical signal.

[0012] A pipeline integrity monitoring method, using a pipeline integrity monitoring device, comprises the following steps: Step 1) The displacement detection module, pump frequency detection module, pressure detection module, flow meter and pressure transmitter respectively upload the displacement data, pump frequency data, air pressure data, flow data and hydraulic data to the data processing module in real time; Step 2) The data processing module integrates and processes the data and uploads it to the monitoring algorithm module, imports it into the algorithm model, calculates the stress according to the pipeline hoop stress algorithm, and compares it with the set value to determine whether the pipeline is intact; Step 3) When it is determined that the pipeline is incomplete and leaking, check the data of each air pressure sensor to find the leak point.

[0013] In step 2), each data forms an algorithm training sample, and each data sample is optimized by comparing the training results of the monitoring algorithm module with the operating conditions of the pipeline.

[0014] The beneficial effects of the present invention are: The present invention is based on the learning ability of the AI ​​algorithm, and is continuously optimized in actual operation to continuously improve monitoring accuracy and reliability. It can quickly feedback the location of the leakage point and the size of the leakage problem, and timely discover and control pipeline leakage incidents, minimize losses, and help maintenance personnel quickly adopt appropriate maintenance plans and promptly and effectively feedback pipeline problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a principle block diagram of the present invention; Figure 2 It is a specific implementation block diagram of the present invention. DETAILED DESCRIPTION

[0016] The following describes the implementation of the present invention through specific embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification.

[0017] The exemplary embodiments of the present invention are now described with reference to the accompanying drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. These embodiments are provided to disclose the present invention in detail and completely and to fully convey the scope of the present invention to those skilled in the art. The terms used in the exemplary embodiments shown in the accompanying drawings are not intended to limit the present invention.

[0018] Unless otherwise specified, the terms (including technical terms) used herein have the commonly understood meanings to those skilled in the art. In addition, it is understood that the terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0019] Example 1 This embodiment provides a pipeline integrity monitoring device, such as Figure 1 As shown, it includes a data acquisition module, a data processing module, a communication module and a monitoring algorithm module. The data acquisition module sends the collected data to the data processing module. The data processing module is electrically connected to the communication module. The data processing module sends the processed data to the monitoring algorithm module through the communication module. The monitoring algorithm module adopts AI technology to establish an algorithm model, imports the received data into the established algorithm model, obtains stress data and compares it with the normal value to determine whether the pipeline is intact. The present invention collects key parameters related to the pipeline through a data acquisition module, establishes an algorithm model based on AI technology, imports the collected data into the established algorithm model, obtains stress data and compares it with normal values ​​to determine whether the pipeline is intact.

[0020] Example 2 Based on Example 1, this embodiment provides a pipeline integrity monitoring device, such as Figure 2 As shown, the data acquisition module includes a displacement detection module, a pump frequency detection module, a pressure detection module, a flow meter and a pressure transmitter.

[0021] The pipeline displacement, pump frequency data, air pressure in the pipeline, flow rate in the pipeline and liquid pressure in the pipeline are collected respectively through the displacement detection module, pump frequency detection module, pressure detection module, flow meter and pressure transmitter.

[0022] Example 3 On the basis of Example 2, this embodiment provides a pipeline integrity monitoring device, wherein the displacement detection module is a turbine displacement detector, and the displacement detection modules are respectively installed at the head and tail ends of the pipeline.

[0023] The two sets of displacement detection modules are used to detect the displacement at both ends of the pipeline system respectively. The displacement detection modules detect the liquid displacement of the pipelines in the pipeline system to form displacement data, and the displacement data is uploaded to the data processing module.

[0024] The data processing module includes a single-chip processor and a data storage device. The single-chip processor is an AM3354BZCZD80 microprocessor, and the data storage device is an M25P16-VMN6TP SOP-8 memory device, which processes the data information collected from the monitoring device. The communication module is a PN5321A3HN / C106 wireless transceiver.

[0025] Example 4 Based on Example 2, this example provides a pipeline integrity monitoring device, wherein a pump body is installed at both ends of the pipeline, and the pump frequency detection module is disposed in the pump body, and the pump frequency detection module is a multimeter electrically connected to the pump body.

[0026] The pump frequency detection module records the pump frequency of the pump body to form pump frequency data. The multimeter displays the changes in the pump power. The flow rate of the pump is proportional to its operating frequency. As the pump frequency increases, the flow rate will also increase. Conversely, as the pump frequency decreases, the flow rate will also decrease.

[0027] Example 5 On the basis of Example 2, this embodiment provides a pipeline integrity monitoring device, wherein the pressure detection module tube is a pipeline air pressure sensor, and a plurality of pipeline air pressure sensors are arranged at equal intervals in the pipeline.

[0028] Pressure detection modules are set up at equal intervals in the pipelines to detect the air pressure in the pipeline system and form air pressure data. The pipeline air pressure is about 1.15 times the water pressure, and a decrease in pressure indicates a leak in the pipeline system.

[0029] Example 6 Based on Example 2, this example provides a pipeline integrity monitoring device, wherein the flow meter is installed at the head and tail ends and the middle of the pipeline, and the flow meter is used to detect the total amount of fluid in the pipeline in a certain time interval. The flow meter detects the total amount of fluid in the pipeline in a certain time interval to form flow data.

[0030] In this embodiment, the flowmeter is an Owei OW00015 clamp-type wall-mounted liquid ultrasonic flowmeter, which is clamped on the outside of the pipe wall when in use. The flowmeter detects the total amount of fluid in the pipeline during a certain time interval. A sudden decrease or increase in the total amount of fluid indicates a leakage. A sudden decrease indicates a leakage before the flowmeter, and a sudden increase indicates a leakage after the flowmeter.

[0031] Example 7 Based on Example 2, this example provides a pipeline integrity monitoring device, wherein the pressure transmitter is installed at the beginning, end and middle of the pipeline, and the pressure transmitter converts the liquid pressure parameter in the pipeline into a standard electrical signal.

[0032] In this embodiment, the pressure transmitter is a Chaohui PT124B-210 four-wire pressure transmitter, which converts the liquid pressure parameters in the pipeline system into standard electrical signals. Through the change of liquid pressure data, a larger decrease value indicates a larger leakage surface, and a smaller value indicates a smaller leakage area of ​​the leakage point.

[0033] Example 8 This embodiment provides a pipeline integrity monitoring method, using a pipeline integrity monitoring device, including the following steps: Step 1) The displacement detection module, pump frequency detection module, pressure detection module, flow meter and pressure transmitter respectively upload the displacement data, pump frequency data, air pressure data, flow data and hydraulic data to the data processing module in real time; Step 2) The data processing module integrates and processes the data and uploads it to the monitoring algorithm module, imports it into the algorithm model, calculates the stress according to the pipeline hoop stress algorithm, and compares it with the set value to determine whether the pipeline is intact; Step 3) When it is determined that the pipeline is incomplete and leaking, check the data of each air pressure sensor to find the leak point.

[0034] In step 2), each data forms an algorithm training sample, and each data sample is optimized by comparing the training results of the monitoring algorithm module with the operating conditions of the pipeline.

[0035] The monitoring algorithm module uses AI technology to establish an algorithm model. At the same time, the algorithm adopts the pipeline annular stress algorithm. The data collected by the monitoring device is imported into the established algorithm model to obtain the stress data.

[0036] The algorithm model uses a calculation formula for rapid measurement. The calculation formula for pipeline annular stress is: f=PD / (2t); In the formula: f is the hoop stress, Pa; P is the pressure inside the pipe, Pa; D is the pipe diameter, mm; t is the pipe wall thickness, mm.

[0037] The pressure in the pipeline indicated by P is the comprehensive data provided by the data acquisition module. If a leak occurs at a certain point in the unit length of the pipeline, the data collected in the data acquisition module will also change accordingly. For example, the displacement detection module installed at the beginning and end collects the flow data of the inlet and outlet ends through the turbine displacement detector.

[0038] The pressure detection modules are arranged in the pipeline in several groups at equal distances according to a certain adjacent spacing. When a leak occurs in one or more places, the leak point can be determined by checking the air pressure sensor at the data fluctuation point. At the same time, the data detected by several groups of air pressure sensors in a unit length of pipeline must be relatively average, and the average value of the detected values ​​is an important reference for pipeline pressure.

[0039] The flowmeter detects the total amount of fluid in the pipeline in a certain time interval, because the relationship between pressure and flow in the pipeline is directly proportional, that is, the greater the pressure, the greater the flow. For any section of the pipeline, the pressure only comes from one end, that is, the direction of the pressure is unidirectional. When the outlet in the pressure direction is closed (the valve is closed), the fluid in the pipe is in a prohibited state. Once the outlet is opened, its flow rate depends on the pressure in the pipeline.

[0040] The pump frequency detection module is mainly used to detect whether the pump power is in a normal working state at this time, because if there is a problem with the pump body, it will also affect the flow change in the pipeline. If it works normally, it means that other detected data are not affected by the pump body; Pressure transmitter is a device that converts pressure into pneumatic or electric signals for control and remote transmission. It has functions such as automatic compensation, communication, self-diagnosis, and logical judgment, and is more suitable for integration. It is usually installed at the pipe transfer or docking position. It can convert the mechanical signal of water pressure into an electronic signal such as current. The pressure and voltage or current are linearly related, generally proportional. Therefore, the voltage or current output by the transmitter increases with the increase of pressure, and can withstand pressure changes with larger flow rates.

[0041] The internal pressure exerted by the medium in the pipeline or the inertial force generated by the flow of the internal medium is stress. Its magnitude changes with the changes in the medium, flow rate and pressure in the pipeline, reflecting the changes in the working state of the medium inside the pipeline and the integrity of the pipeline.

[0042] Based on the above collected data, when the detection data of the displacement detection module, pump frequency detection module, flow meter and pressure detection transmitter tend to the normal average value, the detection data of the pressure detection module should be normal. The normal value can be obtained by substituting it into the above pipeline annular stress calculation formula. Based on the normal value as a reference, the stress data after the change is detected to reflect whether the integrity of the pipeline is normal, and the monitoring algorithm module needs to be continuously trained in the later stage.

[0043] The above examples are merely illustrative of the present invention and do not constitute a limitation on the protection scope of the present invention. All designs that are the same or similar to the present invention fall within the protection scope of the present invention.

Claims

1. A pipeline integrity monitoring device, characterized in that: It includes a data acquisition module, a data processing module, a communication module and a monitoring algorithm module. The data acquisition module sends the collected data to the data processing module. The data processing module is electrically connected to the communication module. The data processing module sends the processed data to the monitoring algorithm module through the communication module. The monitoring algorithm module uses AI technology to establish an algorithm model, imports the received data into the established algorithm model, obtains stress data and compares it with the normal value to determine whether the pipeline is intact.

2. A pipeline integrity monitoring device according to claim 1, characterized in that: The data acquisition module includes a displacement detection module, a pump frequency detection module, a pressure detection module, a flow meter and a pressure transmitter.

3. A pipeline integrity monitoring device according to claim 2, characterized in that: The displacement detection module is a turbine displacement detector, and the displacement detection modules are respectively installed at the head and tail ends of the pipeline.

4. A pipeline integrity monitoring device according to claim 3, characterized in that: A pump body is installed at both the first and second ends of the pipeline. The pump frequency detection module is arranged in the pump body. The pump frequency detection module is a multimeter electrically connected to the pump body.

5. A pipeline integrity monitoring device according to claim 2, characterized in that: The pressure detection module tube is a pipeline air pressure sensor, and a plurality of pipeline air pressure sensors are arranged at equal intervals in the pipeline.

6. A pipeline integrity monitoring device according to claim 2, characterized in that: The flow meter is installed at the beginning and end and the middle of the pipeline. The flow meter is used to detect the total amount of fluid in the pipeline in a certain time interval. The flow meter detects the total amount of fluid in the pipeline in a certain time interval to form flow data.

7. A pipeline integrity monitoring device according to claim 2, characterized in that: The pressure transmitter is installed at the beginning, end and middle of the pipeline, and converts the pressure parameters of the liquid in the pipeline into a standard electrical signal.

8. A pipeline integrity monitoring method, using the pipeline integrity monitoring device according to claim 5, characterized in that: The following steps are involved: Step 1) The displacement detection module, pump frequency detection module, pressure detection module, flow meter and pressure transmitter respectively upload the displacement data, pump frequency data, air pressure data, flow data and hydraulic data to the data processing module in real time; Step 2) The data processing module integrates and processes the data and uploads it to the monitoring algorithm module, imports it into the algorithm model, calculates the stress according to the pipeline hoop stress algorithm, and compares it with the set value to determine whether the pipeline is intact; Step 3) When it is determined that the pipeline is incomplete and leaking, check the data of each air pressure sensor to find the leak point.

9. A pipeline integrity monitoring method according to claim 8, characterized in that: In step 2), each data forms an algorithm training sample, and each data sample is optimized by comparing the training results of the monitoring algorithm module with the operating conditions of the pipeline.

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