Pressure pipeline cathode protection state detection and early warning processing system

Abstract

The invention provides a pressure pipeline cathode protection state detection and early warning processing system which is characterized in that a data acquisition module is activated firstly, a normally-closed electromagnetic relay is controlled to be switched off, the data acquisition module acquires current, voltage, resistance values and humidity values of a monitoring point, the data acquisition module packs the acquired data and sends the packed data to an early warning module, and the early warning module sends the packed data to an early warning module; the data acquisition module is dormant and controls the normally-closed electromagnetic relay to be closed at the same time, after the early warning module receives data of the data acquisition module, whether the data exceed a threshold value or not is judged through the threshold value comparison module, if the data exceed the threshold value, the threshold value comparison module sends the data to the AI module, and the AI module evaluates the early warning level of the data. The evaluation result and the data are sent to the data storage module and sent to a rear-end server through the wireless module, and if the data do not exceed a threshold value, the data are directly sent to the data storage module. Through the integrated detection and early warning system, the monitoring efficiency and the real-time performance of the cathode protection state of the pressure pipeline are remarkably improved.

Description

Technical Field

[0001] The invention belongs to the technical field of pipeline detection, and in particular relates to a pressure pipeline cathode protection state detection and early warning processing system. Background Art

[0002] Pressure pipes are used to transport oil and gas energy. They are made of steel, but steel pipes buried underground are very susceptible to corrosion. If not artificially suppressed, steel pipes are prone to failure accidents such as pipe wall perforation and rupture. Severe accidents can also cause pipeline explosions. Most existing suppression measures use cathodic protection, which pre-buries sacrificial electrodes and electrically connects them to steel pipes to form a galvanic cell structure, which slows down and prevents the corrosion process of steel pipes.

[0003] The laying of pressure pipes is long, and multiple sacrificial electrodes need to be installed along the way. However, the existing cathode measures are too simple, and most of them are carried out through regular inspections, which cannot well detect the status of the sacrificial electrodes, resulting in an increased risk of corrosion of steel pipelines. Summary of the invention

[0004] The purpose of the present invention is to provide a pressure pipeline cathodic protection state detection and early warning processing system to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: a pressure pipeline cathodic protection state detection and early warning processing system, including a data acquisition module, a detection component, an early warning module and a wireless module, the data acquisition module includes: a current collection module, a resistance collection module, a voltage collection module and a humidity collection module;

[0006] The detection components include: sacrificial electrode, reference electrode, humidity probe and normally closed electromagnetic relay;

[0007] The early warning module includes: AI module and threshold comparison module;

[0008] A normally closed electromagnetic relay is arranged between the connection line of the sacrificial electrode and the pressure tube, both ends of the normally closed electromagnetic relay are connected to the data acquisition module, and the controlled end of the normally closed electromagnetic relay is connected to the data acquisition module, the reference electrode is connected to the data acquisition module, humidity probes are arranged beside the sacrificial electrode, the reference electrode and the pressure tube, and the humidity probes are connected to the humidity collection module of the data acquisition module, and the data acquisition module sends the detection data to the early warning module;

[0009] S1: The data acquisition module is activated, and the normally closed electromagnetic relay is controlled to disconnect. The current collection module is started to obtain the current between the sacrificial electrode and the pressure pipe. The voltage collection module is started to obtain the voltage between the sacrificial electrode and the pressure pipe. The resistance collection module is started to obtain the resistance value between the sacrificial electrode and the pressure pipe. The humidity collection module is started to obtain the humidity value of the humidity probe. The data acquisition module packs and sends the collected data to the early warning module, and then the data acquisition module goes into hibernation while controlling the normally closed electromagnetic relay to close.

[0010] S2: After receiving the data from the data acquisition module, the early warning module determines whether the data exceeds the threshold through the threshold comparison module. If the data exceeds the threshold, the threshold comparison module sends the data to the AI module. The AI module evaluates the early warning level of the data and sends the evaluation result and the data to the data storage module and to the backend server through the wireless module. If the data does not exceed the threshold, it is directly sent to the data storage module.

[0011] Preferably, the data storage module includes a data annotation module and a storage unit. The data processed by the early warning module is sent to the data storage module. The annotation information of the data annotation module includes the recording time, the early warning level, and whether it exceeds the threshold. The annotated data is stored in the storage unit.

[0012] Preferably, the wireless module includes a GPS module for obtaining the location information of the monitoring point. The AI module intelligently reads all the data annotations of the storage unit, evaluates the early warning level of the monitoring point, and sends the early warning level and location information of the monitoring point to the backend server through the wireless module.

[0013] Preferably, the humidity collection module is connected to the AI module. The AI module intermittently obtains the data of the humidity probe, predicts the future change of soil humidity, and intelligently adjusts the activation frequency of the data acquisition module.

[0014] Preferably, the backend server actively obtains the data of the data storage module through the wireless module.

[0015] Preferably, the wireless module also includes an active connection module. The active connection module sends a connection signal to the backend server every 5 minutes. The backend server records each connection signal. If the backend server detects that the connection signal is continuously lost 2 - 8 times, it sends a warning message to the maintenance personnel. If the backend server detects that the connection signal is continuously lost more than 8 times, it sends a message indicating that the monitoring point is out of contact to the maintenance personnel.

[0016] Compared with the prior art, the beneficial effects of the present invention are:

[0017] The present invention significantly improves the monitoring efficiency and real-time performance of the cathodic protection status of pressure pipelines through an integrated detection and warning system, effectively overcoming the lagging defects of traditional manual periodic detection. Specifically, the system automatically cuts off the connection between the sacrificial electrode and the pipeline during data acquisition by setting a normally closed electromagnetic relay, eliminating the interference of cathodic protection current on the detection data and ensuring the measurement accuracy of current, voltage, and resistance parameters. At the same time, it combines humidity probes to collect ambient humidity data in real time and constructs a multi-dimensional monitoring system. Through the collaboration of the threshold comparison module and the AI module, the system can dynamically determine whether the collected data exceeds the safety threshold, evaluate the intelligent warning level of abnormal data, and send dangerous data to the background server. Brief Description of the Drawings

[0018] Figure 1 It is a schematic flow diagram of the present invention.

[0019] Reference numerals in the figure: sacrificial electrode 1, reference electrode 2, humidity probe 3, normally closed electromagnetic relay 4. Detailed Embodiments

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0021] Embodiment 1:

[0022] As Figure 1As shown in the figure, a pressure pipeline cathodic protection status detection and early warning processing system provided by the present invention includes a data acquisition module, a detection component, an early warning module, and a wireless module. The data acquisition module includes: a current collection module, a resistance collection module, a voltage collection module, and a humidity collection module; the detection component includes: a sacrificial electrode 1, a reference electrode 2, a humidity probe 3, and a normally closed electromagnetic relay 4; the early warning module includes: an AI module and a threshold comparison module; a normally closed electromagnetic relay 4 is arranged between the connection line of the sacrificial electrode 1 and the pressure pipeline. Both ends of the normally closed electromagnetic relay 4 are connected to the data acquisition module, and the controlled end of the normally closed electromagnetic relay 4 is connected to the data acquisition module. The reference electrode 2 is connected to the data acquisition module. Humidity probes 3 are arranged beside the sacrificial electrode 1, the reference electrode 2, and the pressure pipeline. The humidity probes 3 are all connected to the humidity collection module of the data acquisition module. The data acquisition module sends the detected data to the early warning module; S1: The data acquisition module is activated, and the normally closed electromagnetic relay 4 is controlled to disconnect. The current collection module is started to obtain the current between the sacrificial electrode 1 and the pressure pipeline, the voltage collection module is started to obtain the voltage between the sacrificial electrode 1 and the pressure pipeline, the resistance collection module is started to obtain the resistance value between the sacrificial electrode 1 and the pressure pipeline, the humidity collection module is started to obtain the humidity value of the humidity probe 3. The data acquisition module packs the collected data and sends it to the early warning module. The data acquisition module goes into sleep mode, and at the same time, the normally closed electromagnetic relay 4 is controlled to close; S2: After receiving the data from the data acquisition module, the early warning module judges whether the data exceeds the threshold through the threshold comparison module. If the data exceeds the threshold, the threshold comparison module sends the data to the AI module. The AI module evaluates the early warning level of the data and sends the evaluation result and the data to the data storage module and sends it to the backend server through the wireless module. If the data does not exceed the threshold, it is directly sent to the data storage module. The data storage module includes a data annotation module and a storage unit. The data processed by the early warning module is sent to the data storage module. The annotation information of the data annotation module includes the recording time, the early warning level, and whether it exceeds the threshold. The annotated data is stored in the storage unit. The wireless module includes a GPS module for obtaining the location information of the monitoring point. The AI module intelligently reads all the data annotations of the storage unit and evaluates the early warning level of the monitoring point, and sends the early warning level and location information of the monitoring point to the backend server through the wireless module. The humidity collection module is connected to the AI module. The AI module intermittently obtains the data of the humidity probe 3 and predicts the future soil humidity change, and intelligently adjusts the activation frequency of the data acquisition module. The backend server actively obtains the data of the data storage module through the wireless module. The wireless module also includes an active connection module. The active connection module sends a connection signal to the backend server every 5 minutes. The backend server records each connection signal. If the backend server detects that the connection signal is continuously lost 2 - 8 times, it sends a warning message to the maintenance personnel. If the backend server detects that the connection signal is continuously lost more than 8 times, it sends a monitoring point disconnection message to the maintenance personnel.

[0023] Through the above technical solution, the present invention significantly improves the monitoring efficiency and real-time performance of the cathodic protection state of pressure pipelines through an integrated detection and warning system, effectively overcoming the lag defect of traditional manual periodic detection. Specifically, the system automatically cuts off the connection between the sacrificial electrode 1 and the pipeline during data acquisition by setting a normally closed electromagnetic relay 4, eliminating the interference of cathodic protection current on the detection data and ensuring the measurement accuracy of current, voltage, and resistance parameters; at the same time, it combines humidity probes 3 to collect ambient humidity data in real time to construct a multi-dimensional monitoring system. Through the cooperation of the threshold comparison module and the AI module, the system can dynamically determine whether the collected data exceeds the safety threshold, evaluate the intelligent warning level of abnormal data, and send dangerous data to the background server.

[0024] Embodiment 2:

[0025] As Figure 1 shown, the present invention provides a detection and warning processing system for the cathodic protection state of pressure pipelines. The system includes a data acquisition module, a detection component, a warning module, and a wireless module. The data acquisition module consists of a current collection module, a resistance collection module, a voltage collection module, and a humidity collection module, which are respectively used to collect various parameter data in the cathodic protection system of pressure pipelines. The detection component includes a sacrificial electrode 1, a reference electrode 2, humidity probes 3, and a normally closed electromagnetic relay 4, which is the core part of the system for actual detection. The warning module is composed of an AI module and a threshold comparison module, which are responsible for analyzing and warning the collected data. The wireless module is used to transmit the data collected and analyzed by the system to a remote monitoring center.

[0026] In this system, a normally closed electromagnetic relay 4 is set between the connection line of the sacrificial electrode 1 and the pressure pipeline. Both ends of the normally closed electromagnetic relay 4 are connected to the data acquisition module, and the controlled end of the normally closed electromagnetic relay 4 is also connected to the data acquisition module. This setting enables the system to cut off the connection between the sacrificial electrode 1 and the pressure pipeline when needed, avoiding the interference of cathodic protection current on the measurement. The reference electrode 2 is directly connected to the data acquisition module to provide a stable reference potential. Humidity probes 3 are installed near the sacrificial electrode 1, the reference electrode 2, and the pressure pipeline, and all these humidity probes 3 are connected to the humidity collection module of the data acquisition module to monitor the ambient humidity changes at key positions.

[0027] The working process of the system is divided into two main steps. The first step is data acquisition: When the data acquisition module is activated, first control the normally closed electromagnetic relay 4 to disconnect, cutting off the connection between the sacrificial electrode 1 and the pressure pipe. Then, the current collection module starts to obtain the current between the sacrificial electrode 1 and the pressure pipe, the voltage collection module measures the voltage between them, the resistance collection module determines the resistance value between them, and the humidity collection module reads the humidity values of each humidity probe 3. After the data acquisition is completed, the data acquisition module packs and sends all the acquired data to the warning module, and then the data acquisition module enters the sleep state and controls the normally closed electromagnetic relay 4 to close again, restoring the connection between the sacrificial electrode 1 and the pressure pipe.

[0028] The second step is data processing and warning: After the warning module receives the data packet sent by the data acquisition module, first judge whether each item of data exceeds the preset threshold range through the threshold comparison module. If a certain item of data exceeds the threshold, the threshold comparison module forwards the data to the AI module. The AI module will deeply analyze these abnormal data, evaluate potential risks, and give corresponding warning levels. The evaluation results of the AI module together with the original abnormal data are sent to the data storage module for storage, and at the same time sent to the backend server through the wireless module so that remote monitoring personnel can understand the situation in time. For the normal data that does not exceed the threshold, the system directly sends it to the data storage module for archiving without additional AI analysis. This design effectively reduces the usage frequency of the AI module and reduces the overall power consumption of the system.

[0029] Through this design, the system can comprehensively monitor the operating status of the cathodic protection system of the pressure pipeline, timely discover potential problems, and give corresponding levels of warnings according to the severity of the problems, providing strong guarantee for the safe operation of the pressure pipeline. The system has a high degree of automation, greatly reducing the workload of manual inspection and improving the efficiency and accuracy of detection. At the same time, the intelligent warning function of the system also provides important decision-making support for pipeline maintenance personnel, helping to take more timely and targeted maintenance measures, extend the service life of the pressure pipeline, and improve its operation safety.

[0030] Embodiment 3:

[0031] Such as Figure 1As shown in the figure, the data storage module of the present invention includes a data annotation module and a storage unit, which work together to achieve efficient management and utilization of data. During the operation of the system, the data processed by the warning module is first sent to the data storage module. After receiving this data, the data annotation module will annotate the data according to the preset annotation rules. The annotation information mainly includes three aspects: recording time, warning level, and whether it exceeds the threshold. The recording time annotation uses a timestamp format accurate to seconds, such as "2023-05-15 14:30:25", for subsequent time series analysis. The warning level annotation uses a digital grading system, such as levels 1-5, where the larger the number, the higher the warning level. Whether it exceeds the threshold is marked with a boolean value, true for exceeding and false for not exceeding. After the annotation process is completed, the data annotation module transmits the annotated data to the storage unit. The storage unit adopts a distributed database architecture to ensure high reliability of data storage and fast reading ability. The data is stored in a structured form, and each record contains the original data and the corresponding annotation information. This design enables the AI module to quickly and accurately call historical data with annotation information for learning and model optimization. For example, the AI module can optimize its warning algorithm based on the data distribution of different warning levels. At the same time, the backend database management system can also perform efficient data retrieval and analysis according to the annotation information. To further improve system performance, the data annotation module adopts multi-threaded parallel processing technology, which can simultaneously process annotation tasks of multiple data sources. The storage unit adopts data compression technology, which significantly reduces the occupancy of storage space while ensuring data integrity.

[0032] Embodiment 4:

[0033] As Figure 1As shown, the wireless module of the present invention includes a GPS module for obtaining accurate location information of the monitoring point. The AI module is responsible for intelligently reading the data annotations in the storage unit and evaluating the early warning level of the monitoring point. Finally, the system sends the early warning level and location information of the monitoring point to the backend server through the wireless module. The wireless module uses 5G communication technology to ensure the high speed and stability of data transmission. The built-in GPS module uses the latest GNSS multi-mode and multi-frequency technology, supporting multiple satellite navigation systems such as GPS, GLONASS, Beidou, and Galileo, ensuring accurate location information can be obtained in various complex environments. The AI module is built based on deep learning algorithms and adopts the LSTM (Long Short-Term Memory) network structure, which can effectively process time series data. The AI module regularly reads all data annotations from the storage unit, including historical data and the latest collected data. The reading process adopts a batch reading method to improve data loading efficiency. When evaluating the early warning level, the AI module comprehensively considers multiple factors: historical data trends, current measurement values, environmental factors (such as humidity), and predefined thresholds. The evaluation process is divided into the following steps: First, the AI module performs time series analysis on the historical data to identify potential abnormal patterns. Then, the current measurement value is compared with the historical trend and the preset threshold. Next, the influence of environmental factors on the measurement value is considered. Finally, based on these analysis results, the AI module gives a comprehensive early warning level evaluation. The early warning level evaluation adopts a 1-5 level system, where level 1 indicates normal and level 5 indicates the highest level of alarm. Each level has a clear definition and corresponding handling suggestions. For example, level 3 may indicate that the detection frequency needs to be increased, level 4 indicates that personnel need to be arranged for on-site inspection, and level 5 indicates that emergency measures need to be taken immediately. After the evaluation is completed, the AI module integrates the early warning level information with the location information provided by the GPS module. This information is sent to the backend server through the wireless module. The data transmission uses an encryption protocol to ensure information security. After receiving the information, the backend server immediately updates the display of the monitoring system and triggers the corresponding alarm mechanism according to the early warning level.

[0034] Embodiment Five:

[0035] As Figure 1 shown, the humidity collection module of the present invention is connected to the AI module through a data line. The humidity collection module consists of multiple humidity probes 3 distributed around the pressure pipeline, and these probes collect soil humidity data. The AI module obtains the latest humidity data from the humidity collection module at preset time intervals, such as once an hour. The obtained data includes a timestamp and the corresponding humidity value. The AI module stores this data in the internal memory to form a time series data set.

[0036] The AI module uses time series analysis algorithms such as ARIMA (Autoregressive Integrated Moving Average) or LSTM (Long Short-Term Memory Network) to analyze and model historical humidity data. After the model training is completed, the AI module can predict the trend of soil humidity changes within the next 24 hours. The prediction results include the expected humidity value per hour and the prediction confidence interval.

[0037] Based on the prediction results, the AI module executes a decision algorithm to dynamically adjust the activation frequency of the data acquisition module. When it is predicted that the humidity will rise significantly, the system increases the data acquisition frequency, for example, from once per hour to once every 15 minutes. This is because the rising humidity may accelerate the metal corrosion process and requires closer monitoring. Conversely, if it is predicted that the humidity will remain stable or decline, the system may reduce the acquisition frequency, for example, change to collect data once every two hours, to save energy and storage space.

[0038] The AI module also considers the prediction confidence interval. If the prediction uncertainty is high (manifested as a wider confidence interval), the system tends to maintain a higher acquisition frequency to ensure that important humidity changes are not missed. Over time and with data accumulation, the AI module continuously updates and optimizes its prediction model to improve prediction accuracy.

[0039] In addition, the AI module regularly evaluates the performance of the prediction model, comparing the error between the predicted value and the actual observed value. If it is found that the prediction performance deteriorates, the system will automatically trigger the model retraining process to ensure that the prediction always maintains high accuracy.

[0040] Through this intelligent adjustment mechanism, the system can optimize resource utilization while ensuring the monitoring effect. For example, in the dry season, the system may significantly reduce the data acquisition frequency, and before the rainy season arrives, the system will automatically increase the acquisition frequency to prepare for possible sharp humidity changes. This not only improves the system's adaptability to environmental changes but also enhances the early warning ability for potential risks.

[0041] Example Six:

[0042] As Figure 1 shown, the backend server of the present invention is equipped with a high-performance processor and a large-capacity storage device, and runs specialized data management and analysis software. The wireless module uses 5G communication technology to ensure stable and reliable remote communication. The data storage module uses solid-state drives, which have high-speed read and write capabilities and large-capacity storage space.

[0043] The backend server establishes a connection with the wireless module through a secure network protocol. The server can send data request instructions to the wireless module at any time. These instructions contain parameters such as the type of data requested (e.g., current, voltage, resistance, or humidity data), time range, and data accuracy. After receiving the request, the wireless module passes the instruction to the data storage module.

[0044] Based on the received instruction, the data storage module retrieves the corresponding data from the storage device. During the retrieval process, the data storage module performs preliminary processing on the data, such as sorting it in chronological order and removing duplicate data. After the processing is completed, the data is transmitted back to the backend server through the wireless module.

[0045] To ensure the security and integrity of data transmission, the system adopts an encrypted transmission protocol. Each data packet contains a checksum, and the receiving party verifies the checksum to confirm the data integrity. If it is found that a data packet is damaged or lost, the backend server will automatically request a retransmission.

[0046] The backend server can flexibly adjust the data acquisition strategy according to different monitoring requirements. For example, under normal circumstances, the server may obtain summary data once a day at a fixed time. However, when an anomaly is detected or a warning message is received, the server can immediately initiate more frequent data requests to obtain more detailed real-time data to support quick decision-making and response.

[0047] The server also implements an intelligent data management function. It analyzes the frequency and pattern of data acquisition and automatically optimizes the data request strategy. For example, if it is found that the data changes significantly during a certain period, the system will automatically increase the data acquisition frequency during that period. On the contrary, for periods with less change, the system may reduce the data acquisition frequency to save network resources and processing time.

[0048] In addition, the backend server has data backup and recovery functions. It regularly obtains a complete data backup from the data storage module to ensure the security and availability of data even if on-site devices fail. The server also performs in-depth analysis on the acquired data to generate trend reports and anomaly detection reports to provide decision-making support for management personnel.

[0049] Embodiment Seven:

[0050] The present invention includes a data acquisition module, a detection component, a warning module, and a wireless module. The data acquisition module consists of a current collection module, a resistance collection module, a voltage collection module, and a humidity collection module. The detection component includes a sacrificial electrode, a reference electrode, a humidity probe, and a normally closed electromagnetic relay. The warning module includes an AI module and a threshold comparison module.

[0051] The system is arranged as follows: A normally closed electromagnetic relay is installed on the connection line between the sacrificial electrode and the pressure pipe. Both ends and the controlled end of the normally closed electromagnetic relay are connected to the data acquisition module. The reference electrode is also connected to the data acquisition module. A humidity probe is installed near each of the sacrificial electrode, the reference electrode, and the pressure pipe, and the humidity probe is connected to the humidity collection module of the data acquisition module. The data acquisition module is connected to the early warning module.

[0052] The active contact module in the wireless module is a key component of the system. This module sends a contact signal to the backend server every 5 minutes at preset time intervals. This contact signal contains basic information of the detection point, such as the detection point ID, the sending timestamp, etc. After receiving these contact signals, the backend server will record them in the database, including information such as the signal reception time and the signal content.

[0053] The backend server runs a monitoring program that continuously checks the reception of contact signals for each detection point. When the contact signals of a certain detection point are continuously lost, the monitoring program will trigger different levels of alarms according to the number of lost signals:

[0054] 1. If the contact signals are continuously lost 2 to 8 times (that is, there is no contact for 10 to 40 minutes), the monitoring program will generate a warning message. This warning message is sent to the system maintenance personnel through a preset communication channel (such as SMS, email, or dedicated App notification). The warning message contains information such as the detection point ID, the time of the last successful signal reception, and the number of lost signals. This level of warning alerts the maintenance personnel to the possible communication problems at this detection point, but it has not reached a serious level.

[0055] 2. If the contact signals are continuously lost more than 8 times (that is, there is no contact for more than 40 minutes), the monitoring program will generate a higher-level loss-of-contact alarm. This loss-of-contact alarm is also sent to the system maintenance personnel through a preset communication channel, but a more urgent notification method will be used, such as a phone call or repeated push notifications. The loss-of-contact alarm contains the detection point ID, the time of the last successful signal reception, the number of lost signals, and recommended emergency handling measures.

[0056] This design of the active contact module enables the system to detect and report communication problems or equipment failures in a timely manner. It provides a two-way verification mechanism: not only does the detection system report the status of the pressure pipeline to the server, but the server can also monitor the working status of the detection system itself. This mechanism greatly improves the reliability and real-time performance of the entire cathodic protection monitoring system.

[0057] When maintenance personnel receive an early warning message or a disconnection alarm, they can take appropriate measures based on the alarm level. For early warning messages, it may be necessary to remotely check the system status or schedule routine maintenance. For disconnection alarms, it may be necessary to immediately dispatch a technician to the site for inspection and repair.

[0058] Through this active contact and graded early warning mechanism, system managers can fully understand the working status of each detection point, discover and solve potential problems in a timely manner, and thus ensure the continuity and reliability of cathodic protection status detection of pressure pipelines. This not only improves the overall performance of the system, but also provides a strong guarantee for the safe operation of the pipeline.

[0059] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0060] The above description is only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in this field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A cathodic protection status detection and early warning processing system for pressure pipelines, comprising a data acquisition module, a detection component, an early warning module and a wireless module, characterized in that, The data acquisition module includes: a current collection module, a resistance collection module, a voltage collection module, and a humidity collection module; The detection component includes: a sacrificial electrode, a reference electrode, a humidity probe, and a normally closed electromagnetic relay; The warning module includes: an AI module and a threshold comparison module; A normally closed electromagnetic relay is set between the connection line of the sacrificial electrode and the pressure pipe. Both ends of the normally closed electromagnetic relay are connected to the data acquisition module, and the controlled end of the normally closed electromagnetic relay is connected to the data acquisition module. The reference electrode is connected to the data acquisition module. Humidity probes are arranged beside the sacrificial electrode, the reference electrode, and the pressure pipe, and the humidity probes are all connected to the humidity collection module of the data acquisition module. The data acquisition module sends the detected data to the warning module; S1: The data acquisition module is activated, and the normally closed electromagnetic relay is controlled to disconnect. The current collection module is started to obtain the current between the sacrificial electrode and the pressure pipe, the voltage collection module is started to obtain the voltage between the sacrificial electrode and the pressure pipe, the resistance collection module is started to obtain the resistance value between the sacrificial electrode and the pressure pipe, and the humidity collection module is started to obtain the humidity value of the humidity probe. The data acquisition module packs the collected data and sends it to the warning module. The data acquisition module goes into hibernation, and at the same time, the normally closed electromagnetic relay is controlled to close; S2: After receiving the data from the data acquisition module, the warning module judges whether the data exceeds the threshold through the threshold comparison module. If the data exceeds the threshold, the threshold comparison module sends the data to the AI module. The AI module evaluates the warning level of the data and sends the evaluation result and the data to the data storage module and sends them to the backend server through the wireless module. If the data does not exceed the threshold, it is directly sent to the data storage module.

2. The cathodic protection state detection and early warning processing system for a pressure pipeline according to claim 1, characterized in that, The data storage module includes a data annotation module and a storage unit. The data processed by the warning module is sent to the data storage module. The annotation information of the data annotation module includes the recording time, the warning level, and whether it exceeds the threshold, and the annotated data is stored in the storage unit.

3. The cathodic protection state detection and early warning processing system for a pressure pipeline according to claim 2, characterized in that, The wireless module includes a GPS module for obtaining the location information of the monitoring point. The AI module intelligently reads all the data annotations of the storage unit and evaluates the warning level of the monitoring point, and sends the warning level and location information of the monitoring point to the backend server through the wireless module.

4. The cathodic protection state detection and early warning processing system for a pressure pipeline according to claim 1, characterized in that, The humidity collection module is connected to the AI module. The AI module intermittently obtains the data of the humidity probe, predicts the future soil humidity change, and intelligently adjusts the activation frequency of the data acquisition module.

5. A cathodic protection status detection and early warning processing system for a pressure pipeline according to claim 1, characterized in that, The backend server actively obtains the data of the data storage module through the wireless module.

6. The cathodic protection state detection and early warning processing system for a pressure pipeline according to claim 1, characterized in that The wireless module also includes an active contact module. The active contact module sends a contact signal to the backend server every 5 minutes. The backend server records each contact signal. If the backend server detects that the contact signal is continuously lost 2 - 8 times, it sends a warning message to the maintenance personnel. If the backend server detects that the contact signal is continuously lost more than 8 times, it sends a monitoring point disconnection message to the maintenance personnel.

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