Pipeline active detection early warning system and method

Abstract

The invention provides a pipeline active detection early warning system and method. The system comprises a protective cover, an annular detection robot and an upper computer, a sensor is arranged in the protective cover; the protective cover is used for covering the outside of the pipeline interface, collecting monitoring data of the pipeline interface through an internal sensor and uploading the monitoring data to the upper computer; the annular detection robot is used for crawling along the outer wall of the pipeline, collecting strain data of detection points on the pipeline and uploading the strain data to the upper computer; wherein the detection point comprises a pipeline interface and a pipeline deformation position; and the upper computer is used for identifying the damage risk of the pipeline and performing early warning based on the pipeline category, the monitoring data and the strain data. The leakage risk of the pipeline can be found in advance, and accurate early warning can be carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of fault prediction and health management, and in particular to a pipeline active detection system and method. Background Art

[0002] The underground comprehensive pipeline corridor may include various municipal pipelines such as water supply, rainwater, sewage, recycled water, natural gas, heat, electricity, and communications within the city to meet the needs of life and production. In order to ensure the long-term stable operation of the pipeline system while protecting the environment and public safety, it is necessary to carry out safety monitoring and maintenance of various municipal pipelines.

[0003] However, safety monitoring requires continuous investment of a large amount of materials and modification of the installation environment. The detection range and frequency are fixed, and the breadth of monitoring data is low. During long-term monitoring, the components of the monitoring system may fail, resulting in missed faults. In addition, during the monitoring process, pipeline damage is usually an emergency, and the monitoring facilities can only alarm when or after the pipeline is damaged. At this time, emergency repairs are often time-sensitive. Even if a problem is detected, rapid and effective emergency response may be a challenge. Therefore, through active detection and risk warning, preventive maintenance can be achieved and the frequency and cost of emergency repairs can be reduced. Summary of the invention

[0004] The embodiment of the present invention provides a pipeline active detection and early warning system and method to solve the problem of active detection and risk early warning of pipelines.

[0005] In a first aspect, an embodiment of the present invention provides a pipeline active detection and early warning system, including a protective cover, a ring-shaped detection robot and a host computer; a sensor is arranged inside the protective cover;

[0006] The protective cover is used to cover the outside of the pipeline interface, collect the monitoring data of the pipeline interface through the internal sensor, and upload it to the host computer;

[0007] The ring-shaped detection robot is used to crawl along the outer wall of the pipeline, collect strain data of the detection points on the pipeline, and upload them to the host computer; the detection points include the pipeline interface and the pipeline deformation position;

[0008] The host computer is used to identify pipeline damage risks and issue early warnings based on pipeline categories, monitoring data, and strain data.

[0009] In a possible implementation, there are multiple protective covers; the ring-shaped detection robot includes a distance measurement module;

[0010] The ring detection robot is also used to collect the distance between any two protective covers and upload it to the host computer;

[0011] The host computer is also used to compare the distance between the two protective covers with the historical distance between the two protective covers, and determine whether the pipeline between the two protective covers is deformed based on the comparison result. If deformation occurs, the pipeline area between the two protective covers is set as a detection point.

[0012] In a possible implementation, the sensor in the protective cover includes one or more of a pressure sensor, a temperature sensor, a humidity sensor, a sound sensor, and a gas sensor; the monitoring data includes the gas pressure, temperature, humidity, sound signal, and gas concentration in the protective cover;

[0013] The annular detection robot includes one or more of a strain sensor, a stress sensor, a displacement sensor, a vibration sensor, an electrochemical sensor, a sound sensor, and an optical sensor, and the strain data includes strain amount, stress, displacement, vibration, corrosion, and crack;

[0014] The host computer is specifically used to screen the strain data based on the pipeline category, input the monitoring data and the screened strain data into the risk prediction model corresponding to the pipeline category, obtain the damage risk of the pipeline, and issue an early warning based on the damage risk.

[0015] In a possible implementation, the pipeline category includes pipeline material and pipeline use, the pipeline material includes cast iron, steel pipe, stainless steel, plastic, concrete and fiberglass, and the pipeline use includes water supply, drainage, gas, heating, cooling and industrial fluid;

[0016] The host computer is also used to analyze the correlation between various strain data and pipeline damage of various pipeline materials and pipeline uses before screening the strain data based on pipeline categories, and obtain the strain data category corresponding to each pipeline material and pipeline use.

[0017] In a possible implementation, there are multiple groups of sensors in the protective cover, and each group of sensors is evenly arranged along the longitudinal direction of the protective cover;

[0018] The host computer is also used to analyze the location of leakage points of the pipe interface in the protective cover based on the position and monitoring data of each group of sensors in the protective cover.

[0019] In one possible implementation, the host computer is specifically used to determine at least one high-risk leakage point on the pipe interface in the protective cover based on the interface structure and / or the pipe category, and to determine the groups of sensors corresponding to each high-risk leakage point based on the positional relationship between each group of sensors and each high-risk leakage point, so as to determine the leakage point position of the pipe interface in the protective cover based on the monitoring data of each group of sensors corresponding to each high-risk leakage point.

[0020] In a possible implementation, when the pipeline interface is a steel-plastic conversion joint, the high-risk leakage points include the connection between the metal part of the steel-plastic conversion joint and the steel pipeline, the connection between the plastic part and the plastic pipeline, and the connection between the metal part and the plastic part;

[0021] The upper computer is specifically used to determine that the leakage point position of the pipe interface in the protective cover is the first high-risk leakage point when the monitoring data collected by each group of sensors corresponding to the first high-risk leakage point are all abnormal; wherein the first high-risk leakage point is any high-risk leakage point.

[0022] In a possible implementation, the protective cover further includes a supercapacitor for supplying power to the internal sensor;

[0023] The ring-shaped inspection robot is also used to charge the supercapacitor of the protective cover.

[0024] In a second aspect, an embodiment of the present invention provides a pipeline active detection and early warning method, which is applied to the system of the first aspect or any possible implementation of the first aspect; the method includes:

[0025] The protective cover covers the outside of the pipeline interface, collects monitoring data of the pipeline interface through the internal sensor, and uploads it to the host computer;

[0026] The annular detection robot crawls along the outer wall of the pipeline, collects strain data of the detection points on the pipeline, and uploads it to the host computer; the detection points include the pipeline interface and the pipeline deformation position;

[0027] The host computer identifies pipeline damage risks and issues early warnings based on pipeline categories, monitoring data, and strain data.

[0028] The embodiment of the present invention provides a pipeline active detection and early warning system and method, which uses a protective cover to seal and protect key parts such as interfaces and welds of various municipal pipelines in the pipeline corridor, and uses sensors in the protective cover to continuously monitor the status of the pipeline welds. The mobile sensor carried by the annular detection robot is then used to actively detect the status of the middle section of the pipeline. The status of the pipeline interface and the deformation, corrosion, cracks and other information of the middle section of the pipeline are comprehensively considered to evaluate the pipeline damage and leakage risks, so that the leakage risk of the pipeline can be discovered in advance and accurate early warning can be given. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0030] Figure 1 It is a structural schematic diagram of a pipeline active detection and early warning system provided by an embodiment of the present invention;

[0031] Figure 2 It is a structural schematic diagram of a steel-plastic conversion joint provided by an embodiment of the present invention;

[0032] Figure 3 This is a flow chart of an implementation of a pipeline active detection and early warning method provided by an embodiment of the present invention;

[0033] Figure 4 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0034] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0035] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0036] See also Figure 1 , which shows a schematic diagram of the structure of the pipeline active detection and early warning system provided by an embodiment of the present invention. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0037] The pipeline active detection and early warning system includes a protective cover 11, a ring-shaped detection robot 12 and a host computer 13; a sensor is arranged inside the protective cover 11;

[0038] The protective cover 11 is used to cover the outside of the pipeline interface, collect monitoring data of the pipeline interface through the internal sensor, and upload it to the host computer 13;

[0039] The annular detection robot 12 is used to crawl along the outer wall of the pipeline, collect strain data of detection points on the pipeline, and upload them to the host computer; wherein the detection points include pipeline interfaces and pipeline deformation positions;

[0040] The host computer 13 is used to identify the damage risk of the pipeline and issue an early warning based on the pipeline category, monitoring data and strain data.

[0041] In this embodiment, the protective cover should be made of corrosion-resistant, high and low temperature resistant, and pressure-resistant materials to adapt to the complex underground environment, and should be designed to tightly surround the pipeline while leaving enough space for installing sensors and performing daily maintenance.

[0042] Since the interface of the pipeline is the part that is prone to damage, the sensor in the protective cover is used to monitor the status of the interface in real time to detect leakage in time. The sensors can include the following categories: Pressure sensor: monitors the changes in fluid pressure in the pipeline and the protective cover.

[0043] Flow sensor: detects whether the fluid flow is abnormal.

[0044] Temperature sensor: senses temperature changes of the fluid in the pipeline.

[0045] Sound sensor: Captures abnormal sounds produced when pipes leak.

[0046] Gas sensor: For gas pipelines, it can detect the concentration of leaked gas.

[0047] The sensors should be evenly distributed in the parts of the pipeline where leakage may occur, such as joints, elbows, etc.

[0048] Data acquisition and transmission system:

[0049] Data acquisition: The data collected by the sensors are integrated through the data acquisition unit.

[0050] Data transmission: Data is transmitted to the monitoring center via wired or wireless means.

[0051] Data processing and analysis:

[0052] Data processing: pre-process the collected data, such as filtering, normalization, etc.

[0053] Analytical algorithms: Use machine learning or artificial intelligence algorithms to analyze data and identify leakage patterns.

[0054] Alarm and positioning system:

[0055] Leakage alarm: Once leakage signs are detected, the system will immediately sound an alarm.

[0056] Leak location: Accurately locate the leak point by analyzing the data sent back by different sensors.

[0057] Maintenance and Response:

[0058] Regular inspection: Perform regular inspection and maintenance on the sensor and protective cover.

[0059] Emergency response: Once the leak is confirmed, immediately activate the emergency plan and carry out repairs.

[0060] Implementation Notes:

[0061] Waterproof and moisture-proof: The protective cover and sensor need to have good waterproof and moisture-proof properties.

[0062] Power supply: Ensure a stable power supply to the sensor and the equipment inside the protective cover.

[0063] Anti-interference ability: The system needs to have a certain anti-interference ability to avoid false alarms.

[0064] Through the above points, the operating status of municipal pipelines can be effectively monitored through the sensors in the protective cover, leakage problems can be discovered and dealt with in time, and the safe operation of urban infrastructure can be guaranteed.

[0065] In addition to monitoring municipal pipelines, it is also necessary to actively detect the status of other parts of the pipeline and conduct a comprehensive analysis in combination with the monitoring data collected by sensors to detect pipeline failure trends in advance and achieve risk warning. The ring-shaped detection robot can crawl on the outer wall of the pipeline and collect strain data from the detection points on the pipeline. Specific detection principles may include:

[0066] Ultrasonic Testing (UT): Use ultrasonic technology to detect cracks, slag inclusions and other defects on the surface of pipes and inside welds.

[0067] Magnetic Particle Testing (MT): Detect surface and near-surface defects by gathering magnetic particles on the surface of pipes and welds.

[0068] Penetrant testing (PT): Use penetrants to detect open defects on the surface of pipes and welds.

[0069] Eddy current testing (ET): uses the principle of electromagnetic induction to detect defects on the pipeline surface and near the surface.

[0070] Through the above method, active monitoring of the weld status and overall status of municipal pipelines can be achieved, so as to timely discover potential problems, prevent pipeline leakage or rupture, and ensure the safe operation of the pipeline system.

[0071] The embodiment of the present invention uses a protective cover to seal and protect key parts such as interfaces and welds of various municipal pipelines in the pipeline corridor, and continuously monitors the status of the pipeline welds through sensors in the protective cover. The mobile sensor carried by the annular detection robot is then used to actively detect the status of the middle section of the pipeline. The status of the pipeline interface and the deformation, corrosion, cracks and other information of the middle section of the pipeline are comprehensively considered to evaluate the damage and leakage risks of the pipeline, so as to detect the leakage risk of the pipeline in advance and provide accurate early warning.

[0072] In a possible implementation, there are multiple protective covers; the ring-shaped detection robot includes a distance measurement module;

[0073] The ring detection robot is also used to collect the distance between any two protective covers and upload it to the host computer;

[0074] The host computer is also used to compare the distance between the two protective covers with the historical distance between the two protective covers, and determine whether the pipeline between the two protective covers is deformed based on the comparison result. If deformation occurs, the pipeline area between the two protective covers is set as a detection point.

[0075] In this embodiment, the protective covers can be respectively set in the areas of the pipeline that need special protection, such as pipeline joints, welds, elbows, etc., for continuous protection and status monitoring.

[0076] During use, the pipe body and middle section of the pipeline are less likely to be damaged or leaked, but they may be affected by the environment. For example, after being strained by sedimentation, vibration, etc., the overall shape of the pipeline will change, which may cause the stress at the pipeline interface to increase accordingly, increasing the risk of damage at the interface. Therefore, whether the pipeline is deformed should be used as a factor in selecting the inspection point. Since the joints, welds, elbows and other connection parts of the pipeline have been highly monitored by protective covers, it is only necessary to determine whether the pipeline area between the two protective covers is deformed, which can be determined by the distance between the two protective covers.

[0077] Specific ranging marking points can be set on each protective cover, and the ranging module can be an infrared ranging module. When the pipeline area between the two protective covers is deformed, the part where at least one protective cover is located will be displaced and rotated, and the distance between the ranging marking points on the two protective covers will also change accordingly.

[0078] In addition, when the upper computer determines whether the pipeline between the two protective covers has been deformed, it can also compare the changes in the historical distance between the two protective covers. When the distance between the two protective covers changes suddenly, it means that the pipeline area between the two protective covers has undergone a large deformation in a short period of time. Correspondingly, the risk of pipeline damage is also greater.

[0079] In a possible implementation, the sensor in the protective cover includes one or more of a pressure sensor, a temperature sensor, a humidity sensor, a sound sensor, and a gas sensor; the monitoring data includes the gas pressure, temperature, humidity, sound signal, and gas concentration in the protective cover;

[0080] The annular detection robot includes one or more of a strain sensor, a stress sensor, a displacement sensor, a vibration sensor, an electrochemical sensor, a sound sensor, and an optical sensor, and the strain data includes strain amount, stress, displacement, vibration, corrosion, and crack;

[0081] The host computer is specifically used to screen the strain data based on the pipeline category, input the monitoring data and the screened strain data into the risk prediction model corresponding to the pipeline category, obtain the damage risk of the pipeline, and issue an early warning based on the damage risk.

[0082] In this embodiment, pipelines of different materials and uses have different performances when leaking and being damaged. Selecting appropriate strain data for risk prediction can reduce the amount of data processing of the prediction model and ensure the accuracy of the prediction results.

[0083] The principles for using various monitoring data for damage risk prediction include:

[0084] 1. Temperature monitoring data: Monitor the temperature changes at the pipeline interface to evaluate the impact of thermal stress and thermal expansion on the interface.

[0085] 2. Pressure monitoring data: Real-time monitoring of pressure changes at pipeline interfaces to assess the potential impact of fluid pressure on interfaces.

[0086] 3. Leakage monitoring data: Evaluate the sealing performance of the interface by detecting gas or liquid leakage.

[0087] 4. Corrosion monitoring data: Monitor the corrosion rate and environmental conditions at the pipeline interface to predict the impact of corrosion on the interface.

[0088] 5. Acoustic emission monitoring data: Monitor the health of the interface by capturing the sound waves generated by crack propagation or other structural changes inside the material.

[0089] 6. Optical monitoring data: Use optical sensors to monitor deformation or cracks in the interface.

[0090] According to the type and characteristics of the pipeline, the parameters that characterize the strain state of the pipeline can also be selected from the following parameters:

[0091] Internal pressure: The pressure of the fluid inside the pipe.

[0092] External pressure: The pressure of the soil outside the pipeline or the external load.

[0093] Temperature: The temperature change of the pipeline during operation.

[0094] Displacement / deformation: displacement or deformation of the pipeline during use.

[0095] Corrosion degree: the corrosion condition of the inner or outer wall of the pipeline.

[0096] Cracks / Defects: Cracks or defects in the pipe material.

[0097] Vibration frequency: The frequency at which a pipe responds to fluid flow or external vibration.

[0098] Soil environment: the impact of soil moisture, pH, texture, etc. on pipelines.

[0099] Then collect historical data of the above parameters, including design information, monitoring data, maintenance records, etc., and establish a risk assessment model using the following methods:

[0100] Statistical analysis: Analyze the relationship between various parameters and pipeline damage through historical data.

[0101] Mechanism model: A calculation model of pipeline stress is established based on the principles of material mechanics, structural mechanics, etc.

[0102] Machine Learning: Use data-driven methods such as random forests, support vector machines, neural networks, etc. to train damage prediction models.

[0103] Finally, the monitoring data and screened strain data are input into the risk prediction model corresponding to the pipeline category to predict the risk of pipeline damage in the future. Based on the prediction results, the risk level of the pipeline is evaluated and a corresponding maintenance or replacement plan is formulated.

[0104] The gas type monitored by the gas sensor in the protective cover can be a gas that is easily soluble in water or a fluid transported in a pipeline. A change in gas concentration indicates water leakage at the interface, or it can be the concentration of a gas marker.

[0105] In a possible implementation, the pipeline category includes pipeline material and pipeline use, the pipeline material includes cast iron, steel pipe, stainless steel, plastic, concrete and fiberglass, and the pipeline use includes water supply, drainage, gas, heating, cooling and industrial fluid;

[0106] The host computer is also used to analyze the correlation between various strain data and pipeline damage of various pipeline materials and pipeline uses before screening the strain data based on pipeline categories, and obtain the strain data category corresponding to each pipeline material and pipeline use.

[0107] In this embodiment, statistical methods such as Pearson correlation coefficient and Spearman rank correlation coefficient can be used to evaluate the linear or nonlinear relationship between strain data and pipeline damage, or to establish a regression model between strain data and pipeline damage to evaluate the predictive ability of strain data on damage risk, thereby determining the strain data category corresponding to each pipeline material and pipeline use. The staff can also set the strain data category corresponding to each pipeline material and pipeline use based on experience.

[0108] For example, when the pipe material is cast iron and the pipe purpose is water supply or drainage, the strain data can include strain, stress, displacement, vibration, and heat flux density;

[0109] When the pipe is made of steel or stainless steel and is used for water supply, drainage or high-pressure gas, the strain data includes stress, displacement and vibration;

[0110] When the pipe is used for heating or cooling, the strain data includes strain, stress, displacement, vibration, and heat flux density;

[0111] When the pipe is made of plastic and is used for water supply or drainage, the strain data includes stress, displacement, vibration, and crack;

[0112] When the pipe material is concrete, the strain data includes vibration, corrosion, and cracks.

[0113] In a possible implementation, there are multiple groups of sensors in the protective cover, and each group of sensors is evenly arranged along the longitudinal direction of the protective cover;

[0114] The host computer is also used to analyze the location of leakage points of the pipe interface in the protective cover based on the position and monitoring data of each group of sensors in the protective cover.

[0115] In this embodiment, the host computer can analyze the location of the leakage point by the following steps:

[0116] 1. Sensor Data Analysis

[0117] Single sensor analysis: Analyze a single sensor data to find abnormal changes, such as sudden pressure drops, flow changes, etc.

[0118] Multi-sensor data fusion: Combining data from multiple sensors to improve leak detection accuracy.

[0119] 2. Leak Detection Algorithm

[0120] Model-based approach:

[0121] Normal conditions are simulated using fluid dynamics models and pipeline physics and compared with actual monitoring data.

[0122] If the monitoring data differ significantly from the model predictions, it may indicate a leak.

[0123] Data-driven approach:

[0124] Machine learning methods: Use supervised learning algorithms (such as random forests, support vector machines) or unsupervised learning (such as cluster analysis) to identify leakage patterns.

[0125] Time Series Analysis: Use models such as ARIMA and LSTM to analyze time series data and detect abnormal patterns caused by leakage.

[0126] 3. Leak point location

[0127] Signal propagation model: Uses the propagation characteristics of sound waves or pressure signals, combined with sensor locations, to calculate the leak location.

[0128] Multi-sensor cross positioning:

[0129] The time difference between leakage signals detected by different sensors is compared, and the leakage point is located using the time difference and signal propagation speed.

[0130] Using triangulation, the leak is located using data from at least three sensors.

[0131] 4. Verification and optimization

[0132] Verify the leak point: Verify the accuracy of the leak point through field inspection or other detection methods.

[0133] Optimize algorithms: Adjust leak detection and location algorithms based on verification results to improve accuracy.

[0134] In one possible implementation, the host computer is specifically used to determine at least one high-risk leakage point on the pipe interface in the protective cover based on the interface structure and / or the pipe category, and to determine the groups of sensors corresponding to each high-risk leakage point based on the positional relationship between each group of sensors and each high-risk leakage point, so as to determine the leakage point position of the pipe interface in the protective cover based on the monitoring data of each group of sensors corresponding to each high-risk leakage point.

[0135] In this embodiment, the host computer can determine the high-risk leakage points on the pipeline interface based on the following principles, thereby simplifying the process of locating the leakage points:

[0136] 1. Interface structure analysis

[0137] Interface type: Analyze different types of interfaces, such as welding, threaded connection, flange connection, bonding, etc. Each interface type may have different leakage risks.

[0138] Interface materials: Consider the compatibility and aging of interface materials. Different materials may have different expansion coefficients, which may cause stress when the temperature changes and increase the risk of leakage.

[0139] Interface design: Check whether the interface design meets the standards and whether there are any design defects, such as excessive stress concentration, improper sealing surface, etc.

[0140] Interface integrity: Assess the integrity of the interface, including the condition of seals, tightening torque of fasteners, etc.

[0141] 2. Pipeline Category Analysis

[0142] Pipe material: Pipes of different materials (such as steel pipes, cast iron pipes, plastic pipes, etc.) have different performance in terms of withstanding pressure, temperature changes and chemical corrosion.

[0143] Pipeline purpose: Assess risks based on the medium transported by the pipeline (such as water, oil, gas, chemicals, etc.) and operating conditions (such as pressure, temperature, flow rate, etc.).

[0144] Pipe diameter and wall thickness: Large diameter or thin-walled pipes may be more susceptible to stress concentrations at joints, increasing the risk of leaks.

[0145] Since each sensor has a certain monitoring range, by assigning a correspondence between sensors and high-risk leakage points, possible leakage points can be directly determined based on the monitoring data of each sensor without the need for specific location calculations, greatly improving the efficiency of leakage alarms.

[0146] In a possible implementation, when the pipeline interface is a steel-plastic conversion joint, the high-risk leakage points include the connection between the metal part of the steel-plastic conversion joint and the steel pipeline, the connection between the plastic part and the plastic pipeline, and the connection between the metal part and the plastic part;

[0147] The upper computer is specifically used to determine that the leakage point position of the pipe interface in the protective cover is the first high-risk leakage point when the monitoring data collected by each group of sensors corresponding to the first high-risk leakage point are all abnormal; wherein the first high-risk leakage point is any high-risk leakage point.

[0148] In this embodiment, if Figure 2 As shown, the steel-plastic conversion joint can be divided into a metal part and a plastic part, the metal part is used to connect with a steel (or metal) pipe, the plastic part is used to connect with a plastic pipe, and the metal part is connected with the plastic part. The steel-plastic conversion joint can realize the conversion of metal pipes and plastic pipes.

[0149] In this embodiment, the protective cover for the steel-plastic conversion joint is arranged outside the steel-plastic conversion joint, and has at least four groups of sensors, which are called the first group of sensors, the second group of sensors, the third group of sensors and the fourth group of sensors from left to right. Based on the distance relationship between each group of sensors and each connection point, it can be considered that the sensors corresponding to the connection between the metal part of the steel-plastic conversion joint and the steel pipe are the first group of sensors and the second group of sensors, the sensors corresponding to the connection between the metal part and the plastic part are the second group of sensors and the third group of sensors, and the sensors corresponding to the connection between the plastic part and the plastic pipe are the third group of sensors and the fourth group of sensors. Based on this, when the monitoring data of the first group of sensors and the second group of sensors both indicate that the pipeline is leaking, it is considered that the leakage point is the connection between the metal part of the steel-plastic conversion joint and the steel pipe, and the same applies to the rest.

[0150] In a possible implementation, the protective cover further includes a supercapacitor for supplying power to the internal sensor;

[0151] The ring-shaped inspection robot is also used to charge the supercapacitor of the protective cover.

[0152] In this embodiment, in order to ensure that the sensors in the protective cover can continuously collect and upload monitoring data, supercapacitors can be used to continuously power the sensors. The moving path of the ring-shaped detection robot will pass through the protective cover, and the supercapacitors in each protective cover can be charged by the ring-shaped detection robot during the active detection process to ensure the sustainability of the sensor's power consumption.

[0153] In addition, the power supply of the supercapacitor in the protective cover can be set. When the power of the supercapacitor in the protective cover is about to be exhausted, it means that the monitoring time of the sensor has reached the set time. At this time, a reminder is sent to the host computer or the ring detection robot, and a reminder for active detection work can also be realized simultaneously to ensure that active detection of the pipeline is carried out regularly.

[0154] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0155] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0156] Figure 3 The following is a flowchart of the pipeline active detection and early warning method provided by an embodiment of the present invention, which is described in detail as follows:

[0157] Step 301, the protective cover covers the outside of the pipeline interface, collects monitoring data of the pipeline interface through the internal sensor, and uploads it to the host computer;

[0158] Step 302, the annular detection robot crawls along the outer wall of the pipeline, collects strain data of detection points on the pipeline, and uploads the data to the host computer; wherein the detection points include pipeline interfaces and pipeline deformation positions;

[0159] Step 303: The host computer identifies the damage risk of the pipeline and issues an early warning based on the pipeline category, monitoring data and strain data.

[0160] In a possible implementation, there are multiple protective covers; the ring detection robot includes a distance measurement module; and the method further includes:

[0161] The ring detection robot collects the distance between any two protective covers and uploads it to the host computer;

[0162] The host computer compares the distance between the two protective covers with the historical distance between the two protective covers, and determines whether the pipeline between the two protective covers is deformed based on the comparison result. If deformation occurs, the pipeline area between the two protective covers is set as the detection point.

[0163] In a possible implementation, the sensor in the protective cover includes one or more of a pressure sensor, a temperature sensor, a humidity sensor, a sound sensor, and a gas sensor; the monitoring data includes the gas pressure, temperature, humidity, sound signal, and gas concentration in the protective cover;

[0164] The annular detection robot includes one or more of a strain sensor, a stress sensor, a displacement sensor, a vibration sensor, an electrochemical sensor, a sound sensor, and an optical sensor, and the strain data includes strain amount, stress, displacement, vibration, corrosion, and crack;

[0165] The host computer identifies pipeline damage risks and issues early warnings based on pipeline categories, monitoring data, and strain data, including:

[0166] The host computer screens the strain data based on the pipeline category, inputs the monitoring data and the screened strain data into the risk prediction model corresponding to the pipeline category, obtains the damage risk of the pipeline, and issues an early warning based on the damage risk.

[0167] In a possible implementation, the pipeline category includes pipeline material and pipeline use, the pipeline material includes cast iron, steel pipe, stainless steel, plastic, concrete and fiberglass, and the pipeline use includes water supply, drainage, gas, heating, cooling and industrial fluid;

[0168] Before the host computer screens the strain data based on the pipeline category, the method further includes:

[0169] The host computer analyzes the correlation between various strain data and pipeline damage of various pipeline materials and pipeline uses, and obtains the strain data category corresponding to each pipeline material and pipeline use.

[0170] In a possible implementation, there are multiple groups of sensors in the protective cover, and each group of sensors is evenly arranged along the longitudinal direction of the protective cover;

[0171] The method further includes:

[0172] The host computer analyzes the leakage point position of the pipeline interface in the protective cover based on the position and monitoring data of each group of sensors in the protective cover.

[0173] In a possible implementation, the host computer analyzes the leakage point position of the pipeline interface in the protective cover based on the position and monitoring data of each group of sensors in the protective cover, including:

[0174] The upper computer determines at least one high-risk leakage point on the pipe interface in the protective cover based on the interface structure and / or the pipe category, and determines the groups of sensors corresponding to each high-risk leakage point based on the positional relationship between each group of sensors and each high-risk leakage point, so as to determine the leakage point position of the pipe interface in the protective cover based on the monitoring data of each group of sensors corresponding to each high-risk leakage point.

[0175] In a possible implementation, when the pipeline interface is a steel-plastic conversion joint, the high-risk leakage points include the connection between the metal part of the steel-plastic conversion joint and the steel pipeline, the connection between the plastic part and the plastic pipeline, and the connection between the metal part and the plastic part;

[0176] The host computer determines the location of the leakage point of the pipe interface in the protective cover based on the monitoring data of each group of sensors corresponding to each high-risk leakage point, including:

[0177] When the monitoring data collected by each group of sensors corresponding to the first high-risk leakage point are all abnormal, the upper computer determines that the leakage point position of the pipeline interface in the protective cover is the first high-risk leakage point; wherein the first high-risk leakage point is any high-risk leakage point.

[0178] In a possible implementation, the protective cover further includes a supercapacitor for supplying power to the internal sensor;

[0179] The method further includes:

[0180] The ring-shaped inspection robot charges the supercapacitor of the protective cover.

[0181] The embodiment of the present invention uses a protective cover to seal and protect key parts such as interfaces and welds of various municipal pipelines in the pipeline corridor, and continuously monitors the status of the pipeline welds through sensors in the protective cover. The mobile sensor carried by the annular detection robot is then used to actively detect the status of the middle section of the pipeline. The status of the pipeline interface and the deformation, corrosion, cracks and other information of the middle section of the pipeline are comprehensively considered to evaluate the damage and leakage risks of the pipeline, so as to detect the leakage risk of the pipeline in advance and provide accurate early warning.

[0182] Figure 4 is a schematic diagram of a terminal provided by an embodiment of the present invention. Figure 4 As shown, the terminal 4 of this embodiment includes: a processor 40, a memory 41, and a computer program 42 stored in the memory 41 and executable on the processor 40. When the processor 40 executes the computer program 42, the steps in the above-mentioned embodiments of the active pipeline detection and early warning method are implemented, for example Figure 3 Alternatively, when the processor 40 executes the computer program 42, the functions of each module / unit in the above-mentioned device embodiments are realized, for example, Figure 1Functions of modules / units 11 to 13 are shown.

[0183] Exemplarily, the computer program 42 may be divided into one or more modules / units, which are stored in the memory 41 and executed by the processor 40 to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program 42 in the terminal 4. For example, the computer program 42 may be divided into Figure 1 Modules / units 11 to 13 are shown.

[0184] The terminal 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The terminal 4 may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will appreciate that Figure 4 It is only an example of terminal 4 and does not constitute a limitation on terminal 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0185] The processor 40 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0186] The memory 41 may be an internal storage unit of the terminal 4, such as a hard disk or memory of the terminal 4. The memory 41 may also be an external storage device of the terminal 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the terminal 4. Further, the memory 41 may also include both an internal storage unit and an external storage device of the terminal 4. The memory 41 is used to store the computer program and other programs and data required by the terminal. The memory 41 may also be used to temporarily store data that has been output or is to be output.

[0187] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0188] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0189] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0190] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0193] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned pipeline active detection and early warning method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0194] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A pipeline active detection and early warning system, characterized in that: It includes a protective cover, a ring-shaped detection robot and a host computer; a sensor is arranged inside the protective cover; The protective cover is used to cover the outside of the pipeline interface, collect monitoring data of the pipeline interface through the internal sensor, and upload it to the host computer; The annular detection robot is used to crawl along the outer wall of the pipeline, collect strain data of detection points on the pipeline, and upload them to the host computer; wherein the detection points include pipeline interfaces and pipeline deformation positions; The host computer is used to identify the damage risk of the pipeline and issue an early warning based on the pipeline category, the monitoring data and the strain data.

2. The pipeline active detection and early warning system according to claim 1 is characterized in that: The number of protective covers is multiple; the ring-shaped detection robot includes a distance measurement module; The annular detection robot is also used to collect the distance between any two protective covers and upload it to the host computer; The host computer is also used to compare the distance between the two protective covers with the historical distance between the two protective covers, and determine whether the pipeline between the two protective covers is deformed based on the comparison result. If deformation occurs, the pipeline area between the two protective covers is set as the detection point.

3. The pipeline active detection and early warning system according to claim 1 is characterized in that: The sensor in the protective cover includes one or more of a pressure sensor, a temperature sensor, a humidity sensor, a sound sensor and a gas sensor; the monitoring data includes the gas pressure, temperature, humidity, sound signal and gas concentration in the protective cover; The annular detection robot includes one or more of a strain sensor, a stress sensor, a displacement sensor, a vibration sensor, an electrochemical sensor, a sound sensor, and an optical sensor, and the strain data includes strain, stress, displacement, vibration, corrosion, and crack; The host computer is specifically used to screen the strain data based on the pipeline category, input the monitoring data and the screened strain data into the risk prediction model corresponding to the pipeline category, obtain the damage risk of the pipeline, and issue an early warning based on the damage risk.

4. The pipeline active detection and early warning system according to claim 3 is characterized in that: Pipeline categories include pipe materials and pipe uses. Pipe materials include cast iron, steel pipe, stainless steel, plastic, concrete and fiberglass. Pipe uses include water supply, drainage, gas, heating, cooling and industrial fluids. The host computer is also used to analyze the correlation between various types of strain data and pipeline damage of various types of pipeline materials and pipeline uses before screening the strain data based on the pipeline category, so as to obtain the strain data category corresponding to each pipeline material and pipeline use.

5. The pipeline active detection and early warning system according to claim 1 is characterized in that: There are multiple groups of sensors in the protective cover, and each group of sensors is evenly arranged along the longitudinal direction of the protective cover; The host computer is also used to analyze the leakage point position of the pipeline interface in the protective cover based on the position and monitoring data of each group of sensors in the protective cover.

6. The pipeline active detection and early warning system according to claim 5 is characterized in that: The host computer is specifically used to determine at least one high-risk leakage point on the pipeline interface in the protective cover based on the interface structure and / or pipeline category, and determine the groups of sensors corresponding to each high-risk leakage point based on the positional relationship between each group of sensors and each high-risk leakage point, so as to determine the leakage point position of the pipeline interface in the protective cover based on the monitoring data of each group of sensors corresponding to each high-risk leakage point.

7. The pipeline active detection and early warning system according to claim 6 is characterized in that: When the pipeline interface is a steel-plastic conversion joint, the high-risk leakage points include the connection between the metal part of the steel-plastic conversion joint and the steel pipeline, the connection between the plastic part and the plastic pipeline, and the connection between the metal part and the plastic part; The host computer is specifically used to determine that the leakage point position of the pipe interface in the protective cover is the first high-risk leakage point when the monitoring data collected by each group of sensors corresponding to the first high-risk leakage point are all abnormal; wherein the first high-risk leakage point is any high-risk leakage point.

8. The pipeline active detection and early warning system according to claim 1 is characterized in that: The protective cover also includes a super capacitor for powering the internal sensor; The annular detection robot is also used to charge the supercapacitor of the protective cover.

9. A pipeline active detection and early warning method, characterized in that: Applicable to the pipeline active detection and early warning system according to any one of claims 1 to 8; the method comprises: The protective cover covers the outside of the pipeline interface, collects monitoring data of the pipeline interface through internal sensors, and uploads it to the host computer; The annular detection robot crawls along the outer wall of the pipeline, collects strain data of detection points on the pipeline, and uploads the data to the host computer; wherein the detection points include pipeline interfaces and pipeline deformation positions; The host computer identifies the damage risk of the pipeline and issues an early warning based on the pipeline category, the monitoring data and the strain data.

10. The pipeline active detection and early warning method according to claim 9, characterized in that: The number of protective covers is multiple; the ring-shaped detection robot includes a distance measurement module; The method further comprises: The annular detection robot collects the distance between any two protective covers and uploads it to the host computer; The host computer compares the distance between the two protective covers with the historical distance between the two protective covers, and determines whether the pipeline between the two protective covers is deformed based on the comparison result. If deformation occurs, the pipeline area between the two protective covers is set as the detection point.

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