Pipeline magnetic flux leakage internal detection system and method with autonomous disaster recovery storage function

Abstract

The invention relates to the technical field of pipeline magnetic flux leakage internal detection, in particular to a pipeline magnetic flux leakage internal detection system and method with an autonomous disaster recovery storage function, and the system comprises a central electronic package, a data fusion module and a plurality of intelligent junction boxes. When the communication link state data determines that the intelligent junction box and the central electronic packet have a communication fault, the signal path switching module sends a switching control signal and establishes a data path with the independent memory module; the intelligent junction box autonomously receives sensor data and attitude information, and obtains a timestamp from the independent memory module to form a data frame with a spatio-temporal context; and storing the data frame in an independent memory module. According to the system, through the central electronic packet, the data fusion module and the intelligent junction box, the central electronic packet acquires data in a normal state, the intelligent junction box autonomously stores data frames with spatio-temporal context in a fault state, and then the data is integrated through the data fusion module, so that the problem that a detection data set is fractured after the pipeline magnetic flux leakage inner detector has a fault is solved.

Description

Technical Field

[0001] This application relates to the field of pipeline magnetic flux leakage detection technology, specifically to a pipeline magnetic flux leakage detection system and method with autonomous disaster recovery storage function. Background Technology

[0002] As a core infrastructure for oil and gas resource transportation, pipelines face complex operating conditions such as high temperature, high pressure, internal media corrosion, and external environmental impacts. Defects in the pipeline wall can lead to leaks, causing economic losses and safety risks. Pipeline magnetic flux leakage (MFLC) internal detection technology, which operates an MFLC detector inside the pipeline, uses the principle of magnetic flux leakage to collect sensor signals related to pipeline wall defects, enabling the location and assessment of these defects. This is a key technology for ensuring the safe operation of pipelines. Current pipeline MFLC internal detectors need to integrate data acquisition, transmission, and processing functions to cope with complex scenarios such as sudden changes in pipe diameter, foreign object compression, and severe vibrations. The reliability of its data acquisition architecture directly determines the success or failure of the detection task and the integrity of the data.

[0003] The data acquisition architecture of the pipeline magnetic flux leakage detection system adopts a master-slave centralized control model, forming two implementation schemes around the control model. Scheme 1 is a passive busbar scheme, where the busbar only integrates analog signal conditioning circuitry and level conversion functions, lacking autonomous data processing or decision-making capabilities. All data acquisition, processing, and storage logic relies on the central electronic package, and the busbar only serves as a preliminary conditioning and forwarding node for sensor signals. Scheme 2 is a basic intelligent busbar scheme, where the busbar integrates a microcontroller with basic data processing capabilities such as digital filtering and data packaging. However, all operations of the microcontroller, such as starting acquisition, stopping acquisition, and data uploading, strictly depend on the instructions of the central electronic package, lacking independent decision-making and autonomous operation capabilities, and only serving as an execution unit of the central electronic package.

[0004] In the master-slave centralized control model, the central electronic package is the sole decision-making and control core, while the junction box lacks autonomous operation capabilities. First, if the central electronic package fails or the communication link is interrupted, the detection data after the fault point will be completely lost, making data disaster recovery impossible. Second, data acquisition and storage lack spatiotemporal context integrity. Existing junction boxes do not have independent attitude perception and timestamp management capabilities. Even if they have basic data processing functions, they cannot generate complete data with attitude information and timestamps after being separated from the central electronic package, making subsequent data recovery and utilization difficult. Ultimately, this leads to the risk of fragmentation of the detection dataset, affecting the accuracy of pipeline defect location and assessment. Summary of the Invention

[0005] This application provides a pipeline magnetic flux leakage detection system and method with autonomous disaster recovery storage function to solve the problem of data fragmentation in the detection dataset after the pipeline magnetic flux leakage detector fails.

[0006] In the first aspect, this application provides a pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function, including: a central electronic package, a data fusion module and multiple intelligent junction boxes.

[0007] The central electronic package is configured to send an enable signal to the smart junction box for acquiring sensor data.

[0008] The intelligent junction box includes an environmental sensing module, a decision core module, an independent memory module, and a signal path switching module.

[0009] The environment perception module is configured to generate attitude information and communication link status data to characterize spatial reference and motion context.

[0010] The core decision-making module is configured as follows: It receives the enable signal, uploads sensor data to the central electronic package via the signal path switching module, and monitors the communication link status data from the environmental sensing module.

[0011] If a communication failure is detected between the smart junction box and the central electronic package based on the communication link status data, a switching control signal is sent to the signal path switching module to establish a data path with the independent memory module.

[0012] It receives sensor data and attitude information, and retrieves timestamps from an independent memory module.

[0013] Sensor data, attitude information, and timestamps are encapsulated to form a data frame with spatiotemporal context.

[0014] Data frames are stored in a separate memory module.

[0015] The data fusion module is configured to fuse sensor data stored in the central electronic package with data frames stored in at least one independent memory module in a smart junction box to generate a pipeline inspection dataset.

[0016] Optionally, the environment perception module includes an attitude sensing unit and a communication status monitoring unit.

[0017] The attitude sensing unit is configured to detect the mileage increment data, running speed data and three-axis attitude data of the detection equipment in the pipeline, and generate attitude information.

[0018] The communication status monitoring unit is configured to: collect the heartbeat communication packet transmission status, signal integrity parameters, and communication port level signals between the smart junction box and the central electronic package, and generate communication link status data.

[0019] Optionally, the decision core module is also configured as follows: When the communication link status data detects the continuous loss of a preset number N heartbeat communication packets from the central electronic packet, and the abnormal state of the communication port level signal continues to exceed a preset time threshold T, a switching control signal is generated.

[0020] Optionally, the independent memory module includes non-volatile storage units and sequential units.

[0021] The non-volatile storage unit is an eMMC or MicroSD card; the timing unit has a timing accuracy of no less than milliseconds, and the timestamp is the timing information generated by the timing unit.

[0022] Before storing the data frame, the decision core module is also configured to use a lightweight lossless compression algorithm to compress the data frame.

[0023] Optionally, the signal path switching module is configured as follows: It receives the switching control signal from the decision core module, disconnects the independent memory module from the bus connected to the central electronic package, and switches the independent memory module to the bus connected to the decision core module.

[0024] Optionally, the signal path switching module is also configured to: A hardware trigger signal is generated by detecting the voltage of the VBUS pin of the USB interface.

[0025] Based on a hardware trigger signal, the independent memory module is switched to a data path for communication with external devices.

[0026] When a USB device is detected to be unplugged, the data path for communication with external devices is disconnected, and the data path between the independent memory module and the decision core module is restored.

[0027] Optionally, the data fusion module is also configured as follows: The sensor data stored in the central electronic package and the data frames stored in the independent memory module are preprocessed, the data frames are decompressed, and the sensor data, attitude information and timestamps in the data frames are extracted.

[0028] Based on timestamps, the time axis of sensor data in the independent memory module is aligned with that of sensor data in the central electronic bag, and spatial position calibration is completed by combining attitude information.

[0029] The data stitching algorithm is used to stitch together aligned and calibrated sensor data, and abnormal data segments are removed through redundancy check to generate a complete and continuous pipeline inspection dataset.

[0030] Optionally, the decision core module is also configured as follows: When the smart junction box communicates normally with the central electronic package, the baseline parameters sent by the central electronic package are recorded. The baseline parameters include the period of the enable signal, the frequency of sensor data acquisition, and the data upload sequence.

[0031] After the switching control signal is generated, the acquisition timing is generated based on the baseline parameters, and sensor data and attitude information are acquired.

[0032] Optionally, an emergency energy module may also be included.

[0033] The emergency power module is used to provide power to the decision core module and the independent memory module when the decision core module determines that the main power supply has failed.

[0034] Secondly, this application provides a pipeline magnetic flux leakage detection method with autonomous disaster recovery and storage function, applied to the pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function of the first aspect, including: The central electronic package sends enable signals to multiple smart junction boxes to acquire sensor data.

[0035] The environment perception module generates attitude information and communication link status data to characterize the spatial reference and motion context.

[0036] Based on the enable signal, sensor data is uploaded to the central electronic package via the signal path switching module.

[0037] Monitor communication link status data from the environmental sensing module.

[0038] The system determines whether a communication failure has occurred between the smart junction box and the central electronic package based on communication link status data.

[0039] When a communication failure is detected, a switching control signal is sent to the signal path switching module.

[0040] In response to the switching control signal, a data path is established between the decision core module and the independent memory module through the signal path switching module.

[0041] Receive sensor data and attitude information.

[0042] Retrieve the timestamp from the independent memory module.

[0043] Sensor data, attitude information, and timestamps are encapsulated to form a data frame with spatiotemporal context, and the data frame is stored in an independent memory module.

[0044] The data fusion module integrates sensor data stored in the central electronic package with data frames stored in at least one smart junction box's independent memory module to generate a pipeline inspection dataset.

[0045] As can be seen from the above technical solutions, this application provides a pipeline magnetic flux leakage detection system and method with autonomous disaster recovery and storage function. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function includes: a central electronic package, a data fusion module, and multiple smart junction boxes; the central electronic package is configured to: send an enable signal to the smart junction boxes for collecting sensor data; the smart junction boxes include an environmental perception module, a decision core module, an independent memory module, and a signal path switching module; the environmental perception module is configured to: generate attitude information and communication link status data for characterizing spatial reference and motion context; the decision core module is configured to: receive the enable signal and upload the sensor data via the signal path switching module. The system connects to the central electronic package and monitors communication link status data from the environmental sensing module. If a communication failure is detected between the smart junction box and the central electronic package based on the communication link status data, a switching control signal is sent to the signal path switching module to establish a data path with the independent memory module. The system receives sensor data and attitude information and obtains timestamps from the independent memory module. The sensor data, attitude information, and timestamps are encapsulated to form a data frame with spatiotemporal context. The data frame is stored in the independent memory module. The data fusion module is configured to fuse the sensor data stored in the central electronic package with the data frames stored in the independent memory modules of at least one smart junction box to generate a pipeline detection dataset. This system, through the central electronic package, data fusion module, and smart junction boxes, allows the central electronic package to collect data under normal conditions. In case of a fault, the smart junction box autonomously stores data frames with spatiotemporal context, which are then integrated by the data fusion module. This solves the problem of fragmented detection datasets after a pipeline leakage magnetic field detector malfunctions. Attached Figure Description

[0046] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 One of the schematic diagrams of a pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function provided in the embodiments of this application; Figure 2 A second schematic diagram of the internal pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function provided in this application embodiment; Figure 3 This is a schematic diagram of the environmental perception module structure provided in an embodiment of this application; Figure 4 This is a schematic diagram of the independent memory module structure provided in an embodiment of this application; Figure 5 A flowchart of a pipeline magnetic flux leakage detection method with autonomous disaster recovery storage function provided in this application embodiment.

[0048] Illustration: Among them, 11. Central electronic package; 12. Intelligent junction box; 121. Environmental perception module; 1211. Attitude sensing unit; 1212. Communication status monitoring unit; 122. Decision core module; 123. Independent memory module; 1231. Timing unit; 1232. Non-volatile storage unit; 124. Signal path switching module; 13. Data fusion module; 14. Emergency energy module. Detailed Implementation

[0049] The embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described below do not represent all embodiments consistent with this application. They are merely examples of systems and methods consistent with some aspects of this application.

[0050] Pipeline magnetic flux leakage detectors are complex systems operating inside oil and gas pipelines subjected to high temperatures, high pressures, high impacts, and strong vibrations. Existing data acquisition architectures generally employ a master-slave centralized control model, with a central electronic package (e.g., 11) as the decision-making center, responsible for all decisions, timing control, and data aggregation; multiple junction boxes act as nerve endings, only responsible for the initial conditioning and forwarding of sensor signals. This master-slave centralized control model has significant problems under the complex operating conditions within pipelines. When the central electronic package (e.g., 11) and its communication link fail, all data after the point of failure in the entire detection task will be lost, causing irreversible economic losses and safety risks.

[0051] To address the issue of fragmented detection datasets after a malfunction of the pipeline magnetic flux leakage detector, see [link to relevant documentation]. Figure 1 This application provides a pipeline magnetic flux leakage detection system with autonomous disaster recovery storage function, comprising: Central electronic package 11, data fusion module 13 and multiple smart junction boxes 12.

[0052] The central electronic package 11 is configured to send an enable signal to the smart junction box 12 for acquiring sensor data.

[0053] The central electronic package 11 sends enable signals to each smart junction box 12. The enable signal is a command to trigger sensor data acquisition. The central electronic package 11 will generate and send enable signals at fixed intervals according to the preset scheme of pipeline detection, clearly informing the smart junction box 12 when to start sensor data acquisition, the acquisition duration, and the data upload node.

[0054] The intelligent junction box 12 includes an environmental perception module 121, a decision core module 122, an independent memory module 123, and a signal path switching module 124.

[0055] The environment perception module 121 is configured to generate attitude information and communication link status data to characterize the spatial reference and motion context.

[0056] The decision core module 122 is configured as follows: It receives an enable signal, uploads sensor data to the central electronic package 11 via the signal path switching module 124, and monitors the communication link status data from the environmental sensing module 121.

[0057] If a communication failure is determined based on the communication link status data between the smart junction box 12 and the central electronic package 11, a switching control signal is sent to the signal path switching module 124 to establish a data path with the independent memory module 123.

[0058] It receives sensor data and attitude information, and obtains the timestamp from the independent memory module 123.

[0059] Sensor data, attitude information, and timestamps are encapsulated to form a data frame with spatiotemporal context.

[0060] The data frame is stored in the independent memory module 123.

[0061] The data fusion module 13 is configured to fuse sensor data stored in the central electronic package 11 with data frames stored in at least one smart junction box 12's independent memory module 123 to generate a pipeline inspection dataset.

[0062] Specifically, the environmental perception module 121 generates attitude information and communication link status data to characterize the spatial reference and motion context; after receiving the enable signal from the central electronic package 11, the decision core module 122 uploads the data collected by the sensors to the central electronic package 11 via the signal path switching module 124, while continuously monitoring the communication link status. If a communication failure is detected, a switching control signal is sent to the signal path switching module 124 to establish a data path with the independent memory module 123. Subsequently, it receives sensor data and attitude information, combines them with the timestamp provided by the independent memory module 123 to encapsulate them into a data frame with spatiotemporal context and stores it; the data fusion module 13 then fuses the sensor data stored in the central electronic package 11 with the data frame with spatiotemporal context stored in the independent memory module 123 of the smart junction box 12 to generate a complete and continuous pipeline detection dataset. This not only ensures collaborative data acquisition under normal operating conditions but also solves the problem of data loss during communication failures, adapting to the stringent requirements for the integrity of detection data under complex pipeline conditions.

[0063] Understandably, attitude information and timestamps together constitute the spatiotemporal context of the data frame. This ensures that after a communication failure occurs in the central electronic package 11, the stored data is no longer isolated sensor readings, but rather a complete block of information data with a clear spatial location and attitude orientation. This guarantees that single-point data retains independent resolvability and localizability even after being separated from the main system.

[0064] During the data fusion phase: attitude information is the basis for achieving data stitching and reconstructing fragmented data into a continuous and complete dataset. Attitude information enables the data fusion module 13 to calibrate and stitch together the data from the central electronic package 11 with the backup data from each smart junction box 12 in spatial location based on the spatial motion trajectory.

[0065] In some embodiments, see Figure 3 The environmental perception module 121 includes an attitude sensing unit 1211 and a communication status monitoring unit 1212.

[0066] The attitude sensing unit 1211 is configured to detect the mileage increment data, running speed data and three-axis attitude data of the detection equipment in the pipeline, and generate attitude information.

[0067] The communication status monitoring unit 1212 is configured to: collect the heartbeat communication packet transmission status, signal integrity parameters and communication port level signals between the smart junction box 12 and the central electronic package 11, and generate communication link status data.

[0068] Specifically, to achieve autonomous disaster recovery under complex operating conditions, the intelligent junction box 12 needs to understand its own operating status and communication status. The environmental perception module 121 includes an attitude sensing unit 1211 and a communication status monitoring unit 1212. The attitude sensing unit 1211 detects the mileage increment data, operating speed data, and three-axis attitude data of the detection equipment in the pipeline, and the generated attitude information provides spatial context for the data frames. The communication status monitoring unit 1212 continuously collects communication data between the intelligent junction box 12 and the central electronic package 11, including the heartbeat communication packet transmission status, signal integrity parameters, and communication port level signals. The generated communication link status data can provide the decision core module 122 with the basis for judging communication failures, avoiding misjudging communication failures due to a single parameter, ensuring that the autonomous disaster recovery mode is triggered only when there is a real loss of connection, adapting to communication instability scenarios caused by high temperature and strong vibration in the pipeline, and ensuring the integrity of detection data and the effective execution of disaster recovery response.

[0069] In some embodiments, the decision core module 122 is further configured as follows: When the communication link status data detects the continuous loss of a preset number N heartbeat communication packets from the central electronic packet 11, and the abnormal state of the communication port level signal continues to exceed a preset time threshold T, a switching control signal is generated.

[0070] Specifically, in the pipeline magnetic flux leakage detection scenario, complex operating conditions such as instantaneous electromagnetic interference and slight vibration within the pipeline can cause momentary interruptions in communication between the smart junction box 12 and the central electronic package 11. If a communication fault is determined solely based on a single abnormal signal, it is easy to trigger erroneous switching, affecting normal detection. Therefore, a dual-condition determination mechanism is adopted to determine communication faults. While the environmental perception module 121 of the smart junction box 12 continuously collects communication link status data, the decision core module 122 analyzes the communication link status data. Only when it detects the continuous loss of a preset number N heartbeat communication packets sent by the central electronic package 11, and simultaneously monitors that the abnormal state of the communication port level signal continues to exceed a preset time threshold T, is a communication fault determined, and a switching control signal is generated.

[0071] The N value can be set according to the response speed of the detection system and the pipeline conditions, for example, N can be set to 5 to 10. The T value needs to be adapted to the duration of interference in the pipeline, for example, T can be set to 1 to 3 seconds. The dual judgment logic can effectively filter false fault signals caused by transient interference, avoid mode switching errors, and ensure that the intelligent junction box 12 only switches to the autonomous disaster recovery mode when the central electronic package 11 is truly disconnected. This prevents data loss and maintains the continuous operation of the system's detection function, adapting to the complex and ever-changing communication environment in the pipeline.

[0072] In some embodiments, see Figure 4 The independent memory module 123 includes a non-volatile storage unit 1232 and a timing unit 1231.

[0073] The non-volatile storage unit 1232 is an embedded multimedia card (eMMC) or a microSD card; the timing unit 1231 has a timing accuracy of not less than milliseconds, and the timestamp is the timing information generated by the timing unit 1231.

[0074] Before storing the data frame, the decision core module 122 is also configured to use a lightweight lossless compression algorithm to compress the data frame.

[0075] The intelligent junction box 12 needs to store data frames with spatiotemporal context for an extended period during communication failures, while ensuring data storage efficiency and time accuracy to meet subsequent data fusion requirements. To this end, in some embodiments, the independent memory module 123 employs a combination design of a non-volatile storage unit 1232 and a timing unit 1231. Specifically, the non-volatile storage unit 1232 uses eMMC or MicroSD cards, both of which have large capacity and vibration resistance, adapting to the severe vibration conditions within the pipeline and preventing data loss due to unstable storage media. The timing unit 1231 has a time accuracy of at least milliseconds, generating millisecond-precision timestamps to ensure that data frames accurately mark the acquisition time, providing a basis for subsequent timeline alignment with the data from the central electronic package 11.

[0076] Meanwhile, considering the large amount of pipeline inspection data, direct storage would easily occupy a lot of storage space. Before storing the data frame, the decision core module 122 will use a lightweight lossless compression algorithm to process the data frame. Without losing sensor data, attitude information and timestamp accuracy, the data volume is reduced, the effective storage time of the independent memory module 123 is extended, and the inspection data is avoided due to insufficient storage space.

[0077] In some embodiments, the signal path switching module 124 is configured to: The system receives a switching control signal from the decision core module 122, disconnects the independent memory module 123 from the bus connected to the central electronic package 11, and switches the independent memory module 123 to the bus connected to the decision core module 122.

[0078] When the intelligent junction box 12 and the central electronic package 11 communicate normally, the independent memory module 123 needs to maintain a connection with the central electronic package 11 through the shared bus in order to synchronously receive the configuration information of the central electronic package 11 or back up and store some data issued by the central electronic package 11. However, when the communication between the intelligent junction box 12 and the central electronic package 11 fails due to severe vibration or foreign object compression in the pipeline, if the independent memory module 123 is still connected to the original shared bus, it will not only be unable to receive the control commands of the decision core module 122, but also cause abnormal data transmission due to bus conflict. To this end, the signal path switching module 124 is configured to: after receiving the switching control signal issued by the decision core module 122, perform bus disconnection and switching operations, first disconnect the independent memory module 123 from the shared bus connected to the central electronic package 11 to avoid bus signal interference when communication fails; then reconnect the independent memory module 123 to the dedicated bus directly connected to the decision core module 122 to establish a data path between the decision core module 122 and the independent memory module 123. To ensure that after a communication failure, the decision core module 122 can transmit data frames with spatiotemporal context to the independent memory module 123, while preventing the original bus abnormality from affecting data storage, thereby ensuring the stability and reliability of data storage in the autonomous disaster recovery mode of the intelligent bus box 12.

[0079] In some embodiments, the signal path switching module 124 is further configured to: A hardware trigger signal is generated by detecting the voltage of the VBUS pin of the USB interface.

[0080] Based on the hardware trigger signal, the independent memory module 123 is switched to a data path for communication with external devices.

[0081] When the USB device is detected to be unplugged, the data path for communication with the external device is disconnected, and the data path between the independent memory module 123 and the decision core module 122 is restored.

[0082] After the pipeline leakage magnetic field detection task is completed, when the staff needs to export the spatiotemporal context data frame stored in the independent memory module 123 in the smart junction box 12, the signal path switching module 124 will execute the data export process.

[0083] When a staff member plugs a USB device into the USB interface of the smart junction box 12, the signal path switching module 124 immediately detects the voltage change of the VBUS pin of the USB interface and generates a hardware trigger signal. Based on the hardware trigger signal, the signal path switching module 124 switches the data path of the independent memory module 123 from its original connection with the decision core module 122 to a communication path with the external USB device. At this time, the smart junction box 12 directly presents itself as a standard mass storage device, specifically a USB flash drive. Staff members can quickly obtain the backup data in the independent memory module 123 through regular file reading operations, realizing a plug-and-play data export function.

[0084] After the data export is complete and the staff unplugs the USB device, the signal path switching module 124 detects the removal of the USB device, immediately disconnects the communication path with the external device, and restores the data path between the independent memory module 123 and the decision core module 122, so that the intelligent junction box 12 returns to the state of being ready for testing, providing a path guarantee for data acquisition, storage and autonomous disaster recovery function in case of failure in the next pipeline leakage magnetic field detection task.

[0085] In some embodiments, the data fusion module 13 is further configured to: The sensor data stored in the central electronic package 11 and the data frames stored in the independent memory module 123 are preprocessed, the data frames are decompressed, and the sensor data, attitude information and timestamps in the data frames are extracted.

[0086] Based on the timestamp, the sensor data in the independent memory module 123 is aligned with the time axis of the sensor data in the central electronic package 11, and spatial position calibration is completed by combining the attitude information.

[0087] The data stitching algorithm is used to stitch together aligned and calibrated sensor data, and abnormal data segments are removed through redundancy check to generate a complete and continuous pipeline inspection dataset.

[0088] Specifically, when the central electronic package 11 returns to normal or the detection task is completed, the data fusion module 13 first preprocesses the sensor data stored in the central electronic package 11 and the spatiotemporal context data frame stored in the independent memory module 123. The sensor data, attitude information and timestamp in the data frame can be extracted by decompressing the data frame to ensure that the data of the central electronic package 11 and the data extracted locally by the smart junction box 12 are consistent in format and complete in information.

[0089] Subsequently, the sensor data in the independent memory module 123 is aligned with the sensor data in the central electronic package 11 based on the timestamp, and the spatial position is calibrated by combining the attitude information to correspond to the same physical position of the pipeline detection, so as to avoid spatiotemporal deviation caused by different data sources.

[0090] Finally, the aligned and calibrated sensor data were stitched together using a data stitching algorithm, and a redundancy verification mechanism was activated simultaneously to remove abnormal data segments caused by operating condition interference. This resulted in the generation of a pipeline inspection dataset that covers the entire pipeline inspection path, is continuous and accurate, and provides reliable data support for subsequent pipeline defect location, corrosion degree assessment and other analysis work. This solved the problem of data breakage during the failure of the central electronic package 11.

[0091] The data stitching algorithm first analyzes the characteristics and correlations of the data. Through matching and interpolation techniques, it interfaces the sensor data segments of the central electronic package 11, which have already undergone alignment and calibration, with the sensor data segments of the independent memory module 123. During the stitching process, the algorithm dynamically adjusts the weights and fusion ratios of the data segments to ensure a smooth transition at the stitching points and avoid data abrupt changes or information loss. Furthermore, the algorithm possesses powerful anomaly handling capabilities, automatically identifying and eliminating abnormal data segments caused by operational interference.

[0092] In some embodiments, the decision core module 122 is further configured as follows: When the intelligent junction box 12 and the central electronic package 11 are communicating normally, the baseline parameters sent by the central electronic package 11 are recorded. The baseline parameters include the period of the enable signal, the acquisition frequency of sensor data, and the data upload sequence.

[0093] After the switching control signal is generated, the acquisition timing is generated based on the baseline parameters, and sensor data and attitude information are acquired.

[0094] Specifically, when the intelligent junction box 12 and the central electronic package 11 communicate normally, the decision core module 122 will synchronously record the baseline parameters issued by the central electronic package 11. The baseline parameters include the enable signal period, sensor data acquisition frequency, and data upload timing. The baseline parameters are the benchmark for matching the normal detection rhythm of the system. When complex working conditions such as sudden changes in pipe diameter or severe vibration occur in the pipeline, causing communication failure, the decision core module 122 determines that it needs to switch to autonomous working mode and can autonomously generate the acquisition timing based on the previously recorded baseline parameters. For example, when the intelligent junction box 12 and the central electronic package 11 are communicating normally, the enable signal periodically triggers sensor data acquisition. The leakage magnetic field sensor signal and the attitude information of the environmental perception module 121 are acquired at the original acquisition frequency. This ensures that the autonomously acquired data is consistent with the sensor data received and stored by the central electronic package 11 in terms of acquisition rhythm and data dimension. This avoids data fusion misalignment caused by inconsistent acquisition timing. When the data fusion module 13 integrates the data of the central electronic package 11 and the local data of the intelligent junction box 12, it can effectively achieve spatiotemporal alignment, ensuring the continuity and accuracy of the final pipeline detection dataset, thereby meeting the pipeline detection needs under various complex working conditions.

[0095] In some embodiments, see Figure 2 It also includes an emergency energy module 14.

[0096] The emergency power module 14 is used to provide power to the decision core module 122 and the independent memory module 123 when the decision core module 122 determines that the main power supply has failed.

[0097] In pipeline magnetic flux leakage detection scenarios, the intelligent junction box 12 relies on a main power supply. However, complex operating conditions within the pipeline may cause the main power supply to fail. If the intelligent junction box 12 stops working due to power failure, data acquisition and storage will be interrupted during the fault, failing to achieve disaster recovery goals. To address this, an emergency power module 14 is added. When the decision core module 122 determines that the main power supply has failed, it automatically switches to the emergency power module 14 to provide emergency power to the decision core module 122 and the independent memory module 123. This ensures that after the main power supply fails, the decision core module 122 can still operate normally for fault determination and data encapsulation logic, and the independent memory module 123 can completely store data frames with spatiotemporal context, avoiding data acquisition interruption or data corruption due to power failure. This improves the system survivability and data disaster recovery capability of the intelligent junction box 12 under extreme power failure conditions, ultimately ensuring the continuity and integrity of pipeline detection data.

[0098] In some embodiments, this application provides a pipeline magnetic flux leakage detection method with autonomous disaster recovery storage function, applied to the pipeline magnetic flux leakage detection system with autonomous disaster recovery storage function provided in the above embodiments. See [link to relevant documentation]. Figure 5 ,include: S101, the central electronic package 11 sends an enable signal to multiple smart junction boxes 12 for acquiring sensor data.

[0099] S102, The environment perception module 121 generates attitude information and communication link status data to characterize the spatial reference and motion context.

[0100] S103. Based on the enable signal, the sensor data is uploaded to the central electronic package 11 via the signal path switching module 124.

[0101] S104. Monitor the communication link status data from the environmental sensing module 121.

[0102] S105. Determine whether a communication failure has occurred between the intelligent junction box 12 and the central electronic package 11 based on the communication link status data.

[0103] S106. When a communication failure is detected, a switching control signal is sent to the signal path switching module 124.

[0104] S107. In response to the switching control signal, a data path is established between the decision core module 122 and the independent memory module 123 through the signal path switching module 124.

[0105] S108: Receive sensor data and attitude information.

[0106] S109. Obtain the timestamp from independent memory module 123.

[0107] S110. Encapsulate sensor data, attitude information and timestamps to form a data frame with spatiotemporal context, and store the data frame in independent memory module 123.

[0108] S111. The sensor data stored in the central electronic package 11 is fused with the data frames stored in the independent memory module 123 in at least one smart junction box 12 through the data fusion module 13 to generate a pipeline inspection dataset.

[0109] As can be seen from the above technical solutions, this application provides a pipeline magnetic flux leakage detection system and method with autonomous disaster recovery storage function. The pipeline magnetic flux leakage detection system with autonomous disaster recovery storage function includes: a central electronic package 11, a data fusion module 13, and multiple smart junction boxes 12; the central electronic package 11 is configured to send an enable signal to the smart junction boxes 12 for collecting sensor data; the smart junction box 12 includes an environmental perception module 121, a decision core module 122, an independent memory module 123, and a signal path switching module 124; the environmental perception module 121 is configured to generate attitude information and communication link status data for characterizing spatial reference and motion context; the decision core module 122 is configured to receive the enable signal and transmit the sensor data via the signal path switching module 124. The data is transmitted to the central electronic package 11; and the communication link status data from the environmental perception module 121 is monitored; if a communication failure is determined based on the communication link status data between the smart junction box 12 and the central electronic package 11, a switching control signal is sent to the signal path switching module 124 to establish a data path with the independent memory module 123; sensor data and attitude information are received, and a timestamp is obtained from the independent memory module 123; the sensor data, attitude information and timestamp are encapsulated to form a data frame with spatiotemporal context; the data frame is stored in the independent memory module 123; the data fusion module 13 is configured to fuse the sensor data stored in the central electronic package 11 with the data frame stored in the independent memory module 123 of at least one smart junction box 12 to generate a pipeline detection dataset. This system uses a central electronic package 11, a data fusion module 13, and an intelligent junction box 12. Under normal conditions, the central electronic package 11 collects data. In case of a fault, the intelligent junction box 12 autonomously stores data frames with spatiotemporal context. The data is then integrated by the data fusion module 13 to solve the problem of data fragmentation in the detection dataset after the pipeline leakage magnetic field detector malfunctions.

Claims

1. A pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function, characterized in that, include: Central electronic package, data fusion module and multiple smart junction boxes; The central electronic package is configured to send an enable signal to the smart junction box for acquiring sensor data. The intelligent junction box includes an environmental perception module, a decision core module, an independent memory module, and a signal path switching module; The environment perception module is configured to generate attitude information and communication link status data to characterize the spatial reference and motion context; The decision core module is configured as follows: Upon receiving the enable signal, the sensor data is uploaded to the central electronic package via the signal path switching module; and the communication link status data from the environmental sensing module is monitored. If, based on the communication link status data, it is determined that a communication failure has occurred between the smart junction box and the central electronic package, a switching control signal is sent to the signal path switching module to establish a data path with the independent memory module. Receive the sensor data and the attitude information, and obtain the timestamp from the independent memory module; The sensor data, the attitude information, and the timestamp are encapsulated to form a data frame with spatiotemporal context; The data frame is stored in the independent memory module; The data fusion module is configured to fuse sensor data stored in the central electronic package with data frames stored in at least one independent memory module in the smart junction box to generate a pipeline inspection dataset.

2. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, The environmental perception module includes an attitude sensing unit and a communication status monitoring unit; The attitude sensing unit is configured to detect the mileage increment data, running speed data and three-axis attitude data of the detection equipment in the pipeline, and generate the attitude information. The communication status monitoring unit is configured to: collect the heartbeat communication packet transmission status, signal integrity parameters, and communication port level signals between the smart junction box and the central electronic package, and generate the communication link status data.

3. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 2, characterized in that, The decision core module is also configured as follows: When the communication link status data detects the continuous loss of a preset number N heartbeat communication packets from the central electronic packet, and the abnormal state of the communication port level signal continues to exceed a preset time threshold T, the switching control signal is generated.

4. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, The independent memory module includes a non-volatile storage unit and a timing unit; The non-volatile storage unit is an eMMC or MicroSD card; the timing unit has a timing accuracy of not less than milliseconds, and the timestamp is the timing information generated by the timing unit; Before storing the data frame, the decision core module is also configured to use a lightweight lossless compression algorithm to compress the data frame.

5. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, The signal path switching module is configured as follows: The system receives the switching control signal from the decision core module, disconnects the independent memory module from the bus connected to the central electronic package, and switches the independent memory module to the bus connected to the decision core module.

6. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, The signal path switching module is also configured to: A hardware trigger signal is generated by detecting the voltage of the VBUS pin of the USB interface. Based on the hardware trigger signal, the independent memory module is switched to a data path for communication with external devices; When a USB device is detected to be unplugged, the data path for communication with the external device is disconnected, and the data path between the independent memory module and the decision core module is restored.

7. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, The data fusion module is also configured to: The sensor data stored in the central electronic bag and the data frames stored in the independent memory module are preprocessed, the data frames are decompressed, and the sensor data, attitude information and timestamps in the data frames are extracted. Based on the timestamp, the time axis of the sensor data in the independent memory module is aligned with that of the sensor data in the central electronic bag, and spatial position calibration is completed by combining the attitude information. The data stitching algorithm is used to stitch together aligned and calibrated sensor data, and abnormal data segments are removed through redundancy check to generate a complete and continuous pipeline inspection dataset.

8. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, The decision core module is also configured as follows: When the smart junction box and the central electronic package are communicating normally, the baseline parameters sent by the central electronic package are recorded. The baseline parameters include the period of the enable signal, the acquisition frequency of sensor data, and the data upload sequence. After the switching control signal is generated, the acquisition timing is generated based on the baseline parameters, and the sensor data and attitude information are acquired.

9. The pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function according to claim 1, characterized in that, It also includes an emergency energy module; The emergency energy module is used to provide power to the decision core module and the independent memory module when the decision core module determines that the main power supply has failed.

10. A pipeline magnetic flux leakage detection method with autonomous disaster recovery and storage function, applied to the pipeline magnetic flux leakage detection system with autonomous disaster recovery and storage function as described in any one of claims 1-9, characterized in that, include: The central electronic package sends enable signals to multiple smart junction boxes to acquire sensor data. The environment perception module generates attitude information and communication link status data to characterize the spatial reference and motion context. Based on the enable signal, the sensor data is uploaded to the central electronic package via the signal path switching module; Monitor communication link status data from the environmental sensing module; Based on the communication link status data, it is determined whether a communication failure has occurred between the smart junction box and the central electronic package; When a communication failure is detected, a switching control signal is sent to the signal path switching module; In response to the switching control signal, a data path is established between the decision core module and the independent memory module through the signal path switching module; Receive the sensor data and the attitude information; Obtain the timestamp from the independent memory module; The sensor data, the attitude information, and the timestamp are encapsulated to form a data frame with spatiotemporal context. The data frame is stored in the independent memory module; The data fusion module fuses the sensor data stored in the central electronic package with the data frames stored in at least one independent memory module in the smart junction box to generate a pipeline inspection dataset.

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