Cable outer sheath fault location system and method

Abstract

The present invention discloses a cable outer sheath fault location system and method, the method comprises obtaining the cable outer sheath historical data, constructing a parameter three-dimensional influence model based on the parameter influence relationship according to the cable outer sheath historical data; obtaining the cable outer sheath current data, outputting the suspected fault section according to the parameter three-dimensional influence model and the cable outer sheath current data; outputting the cable outer sheath fault position according to the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold. The beneficial effect of the present invention is that it realizes the accurate location of the fault, and avoids the false alarm of the fault by mutual verification through the influence relationship between the parameters.

Description

Technical Field

[0001] The present invention relates to the technical field of cable fault location, and in particular to a cable outer sheath fault location system and method. Background Art

[0002] As an important part of the cable, the cable sheath plays a vital role in the safe operation of the cable. Once the outer sheath fails, such as damage or aging, it will not only affect the normal use of the cable, but may also cause more serious safety problems. Therefore, accurately locating the cable sheath fault and repairing it in time is an important measure to ensure the safe and stable operation of the power system.

[0003] Sensors play a vital role in cable sheath fault location technology. Sensors can monitor the operating status of the cable sheath in real time, collect relevant data and analyze and process it to accurately locate the fault point. However, the accuracy of the sensor has a direct impact on the accuracy of cable sheath fault location. If the sensor is not accurate enough, it may cause deviation or misjudgment of fault location, thereby delaying the fault repair time.

[0004] The patent "A method, device, equipment and medium for identifying cable outer sheath fault", publication number: CN117647700A, publication date: March 5, 2024, specifically discloses a method including: when the cable is in the operating state and the grounding plate of the metal shielding layer of the cable is switched to the suspended state, a short-circuit control signal is sent to the short-circuit control device, and the short-circuit control device is controlled to the first state or the second state by the short-circuit control signal; in the first state, the grounding plate is connected to the grounding end, and in the second state, the grounding plate is disconnected from the grounding end; one end of the short-circuit control device is connected to the grounding plate of the metal shielding layer of the cable, and the other end is connected to the grounding end; when the grounding plate is disconnected from the grounding end, the voltage value at each position of the cable outer sheath is obtained; if the voltage value at the target position meets the voltage fault condition, the target position is determined to be the outer sheath fault position. The disadvantage of this scheme is that it depends on the monitoring accuracy of the voltage value. Once a voltage acquisition device fails, the positioning of the fault position will be abnormal.

[0005] The patent "A method for locating defects in high-voltage cable sheaths based on broadband impedance spectrum of sheath grounding loop", publication number: CN117434386A, publication date: January 23, 2024, specifically discloses the steps of establishing a high-voltage cable cross-connection model; using CT to inject a frequency sweep signal at the metal sheath of the first section of the cable, and synchronously measuring the broadband response current signal of the injection port; establishing a broadband impedance spectrum when the cable sheath is intact according to the amplitude and phase of the response current signal and the injected voltage signal; when there is a defect in at least one phase of the cable metal sheath, respectively establish broadband impedance spectra when the sheath is defective and when the adjacent phase metal sheath is intact; after integral transformation of the real part of the input impedance, locate the defect according to the broadband anti-periodic characteristics of the cable sheath grounding loop. The disadvantages of this scheme are: it is necessary to construct a broadband impedance spectrum, which is complex to calculate and inefficient. Summary of the invention

[0006] In view of the problem that the cable outer sheath fault positioning in the prior art depends on the accuracy of the sensor and has low positioning efficiency, the present invention provides a cable outer sheath fault positioning system and method, which constructs a parameter three-dimensional influence model based on the interaction relationship of parameters in the cable outer sheath historical data and their influence on the health status of the cable outer sheath, and then obtains the suspected fault section according to the current data of the cable outer sheath and the parameter three-dimensional influence model, and outputs the cable outer sheath fault position according to the overlap frequency of the suspected fault section, which not only realizes the accurate positioning of the fault, but also avoids the false alarm of the fault by mutual verification through the influence relationship between the parameters.

[0007] In order to achieve the above-mentioned technical objectives, the present invention provides a technical solution, which is a cable outer sheath fault locating system, including: a data acquisition module, used to collect and record cable outer sheath data; a three-dimensional modeling module, used to construct a parameter three-dimensional influence model based on the cable outer sheath data; a suspicious analysis module, used to output a suspected fault section according to the parameter three-dimensional influence model; a fault locating module, used to output the cable outer sheath fault position according to the overlap frequency of the suspected fault section.

[0008] Furthermore, the data acquisition module includes a temperature sensor, a humidity sensor and a pressure sensor.

[0009] Another technical solution provided by the present invention is a method for locating a cable outer sheath fault, comprising the following steps: obtaining historical data of the cable outer sheath, and constructing a parameter three-dimensional influence model based on parameter influence relationship according to the historical data of the cable outer sheath; obtaining current data of the cable outer sheath, and outputting a suspected fault section according to the parameter three-dimensional influence model and the current data of the cable outer sheath; and outputting the cable outer sheath fault position according to the overlap frequency of the suspected fault section and a preset overlap frequency threshold.

[0010] Furthermore, the three-dimensional parameter influence model based on the parameter influence relationship constructed according to the historical data of the cable outer sheath includes: obtaining the historical data of the cable outer sheath, extracting the fluctuation characteristic parameters of the historical data of the cable outer sheath, and constructing a first parameter influence curve based on the mutual influence relationship of the fluctuation characteristic parameters; dividing the historical data of the cable outer sheath to obtain the historical fault data of the cable outer sheath and the historical normal data of the cable outer sheath; extracting the fault characteristic parameters of the cable outer sheath according to the historical fault data of the cable outer sheath and the historical normal data of the cable outer sheath, and constructing a second parameter influence curve based on the historical fault data of the cable outer sheath and the fault characteristic parameters; constructing the three-dimensional parameter influence model with the first parameter influence curve and the second parameter influence curve.

[0011] Furthermore, constructing the first parameter influence curve based on the mutual influence relationship of the fluctuation characteristic parameters includes: obtaining the distance of each fluctuation characteristic parameter based on a distance algorithm; and constructing the first parameter influence curve with the distance and influence value of each fluctuation characteristic parameter.

[0012] Furthermore, the construction of the second parameter influence curve based on the historical fault data of the cable outer sheath and the fault characteristic parameters includes: obtaining the distance between the fault characteristic parameters and the fault location based on a distance algorithm; and constructing the second parameter influence curve based on the distance between the fault characteristic parameters and the fault location, the fault characteristic parameter value, and the fault characteristic parameter value monitoring timing.

[0013] Further, the construction of the parameter three-dimensional influence model with the first parameter influence curve and the second parameter influence curve also includes: obtaining cable layout data, constructing a three-dimensional model according to the cable layout data; constructing the parameter three-dimensional influence model based on the three-dimensional model and the first parameter influence curve and the second parameter influence curve. Further, the output of the suspected fault section according to the parameter three-dimensional influence model and the current data of the cable outer sheath includes: obtaining the suspected fault location points according to the parameter three-dimensional influence model and the current data of the cable outer sheath, and obtaining the suspected fault location points with at least two identical acquisition layout points. Further, the output of the cable outer sheath fault location according to the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold includes: obtaining all suspected fault sections, calculating the coincidence frequency of the location points in each suspected fault section; if the coincidence frequency of the location point is greater than the preset coincidence frequency threshold, the location is determined to be the cable outer sheath fault location.

[0014] Furthermore, the method of outputting the fault position of the cable outer sheath based on the overlap frequency of the suspected fault section and the preset overlap frequency threshold also includes: if any suspected fault section does not overlap, obtaining the historical suspected fault sections in a preset time period, calculating the time sequence overlap frequency of the suspected fault section and the time sequence overlap trend of the suspected fault section based on the historical suspected fault sections and the current suspected fault section, and outputting the fault position of the cable outer sheath based on the time sequence overlap frequency of the suspected fault section, the time sequence overlap trend of the suspected fault section and the preset overlap frequency threshold.

[0015] The beneficial effects of the present invention are as follows: (1) A three-dimensional model of cable laying is constructed based on cable laying data, and the mutual influence relationship of each collection and laying point in the three-dimensional model is obtained by combining the first parameter influence curve, and the relationship between each collection and laying point data and different cable outer sheath position points is obtained by combining the second parameter influence curve, thereby obtaining a parameter three-dimensional influence model. Through the physical space structure of the cable laying, the distribution and change law of different parameters in the current space and the mutual influence relationship are obtained, so that the fault position of the cable outer sheath can be quickly located, and the efficiency and accuracy of fault diagnosis can be improved.

[0016] (2) The fault location of the cable outer sheath is determined based on the overlap of the suspected fault section, which effectively eliminates accidental factors and further screens out errors caused by abnormal monitoring parameters due to abnormal sensors, thereby improving the accuracy of fault location. At the same time, the preset overlap frequency threshold can be adjusted according to the actual situation of the cable system, historical fault data, and operation and maintenance strategies, so that the fault location result will not be too conservative and miss real faults, nor will it be too sensitive and generate a large number of false alarms, and it is more applicable. The use of suspected fault sections and three-dimensional models can intuitively obtain the overlap position without the need for a large number of position calculations, thereby improving the efficiency of fault location. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 The present invention is a schematic flow chart of a cable outer sheath fault locating method. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific implementation method described herein is only an optimal embodiment of the present invention, which is only used to explain the present invention and does not limit the scope of protection of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0019] As a first embodiment of the present invention, a cable outer sheath fault location system includes:

[0020] Data acquisition module, used to collect and record the data of the cable outer sheath;

[0021] 3D modeling module, used to build a parametric 3D influence model based on cable outer sheath data;

[0022] Suspicious analysis module, used to output suspected fault sections based on the parameter three-dimensional impact model;

[0023] The fault location module is used to output the fault location of the cable outer sheath according to the coincidence frequency of the suspected fault section.

[0024] In this embodiment, the data acquisition module is communicatively connected to the three-dimensional modeling module and the suspicious analysis module, the three-dimensional modeling module is communicatively connected to the suspicious analysis module, and the suspicious analysis module is communicatively connected to the fault location module. Among them, the data acquisition module obtains the historical data of the cable outer sheath and outputs it to the three-dimensional modeling module, the three-dimensional modeling module constructs a parameter three-dimensional influence model based on the parameter influence relationship according to the historical data of the cable outer sheath, the data acquisition module obtains the current data of the cable outer sheath and outputs it to the suspicious analysis module, the suspicious analysis module calls the parameter three-dimensional influence model in the three-dimensional modeling module to output the suspected fault section to the fault location module, and the fault location module outputs the fault position of the cable outer sheath according to the overlap frequency of the suspected fault section and the preset overlap frequency threshold.

[0025] The fault location module can be connected to the user end, or it can include a display screen that interacts with the user. The three-dimensional model of the cable is displayed on the display screen, and the fault location is located in the three-dimensional model of the cable, so that the operation and maintenance personnel can intuitively obtain the fault location and improve fault maintenance and processing.

[0026] In this embodiment, the data acquisition module includes a temperature sensor, a humidity sensor, and a pressure sensor. The cable outer sheath data is obtained by the data collected by each sensor. In some cases, the cable outer sheath data includes pre-known cable data, such as laying depth or height, cable outer sheath thickness, cable outer sheath material, etc.

[0027] In the three-dimensional modeling module, the first analysis module calls the cable outer sheath historical data collected by the data acquisition module, extracts the fluctuation characteristic parameters of the cable outer sheath historical data, and constructs a first parameter influence curve with the characteristic parameters in the cable outer sheath data as the mutual influence relationship of the fluctuation characteristic parameters. The second analysis module divides the cable outer sheath historical data to obtain the cable outer sheath historical fault data and the cable outer sheath historical normal data, extracts the cable outer sheath fault characteristic parameters that affect the cable outer sheath fault according to the cable outer sheath historical fault data and the cable outer sheath historical normal data, and constructs a second parameter influence curve based on the cable outer sheath historical fault data and the fault characteristic parameters. The third analysis module constructs a parameter three-dimensional influence model with the first parameter influence curve and the second parameter influence curve.

[0028] The first parameter influence curve is used to verify the collected data of each sensor to avoid errors in the final fault location caused by damage to a sensor or abnormal collection of erroneous data. At the same time, the parameter three-dimensional influence model is used to intuitively obtain the influence of the collection parameters of each sensor under the three-dimensional mode on the distance, thereby improving the accuracy of fault location while improving the efficiency of fault location.

[0029] like Figure 1 As shown, as a second embodiment of the present invention, a method for locating a cable outer sheath fault includes the following steps:

[0030] Obtain historical data of the cable outer sheath, and construct a three-dimensional parameter influence model based on parameter influence relationship according to the historical data of the cable outer sheath;

[0031] Obtain the current data of the cable outer sheath, and output the suspected fault section based on the parameter three-dimensional influence model and the current data of the cable outer sheath;

[0032] The fault location of the cable outer sheath is output based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold.

[0033] In this embodiment, a three-dimensional parameter influence model is constructed based on the interaction relationship of parameters in the historical data of the cable outer sheath and their influence on the health status of the cable outer sheath, and then the suspected fault section is obtained according to the current data of the cable outer sheath and the three-dimensional parameter influence model, and the cable outer sheath fault position is output according to the overlap frequency of the suspected fault section. This achieves accurate positioning of the fault and avoids false alarms of the fault.

[0034] Specifically, the cable outer sheath historical data includes the cable outer sheath historical temperature data, the cable outer sheath historical humidity data, the cable outer sheath historical pressure data, and the cable outer sheath historical fault location data. The parameter three-dimensional influence model based on the parameter influence relationship is constructed according to the cable outer sheath historical data, including:

[0035] Acquire historical data of the cable outer sheath, extract fluctuation characteristic parameters of the historical data of the cable outer sheath, and construct a first parameter influence curve based on the mutual influence relationship of the fluctuation characteristic parameters;

[0036] Divide the cable outer sheath historical data to obtain the cable outer sheath historical fault data and the cable outer sheath historical normal data;

[0037] Extracting the fault characteristic parameters of the cable outer sheath according to the historical fault data of the cable outer sheath and the historical normal data of the cable outer sheath, and constructing the second parameter influence curve based on the historical fault data of the cable outer sheath and the fault characteristic parameters;

[0038] A parameter three-dimensional influence model is constructed using the first parameter influence curve and the second parameter influence curve.

[0039] In this embodiment, the fluctuation characteristic parameters are characteristic parameters that affect the change of the cable outer sheath data, such as the cable laying depth or height, the cable outer sheath thickness, the cable outer sheath material, the cable outer sheath temperature, the cable outer sheath humidity and the cable outer sheath pressure, etc. The fault characteristic parameters are characteristic parameters that affect the cable outer sheath fault, such as the cable outer sheath temperature, the cable outer sheath humidity and the cable outer sheath pressure, etc. A first parameter influence curve is constructed according to the mutual influence relationship of the fluctuation characteristic parameters to characterize the mutual influence between the various parameters of the cable outer sheath, such as the influence of the cable laying depth or height on the cable outer sheath thickness, the influence of the cable outer sheath thickness and the cable outer sheath material on the cable outer sheath humidity level, etc. A second parameter influence curve is constructed according to the fault characteristic parameters to characterize the influence of various fault characteristic parameters on the cable outer sheath, such as the influence of the cable outer sheath temperature on the cable outer sheath loss, and the influence of the cable outer sheath humidity on the cable outer sheath loss. The three-dimensional parameter influence model is constructed with the first parameter influence curve and the second parameter influence curve, so that when the suspected fault section is obtained according to the three-dimensional parameter influence model, the mutual influence between the parameters can be obtained. For example, some parameters have little influence in the fault data and are easily ignored, but in actual applications, the parameters will affect the fault characteristic parameters, resulting in changes in the fault characteristic parameters. The mutual influence between the parameters and the influence of the fault characteristic parameters on the cable outer sheath fault are combined and calculated to finally obtain the suspected fault section, thereby improving the accuracy of fault location.

[0040] At this time, constructing the first parameter influence curve based on the mutual influence relationship of the fluctuation characteristic parameters includes:

[0041] Obtain the distance of each fluctuation characteristic parameter based on the distance algorithm;

[0042] The first parameter influence curve is constructed based on the distance and influence value of each fluctuation characteristic parameter.

[0043] Through the distance algorithm, the spatial distance between various fluctuation characteristic parameters can be determined, and then the correlation between their interaction and distance can be obtained. This can reveal the distance effect on the fluctuation characteristic parameter data when the sensor is placed at different positions on the cable outer sheath in practical applications, enhance the accuracy of the analysis of the interaction relationship between parameters, further improve the accuracy of the final fault location, and at the same time be applicable to various sensor placement methods to improve applicability.

[0044] The second parameter influence curve is constructed based on the historical fault data of the cable outer sheath and the fault characteristic parameters, including:

[0045] Obtain the distance between the fault characteristic parameters and the fault location based on the distance algorithm;

[0046] A second parameter influence curve is constructed based on the distance between the fault characteristic parameter and the fault location, the fault characteristic parameter value, and the fault characteristic parameter value monitoring time sequence.

[0047] The distance between the fault characteristic parameter and the fault location is calculated by the distance algorithm, and the relative position relationship between the fault characteristic parameter and the fault location in space is quantified, so as to construct the second parameter influence curve to show the trend of the fault characteristic parameter value changing with the distance from the fault location and the monitoring time sequence, reveal the intrinsic connection between the fault characteristic parameter and the fault location and the monitoring time sequence, improve the accuracy of fault location positioning, and improve the efficiency of fault diagnosis. At the same time, the complex relationship between the fault characteristic parameter and the fault location and the time sequence change law under different fault conditions are considered, so that the finally constructed parameter three-dimensional influence model is more robust and adaptable.

[0048] Among them, the influence of each fault characteristic parameter on the fault under long-term conditions is obtained according to the change of fault characteristic parameters in a long time sequence before the fault occurs. For example, long-term high temperature is more likely to cause a fault. Therefore, the fault characteristic parameters in a long time sequence before the fault occurs are obtained based on the fault characteristic parameter value monitoring time sequence and the fault characteristic parameter historical value. For example, a long period of temperature and humidity conditions may lead to a loss of the cable outer sheath and cause a fault.

[0049] In this embodiment, constructing the parameter three-dimensional influence model using the first parameter influence curve and the second parameter influence curve further includes:

[0050] Acquire cable layout data, and construct a three-dimensional model based on the cable layout data;

[0051] A parameter three-dimensional influence model is constructed based on the three-dimensional model and the first parameter influence curve and the second parameter influence curve.

[0052] The cable laying data includes the cable laying length, the cable laying width, the cable laying inflection point data and the collection laying point data. The collection laying point data includes the collection type and the collection laying point location. A three-dimensional model of the cable laying is constructed based on the cable laying data. The mutual influence relationship of each collection laying point in the three-dimensional model is obtained by combining the first parameter influence curve. The relationship between each collection laying point data and different cable outer sheath position points is obtained by combining the second parameter influence curve to obtain the parameter three-dimensional influence model. Through the physical space structure of the cable laying, the distribution and change rules of different parameters in the current space and the mutual influence relationship are obtained, so that the fault position of the cable outer sheath can be quickly located, improving the efficiency and accuracy of fault diagnosis.

[0053] The current data of the cable sheath includes the collected data of each sensor. When each sensor uploads the collected data, it will upload its own number accordingly. According to the number of each sensor, the collection type and collection point location of the corresponding sensor number can be obtained. According to the parameter three-dimensional influence model and the current data output of the cable sheath, the suspected fault sections include:

[0054] The suspected fault location points are obtained according to the parameter three-dimensional influence model and the current data of the cable outer sheath, and the suspected fault section is obtained by using the suspected fault location points containing at least two identical acquisition layout points.

[0055] The current data of the cable outer sheath is mapped to the parameter three-dimensional influence model to ensure that each collection layout point obtains the influence relationship between the collected data based on the first parameter influence curve, thereby verifying the accuracy of the collected data at each collection layout point, and compensating the parameter data at the sensorless collection position to avoid missing the fault position. At the same time, based on the collection timing of the current data of the cable outer sheath and the positional relationship between each sensor, the second parameter influence curve is used to obtain the suspected fault location point. At this time, the suspected fault location point is obtained based on the similarity with the historical fault data. Then, the suspected fault location points containing at least two identical collection layout points are connected to obtain a suspected fault section, that is, two identical collection layout points are combined with the remaining collection layout points to obtain different suspected fault location points. At this time, the positions between the two suspected fault location points are likely to have faults.

[0056] At this time, the fault location of the cable outer sheath is output based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold, including:

[0057] Obtain all suspected fault sections and calculate the coincidence frequency of location points in each suspected fault section;

[0058] If the coincidence frequency of the position point is greater than the preset coincidence frequency threshold, the position is determined to be the cable outer sheath fault position.

[0059] In this embodiment, the preset coincidence frequency threshold is 1 / N, where N is the total number of suspected fault sections, that is, once there is a coincidence of suspected fault sections, the coincidence position point is output as the cable outer sheath fault position. Thus, the cable outer sheath fault position is determined based on the coincidence of suspected fault sections, which effectively eliminates accidental factors, further eliminates errors caused by abnormal monitoring parameters due to abnormal sensors, and improves the accuracy of fault location. At the same time, the setting of the preset coincidence frequency threshold can be adjusted according to the actual situation of the cable system, historical fault data, and operation and maintenance strategies, so that the fault location result will not be too conservative and miss real faults, nor will it be too sensitive and generate a large number of false alarms, and it is more applicable. The use of suspected fault sections and three-dimensional models can intuitively obtain the coincidence position without a large number of position calculations, thereby improving the efficiency of fault location.

[0060] As a third embodiment of the present invention, outputting the fault position of the cable outer sheath based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold also includes:

[0061] If any suspected fault sections do not overlap, obtain the historical suspected fault sections for a preset time period, calculate the suspected fault section timing overlap frequency and the suspected fault section timing overlap trend based on the historical suspected fault sections and the current suspected fault sections, and output the cable outer sheath fault position based on the suspected fault section timing overlap frequency, the suspected fault section timing overlap trend and the preset overlap frequency threshold.

[0062] At this time, the preset coincidence frequency thresholds include: current coincidence frequency threshold, historical coincidence frequency threshold and coincidence trend threshold. When the current suspected fault section does not overlap, by introducing the historical suspected fault section data, the coincidence frequency and coincidence trend of the historical suspected fault section data and the current suspected fault section are determined, and the coincidence position of the historical suspected fault section and the current suspected fault section is screened as the cable outer sheath fault position, or when the coincidence trend exceeds the coincidence trend threshold, the position is output as the cable outer sheath fault position.

[0063] Specifically, according to the timing coincidence frequency of the suspected fault section, the timing coincidence trend of the suspected fault section and the preset coincidence frequency threshold, the fault position of the cable outer sheath is output, including:

[0064] The coincidence position where the sequence coincidence frequency of the suspected fault section is greater than the historical coincidence frequency threshold is taken as the cable outer sheath fault position; or / and,

[0065] The coincidence position where the timing coincidence trend of the suspected fault section is greater than the coincidence trend threshold is taken as the fault position of the cable outer sheath.

[0066] The timing overlap trend of the suspected fault section is calculated based on the relative distance between the adjacent suspected fault sections of the adjacent time series, and the timing overlap trend of the suspected fault section is obtained based on the trend of the relative distance change. For example, in the three time series A, B, and C, the suspected fault sections of the A and B time series are projected into the same three-dimensional stereo model to obtain the relative distance between the adjacent suspected fault sections of A and B, and then the suspected fault sections of the B and C time series are projected into the same three-dimensional stereo model to obtain the relative distance between the adjacent suspected fault sections of B and C. If the relative distance decreases, it is determined that the overlap trend is increasing; if the relative distance increases, it is determined that the overlap trend is decreasing; when the overlap trend is greater than the overlap trend threshold, it is determined that there must be overlap in the future time series. At this time, the overlap position of the future time series is output as the cable sheath fault position, so that the possibility of cable sheath fault can be predicted in advance and its location can be located, thereby improving the efficiency and accuracy of fault maintenance.

[0067] The specific implementation described above is a preferred implementation of a cable outer sheath fault locating system and method of the present invention, and is not intended to limit the specific implementation scope of the present invention. The scope of the present invention includes but is not limited to this specific implementation. All equivalent changes made in accordance with the shape and structure of the present invention are within the protection scope of the present invention.

Claims

1. A method for locating a cable outer sheath fault, characterized in that: The steps include: Obtain historical data of the cable outer sheath, and construct a three-dimensional parameter influence model based on parameter influence relationship according to the historical data of the cable outer sheath; Obtain the current data of the cable outer sheath, and output the suspected fault section based on the parameter three-dimensional influence model and the current data of the cable outer sheath; Output the fault position of the cable outer sheath based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold; The three-dimensional parameter influence model based on the parameter influence relationship is constructed according to the historical data of the cable outer sheath, including: Acquire historical data of the cable outer sheath, extract fluctuation characteristic parameters of the historical data of the cable outer sheath, and construct a first parameter influence curve based on the mutual influence relationship of the fluctuation characteristic parameters; Divide the cable outer sheath historical data to obtain the cable outer sheath historical fault data and the cable outer sheath historical normal data; Extracting the fault characteristic parameters of the cable outer sheath according to the historical fault data of the cable outer sheath and the historical normal data of the cable outer sheath, and constructing the second parameter influence curve based on the historical fault data of the cable outer sheath and the fault characteristic parameters; Constructing a parameter three-dimensional influence model using the first parameter influence curve and the second parameter influence curve; The constructing of the parameter three-dimensional influence model by using the first parameter influence curve and the second parameter influence curve comprises: Acquire cable layout data, and construct a three-dimensional model based on the cable layout data; Constructing a parameter three-dimensional influence model based on the three-dimensional model and the first parameter influence curve and the second parameter influence curve; The output of the suspected fault section according to the parameter three-dimensional influence model and the current data of the cable outer sheath includes: Obtain the suspected fault location point according to the parameter three-dimensional influence model and the current data of the cable outer sheath, and obtain the suspected fault section with the suspected fault location points containing at least two identical acquisition layout points; The method of outputting the fault position of the cable outer sheath based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold comprises: Obtain all suspected fault sections and calculate the coincidence frequency of location points in each suspected fault section; If the coincidence frequency of the position point is greater than the preset coincidence frequency threshold, the position is determined to be the cable outer sheath fault position; The output of the suspected fault section according to the parameter three-dimensional impact model and the current data of the cable outer sheath includes: Obtain the suspected fault location point according to the parameter three-dimensional influence model and the current data of the cable outer sheath, and obtain the suspected fault section with the suspected fault location points containing at least two identical acquisition layout points; The method of outputting the fault position of the cable outer sheath based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold comprises: Obtain all suspected fault sections and calculate the coincidence frequency of location points in each suspected fault section; If the coincidence frequency of the position point is greater than the preset coincidence frequency threshold, the position is determined to be the cable outer sheath fault position; The fluctuation characteristic parameters are characteristic parameters that affect the data change of the cable outer sheath, and the fault characteristic parameters are characteristic parameters that affect the fault of the cable outer sheath.

2. A cable outer sheath fault location method according to claim 1, characterized in that: The constructing of the first parameter influence curve based on the mutual influence relationship of the fluctuation characteristic parameters comprises: Obtain the distance of each fluctuation characteristic parameter based on the distance algorithm; The first parameter influence curve is constructed based on the distance and influence value of each fluctuation characteristic parameter.

3. A cable outer sheath fault location method according to claim 2, characterized in that: The second parameter influence curve is constructed based on the historical fault data of the cable outer sheath and the fault characteristic parameters, including: Obtain the distance between the fault characteristic parameters and the fault location based on the distance algorithm; A second parameter influence curve is constructed based on the distance between the fault characteristic parameter and the fault location, the fault characteristic parameter value, and the fault characteristic parameter value monitoring time sequence.

4. A cable outer sheath fault location method according to claim 3, characterized in that: The method of outputting the fault position of the cable outer sheath based on the coincidence frequency of the suspected fault section and the preset coincidence frequency threshold also includes: If any suspected fault sections do not overlap, obtain the historical suspected fault sections for a preset time period, calculate the suspected fault section timing overlap frequency and the suspected fault section timing overlap trend based on the historical suspected fault sections and the current suspected fault sections, and output the cable outer sheath fault position based on the suspected fault section timing overlap frequency, the suspected fault section timing overlap trend and the preset overlap frequency threshold.

5. A cable outer sheath fault location system, based on the cable outer sheath fault location method according to any one of claims 1 to 4, characterized in that: include: Data acquisition module, used to collect and record the data of the cable outer sheath; 3D modeling module, used to build parameter 3D influence model based on cable outer sheath data; Suspicious analysis module, used to output suspected fault sections based on the parameter three-dimensional impact model; The fault location module is used to output the fault location of the cable outer sheath according to the coincidence frequency of the suspected fault section.

6. A cable outer sheath fault location system according to claim 5, characterized in that: The data acquisition module includes a temperature sensor, a humidity sensor and a pressure sensor.

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