A buried pipeline cathodic protection fault detection method and device, electronic equipment and storage medium

Abstract

The application discloses a buried pipeline cathode protection fault detection method and device, electronic equipment and a storage medium. The method comprises the following steps: determining each node data of a node in a current stage; determining at least one node data feature of the node data based on the each node data; performing fault analysis on the each node data and the each node data feature of the node based on a pre-constructed fault detection rule to determine the working condition of the node in the current stage. By adopting the technical scheme of the application, the each node data of the node is determined in the current stage, the at least one node data feature of the node data is determined based on the each node data, the fault analysis is performed on the each node data and the each node data feature of the node based on the pre-constructed fault detection rule, and the working condition of the node in the current stage is determined, so that the rapid determination of the working condition of the node is realized, and the problems of high complexity and long time consumption of the traditional manual detection are avoided.

Description

Technical Field

[0001] This invention relates to the field of neural network technology, and in particular to a method, apparatus, electronic device, and storage medium for detecting cathodic protection faults in buried pipelines. Background Technology

[0002] Pipeline corrosion frequently causes equipment damage and resource waste. This is particularly acute in the oil and gas pipeline industries, where corrosion is a pressing issue. Pipeline corrosion reduces pipe wall thickness, leading to deformation, rupture, or even perforation, resulting in leaks.

[0003] Common pipeline corrosion protection technologies include the use of corrosion inhibitors, external anti-corrosion coatings, and cathodic protection. Among these, cathodic protection is currently the most widely used. However, the maintenance of cathodic protection systems still relies on regular inspections by pipeline maintenance personnel. Summary of the Invention

[0004] This invention provides a method, device, electronic equipment, and storage medium for detecting faults in cathodic protection of buried pipelines, in order to solve the problem that the maintenance of existing cathodic protection systems still relies on regular inspections by pipeline maintenance personnel, which results in low efficiency.

[0005] According to one aspect of the present invention, a method for detecting cathodic protection faults in buried pipelines is provided, the method comprising: At this stage, the data of each node is determined, including the set potential, test potential, output voltage, and output current; the nodes are the system parts in the buried pipeline cathodic protection system that need to be tested. Based on the data from each node, determine at least one node data feature of the node data. Based on pre-built fault detection patterns, fault analysis is performed on the data of each node and the characteristics of each node data to determine the working condition of the node at the current stage.

[0006] According to another aspect of the present invention, a fault detection device for cathodic protection of buried pipelines is provided, the device comprising: The node data determination module is used to determine the node data of each node at the current stage. The node data includes the set potential, test potential, output voltage, and output current. The node is the system part of the buried pipeline cathodic protection system that needs to be tested. The feature data determination module is used to determine at least one node data feature based on the data of each node. The operating condition determination module is used to perform fault analysis on the node data and characteristics of each node based on pre-built fault detection rules, and to determine the operating condition of the node at the current stage.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory that is communicatively connected to at least one processor; wherein, The memory stores a computer program that can be executed by at least one processor, such that the at least one processor is able to perform the buried pipeline cathodic protection fault detection method according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the buried pipeline cathodic protection fault detection method of any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the buried pipeline cathodic protection fault detection method of any embodiment of the present invention.

[0010] The technical solution of this invention, in the current stage, determines the node data of each node, including set potential, test potential, output voltage, and output current; the node is a system part in the buried pipeline cathodic protection system that needs to be detected; based on the node data, at least one node data feature of the node data is determined; based on the pre-constructed fault detection rules, fault analysis is performed on the node data and the node data features to determine the operating condition of the node in the current stage, thereby achieving rapid determination of the node operating condition, avoiding the problems of high complexity and long time consumption of traditional manual detection, and realizing automated determination of operating condition.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a method for detecting cathodic protection faults in buried pipelines provided in an embodiment of the present invention; Figure 2This is a flowchart of another method for detecting cathodic protection faults in buried pipelines provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a cathodic protection fault detection device for buried pipelines provided in an embodiment of the present invention; Figure 4 This is a structural block diagram of an electronic device for a method of detecting cathodic protection faults in buried pipelines provided in an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] In one embodiment, Figure 1 This is a flowchart of a method for detecting cathodic protection faults in buried pipelines according to an embodiment of the present invention. This embodiment is applicable to the cathodic protection of buried pipelines. The method can be executed by a cathodic protection fault detection device for buried pipelines. This device can be implemented in hardware and / or software and can be configured in an electronic device with data processing capabilities. Figure 1 As shown, the method includes: S110. At the current stage, determine the data of each node, including the set potential, test potential, output voltage, and output current; the node is the system part of the buried pipeline cathodic protection system that needs to be tested.

[0017] A cathodic protection system for buried pipelines is a complete set of protective devices and facilities designed to inhibit electrochemical corrosion of buried steel pipelines in soil. It uses electrochemical principles to force the entire pipeline to polarize into a cathode, thereby preventing the pipeline metal from losing electrons and corroding. It mainly consists of a protective pipeline, an anode device, a reference electrode, power supply equipment, and connecting cables. It is often used in conjunction with an external anti-corrosion coating for the pipeline to achieve long-term anti-corrosion protection for buried pipelines.

[0018] The set potential refers to the pipeline-to-ground control potential value preset by a potentiostat during the operation of the cathodic protection system. The system automatically adjusts the output current to polarize the buried pipeline to the set potential, achieving continuous and effective cathodic protection. The test potential is the pipeline-to-ground potential value measured on-site using a reference electrode (saturated copper sulfate electrode) under the actual operating conditions of the buried pipeline cathodic protection system. It is used to determine whether the pipeline has achieved cathodic protection and whether there is under-protection or over-protection. The output voltage refers to the actual terminal voltage output by the potentiostat (impressed current cathodic protection power supply) to the anode-cathode circuit in the cathodic protection system, i.e., the working voltage between the positive and negative terminals of the power supply. It is used to overcome soil resistance, cable resistance, anode polarization resistance, etc., to provide sufficient protective current to the pipeline. The output current refers to the actual working current output by the potentiostat in the impressed current cathodic protection system, flowing through the cable into the auxiliary anode, and reaching the protected pipeline through the soil medium. It is the direct driving force for achieving pipeline cathodic polarization and reaching the protection potential.

[0019] Nodes can be system parts in a buried pipeline cathodic protection system that require testing. Nodes can include potentiostats, auxiliary anodes, reference electrodes, cables and junction boxes, test posts, insulating joints / insulating flanges, anode ground beds, sacrificial anodes, anode cables, test posts, junction boxes, etc.

[0020] For the collection of data from each node, the data is collected according to a preset collection cycle. Each collection window contains several collection time points, and each collection point collects node data once.

[0021] Node data can be acquired through real-time collection or by retrieving data from a database.

[0022] The data for each node in the determined node includes: Data cleaning and standardization are performed on the data of each node.

[0023] For the acquisition of data from each node, the raw data will be cleaned to eliminate abnormal data and standardized. The four signals of set potential, test potential, output voltage and output current will be time-centered. The output current mA unit will be converted to A to unify the physical dimensions.

[0024] The data for each node in the determined node includes: If any node contains null values, they are removed.

[0025] When collecting data from each node at the current stage, a parameter in the node data may be null. Therefore, this null value can be extracted or filled using methods such as linear interpolation, adjacent mean filling, and global mean / median filling.

[0026] S120. Based on the data of each node, determine at least one node data feature of the node data.

[0027] In addition to analyzing the data of each node, it is also necessary to perform data feature analysis on the data of each node to determine several node data features for each node.

[0028] This application specifies node data characteristics including overall signal rise and fall rates, differential mean, and first and last difference. In addition, different data characteristics can be set according to different actual situations, such as the mean, standard deviation, and range of each set potential, each test potential, each output voltage, and each output current within the same stage.

[0029] The overall signal rise / fall rate refers to the average rate of change of the signal (potential / output voltage / output current) over the entire monitoring period. The differential mean is calculated by taking the first-order difference (difference between adjacent time points) of the time-series signal and then averaging it; it characterizes the average amplitude of the signal's change over time. The first-to-last difference is the direct difference between the last and first values ​​of the time-series signal.

[0030] S130. Based on the pre-built fault detection rules, perform fault analysis on the data of each node and the characteristics of each node data to determine the working condition of the node at the current stage.

[0031] Fault detection patterns can be obtained through data analysis of sample data. Specifically, they can be derived by analyzing node data to determine the operating conditions of the corresponding nodes.

[0032] By using pre-built fault detection patterns, fault analysis is performed on the data of each node and the characteristics of each node's data to determine the operating condition of the node.

[0033] The operating conditions include no fault, reference fault, insulation flange fault, current-carrying cable fault, test cable fault, and anode ground bed fault.

[0034] The absence of faults indicates that the electrical signals at each node of the cathodic protection are stable without drift, the voltage and current are properly matched, and there are no abnormal faults in the system.

[0035] Reference failure indicates that an abnormality in the reference electrode causes deviations and drifts in the set potential and test potential; An insulation flange failure indicates a decline in the insulation performance of the insulation flange, causing abnormal fluctuations in circuit potential and current. Current-carrying cable faults indicate that the current-carrying cable is aging and has poor contact, causing distortion of the output current and voltage timing. A test cable fault indicates an abnormality in the test circuit cable, causing distortion in the test potential sampling. Anode ground bed failure indicates corrosion and poor grounding of the anode ground bed, resulting in significant changes in overall output power and circuit equivalent resistance.

[0036] Furthermore, among common faults in buried pipeline cathodic protection systems, reference electrode faults can be subdivided into positive and negative drift of the reference electrode potential, and cable faults can be subdivided into current-carrying cable faults and reference cable faults. Positive drift of the reference electrode potential leads to a decrease in output voltage and current, and a positive shift in the potential at the test pile; negative drift of the reference electrode potential leads to an increase in output voltage and current, and a negative shift in the potential at the test pile; current-carrying cable faults lead to a decrease in output voltage and current to 0, and a positive shift in the potential at the test pile; reference cable faults lead to an increase in output voltage to the limit voltage, an increase in output current, and a negative shift in the potential at the test pile; increased anode bed resistance leads to an increase in output voltage; insulation joint failure, and the absence of a cathodic protection system on the other side of the pipeline, leads to an increase in output voltage and current, and a positive shift in the potential at the test pile; when the pipeline is subjected to DC interference, the output voltage, current, and potential at the test pile will fluctuate. Different faults will bring different feedback to the monitoring data of the pipeline cathodic protection system.

[0037] The process of constructing fault detection patterns includes: Determine the sample node data and the corresponding sample operating conditions. The sample node data includes the sample set potential, sample test potential, sample output voltage, and sample output current. Based on the sample node data, the random forest model is trained to obtain the fault detection rules.

[0038] Random forest is a supervised machine learning model based on ensemble learning. It consists of multiple independent decision trees. The output node's condition is determined by combining the predictions of multiple decision trees through voting (classification) or averaging (regression).

[0039] During the training phase of the random forest model, each decision tree adopts an independent learning mechanism: each tree only randomly selects a portion of features and samples for training, automatically finding the best split point for each feature.

[0040] To determine the fault detection patterns, sample node data and corresponding sample operating conditions are pre-constructed, and a random forest model is trained based on the sample node data to generate fault detection patterns.

[0041] In practical applications, a random forest model can be directly used to determine the operating conditions. When using the random forest model to determine the operating conditions, multiple decision trees are invoked to make independent judgments, and the fault category prediction result of each tree is output. After obtaining the prediction results of each decision tree, a hard voting strategy can be used to count the number of votes for each fault category, and the category with the highest number of votes is taken as the final prediction result. Alternatively, each tree can output the probability of each category, and the probabilities of all trees are averaged; the category with the highest average probability is the final result. Alternatively, each tree can be assigned a weight (e.g., weighted by tree accuracy and generalization ability), with trees with higher accuracy receiving greater voting weight.

[0042] The technical solution provided by this invention determines the node data of each node at the current stage. The node data includes set potential, test potential, output voltage, and output current. The node is a system part in the buried pipeline cathodic protection system that needs to be detected. Based on the node data, at least one node data feature of the node data is determined. Based on the pre-constructed fault detection rules, fault analysis is performed on the node data and the node data features to determine the operating condition of the node at the current stage. This achieves rapid determination of the node operating condition, avoiding the problems of high complexity and long time consumption of traditional manual detection, and realizing automated determination of operating conditions.

[0043] In one embodiment, Figure 2 This is a flowchart of another method for detecting cathodic protection faults in buried pipelines provided by an embodiment of the present invention. The relationship between this embodiment and the above embodiments is based on a pre-constructed fault detection rule, and involves fault analysis of the data of each node and the characteristics of each node data. Figure 2 As shown, the method includes: S210. At the current stage, determine the data of each node, including the set potential, test potential, output voltage, and output current; the node is the system part of the buried pipeline cathodic protection system that needs to be tested.

[0044] S220. Based on the data of each node, determine at least one node data feature of the node data.

[0045] S230. Concatenate the node data features of the node data with the node data to form a one-dimensional feature vector.

[0046] S240. Based on the pre-constructed fault detection rules, perform fault analysis on the one-dimensional feature vector.

[0047] In order to ensure that node data and node data features can be analyzed by the random forest model at the same time during fault analysis, a one-dimensional feature vector can be constructed by concatenating the node data features with the node data. This one-dimensional feature vector is then input into the random forest model for operating condition analysis.

[0048] Specifically, the node data features of the node data are concatenated with the node data itself to form a one-dimensional feature vector, including: The node data features and the node data itself are normalized, and a one-dimensional feature vector is constructed from the normalization result.

[0049] After constructing the one-dimensional feature vector, since the parameters in the one-dimensional feature vector are of different magnitudes, in order to ensure the fast calculation of the random forest model, the node data features of the node data can be normalized with the node data before constructing the one-dimensional feature vector.

[0050] The technical solution provided by this invention determines at least one node data feature based on the data of each node; and performs fault analysis on the one-dimensional feature vector based on the pre-constructed fault detection rules, thereby ensuring the orderliness and accuracy of the random forest model calculation.

[0051] In one embodiment, Figure 3 This is a schematic diagram of the structure of a cathodic protection fault detection device for buried pipelines provided in an embodiment of the present invention. Figure 3 As shown, the device includes: a node data determination module 310, a feature data determination module 320, and a working condition determination module 330, wherein: The node data determination module 310 is used to determine the node data of each node at the current stage. The node data includes the set potential, test potential, output voltage, and output current. The node is the system part of the buried pipeline cathodic protection system that needs to be tested. The feature data determination module 320 is used to determine at least one node data feature based on the node data of each node. The operating condition determination module 330 is used to perform fault analysis on the node data and characteristics of each node based on the pre-built fault detection rules, and determine the operating condition of the node at the current stage.

[0052] In one embodiment, the optional operating conditions include no fault, reference fault, insulation flange fault, current-carrying cable fault, test cable fault, and anode ground bed fault.

[0053] In one embodiment, optionally, the process of constructing the fault detection pattern includes: Determine the sample node data and the corresponding sample operating conditions. The sample node data includes the sample set potential, sample test potential, sample output voltage, and sample output current. Based on the sample node data, the random forest model is trained to obtain the fault detection rules.

[0054] In one embodiment, optionally, based on pre-built fault detection rules, fault analysis is performed on the node data and characteristics of each node, including: The node data features of the node data are concatenated with the node data to form a one-dimensional feature vector; Based on pre-constructed fault detection rules, fault analysis is performed on one-dimensional feature vectors.

[0055] In one embodiment, optionally, the node data features of the node data are concatenated with the node data to form a one-dimensional feature vector, including: The node data features and the node data itself are normalized, and a one-dimensional feature vector is constructed from the normalization result.

[0056] In one embodiment, optionally, determining the node data of each node includes: Data cleaning and standardization are performed on the data of each node.

[0057] In one embodiment, optionally, determining the node data of each node includes: If any node contains null values, they are removed.

[0058] The buried pipeline cathodic protection fault detection device provided in this embodiment of the invention can execute the buried pipeline cathodic protection fault detection method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0059] In one embodiment, Figure 4 This is a structural block diagram of an electronic device for a cathodic protection fault detection method for buried pipelines provided in an embodiment of the present invention, as shown below. Figure 4The diagram illustrates a schematic representation of an electronic device 10 that can be used to implement embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0060] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor 11, and the computer program is executed by the at least one processor 11 to enable the at least one processor 11 to execute the buried pipeline cathodic protection fault detection method provided by the present invention.

[0061] The processor 11 can perform various appropriate actions and processes based on a computer program stored in the read-only memory (ROM) 12 or a computer program loaded from the storage unit 18 into the random access memory (RAM) 13. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0062] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0063] Processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the buried pipeline cathodic protection fault detection method provided by the present invention.

[0064] In some embodiments, the buried pipeline cathodic protection fault detection method provided herein can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the buried pipeline cathodic protection fault detection method by any other suitable means (e.g., by means of firmware).

[0065] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard parts (ASSPs), systems-on-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0066] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0067] In the context of this invention, a computer-readable storage medium stores computer instructions that are used to cause a processor to execute and implement the method provided by this invention.

[0068] The present invention also provides a computer program product comprising a computer program that, when executed by a processor, implements the method provided according to embodiments of the present invention. A computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. The computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, the computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0069] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0070] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0071] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0072] This invention also provides a computer program product, including a computer program that, when executed by a processor, can implement the methods provided in any embodiment of this application.

[0073] In the implementation of the computer program product, computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0074] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0075] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for detecting cathodic protection faults in buried pipelines, characterized in that, include: At this stage, the node data of each node is determined, including the set potential, test potential, output voltage, and output current. The node is a system part in the cathodic protection system for buried pipelines that needs to be inspected. Based on the node data, at least one node data feature of the node data is determined; Based on pre-built fault detection patterns, fault analysis is performed on the node data and characteristics of each node to determine the node's operating condition at the current stage.

2. The method according to claim 1, characterized in that, The operating conditions include no fault, reference fault, insulation flange fault, current-carrying cable fault, test cable fault, and anode ground bed fault.

3. The method according to claim 1, characterized in that, The process of constructing the fault detection rules includes: Determine the sample node data and the corresponding sample operating conditions, wherein the sample node data includes the sample set potential, sample test potential, sample output voltage, and sample output current; Based on the sample node data, the random forest model is trained to obtain the fault detection pattern.

4. The method according to claim 1, characterized in that, Based on pre-built fault detection patterns, fault analysis is performed on the node data and characteristics of each node, including: The node data features of the node data are concatenated with the node data to form a one-dimensional feature vector; Based on the pre-constructed fault detection rules, fault analysis is performed on the one-dimensional feature vector.

5. The method according to claim 4, characterized in that, The node data features of the node data are concatenated with the node data to form a one-dimensional feature vector, including: The node data features of the node data are normalized with the node data itself, and a one-dimensional feature vector is constructed from the normalization result.

6. The method according to claim 1, characterized in that, Determine the data for each node, including: Data cleaning and standardization are performed on the data of each node.

7. The method according to claim 1, characterized in that, Determine the data for each node, including: If any node contains null values, they are removed.

8. A fault detection device for cathodic protection of buried pipelines, characterized in that, include: The node data determination module is used to determine the node data of each node at the current stage. The node data includes set potential, test potential, output voltage, and output current. The node is a system part of the buried pipeline cathodic protection system that needs to be tested. The feature data determination module is used to determine at least one node data feature of the node data based on each of the node data. The operating condition determination module is used to perform fault analysis on the node data and characteristics of each node based on pre-built fault detection rules, and determine the operating condition of the node at the current stage.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the buried pipeline cathodic protection fault detection method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for detecting cathodic protection faults in buried pipelines as described in any one of claims 1-7.

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