A direct current line fault detection method and device

Abstract

A DC line fault detection method and device, the method comprising: segmenting the DC line operation process continuously according to fixed time windows or events to obtain a plurality of adjacent segments, each segment containing at least one operation data, extracting the operation state characteristics after the current segment operation ends; calculating the current operation state criterion value according to the current segment and a preset number of historical segments; determining the operation state of the DC line according to the operation state criterion values and their change directions of a plurality of continuous segments in the current segment and the preset number of historical segments; if the DC line is in a suspicious operation state, performing a fault detection operation on the DC line. The triggering of the fault detection is based on the change trend of the operation state, the fault detection is triggered without relying on fixed thresholds, the influence of operation condition changes, load fluctuations and environmental interference on the detection results is effectively reduced, the stability and reliability of the detection results are improved, and the detection cost is low.

Description

Technical Field

[0001] This application relates to the field of smart grid technology, specifically to a method and apparatus for detecting DC line faults. Background Technology

[0002] With the widespread application of DC power distribution technology in distributed energy access, DC load power supply, and new power distribution systems, the operational safety and reliability of DC lines, as an important component of DC power distribution systems, are receiving increasing attention. Currently, DC line fault detection mainly relies on the monitoring and analysis of electrical parameters, but this still has limitations. Existing DC line fault detection methods can be mainly classified into the following categories:

[0003] Fault detection based on protection device operation: After a severe fault such as a short circuit or grounding occurs in a DC line and triggers the operation of protection devices such as circuit breakers and relays, fault identification and location are achieved by analyzing the protection operation information or the traveling wave signal of the fault. For example, in some high-voltage DC systems, the arrival time of the traveling wave front is used to trigger protection and perform fault detection. It has high reliability for obvious and sudden faults, but it usually only works when the fault has developed to a relatively serious stage, making it difficult to identify abnormal operating states or potential faults that have not yet triggered protection operation in a timely manner, and thus exhibiting a certain degree of lag.

[0004] Fault detection methods based on real-time monitoring thresholds: By continuously monitoring operating parameters such as DC voltage, DC current, and insulation resistance, a line abnormality is determined when the monitored quantity exceeds a preset threshold. For example, by comparing the current difference between the two ends of the line, an alarm is triggered when the difference exceeds a set threshold. However, this method is highly dependent on the threshold setting and is easily affected by load fluctuations, changes in operating conditions, and environmental interference, resulting in the risk of misjudgment and missed judgment, and poor reliability of the detection results.

[0005] Fault detection methods based on signal feature analysis or intelligent algorithms involve extracting features from acquired signals such as voltage and current (e.g., Fourier transform, wavelet analysis), or using machine learning and deep learning models to identify fault modes. For example, in multi-terminal DC systems, neural network models are used to classify waveform features to determine fault types. While these methods offer strong detection capabilities, they are highly dependent on data quality and model training, have high algorithm complexity, are difficult to adjust parameters, and are easily affected by field noise and operating condition changes in practical engineering applications, resulting in poor stability of detection results and high detection costs. Summary of the Invention

[0006] This application provides a DC line fault detection method and apparatus, which can solve the technical problems of poor stability and reliability of detection results and high detection cost in the current DC line fault detection technology.

[0007] To achieve the above objectives, in a first aspect, this application provides a DC line fault detection method, the method comprising:

[0008] The operation process of the DC line is continuously segmented according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operation data. After the operation of the current segment ends, its operation status characteristics are extracted.

[0009] Calculate the current operating status criterion value based on the current segment and a preset number of historical segments.

[0010] The operating status of the DC line is determined based on the operating status criterion values ​​and their changing directions of multiple consecutive segments in the current segment and a preset number of historical segments.

[0011] If the DC line is in a suspicious operating state, a fault detection operation is performed on the DC line.

[0012] Furthermore, in one embodiment, the operating data includes DC voltage, DC current, insulation monitoring parameters, DC power, or energy-related parameters; the insulation monitoring parameters include leakage current and insulation resistance.

[0013] In another embodiment, the event includes changes in operating conditions, power step changes, or load switching.

[0014] Furthermore, in one embodiment, the operating state characteristics include at least one of statistical characteristics, energy characteristics, and time-frequency characteristics.

[0015] Furthermore, in one embodiment, calculating the current operating status criterion value based on the current segment and a preset number of historical segments includes:

[0016] Based on a preset number of historical segments, the baseline operating status characteristics are calculated; the preset number is determined comprehensively based on the DC line load change rate, sampling frequency, and segment length.

[0017] The deviation of the current segment's operating status characteristics from the baseline operating status characteristics is calculated to obtain the operating status criterion value.

[0018] The operating status criteria are feature difference, normalized offset, or comprehensive deviation.

[0019] Furthermore, in one embodiment, determining the operating status of the DC line based on the operating status criterion values ​​and their changing directions of multiple consecutive segments in the current segment and a preset number of historical segments includes:

[0020] If the operating status criterion values ​​of the multiple consecutive sections show the same direction of change, and the operating status criterion values ​​of each section meet the preset offset judgment conditions, the DC line is in a suspicious operating state.

[0021] The number of the multiple consecutive segments is set according to actual needs; the same direction of change is either a continuous increase in value or a continuous decrease in value.

[0022] The offset determination criteria are determined based on the statistical characteristics of the preset number of historical segments, and the statistical characteristics include the fluctuation range or standard deviation of the operating status criterion values ​​in the preset number of historical segments.

[0023] Furthermore, in one embodiment, performing a fault detection operation on the DC line includes:

[0024] If, within a preset time period, at least one of the operating data continuously deviates from the normal operating state, and the direction of change of the deviation from the normal operating state is consistent with the direction of change of the operating state criterion value, the suspected operating state is confirmed to have fault characteristics, and the fault detection operation is executed.

[0025] The time period is set based on the load change rate of the DC power distribution system, sampling frequency, section length, historical operating status criterion recovery characteristics, and engineering experience.

[0026] Furthermore, in one embodiment, the fault detection operation includes fault location detection, insulation status detection, alarm information output, and operation strategy adjustment.

[0027] Perform one or more of the fault detection operations on the DC line.

[0028] Furthermore, in one embodiment, the method further includes: setting a cooling time, wherein after each fault detection operation is completed, the operating status of the DC line is monitored only during the cooling time without performing the fault detection operation; the cooling time is set according to the load change rate of the DC power distribution system, the recovery characteristics of historical operating status criteria, and engineering experience.

[0029] Secondly, this application provides a DC line fault detection device, the device comprising:

[0030] The feature extraction module is used to continuously segment the DC line operation process according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operation data. After the current segment finishes operation, its operation status features are extracted.

[0031] The calculation module is used to calculate the current operating status criterion value based on the current segment and a preset number of historical segments.

[0032] The status determination module is used to determine the operating status of the DC line based on the operating status criterion values ​​and their changing directions of multiple consecutive segments in the current segment and a preset number of historical segments;

[0033] The detection module is used to perform fault detection operations on the DC line if the DC line is in a suspicious operating state.

[0034] The beneficial effects of the technical solutions provided in this application include:

[0035] This application divides at least one continuous operating data point during the operation of a DC line into multiple adjacent operating data segments according to a preset segmentation rule. It extracts the operating state characteristics of each operating data segment, calculates the value of the current operating state criterion based on the current operating data segment and a preset number of historical operating data segments, and determines the operating state of the DC line based on the values ​​of the operating state criterion across multiple operating data segments and their changing directions. If the DC line is in a suspicious operating state, a fault detection operation is performed on the DC line. By segmenting and characterizing the operating parameters, and calculating the operating state criterion based on changes in operating state characteristics, fault detection is triggered based on the changing trend of the operating state, rather than a single instantaneous quantity. This allows for fault detection without relying on a fixed threshold, effectively reducing the impact of changes in operating conditions, load fluctuations, and environmental interference on the detection results, and improving the stability and reliability of the detection results. Furthermore, this application does not rely on complex neural network algorithms, resulting in low detection costs. Attached Figure Description

[0036] Figure 1 This is a flowchart of a DC line fault detection method according to an embodiment of this application.

[0037] Figure 2 This is a flowchart illustrating the specific steps involved in determining the suspicious state of a DC line according to an embodiment of this application.

[0038] Figure 3 This is a block diagram of a DC line fault detection device according to an embodiment of this application. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0040] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0041] In a first aspect, embodiments of this application provide a method for detecting DC line faults.

[0042] In one embodiment, see Figure 1 As shown, the above-mentioned DC line fault detection method includes:

[0043] S1. The DC line operation process is continuously segmented according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operation data. After the current segment finishes operation, its operation status characteristics are extracted. The fixed time window can be set to segment every 50 milliseconds, 100 milliseconds, or 500 milliseconds, depending on actual needs.

[0044] S2. Calculate the current operating status criterion value based on the current segment and a preset number of historical segments.

[0045] S3. Determine the operating status of the DC line based on the operating status criterion values ​​and their changing directions of multiple consecutive segments in the current segment and a preset number of historical segments.

[0046] S4. If the DC line is in a suspicious operating state, perform a fault detection operation on the DC line.

[0047] In this embodiment, the continuous segmentation of the DC line operation process and the extraction of operation status features are performed in real time during the DC line operation. Each time the segmentation condition is met (e.g., segmentation is performed every 50 milliseconds of operation), a current segment is obtained. After the current segment finishes running, its status features are extracted. All segments before the current segment are historical segments.

[0048] Each section contains at least one type of operational data, with a sampling frequency of 1 kHz. The sampling frequency can be adjusted within a certain range according to the scale of the DC power distribution system, sensor performance, and actual needs.

[0049] The operational data includes DC voltage, DC current, insulation monitoring parameters, DC power, or energy-related parameters. Insulation monitoring parameters include leakage current and insulation resistance. To reduce the impact of noise on subsequent judgments, the collected data can first undergo analog filtering and digital denoising processing, such as low-pass filtering, wavelet denoising, or moving average filtering, to improve the signal-to-noise ratio and stability of the data.

[0050] In this embodiment, the operation process of the DC line is continuously segmented according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operating data, including DC voltage, DC current, insulation monitoring quantity, DC power, or energy-related parameters. After the current segment finishes operation, its operating status characteristics are extracted. Then, based on the current segment and a preset number of historical segments, an operating status criterion value is calculated. Next, the operating status of the DC line is determined based on the operating status criterion values ​​of multiple consecutive segments and their changing directions. If multiple segments are determined to be in a suspicious operating state, a fault detection operation is performed on the DC line.

[0051] By constructing an operating status criterion that reflects the trend of changes in operating status, abnormal operating trends can be identified even when the DC line does not trigger protection actions, thus enabling early triggering of fault detection. Based on the persistent deviation judgment mechanism of the operating status criterion, instantaneous disturbances and true abnormal trends can be distinguished, reducing the impact of changes in operating conditions, load fluctuations and environmental interference on the detection results. Fault detection operations are only triggered in a targeted manner after a suspicious operating state is determined, avoiding frequent invalid detections under normal operating conditions, thereby reducing system burden and detection costs.

[0052] Furthermore, in one embodiment, the events in step S1 above include changes in operating conditions, power jumps, or load switching.

[0053] In this embodiment, an adaptive segmentation mechanism triggered by events such as changes in operating conditions, power jumps, or load switching is introduced. This enables the segmentation of operating data to dynamically respond to changes in the actual operating state of the DC power distribution system. When changes in operating conditions, power jumps, or load switching occur in the DC power distribution system, segmentation is performed in a timely manner. This accurately captures the operating state characteristics before and after these key events, avoiding the problem of fragmented or submerged event characteristics caused by fixed time window segmentation. It ensures that feature data reflecting the true operating state can be extracted in a timely manner when the system state changes significantly, thereby improving the accuracy of operating state criterion construction and the reliability of suspicious operating state identification. This makes fault detection triggering more closely aligned with actual operating conditions, further enhancing the stability and relevance of detection results.

[0054] Furthermore, in one embodiment, the operating state characteristics in step S1 above include at least one of statistical characteristics, energy characteristics, and time-frequency characteristics, wherein the statistical characteristics include mean, variance, and rate of change, the energy characteristics include energy magnitude, and the time-frequency characteristics include energy in a specific frequency band.

[0055] In this embodiment, by extracting operating status features, each segment corresponds to a feature description that reflects the operating status of its DC line.

[0056] Furthermore, in one embodiment, in step S2 above, the current operating status criterion value is calculated based on the current segment and a preset number of historical segments. The specific steps are as follows:

[0057] Based on a preset number of historical segments, the baseline operating status characteristics are calculated; wherein, the preset number is determined comprehensively based on the DC line load change rate, sampling frequency and segment length. In this embodiment, 3 or 5 historical segments can be selected.

[0058] The deviation of the current segment's operating status characteristics from the aforementioned baseline operating status characteristics is calculated to obtain the operating status criterion value.

[0059] The above operating status criteria are feature difference, normalized offset, or comprehensive deviation.

[0060] In this embodiment, a preset number of historical segments are determined based on the DC line load change rate, sampling frequency, and segment length to calculate the baseline operating status characteristics. This allows the baseline to adaptively reflect the actual operating characteristics and historical normal state of the DC line, avoiding baseline lag or oversensitivity caused by a fixed historical window length. Then, the deviation of the current segment's operating status characteristics from the baseline operating status characteristics is calculated to obtain the operating status criterion value. This operating status criterion characterizes the degree of deviation of the DC line's operating status from the historical normal state in the form of feature difference, normalized offset, or comprehensive deviation. Its value changes with the DC line's operating status, reflecting the changing trend of the DC line's operating status. Thus, without relying on protection actions or fixed thresholds, an effective quantitative assessment of the changing trend of the DC line's operating status can be achieved, improving the timeliness and adaptability of fault detection, while reducing the interference of changes in operating conditions on the detection results, and improving the stability and reliability of detection.

[0061] Furthermore, in one embodiment, in step S3 above, the operating status of the DC line is determined based on the operating status criterion values ​​and their changing directions of multiple consecutive segments in the current segment and a preset number of historical segments. The specific steps are as follows:

[0062] If the operating status criterion values ​​of multiple consecutive sections show the same direction of change, and the operating status criterion values ​​of each section meet the preset offset judgment conditions, the DC line is in a suspicious operating state.

[0063] The number of the above-mentioned consecutive segments can be set according to actual needs. In this embodiment, 3 or 5 consecutive segments can be used; the same direction of change is either a continuous increase in value or a continuous decrease in value.

[0064] The aforementioned offset determination criteria are determined based on the statistical characteristics of a preset number of historical segments. These statistical characteristics include the fluctuation range or standard deviation of the operating status criterion values ​​in the preset number of historical segments.

[0065] In this embodiment, a "persistent offset" determination mechanism is introduced. Instead of relying on the criteria results of a single operating segment, the judgment is based on the trend of operating status criteria values ​​and their changing directions across multiple consecutive segments. Only when the operating status criteria values ​​of multiple consecutive segments exhibit the same changing direction and all segments meet the offset determination conditions determined based on historical segment statistical characteristics, is the DC line determined to be in a suspicious operating state. By performing continuity and trend judgments on the operating status criteria corresponding to multiple consecutive segments, short-term fluctuations caused by random disturbances or instantaneous noise can be effectively distinguished from genuine abnormal operating trends. The number of consecutive segments can be flexibly set according to actual needs. The same direction of change includes continuous increase or decrease of value. The offset judgment condition is determined based on the statistical characteristics such as the fluctuation range or standard deviation of the operating status criterion value in the preset number of historical segments. This effectively distinguishes between instantaneous changes caused by factors such as noise and load fluctuations and continuous operating trend changes caused by potential faults or abnormal developments. It avoids the influence of instantaneous disturbances or occasional noise on the judgment result, improves the accuracy and reliability of suspicious operating status identification, and enables the offset judgment condition to adapt to different operating conditions, thereby enhancing the engineering adaptability and stability of the detection method.

[0066] Further, see Figure 2 As shown, another specific embodiment for judging the suspicious state of a DC line is given, and the specific steps are as follows:

[0067] A1. The operation process of a DC line is continuously segmented according to a fixed time window or event to obtain multiple adjacent segments.

[0068] A2. Extract the operational status features after the current segment has finished running.

[0069] A3. Calculate the current operating status criterion value based on the current segment and the preset number of historical segments.

[0070] A4. Determine whether the operating status criteria values ​​of multiple consecutive segments show the same direction of change, and whether the operating status criteria values ​​of each segment meet the preset offset judgment conditions. If yes, proceed to step A5; otherwise, proceed to step A1.

[0071] A5. The DC line is determined to be in a suspicious operating state.

[0072] Furthermore, in one embodiment, in step S4 above, a fault detection operation is performed on the DC line, specifically as follows:

[0073] If, within a preset time period, at least one data point in the operating data continuously deviates from the normal operating state, and the direction of change of the deviation from the normal operating state is consistent with the direction of change of the operating state criterion value, the suspected operating state is confirmed to have fault characteristics, and a fault detection operation is performed.

[0074] The above time period is set based on the load change rate of the DC power distribution system, sampling frequency, section length, historical operating status criterion recovery characteristics, and engineering experience.

[0075] In this embodiment, after determining that the DC line is in a suspicious state, it is further judged whether the suspicious state has fault characteristics. That is, within a preset time period, it is judged whether at least one data in the operating data continuously deviates from the normal operating state and whether the direction of change of the deviation from the normal operating state is consistent with the direction of change of the operating state criterion value. The time period is set according to the load change rate of the DC power distribution system, sampling frequency, section length, historical operating state criterion recovery characteristics and engineering experience. Thus, based on the suspicious trend identified by the operating state criterion, the continuous deviation of the original operating data is further verified to confirm whether the suspicious operating state has real fault characteristics, effectively eliminating possible misjudgments of the operating state criterion and improving the accuracy of fault detection. At the same time, a graded triggering method is used to perform fault detection operation. After initially judging it as a suspicious operating state, a rapid confirmation test is performed first. If the rapid confirmation result still indicates that an abnormal trend exists, a high-precision fault location or insulation test is further performed. While ensuring the reliability of detection, the system burden caused by directly performing high-precision detection is avoided, achieving a balance between detection accuracy and system overhead and reducing detection costs.

[0076] Furthermore, in one embodiment, the above-mentioned fault detection operation includes fault location detection, insulation status detection, alarm information output, and operation strategy adjustment; one or more of the fault detection operations are performed on the DC line.

[0077] In this embodiment, by setting the fault detection operation to include one or more of the following: fault location detection, insulation status detection, alarm information output, and operation strategy adjustment, the fault detection can flexibly select the corresponding detection and response measures according to the actual suspicious state of the DC line, thereby realizing the rational allocation of detection resources and the diversification of fault handling strategies.

[0078] Furthermore, in one embodiment, the above-mentioned DC line fault detection method further includes: setting a cooling time, and after completing each fault detection operation, monitoring only the operating status of the DC line without performing the fault detection operation during the cooling time; wherein, the cooling time is set according to the load change rate of the DC power distribution system, the recovery characteristics of historical operating status criteria, and engineering experience. In this embodiment, the cooling time can be 0.5 seconds to 10 seconds.

[0079] In this embodiment, by setting a cooling time, after each fault detection operation is completed, the operating status of the DC line is monitored only during the cooling time without performing the fault detection operation. The cooling time is set according to the load change rate of the DC power distribution system, the recovery characteristics of historical operating status criteria, and engineering experience. This avoids triggering the detection again after the fault detection is triggered because the operating status has not yet stabilized. It prevents the increased system burden and waste of resources caused by frequent triggering of fault detection operations, and ensures that the normal monitoring process is resumed after the operating status has stabilized. This is conducive to the long-term stable operation of the DC line, further reduces the detection cost, and improves the targeting of the detection and the reliability of the system operation.

[0080] Secondly, embodiments of this application also provide a DC line fault detection device.

[0081] In one embodiment, see Figure 3 As shown, the aforementioned DC line fault detection device includes a feature extraction module, a calculation module, a state determination module, and a detection module, specifically:

[0082] The feature extraction module is used to continuously segment the DC line operation process according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operation data. After the current segment finishes operation, its operation status features are extracted.

[0083] The calculation module is used to calculate the current operating status criterion value based on the current segment and a preset number of historical segments.

[0084] The status determination module is used to determine the operating status of the DC line based on the operating status criterion values ​​and their changing directions of the current segment and multiple consecutive segments in a preset number of historical segments.

[0085] The detection module is used to perform fault detection operations on the DC line if the DC line is in a suspicious operating state.

[0086] In this application, the operation process of a DC line is continuously segmented according to a fixed time window or event to obtain multiple adjacent segments and extract operating status features. Operating status criterion values ​​are calculated based on the current segment and a preset number of historical segments. The operating status of the DC line is then determined based on the operating status criterion values ​​of multiple consecutive segments and their changing directions. Finally, when a suspicious operating status is identified, a fault detection operation is performed, thus constructing a complete fault detection system based on the changing trends of DC line operating status. This system introduces an adaptive segmentation mechanism triggered by events such as changes in operating conditions, power jumps, or load switching. This allows the segmentation of operating data to dynamically respond to actual changes in the operating status of the DC distribution system, accurately capturing operating status features before and after key events, and preventing event features from being fragmented or overwhelmed.

[0087] Meanwhile, by extracting statistical features, energy features, and time-frequency features, each segment is given a characteristic description that reflects its operating status. Then, based on the DC line load change rate, sampling frequency, and segment length, a preset number of historical segments are determined to calculate the baseline operating status characteristics, so that the baseline can adaptively reflect the actual operating characteristics and historical normal status of the DC line.

[0088] Further calculations are performed to determine the deviation of the current section's operating status characteristics from the baseline operating status characteristics, resulting in an operating status criterion value. This value is characterized by the deviation of the DC line's operating status from its historical normal state, expressed as a feature difference, normalized offset, or comprehensive deviation. The value of this criterion value changes with the DC line's operating status and reflects the trend of its changes.

[0089] A "persistent deviation" judgment mechanism is introduced, which makes trend judgments based on the operating status criteria values ​​and their changing directions of multiple consecutive segments. A DC line is only judged as having a suspicious operating state when the operating status criteria values ​​of multiple consecutive segments show the same changing direction and all segments meet the deviation judgment conditions determined based on the statistical characteristics of historical segments. This effectively distinguishes between instantaneous changes caused by factors such as noise and load fluctuations and continuous operating trend changes caused by potential faults or abnormal developments, avoiding the influence of instantaneous disturbances or occasional noise on the judgment results. After determining a suspicious state, the persistent deviation of the original operating data is used again to confirm whether there are real fault characteristics. A graded triggering method is used to execute fault detection operations, including fault location detection, insulation status detection, alarm information output, and operating strategy adjustment.

[0090] Finally, by setting a cooling time to avoid frequent triggering of detection, effective quantitative assessment of the changing trend of DC line operating status and early triggering of fault detection can be achieved without relying on protection actions or fixed thresholds. This improves the timeliness, stability, and pertinence of fault detection, reduces the impact of changes in operating conditions, load fluctuations, and environmental interference on detection results, avoids frequent invalid detections under normal operating conditions, reduces system burden and resource waste, achieves a balance between detection accuracy and system overhead, reduces detection costs, and is conducive to the long-term stable operation of DC lines.

[0091] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0092] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0093] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0094] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0095] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0096] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0097] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for detecting faults in DC lines, characterized in that, The method includes: The operation process of the DC line is continuously segmented according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operation data. After the current segment has finished operating, its operation status characteristics are extracted. Calculate the baseline operating status characteristics based on a preset number of historical segments; The deviation of the current segment's operating status characteristics from the baseline operating status characteristics is calculated to obtain the operating status criterion value; the operating status criterion is the feature difference, normalized offset, or comprehensive deviation degree. If the operating status criterion values ​​of the multiple consecutive sections show the same direction of change, and the operating status criterion values ​​of each section meet the preset offset judgment conditions, the DC line is in a suspicious operating state. If the DC line is in a suspicious operating state, a fault detection operation is performed on the DC line.

2. The DC line fault detection method as described in claim 1, characterized in that, The operating data includes DC voltage, DC current, insulation monitoring quantities, DC power, or energy-related parameters; the insulation monitoring quantities include leakage current and insulation resistance.

3. The DC line fault detection method as described in claim 1, characterized in that, The events include changes in operating conditions, power surges, or load switching.

4. The DC line fault detection method as described in claim 1, characterized in that, The operational status characteristics include at least one of statistical characteristics, energy characteristics, and time-frequency characteristics.

5. The DC line fault detection method as described in claim 1, characterized in that, The preset quantity is determined based on the DC line load change rate, sampling frequency, and section length.

6. The DC line fault detection method as described in claim 1, characterized in that, The number of the multiple consecutive segments is set according to actual needs; the same direction of change is either a continuous increase in value or a continuous decrease in value; The offset determination criteria are determined based on the statistical characteristics of the preset number of historical segments, and the statistical characteristics include the fluctuation range or standard deviation of the operating status criterion values ​​in the preset number of historical segments.

7. The DC line fault detection method as described in claim 1, characterized in that, Performing fault detection operations on the DC line includes: If, within a preset time period, at least one of the data in the operating data continuously deviates from the normal operating state, and the direction of change of the deviation from the normal operating state is consistent with the direction of change of the operating state criterion value, it is confirmed that the suspicious operating state has fault characteristics, and the fault detection operation is executed. The time period is set based on the load change rate of the DC power distribution system, sampling frequency, section length, historical operating status criterion recovery characteristics, and engineering experience.

8. The DC line fault detection method as described in claim 1 or claim 7, characterized in that, The fault detection operation includes fault location detection, insulation status detection, alarm information output, and operation strategy adjustment. Perform one or more of the fault detection operations on the DC line.

9. The DC line fault detection method as described in claim 1, characterized in that, Also includes: A cooling time is set so that after each fault detection operation is completed, the operating status of the DC line is monitored only during the cooling time without performing the fault detection operation; the cooling time is set according to the load change rate of the DC power distribution system, the recovery characteristics of historical operating status criteria, and engineering experience.

10. A DC line fault detection device, characterized in that, The device includes: The feature extraction module is used to continuously segment the DC line operation process according to a fixed time window or event to obtain multiple adjacent segments. Each segment contains at least one type of operation data. After the current segment finishes operation, its operation status features are extracted. The calculation module is used to calculate the baseline operating status characteristics based on a preset number of historical segments; it is also used to calculate the deviation of the operating status characteristics of the current segment from the baseline operating status characteristics to obtain the operating status criterion value; the operating status criterion is the feature difference, the normalized offset, or the comprehensive deviation degree. The status determination module is used to determine the DC line as a suspicious operating state if the operating status criterion values ​​of the multiple consecutive segments show the same direction of change and the operating status criterion values ​​of each segment meet the preset offset judgment conditions. The detection module is used to perform fault detection operations on the DC line if the DC line is in a suspicious operating state.

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