Intelligent sniffing system and method based on cable fault detection

Abstract

The invention relates to the technical field of cable fault detection, in particular to an intelligent sniffing system and method based on cable fault detection, and the system comprises a monitoring layer, a judgment layer and a sniffing layer. The cable distribution topology is constructed through the monitoring layer, after the cable distribution topology is constructed, power transmission information of electricity users on all sections of cables in the cable distribution topology is synchronously collected, and the judgment layer operates to synchronously obtain the power transmission information, collected in the monitoring layer, of the electricity users on the cables. The method comprises the following steps: synchronously acquiring power transmission information of electricity users on a cable, capturing the cable possibly having a fault problem, further combining with an image recognition technology, sniffing point locations, possibly having the fault problem, on the cable possibly having the fault problem, so as to obtain a sniffing point location of the cable possibly having the fault problem; therefore, a power cable management end worker is assisted to carry out rapid positioning and maintenance aiming at the fault problem that the bare cable is not completely broken.

Description

Technical Field

[0001] The present invention relates to the technical field of cable fault detection, and in particular to an intelligent sniffing system and method based on cable fault detection. Background Art

[0002] Incomplete disconnection of exposed cables is a relatively dangerous situation. It may be caused by external force damage, aging, etc. At this time, the cable is not completely disconnected, and the current transmission is unstable, which can easily cause local overheating, voltage fluctuations and other problems, posing a threat to the operation of surrounding equipment and personnel safety, and needs to be detected and repaired in time.

[0003] The invention patent with application number 201610240293.X discloses a cable fault location system based on intelligent collection and analysis, wherein the cable is formed by connecting multiple cables of different lengths and cross-sectional areas through insulating joints, and is characterized in that the cable fault location system comprises a fault cable, a reference cable, a short-circuit wire (6), a grounding switch, a data acquisition unit, a cable resistance detection unit and a processor unit (5), wherein one end of the fault cable and the reference cable are reference ends and the other ends are test ends, the reference ends of the fault cable and the reference cable are connected through the short-circuit wire (6), and the reference end of the fault cable is also grounded through the grounding switch, the cable resistance detection unit is respectively connected to the test ends of the fault cable and the reference cable, and the data acquisition unit and the cable resistance detection unit are both connected to the processor Unit (5); the data acquisition unit acquires the cable information of each cable segment in the faulty cable and unifies it to obtain the unified total length L of the cable; when the grounding switch is opened, the cable resistance detection unit detects the voltage and current information and sends it to the processor unit (5); the processor unit (5) acquires the cable resistance R between the faulty cable test end and the fault point; when the grounding switch is closed, the cable resistance detection unit detects the voltage and current information and sends it to the processor unit (5); the processor unit (5) acquires the cable resistance R2 between the faulty cable test end and the reference end; the processor unit (5) acquires the unified distance Lx from the faulty cable test end to the fault point according to Lx=LX(R1 / R2); and then the processor unit (5) converts the actual distance Lx′ from the faulty cable test end to the fault point according to Lx and the cable information of each cable segment.

[0004] The application aims to solve the problem that "because high-voltage cables have cross-connections and T-connectors, the wave impedance changes suddenly, making the positioning of reflected waves very complicated and difficult to locate. The high-voltage pulse also has energy loss at this point, making it difficult to reach distant places."

[0005] However, there is currently no targeted fault monitoring and fault point sniffing technology to address the problem of incomplete disconnection of exposed cables.

[0006] To this end, we propose an intelligent sniffing system and method based on cable fault detection. Summary of the invention

[0007] In view of the above-mentioned shortcomings of the prior art, the present invention provides an intelligent sniffing system and method based on cable fault detection, which solves the technical problems raised in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] In a first aspect, an intelligent sniffing system based on cable fault detection comprises: a monitoring layer, a determination layer and a sniffing layer;

[0010] The cable distribution topology is constructed through the monitoring layer. After the cable distribution topology is constructed, the power transmission information of the power users on each cable line in the cable distribution topology is synchronously collected. The decision layer runs to synchronously obtain the power transmission information of the power users on the cable lines collected in the monitoring layer, and identifies the cable line from which the cable fault originates based on the cable line power transmission information. The sniffing layer further receives the identification result of the cable line from which the cable fault originates in the decision layer, and sniffs the fault point on the cable line from which the cable fault originates.

[0011] The determination layer includes a receiving module, an analyzing module and an identifying module. The receiving module is used to receive the cable line power transmission information collected in the monitoring layer. The analyzing module is used to traverse the cable line power transmission information received by the receiving module, and analyze the cable line fault risk based on the cable line power transmission information. The identifying module is used to receive the cable fault risk analysis result in the analyzing module, and identify the cable line that may have a fault problem based on the analysis result.

[0012] The cable fault risk analysis logic in the analysis module is expressed as:

[0013]

[0014] Where: k is the cable fault risk value; U MAX , U MIN It is the maximum voltage value and the minimum voltage value in the power transmission information of the cable line; I MAX ,I MIN It is the maximum current value and the minimum current value in the power transmission information of the cable line; is the power factor; THD MAX 、THD MIN are the maximum harmonic content and the minimum harmonic content in the cable power transmission information; ε1, ε2, ε3, and ε4 are corrections; m is the total number of types of cable power transmission information; γ is the normalization factor; t0 is the cumulative collection time of the cable power transmission information;

[0015] Among them, based on the above formula, the cable failure risk value k of each power user on the cable line is obtained, It represents the maximum power and minimum power in the power transmission information of the cable line. The values ​​of modified ε1, ε2, ε3, and ε4 are not less than 1 and not greater than 2. The normalization factor γ is greater than 1. The larger the cable fault risk value k is, the higher the cable fault risk is. Conversely, the lower the cable fault risk is.

[0016] Furthermore, the monitoring layer includes a construction module, a collection module and a management module. The construction module is used to upload cable line distribution parameters, and construct a cable line distribution topology through the cable line distribution parameters. The collection module is used to collect power transmission information of power users on each section of the cable line in the cable line distribution topology. The management module is used to receive the cable line distribution topology constructed in the construction module and the cable line power transmission information collected in the collection module, and store the cable line distribution topology and the cable line power transmission information.

[0017] Among them, the cable line distribution parameters uploaded in the construction module are the node position coordinates of each interconnected cable line segment. The construction module is connected to each other based on the node position coordinates of each interconnected cable line segment to construct a cable line distribution topology. After the cable line distribution topology is completed in the construction module, it is synchronously placed in the three-dimensional coordinate system, and the scale of the three-dimensional coordinate system is equal to the ratio of the distance between any two points on the cable line distribution topology to the actual distance between any two points. Each electricity user on the cable line distribution topology is marked in the cable line distribution topology based on further uploading of the position coordinates.

[0018] Furthermore, the acquisition module is integrated with voltage and current sensors, power sensors and harmonic sensors. The power transmission information of the power users on the cable line collected by the acquisition module includes: voltage, current, power and harmonic content. After collecting the power transmission information of the power users on the cable line, the acquisition module further marks the collection position coordinates of the collected power transmission information of the power users.

[0019] When the management module stores the cable distribution topology and the cable power transmission information, two sets of differentiated storage intervals are set, and the two sets of differentiated storage intervals are used to differentiate and store the cable distribution topology and the cable power transmission information;

[0020] Among them, when storing the cable power transmission information, the management module synchronously performs a data iteration operation, and the data iteration operation is: deleting the cable power transmission information stored in the differentiated storage intervals, so that the cable power transmission information stored in the differentiated storage intervals is always no less than three groups.

[0021] Furthermore, the collection modules are provided in several groups, and the collection modules are respectively installed at the access positions of the power lines of the power users on the cable line and the cable line;

[0022] The acquisition module collects the power transmission information of the power users on each cable line in the cable line distribution topology in accordance with:

[0023]

[0024] Where: d is the operation cycle of the acquisition module; n is the set of electricity users; T(t i ∪t i+1 ) is the duration of the union of the electricity consumption time threshold of the i-th electricity user and the electricity consumption time threshold of the i+1-th electricity user; λ is a constant;

[0025] When the collection module operation cycle d obtained based on formula (1) is greater than 0.5, the collection module operation cycle d is taken as 0.5, otherwise, the collection module operation cycle d is applied, the constant λ is customized by the system end user and is greater than zero, the power consumption time threshold of all power users belongs to the 24 hours starting from 00:00 before the system is operated, the collection module runs continuously based on d, and collects the power transmission information of the power users on each cable line in the cable line distribution topology. After collecting the power transmission information of the power user, the collection module synchronously identifies the current value in the power transmission information, and when the current value is zero, the current value is deleted from all the power transmission information of the power user collected at the same time as the current value.

[0026] Furthermore, the values ​​of ε1, ε2, ε3, and ε4 are further modified to obey:

[0027] The maximum and minimum values ​​in the correction multiplication term are derived from the power transmission information of two sets of adjacent cable lines. The correction value is not less than 1 and not greater than 2. Otherwise, the correction value is 1.

[0028] The value of the normalization factor is defined by the system user or set to

[0029] After the cable fault risk value k of the power user on each cable line is obtained, each group of risk values ​​k is distinguished based on the cable line from which the risk value k comes;

[0030] The identification module is set with an identification logic, and the identification module identifies the cable line that may have a fault problem based on the identification logic. The identification logic is expressed as:

[0031] A determination threshold for cables that may have fault problems is set, and based on the comparison between the determination value and each group of risk values ​​k, the cables corresponding to the risk values ​​k that meet the determination threshold are used as the identification results of the identification module; when all risk values ​​k do not meet the determination threshold, the largest group of risk values ​​k is obtained in each partition interval, and the largest group of risk values ​​k is further obtained from all the obtained risk values ​​k, and the cables corresponding to the risk values ​​k are used as the identification results of the identification module.

[0032] Furthermore, the sniffing layer includes a picking module, a camera module, and a sniffing module. The picking module is used to receive the risk value k finally identified in the determination layer, capture the cable line at the position coordinate corresponding to the risk value k in the cable distribution topology, and pick up the local cable line from the position coordinate corresponding to the risk value k to the next node on the captured cable line. The camera module is used to receive the local cable line in the cable distribution topology picked up by the picking module, obtain the coordinates of both ends of the local cable line, set the cable line image acquisition path based on the two sets of coordinates, and collect the local cable line surface image along the cable line image acquisition path. The sniffing module is used to receive the local cable line surface image, segment the local cable line surface image to obtain several groups of sub-local cable line surface images, identify the similarity of each sub-local cable line surface image, and based on the similarity recognition result, sniff the fault point on the cable line corresponding to the local cable line in the cable distribution topology;

[0033] Among them, the camera module is integrated by a drone and a camera. When the camera module is in operation, the camera carried by the drone collects local cable surface images based on the cable image acquisition path. When collecting the local cable surface images, the image edges in the local cable surface images are adjusted based on the drone movement and the camera focal length and object distance so that the contour edges of the cable in the image coincide with each other.

[0034] Furthermore, the number of local cable surface images collected by the camera module is one, and the local cable surface image is a global image of the cable surface in a direction perpendicular to the ground. When the sniffing module performs segmentation processing on the local cable surface image, the size and aspect ratio of each sub-local cable surface image obtained by segmentation are equal;

[0035] When the local cable line surface image is segmented, the number of segments is customized by the system end user and follows the setting logic that the longer the length of the local cable line corresponding to the local cable line surface image is, the more segments are needed.

[0036] Furthermore, the similarity of the sub-local cable surface images is calculated by the following formula:

[0037]

[0038] Where: SIMM (a, b) is the similarity between the sub-local cable line surface image a and the sub-local cable line surface image b; Hu a (i) is the value of the ith Hu moment of the sub-local cable surface image a; Hu b (i) is the value of the i-th Hu moment of the sub-local cable surface image b; d H u,max is a set of Euclidean distance values ​​defined by the system user; is the similarity between the sub-local cable line surface image a and the sub-local cable line surface image b based on hue, brightness and saturation;

[0039] in, Based on the above formula, two groups of sub-local cable line surface images with the lowest similarity are obtained, and the average similarity of the two groups of sub-local cable line surface images and the remaining sub-local cable line surface images is further calculated. The corresponding sub-local cable line surface image with low average similarity is used as the area where the fault point is located, and then the center point of the corresponding sub-local cable line surface image with low average similarity corresponds to the position coordinate in the cable line distribution topology as the fault point sniffed by the sniffing module.

[0040] Furthermore, the receiving module is interactively connected to the management module via a wireless network, the management module is interactively connected to the construction module and the acquisition module via a wireless network, the receiving module is interactively connected to the analysis module and the identification module via a wireless network, the identification module is interactively connected to the picking module via a wireless network, and the picking module is interactively connected to the camera module and the sniffing module via a wireless network.

[0041] In a second aspect, an intelligent sniffing method based on cable fault detection comprises the following steps:

[0042] Step 1: Upload the cable distribution parameters and build the cable distribution topology according to the cable distribution parameters;

[0043] Step 2: Collect power transmission information of power users on each section of the cable line in the cable line distribution topology, obtain the cable distribution topology, and store it together with the power transmission information of the power users on the cable line;

[0044] Step 3: Analyze the cable line fault risk according to the cable line power transmission information, and identify the cable lines that may have fault problems based on the power line fault risk analysis results;

[0045] Step 31: Setting and applying the cable fault risk analysis logic;

[0046] Step 32: Setting and applying the logic for identifying cables that may have fault problems;

[0047] Step 4: Obtain identification results of cables that may have fault problems, and pick up local cables that may have fault problems on the cables that may have fault problems;

[0048] Step 41: Setting and applying a local cable line picking logic that may have a fault problem on a cable line that may have a fault problem;

[0049] Step 5: Obtain a local cable line where a fault problem may occur, and sniff out a fault point where a fault problem may occur on the local cable line;

[0050] Step 51: Setting and applying fault point sniffing logic.

[0051] Compared with the known public technology, the technical solution provided by the present invention has the following advantages:

[0052] Beneficial effects:

[0053] The present invention provides an intelligent sniffing system and method based on cable fault detection. During the system operation stage, by constructing a cable distribution topology, power transmission information of power users on the cable line is synchronously collected, and cables that may have fault problems are captured. Further combined with image recognition technology, points on the cable lines that may have fault problems are sniffed, thereby assisting power cable management personnel to quickly locate and repair faults caused by incomplete disconnection of exposed cables, effectively maintaining the long-term stable operation of the power cable network, ensuring that the power cable network continues to provide power transmission services, and providing good power services to power users in the power cable network. At the same time, based on the method in the scheme, further operation logic support is provided for the above-mentioned system, ensuring the stable and continuous operation of the above-mentioned system, and providing more targeted fault maintenance services for the power cable network. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 It is a structural diagram of an intelligent sniffing system based on cable fault detection;

[0056] Figure 2 A schematic diagram of a process of an intelligent sniffing method based on cable fault detection;

[0057] Figure 3 This is an example diagram showing the segmentation results of the local cable surface image in the present invention;

[0058] Figure 4 It is a schematic diagram of the direction of collecting images of the local cable surface in the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] The present invention will be further described below in conjunction with the embodiments.

[0061] Embodiment 1:

[0062] An intelligent sniffing system based on cable fault detection in this embodiment, such as Figure 1 As shown, it includes: monitoring layer, decision layer and sniffing layer;

[0063] The cable distribution topology is constructed through the monitoring layer. After the cable distribution topology is constructed, the power transmission information of the power users on each cable line in the cable distribution topology is synchronously collected. The decision layer runs to synchronously obtain the power transmission information of the power users on the cable lines collected in the monitoring layer, and identifies the cable line from which the cable fault originates based on the cable line power transmission information. The sniffing layer further receives the identification result of the cable line from which the cable fault originates in the decision layer, and sniffs the fault point on the cable line from which the cable fault originates.

[0064] The monitoring layer includes a construction module, a collection module and a management module. The construction module is used to upload cable line distribution parameters and construct a cable line distribution topology through the power line distribution parameters. The collection module is used to collect power transmission information of power users on each section of the cable line in the cable line distribution topology. The management module is used to receive the cable line distribution topology constructed in the construction module and the cable line power transmission information collected in the collection module, and store the cable line distribution topology and the cable line power transmission information.

[0065] Among them, the cable line distribution parameters uploaded in the construction module are the node position coordinates of the interconnected cable lines of each section. The construction module is connected to each other based on the node position coordinates of the interconnected cable lines of each section to construct the cable line distribution topology. After the cable line distribution topology is completed in the construction module, it is synchronously placed in the three-dimensional coordinate system, and the scale of the three-dimensional coordinate system is equal to the ratio of the distance between any two points on the cable line distribution topology to the actual distance between any two points. Each electricity user on the cable line distribution topology is marked in the cable line distribution topology based on further uploading of the position coordinates;

[0066] The determination layer includes a receiving module, an analysis module and an identification module. The receiving module is used to receive the cable line power transmission information collected in the monitoring layer. The analysis module is used to traverse the cable line power transmission information received by the receiving module, and analyze the cable line fault risk based on the cable line power transmission information. The identification module is used to receive the cable fault risk analysis result in the analysis module, and identify the cable line that may have a fault problem based on the analysis result.

[0067] The cable fault risk analysis logic in the analysis module is expressed as:

[0068]

[0069] Where: k is the cable fault risk value; U MAX , U MIN It is the maximum voltage value and the minimum voltage value in the power transmission information of the cable line; I MAX ,I MIN It is the maximum current value and the minimum current value in the power transmission information of the cable line; is the power factor; THD MAX 、THD MIN are the maximum harmonic content and the minimum harmonic content in the cable power transmission information; ε1, ε2, ε3, and ε4 are corrections; m is the total number of types of cable power transmission information; γ is the normalization factor; t0 is the cumulative collection time of the cable power transmission information;

[0070] Among them, based on the above formula, the cable failure risk value k of each power user on the cable line is obtained: It represents the maximum power and minimum power in the power transmission information of the cable line. The values ​​of the modified ε1, ε2, ε3, and ε4 are not less than 1 and not greater than 2. The normalization factor γ is greater than 1. The larger the cable fault risk value k is, the higher the cable fault risk is. Conversely, the lower the cable fault risk is.

[0071] The sniffing layer includes a picking module, a camera module, and a sniffing module. The picking module is used to receive the risk value k finally identified in the determination layer, capture the cable line at the position coordinate corresponding to the risk value k in the cable distribution topology, and pick up the local cable line from the position coordinate corresponding to the risk value k to the next node on the captured cable line. The camera module is used to receive the local cable line in the cable distribution topology picked up by the picking module, obtain the coordinates of both ends of the local cable line, set the cable line image acquisition path based on the two sets of coordinates, and collect the local cable line surface image along the cable line image acquisition path. The sniffing module is used to receive the local cable line surface image, segment the local cable line surface image, obtain several groups of sub-local cable line surface images, identify the similarity of each sub-local cable line surface image, and based on the similarity recognition result, sniff the fault point on the cable line corresponding to the local cable line in the cable distribution topology;

[0072] The camera module is integrated with a drone and a camera. When the camera module is in operation, the drone carries a camera to collect local cable surface images based on the cable image collection path. When collecting the local cable surface images, the drone movement, camera focal length, and object distance are adjusted to make the image edge in the local cable surface image coincide with the contour edge of the cable in the image.

[0073] The receiving module is interactively connected to the management module through a wireless network, the management module is interactively connected to the construction module and the acquisition module through a wireless network, the receiving module is interactively connected to the analysis module and the recognition module through a wireless network, the recognition module is interactively connected to the picking module through a wireless network, and the picking module is interactively connected to the camera module and the sniffing module through a wireless network.

[0074] In this embodiment, the construction module runs to upload the cable line distribution parameters, and the cable line distribution topology is constructed by the cable line distribution parameters. The collection module synchronously collects the power transmission information of the power users on each section of the cable line in the cable line distribution topology. The management module post-operates to receive the cable line distribution topology constructed in the construction module and the cable line power transmission information collected in the collection module, and stores the cable line distribution topology and the cable line power transmission information. The receiving module further receives the cable line power transmission information collected in the monitoring layer. The analysis module traverses the cable line power transmission information received by the receiving module in real time, analyzes the cable line fault risk based on the cable line power transmission information, and then the identification module receives the cable fault risk analysis result in the analysis module, identifies the cable line that may have a fault problem based on the analysis result, and picks up the module. The risk value k finally identified in the receiving decision layer is captured in the cable distribution topology, and the cable with the position coordinates corresponding to the risk value k is picked up from the captured cable to the local cable with the position coordinates corresponding to the risk value k to the next node. The camera module synchronously receives the local cable in the cable distribution topology picked up by the picking module, obtains the coordinates of both ends of the local cable, sets the cable image acquisition path based on the two sets of coordinates, and collects the surface image of the local cable along the cable image acquisition path. Finally, the local cable surface image is received by the sniffing module, and the local cable surface image is segmented to obtain several groups of sub-local cable surface images. The similarity of each sub-local cable surface image is identified, and based on the similarity recognition result, the fault point on the cable corresponding to the local cable in the cable distribution topology is sniffed.

[0075] Through the operation of the system in the above embodiment, continuous and accurate sniffing and positioning services are provided for the fault problem of incomplete disconnection of the exposed cable, thereby serving the safe management of the exposed cable and ensuring the long-term safe and stable operation of the exposed cable.

[0076] See also Figure 3As shown in the figure, based on the arrows in the figure, the local cable surface image segmentation results are displayed, see Figure 4 As shown, based on the arrows in the figure, the direction of collecting the local cable surface image is displayed.

[0077] Embodiment 2:

[0078] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The intelligent sniffing system based on cable fault detection in Example 1 is further described in detail:

[0079] The acquisition module is integrated with voltage, current sensors, power sensors and harmonic sensors. The power transmission information of the power users on the cable line collected by the acquisition module includes: voltage, current, power and harmonic content. After collecting the power transmission information of the power users on the cable line, the acquisition module further marks the collection position coordinates of the collected power transmission information of the power users;

[0080] When the management module stores the cable distribution topology and the cable power transmission information, two sets of differentiated storage intervals are set, and the two sets of differentiated storage intervals are used to differentiate and store the cable distribution topology and the cable power transmission information;

[0081] The management module synchronously performs a data iteration operation when storing the cable power transmission information, and the data iteration operation is: deleting the cable power transmission information stored in the differentiated storage intervals, so that the cable power transmission information stored in the differentiated storage intervals is always not less than three groups;

[0082] There are several groups of collection modules, which are respectively installed at the access positions of the power lines of power users and the cable lines on the cable lines;

[0083] The acquisition module collects the power transmission information of the power users on each cable line in the cable line distribution topology and follows the following rules:

[0084]

[0085] Where: d is the operation cycle of the acquisition module; n is the set of electricity users; T(t i ∪t i+1 ) is the duration of the union of the electricity consumption time threshold of the i-th electricity user and the electricity consumption time threshold of the i+1-th electricity user; λ is a constant;

[0086] When the collection module operation cycle d obtained based on formula (1) is greater than 0.5, the collection module operation cycle d is taken as 0.5, otherwise, the collection module operation cycle d is applied, the constant λ is defined by the system end user and is greater than zero, the power consumption time threshold of all power users belongs to the 24 hours starting from 00:00 before the system is operated, the collection module runs continuously based on d, and collects the power transmission information of the power users on each cable line in the cable line distribution topology. After collecting the power transmission information of the power user, the collection module synchronously identifies the current value in the power transmission information, and when the current value is zero, the current value is deleted from all the power transmission information of the power user collected at the same time as the current value;

[0087] Modify the values ​​of ε1, ε2, ε3, and ε4 to further obey:

[0088] The maximum and minimum values ​​in the correction multiplication term are derived from the power transmission information of two sets of adjacent cable lines. The correction value is not less than 1 and not greater than 2. Otherwise, the correction value is 1.

[0089] The value of the normalization factor is defined by the system user or set to

[0090] After the cable fault risk value k of the power user on each cable line is obtained, each group of risk values ​​k is distinguished based on the cable line from which the risk value k comes;

[0091] The identification module is set with identification logic. The identification module identifies the cables that may have fault problems based on the identification logic. The identification logic is expressed as:

[0092] A determination threshold for cables that may have fault problems is set, and based on the comparison between the determination value and each group of risk values ​​k, the cables corresponding to the risk values ​​k that meet the determination threshold are used as the identification results of the identification module; when all risk values ​​k do not meet the determination threshold, the largest group of risk values ​​k is obtained in each partition interval, and the largest group of risk values ​​k is further obtained from all the obtained risk values ​​k, and the cables corresponding to the risk values ​​k are used as the identification results of the identification module.

[0093] In this embodiment, through the above-mentioned settings, further operation data support is provided for the system in Example 1, ensuring that the system in Example 1 operates more stably, and in this embodiment, the logic of the acquisition module when collecting power transmission information of power users on each section of the cable line in the cable line distribution topology is further limited, ensuring the stable collection of power transmission information of power users on each section of the cable line in the cable line distribution topology.

[0094] Embodiment three:

[0095] In terms of specific implementation, based on Example 1, this example refers to Figure 1The intelligent sniffing system based on cable fault detection in Example 1 is further described in detail:

[0096] The number of local cable surface images collected by the camera module is one, and the local cable surface image is a global image of the cable surface in a direction perpendicular to the ground. When the sniffing module performs segmentation processing on the local cable surface image, the size and aspect ratio of each sub-local cable surface image obtained by segmentation are equal;

[0097] When the local cable line surface image is segmented, the number of segments is customized by the system end user, and the setting logic is that the longer the length of the local cable line corresponding to the local cable line surface image is, the more the number of segments is.

[0098] The similarity of the sub-local cable surface images is calculated using the following formula:

[0099]

[0100] Where: SIMM (a, b) is the similarity between the sub-local cable line surface image a and the sub-local cable line surface image b; Hu a (i) is the value of the ith Hu moment of the sub-local cable surface image a; Hu b (i) is the value of the i-th Hu moment of the sub-local cable surface image b; d H u,max is a set of Euclidean distance values ​​defined by the system user; is the similarity between the sub-local cable line surface image a and the sub-local cable line surface image b based on hue, brightness and saturation;

[0101] in, Based on the above formula, two groups of sub-local cable line surface images with the lowest similarity are obtained, and the average similarity of the two groups of sub-local cable line surface images and the remaining sub-local cable line surface images is further calculated. The corresponding sub-local cable line surface image with low average similarity is used as the area where the fault point is located, and then the center point of the corresponding sub-local cable line surface image with low average similarity corresponds to the position coordinate in the cable line distribution topology as the fault point sniffed by the sniffing module.

[0102] In this embodiment, the logic for obtaining the similarity of the sub-local cable surface images is further limited through the above-mentioned logical formula to ensure that the sniffing layer in Example 1 operates stably to accurately locate the fault points on the cable that may have fault problems.

[0103] Embodiment 4:

[0104] In terms of specific implementation, based on Example 1, this example refers to Figure 2The intelligent sniffing system based on cable fault detection in Example 1 is further described in detail:

[0105] An intelligent sniffing method based on cable fault detection comprises the following steps:

[0106] Step 1: Upload the cable distribution parameters and build the cable distribution topology according to the cable distribution parameters;

[0107] Step 2: Collect power transmission information of power users on each section of the cable line in the cable line distribution topology, obtain the cable distribution topology, and store it together with the power transmission information of the power users on the cable line;

[0108] Step 3: Analyze the cable line fault risk according to the cable line power transmission information, and identify the cable lines that may have fault problems based on the power line fault risk analysis results;

[0109] Step 31: Setting and applying the cable fault risk analysis logic;

[0110] Step 32: Setting and applying the logic for identifying cables that may have fault problems;

[0111] Step 4: Obtain identification results of cables that may have fault problems, and pick up local cables that may have fault problems on the cables that may have fault problems;

[0112] Step 41: Setting and applying a local cable line picking logic that may have a fault problem on a cable line that may have a fault problem;

[0113] Step 5: Obtain a local cable line where a fault problem may occur, and sniff out a fault point where a fault problem may occur on the local cable line;

[0114] Step 51: Setting and applying fault point sniffing logic.

[0115] To sum up, in the system operation stage of the above embodiment, by constructing a cable distribution topology, the power transmission information of electricity users on the cable line is synchronously collected, and the cable lines that may have fault problems are captured. The image recognition technology is further combined to sniff the points where the fault problems may occur on the cable lines that may have fault problems, so as to assist the power cable management personnel to quickly locate and repair the fault problems of incomplete disconnection of exposed cables, effectively maintain the long-term stable operation of the power cable network, ensure that the power cable network continues to provide power transmission services, and provide good electricity services for electricity users in the power cable network. At the same time, based on the method in the scheme, further operation logic support is provided for the above system, ensuring the stable and continuous operation of the above system, and providing more targeted fault maintenance services for the power cable network.

[0116] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent sniffing system based on cable fault detection, characterized in that: include: Monitoring layer, decision layer and sniffing layer; The cable distribution topology is constructed through the monitoring layer. After the cable distribution topology is constructed, the power transmission information of the power users on each cable line in the cable distribution topology is synchronously collected. The decision layer runs to synchronously obtain the power transmission information of the power users on the cable lines collected in the monitoring layer, and identifies the cable line from which the cable fault originates based on the cable line power transmission information. The sniffing layer further receives the identification result of the cable line from which the cable fault originates in the decision layer, and sniffs the fault point on the cable line from which the cable fault originates. The determination layer includes a receiving module, an analyzing module and an identifying module. The receiving module is used to receive the cable line power transmission information collected in the monitoring layer. The analyzing module is used to traverse the cable line power transmission information received by the receiving module, and analyze the cable line fault risk based on the cable line power transmission information. The identifying module is used to receive the cable fault risk analysis result in the analyzing module, and identify the cable line that may have a fault problem based on the analysis result. The cable fault risk analysis logic in the analysis module is expressed as: Where: k is the cable fault risk value; U MAX , U MIN It is the maximum voltage value and the minimum voltage value in the power transmission information of the cable line; I MAX ,I MIN It is the maximum current value and the minimum current value in the power transmission information of the cable line; is the power factor; THD MAX 、THD MIN are the maximum harmonic content and the minimum harmonic content in the cable power transmission information; ε1, ε2, ε3, and ε4 are corrections; m is the total number of types of cable power transmission information; γ is the normalization factor; t0 is the cumulative collection time of the power transmission information of the cable line; Among them, based on the above formula, the cable failure risk value k of each power user on the cable line is obtained: It represents the maximum power and minimum power in the power transmission information of the cable line. The values ​​of modified ε1, ε2, ε3, and ε4 are not less than 1 and not greater than 2. The normalization factor γ is greater than 1. The larger the cable fault risk value k is, the higher the cable fault risk is. Conversely, the lower the cable fault risk is.

2. According to claim 1, an intelligent sniffing system based on cable fault detection is characterized in that: The monitoring layer includes a construction module, a collection module and a management module. The construction module is used to upload cable line distribution parameters, and construct a cable line distribution topology through the power line distribution parameters. The collection module is used to collect power transmission information of power users on each section of the cable line in the cable line distribution topology. The management module is used to receive the cable line distribution topology constructed in the construction module and the cable line power transmission information collected in the collection module, and store the cable line distribution topology and the cable line power transmission information. Among them, the cable line distribution parameters uploaded in the construction module are the node position coordinates of each interconnected cable line segment. The construction module is connected to each other based on the node position coordinates of each interconnected cable line segment to construct a cable line distribution topology. After the cable line distribution topology is completed in the construction module, it is synchronously placed in the three-dimensional coordinate system, and the scale of the three-dimensional coordinate system is equal to the ratio of the distance between any two points on the cable line distribution topology to the actual distance between any two points. Each electricity user on the cable line distribution topology is marked in the cable line distribution topology based on further uploading of the position coordinates.

3. The intelligent sniffing system based on cable fault detection according to claim 2 is characterized in that: The acquisition module is integrated with voltage and current sensors, power sensors and harmonic sensors. The power transmission information of the power users on the cable line collected by the acquisition module includes: voltage, current, power and harmonic content. After collecting the power transmission information of the power users on the cable line, the acquisition module further marks the collection position coordinates of the collected power transmission information of the power users; When the management module stores the cable distribution topology and the cable power transmission information, two sets of differentiated storage intervals are set, and the two sets of differentiated storage intervals are used to differentiate and store the cable distribution topology and the cable power transmission information; Among them, when storing the cable power transmission information, the management module synchronously performs a data iteration operation, and the data iteration operation is: deleting the cable power transmission information stored in the differentiated storage intervals, so that the cable power transmission information stored in the differentiated storage intervals is always no less than three groups.

4. The intelligent sniffing system based on cable fault detection according to claim 3 is characterized in that: The collection modules are provided in several groups, and the collection modules are respectively installed at the access positions of the power lines of the power users on the cable line and the cable line; The acquisition module collects the power transmission information of the power users on each cable line in the cable line distribution topology in accordance with: Where: d is the operation cycle of the acquisition module; n is the set of electricity users; T(t i ∪t i+1 ) is the duration of the union of the electricity consumption time threshold of the ith electricity user and the electricity consumption time threshold of the i+1th electricity user; λ is a constant; When the collection module operation cycle d obtained based on formula (1) is greater than 0.5, the collection module operation cycle d is taken as 0.5, otherwise, the collection module operation cycle d is applied, the constant λ is customized by the system end user and is greater than zero, the power consumption time threshold of all power users belongs to the 24 hours starting from 00:00 before the system is operated, the collection module runs continuously based on d, and collects the power transmission information of the power users on each cable line in the cable line distribution topology. After collecting the power transmission information of the power user, the collection module synchronously identifies the current value in the power transmission information, and when the current value is zero, the current value is deleted from all the power transmission information of the power user collected at the same time as the current value.

5. An intelligent sniffing system based on cable fault detection according to claim 1 or 4, characterized in that: Modify the values ​​of ε1, ε2, ε3, and ε4 to further obey: The maximum and minimum values ​​in the correction multiplication term are derived from the power transmission information of two sets of adjacent cable lines. The correction value is not less than 1 and not greater than 2. Otherwise, the correction value is 1. The value of the normalization factor is defined by the system user or set to After the cable fault risk value k of the power user on each cable line is obtained, each group of risk values ​​k is distinguished based on the cable line from which the risk value k comes; The identification module is set with an identification logic, and the identification module identifies the cable line that may have a fault problem based on the identification logic. The identification logic is expressed as: A determination threshold for cables that may have fault problems is set, and based on the comparison between the determination value and each group of risk values ​​k, the cables corresponding to the risk values ​​k that meet the determination threshold are used as the identification results of the identification module; when all risk values ​​k do not meet the determination threshold, the largest group of risk values ​​k is obtained in each partition interval, and the largest group of risk values ​​k is further obtained from all the obtained risk values ​​k, and the cables corresponding to the risk values ​​k are used as the identification results of the identification module.

6. The intelligent sniffing system based on cable fault detection according to claim 1 is characterized in that: The sniffing layer includes a picking module, a camera module, and a sniffing module. The picking module is used to receive the risk value k finally identified in the determination layer, capture the cable line at the position coordinate corresponding to the risk value k in the cable line distribution topology, and pick up the local cable line from the position coordinate corresponding to the risk value k to the next node on the captured cable line. The camera module is used to receive the local cable line in the cable line distribution topology picked up by the picking module, obtain the coordinates of both ends of the local cable line, set the cable line image acquisition path based on the two sets of coordinates, and collect the local cable line surface image along the cable line image acquisition path. The sniffing module is used to receive the local cable line surface image, segment the local cable line surface image to obtain several groups of sub-local cable line surface images, identify the similarity of each sub-local cable line surface image, and based on the similarity recognition result, sniff the fault point on the cable line corresponding to the local cable line in the cable line distribution topology; Among them, the camera module is integrated by a drone and a camera. When the camera module is in operation, the camera carried by the drone collects local cable surface images based on the cable image acquisition path. When collecting the local cable surface images, the image edges in the local cable surface images are adjusted based on the drone movement and the camera focal length and object distance so that the contour edges of the cable in the image coincide with each other.

7. The intelligent sniffing system based on cable fault detection according to claim 6 is characterized in that: The number of local cable surface images collected by the camera module is one, and the local cable surface image is a global image of the cable surface in a direction perpendicular to the ground. When the sniffing module performs segmentation processing on the local cable surface image, the size and aspect ratio of each sub-local cable surface image obtained by segmentation are equal; When the local cable line surface image is segmented, the number of segments is customized by the system end user and follows the setting logic that the longer the length of the local cable line corresponding to the local cable line surface image is, the more segments are needed.

8. The intelligent sniffing system based on cable fault detection according to claim 6 is characterized in that: The similarity of the sub-local cable surface images is calculated by the following formula: Where: SIMM (a, b) is the similarity between the sub-local cable line surface image a and the sub-local cable line surface image b; Hu a (i) is the value of the ith Hu moment of the sub-local cable surface image a; Hu b (i) is the value of the i-th Hu moment of the sub-local cable surface image b; dHu,max is a set of Euclidean distance values ​​defined by the system end user; is the similarity between the sub-local cable line surface image a and the sub-local cable line surface image b based on hue, brightness and saturation; in, Based on the above formula, two groups of sub-local cable line surface images with the lowest similarity are obtained, and the average similarity of the two groups of sub-local cable line surface images and the remaining sub-local cable line surface images is further calculated. The corresponding sub-local cable line surface image with low average similarity is used as the area where the fault point is located, and then the center point of the corresponding sub-local cable line surface image with low average similarity corresponds to the position coordinate in the cable line distribution topology as the fault point sniffed by the sniffing module.

9. The intelligent sniffing system based on cable fault detection according to claim 1 is characterized in that: The receiving module is interactively connected to the management module via a wireless network, the management module is interactively connected to the construction module and the acquisition module via a wireless network, the receiving module is interactively connected to the analysis module and the identification module via a wireless network, the identification module is interactively connected to the picking module via a wireless network, and the picking module is interactively connected to the camera module and the sniffing module via a wireless network.

10. An intelligent sniffing method based on cable fault detection, the method being an implementation method of an intelligent sniffing system based on cable fault detection as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Upload the cable distribution parameters and build the cable distribution topology according to the cable distribution parameters; Step 2: Collect power transmission information of power users on each section of the cable line in the cable line distribution topology, obtain the cable distribution topology, and store it together with the power transmission information of the power users on the cable line; Step 3: Analyze the cable line fault risk according to the cable line power transmission information, and identify the cable lines that may have fault problems based on the power line fault risk analysis results; Step 31: Setting and applying the cable fault risk analysis logic; Step 32: Setting and applying the logic for identifying cables that may have fault problems; Step 4: Obtain identification results of cables that may have fault problems, and pick up local cables that may have fault problems on the cables that may have fault problems; Step 41: Setting and applying a local cable line picking logic that may have a fault problem on a cable line that may have a fault problem; Step 5: Obtain a local cable line where a fault problem may occur, and sniff out a fault point where a fault problem may occur on the local cable line; Step 51: Setting and applying fault point sniffing logic.

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