Cable defect detection system and method based on comprehensive information evaluation

Abstract

The embodiment of the invention discloses a cable defect detection system and method based on comprehensive information evaluation, and the method comprises the steps: determining the information type of first collection information under the condition that the first collection information of a to-be-evaluated cable is detected to have a suspected defect, determining a plurality of auxiliary evaluation information associated with the first acquisition information based on the information category, determining a defect detection condition associated with the suspected defect, and detecting the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determining whether the to-be-evaluated cable has a cable defect according to the information detection result, and determining defect information of the to-be-evaluated cable based on the suspected defect and the information detection result under the condition of determining that the cable defect exists. According to the scheme, the associated information of the suspected defect information is further subjected to defect evaluation, so that the multi-dimensional parameter data can be gathered to detect and identify the cable defect, and the defect identification accuracy is improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of cable detection technology, and in particular, to a cable defect detection system and method based on comprehensive information evaluation. Background Art

[0002] Cable is a product that insulates and covers conductive materials (such as copper and aluminum) and is used to transmit electricity or communication signals to different locations. The cable production process refers to the process of making finished cables from raw materials through a series of processing and treatment processes. The cable production process can be divided into the main steps of raw material preparation, conductor twisting, insulation treatment, braided shielding, and outer sheath treatment. The production process of different types of cables may be different. For example, the manufacturing process of high-voltage cables may include more links and complex processes.

[0003] Poor cable quality, rough manufacturing process, imperfect process control, etc. may cause internal cable breaks or short circuits, and even cause power outages in the entire power system, causing great inconvenience and losses to production and life. Therefore, it is extremely important to detect cable defects and repair them in a timely manner during the cable production process. Most of the related cable defect detection technologies use fixed thresholds or fault images for real-time information collection and comparison during the cable production process. The discrimination mechanism of this method is relatively simple, which is prone to misjudgment and cannot more accurately determine the cable defects. Summary of the invention

[0004] The embodiments of the present invention provide a cable defect detection system and method based on comprehensive information evaluation, which solves the problem that the discrimination mechanism in the existing cable defect detection technology is relatively single, which is easy to cause misjudgment and cannot more accurately determine the cable defect situation. It can integrate multi-dimensional parameter data to detect and identify cable defects, thereby improving the accuracy of defect identification.

[0005] In a first aspect, an embodiment of the present invention provides a cable defect detection method based on comprehensive information evaluation, comprising:

[0006] In the case where it is detected that there is a suspected defect in the first collected information of the cable to be evaluated, determining the information category of the first collected information, and determining a plurality of auxiliary evaluation information associated with the first collected information based on the information category;

[0007] Determine a defect detection condition associated with the suspected defect, detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determine whether the cable to be evaluated has a cable defect according to the information detection result;

[0008] In the case where it is determined that the cable defect exists, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection result.

[0009] Optionally, the determining, based on the information category, a plurality of auxiliary evaluation information associated with the first collected information includes:

[0010] In the case where the information category is an image category, determining a first photographing device for collecting the first information, and determining images photographed by a plurality of second photographing devices associated with the first photographing device as auxiliary evaluation information;

[0011] In the case where the information category is a parameter category, a plurality of influencing parameters and influencing parameter values ​​of the first collected information are determined, and the influencing parameters and influencing parameter values ​​are determined as auxiliary evaluation information.

[0012] Optionally, the determining the defect detection condition associated with the suspected defect includes:

[0013] In the case where the information category is an image category, determining a comparison image and a similarity threshold based on the suspected defect, and generating a defect detection condition according to the comparison image and the similarity threshold;

[0014] In the case where the information category is a parameter category, comparison change data corresponding to the multiple influencing parameters are determined based on the suspected defect, and corresponding defect detection conditions are generated according to the comparison change data.

[0015] Optionally, the determining the defect detection condition associated with the suspected defect further includes:

[0016] In the case where the information category is an image category, determining a defect parameter and an associated evaluation threshold based on the suspected defect, and generating a defect detection condition according to the defect parameter and the evaluation threshold;

[0017] In the case where the information category is a parameter category, a parameter value comparison range corresponding to the multiple influencing parameters is determined based on the suspected defect, and a corresponding defect detection condition is generated according to the parameter value comparison range.

[0018] Optionally, determining whether the cable to be evaluated has a cable defect according to the information detection result includes:

[0019] In the case where the information category is an image category, determining a quantity ratio of the auxiliary evaluation information that meets the defect detection condition, and determining whether the cable to be evaluated has a cable defect according to the quantity ratio;

[0020] When the information category is a parameter category, it is determined whether the auxiliary evaluation information satisfies the corresponding defect detection condition. If so, it is determined that the cable to be evaluated has a cable defect. If not, it is determined that the cable to be evaluated does not have a cable defect.

[0021] Optionally, the determining the defect information of the cable to be evaluated based on the suspected defect and the information detection result includes:

[0022] Determine the suspected defect as the main defect of the cable to be evaluated, and when the information category is an image category, determine the defect information of the cable to be evaluated based on the main defect and the auxiliary evaluation information that meets the defect detection condition;

[0023] In the case where the information category is a parameter category, a secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection condition, and the main defect and the secondary defect are determined as defect information of the cable to be evaluated.

[0024] Optionally, the determining the defect information of the cable to be evaluated based on the main defect and the auxiliary evaluation information satisfying the defect detection condition includes:

[0025] Determine the sum of the first collected information and the auxiliary evaluation information as the total information quantity, and determine the sum of the first collected information and the auxiliary evaluation information that meets the defect detection condition as the defect information quantity;

[0026] The ratio of the defect information quantity to the total information quantity is calculated, the defect degree of the main defect is determined according to the ratio, and the main defect and the defect degree are determined as defect information.

[0027] In a second aspect, an embodiment of the present invention further provides a cable defect detection system based on comprehensive information evaluation, comprising:

[0028] A category determination module, configured to determine the information category of the first collected information when a suspected defect is detected in the first collected information of the cable to be evaluated;

[0029] An evaluation information determination module, configured to determine a plurality of auxiliary evaluation information associated with the first collected information based on the information category;

[0030] An information detection module, used to determine a defect detection condition associated with the suspected defect, and detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result;

[0031] The defect judgment module is used to determine whether the cable to be evaluated has a cable defect according to the information detection result.

[0032] A defect information determination module is used to determine the defect information of the cable to be evaluated based on the suspected defect and the information detection result when it is determined that the cable defect exists.

[0033] In a third aspect, an embodiment of the present invention further provides a cable defect detection device based on comprehensive information evaluation, the device comprising:

[0034] one or more processors;

[0035] a storage device for storing one or more programs,

[0036] When the one or more programs are executed by the one or more processors, the one or more processors implement the cable defect detection method based on comprehensive information evaluation described in an embodiment of the present invention.

[0037] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer executable instructions, which, when executed by a computer processor, are used to execute the cable defect detection method based on comprehensive information evaluation described in an embodiment of the present invention.

[0038] In an embodiment of the present invention, when it is detected that the first collected information of the cable to be evaluated has a suspected defect, the information category of the first collected information of the cable to be evaluated is determined, multiple auxiliary evaluation information associated with the first collected information of the cable to be evaluated is determined based on the information category, the defect detection condition associated with the suspected defect is determined, the multiple auxiliary evaluation information is detected based on the defect detection condition to obtain an information detection result, and it is determined whether the cable to be evaluated has a cable defect based on the information detection result. When it is determined that the cable to be evaluated has a cable defect, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection result. This solution solves the problem that the discrimination mechanism in the existing cable defect detection technology is relatively single, which is easy to cause misjudgment and cannot more accurately determine the cable defect situation by further defect evaluation on the associated information of the suspected defect information. It can collect multi-dimensional parameter data to detect and identify cable defects and improve the accuracy of defect identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flowchart of a cable defect detection method based on comprehensive information evaluation provided by an embodiment of the present invention;

[0040] Figure 2 A flowchart of a method for determining defect detection conditions associated with a suspected defect provided by an embodiment of the present invention;

[0041] Figure 3 A flowchart of a method for determining defect information of a cable to be evaluated provided by an embodiment of the present invention;

[0042] Figure 4 A module structure block diagram of a cable defect detection system based on comprehensive information evaluation provided by an embodiment of the present invention;

[0043] Figure 5 A schematic structural diagram of a cable defect detection device based on comprehensive information evaluation provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than to limit the embodiments of the present invention. It is also necessary to explain that, for ease of description, only parts related to the embodiments of the present invention are shown in the accompanying drawings, rather than all structures.

[0045] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and or or" in the specification and claims represents at least one of the connected objects, and the character "or" generally indicates that the objects associated before and after are in an "or" relationship.

[0046] The cable defect detection method based on comprehensive information evaluation provided in the embodiment of the present application can be applied to defect detection scenarios in the cable production process. The cable defect detection method based on comprehensive information evaluation provided in the embodiment of the present application, the execution subject of each step can be a computer device, which refers to any electronic device with data calculation, processing and storage capabilities, such as mobile phones, PCs (Personal Computers), tablet computers and other terminal devices, and can also be servers and other devices, which are not limited in the embodiment of the present application.

[0047] Figure 1 A flowchart of a cable defect detection method based on comprehensive information evaluation provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, specifically including:

[0048] Step S101: when it is detected that there is a suspected defect in first collected information of a cable to be evaluated, determining an information category of the first collected information, and determining a plurality of auxiliary evaluation information associated with the first collected information based on the information category.

[0049] Among them, the first collected information is used to characterize the collected information for the first cable defect inspection; the information category is used to characterize the classification of the first collected information; and the auxiliary evaluation information is used to characterize the information that assists in determining whether the cable to be evaluated has defects. In the case where it is detected that the first collected information of the cable to be evaluated has suspected defects, the information category of the first collected information is determined, and multiple auxiliary evaluation information associated with the first collected information is determined based on the information category of the first collected information. Optionally, the information category of the first collected information includes an image category and a parameter category. The image category is used to characterize the image information captured by the shooting device, and the parameter category is used to characterize the parameter information collected by different types of sensors. When the information category is an image category, the first shooting device of the first collected information is determined, and the images captured by multiple second shooting devices associated with the first shooting device are determined as auxiliary evaluation information. When the information category is a parameter category, multiple influencing parameters and influencing parameter values ​​of the first collected information are determined, and the influencing parameters and influencing parameter values ​​are determined as auxiliary evaluation information. In one embodiment, the information category of the first collected information is an image category, the first shooting device of the first collected information is device 1, and the second shooting devices associated with device 1 include devices 2, 3, and 4. The images currently captured by devices 2, 3, and 4 are image a, image b, and image c, respectively. Then, image a, image b, and image c are determined as auxiliary evaluation information. In another embodiment, the information category of the first collected information is a parameter category, which is an extrusion temperature parameter. The influencing parameters of the extrusion temperature parameter are the extrusion speed and the load. The currently collected extrusion speed is 1.2 m / min and the load is 20 kW. Then, the extrusion speed of 1.2 m / min and the load of 20 kW are determined as auxiliary evaluation information. Classifying the first collected information by images and parameters can improve the accuracy and availability of the auxiliary evaluation information.

[0050] Step S102: Determine a defect detection condition associated with the suspected defect.

[0051] Among them, the defect detection condition is used to characterize the condition for judging whether there is a defect in the auxiliary evaluation information. After determining the information category of the first collected information and the multiple auxiliary evaluation information associated with the first collected information, the defect detection condition associated with the suspected defect of the first collected information is determined. In one embodiment, the condition judgment parameter and the evaluation threshold of the condition judgment parameter are determined according to the suspected defect, and the defect detection condition template associated with the condition judgment parameter is determined, and the evaluation threshold of the condition judgment parameter is substituted into the defect detection condition template to obtain the defect detection condition associated with the suspected defect of the first collected information.

[0052] Step S103: Detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determine whether the cable to be evaluated has a cable defect according to the information detection result.

[0053] Among them, after determining the defect detection conditions associated with the suspected defects of the first collected information, the auxiliary evaluation information is detected based on the defect detection conditions associated with the suspected defects to obtain information detection results, and whether the cable to be evaluated has a cable defect is determined based on the information detection results. Optionally, when the information category is an image category, the number ratio of the auxiliary evaluation information that meets the defect detection conditions is determined, and whether the cable to be evaluated has a cable defect is determined based on the number ratio. When the information category is a parameter category, it is determined whether there is auxiliary evaluation information that meets the corresponding defect detection conditions. If so, it is determined that the cable to be evaluated has a cable defect. If not, it is determined that the cable to be evaluated does not have a cable defect. In one embodiment, the information category of the first collected information is image category, image a, image b, image c, and image d are auxiliary evaluation information, and the defect detection condition is that the thickness of the insulation layer is less than 0.6mm. When more than 50% of the auxiliary evaluation information meets the defect detection condition, it is determined that the cable to be evaluated has a cable defect, and the insulation layer thicknesses in image a, image b, image c, and image d are 0.5mm, 0.55mm, 0.7mm, and 0.45mm, respectively. 75% of the auxiliary evaluation information is less than 0.6mm, and more than 50% of the auxiliary evaluation information meets the defect detection condition, that is, the cable to be evaluated has a cable defect. In another embodiment, the information category of the first collected information is parameter category, which is an extrusion temperature parameter, and the influencing parameters are extrusion speed and load. The extrusion speed is 2.1m / min, the load is 20kw, and the defect detection conditions are respectively extrusion speed greater than 1.9m / min, load greater than 25kw, and extrusion speed greater than 1.9m / min. There are influencing parameters that meet the corresponding defect detection conditions, that is, the cable to be evaluated has a cable defect.

[0054] Step S104: When it is determined that the cable defect exists, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection result.

[0055] Wherein, in the case where it is determined that there is a cable defect, the defect information of the cable to be evaluated is determined based on the suspected defect of the first collected information and the information detection results of the auxiliary evaluation information. In one embodiment, the suspected defect of the first collected information is determined as the main defect of the cable to be evaluated. When the information category is an image category, the defect information of the cable to be evaluated is determined based on the main defect and the auxiliary evaluation information that meets the defect detection conditions. When the information category is a parameter category, the secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection conditions, and the main defect and the secondary defect are determined as the defect information of the cable to be evaluated. Determining the defect information of the cable to be evaluated associated with different categories of first collected information in different ways can collect multi-dimensional parameter data to detect and identify cable defects, thereby improving the accuracy of defect identification.

[0056] From the above, it can be seen that when it is detected that the first collected information of the cable to be evaluated has a suspected defect, the information category of the first collected information of the cable to be evaluated is determined, and multiple auxiliary evaluation information associated with the first collected information of the cable to be evaluated is determined based on the information category, and the defect detection conditions associated with the suspected defect are determined. Based on the defect detection conditions, multiple auxiliary evaluation information is detected to obtain information detection results, and it is determined whether the cable to be evaluated has a cable defect based on the information detection results. When it is determined that the cable to be evaluated has a cable defect, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection results. This solution solves the problem that the discrimination mechanism in the existing cable defect detection technology is relatively single, which is easy to cause misjudgment and cannot more accurately determine the cable defect situation by further defect evaluation on the associated information of the suspected defect information. It can collect multi-dimensional parameter data to detect and identify cable defects and improve the accuracy of defect identification.

[0057] Figure 2 A flowchart of a method for determining defect detection conditions associated with a suspected defect provided by an embodiment of the present invention, such as Figure 2 As shown, specifically including:

[0058] Step S201: when it is detected that there is a suspected defect in first collected information of a cable to be evaluated, determine the information category of the first collected information, and determine a plurality of auxiliary evaluation information associated with the first collected information based on the information category.

[0059] Step S202: When the information category is an image category, a comparison image and a similarity threshold are determined based on the suspected defect, and defect detection conditions are generated according to the comparison image and the similarity threshold; when the information category is a parameter category, comparison change data corresponding to the multiple influencing parameters are determined based on the suspected defect, and corresponding defect detection conditions are generated according to the comparison change data.

[0060] Wherein, the comparison image is used to represent the pre-stored image for comparison with the auxiliary evaluation information. In the case where the information category of the first acquisition information is an image category, the comparison image and the similarity threshold are determined based on the suspected defect, and the defect detection condition is generated according to the comparison image and the similarity threshold. In the case where the information category of the first acquisition information is a parameter category, the comparison change data corresponding to multiple influencing parameters are determined based on the suspected defect, and the corresponding defect detection condition is generated according to the comparison change data. In one embodiment, the information category of the first acquisition information is an image category, the suspected defect is that the thickness of the insulating layer is too small, and the comparison image associated with the insulation layer thickness being too small is determined to be image A, the similarity threshold is 65%, and the defect detection condition generated according to the comparison image and the similarity threshold is that the similarity with image A is greater than 65%. In another embodiment, the information category of the first acquisition information is a parameter category, the influencing parameters are extrusion speed and load, the comparison change data of the extrusion speed is a change speed of 0.3m / min, and the change speed of the load is 10kw / h, then the defect detection condition corresponding to the extrusion speed is a change speed greater than 0.3m / min, and the defect detection condition corresponding to the load is a change speed greater than 10kw / h. In another embodiment, when the information category of the first acquired information is an image category, defect parameters and associated evaluation thresholds are determined based on suspected defects, and defect detection conditions are generated according to the defect parameters and the evaluation thresholds. When the information category of the first acquired information is a parameter category, parameter value comparison ranges corresponding to multiple influencing parameters are determined based on the suspected defects, and corresponding defect detection conditions are generated according to the parameter value comparison ranges.

[0061] Step S203: Detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determine whether the cable to be evaluated has a cable defect according to the information detection result.

[0062] Step S204: When it is determined that the cable defect exists, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection result.

[0063] From the above, it can be seen that when the information category of the first collected information is an image category, a comparison image and a similarity threshold are determined based on the suspected defect, and a defect detection condition is generated according to the comparison image and the similarity threshold. When the information category of the first collected information is a parameter category, comparison change data corresponding to multiple influencing parameters are determined based on the suspected defect, and corresponding defect detection conditions are generated according to the comparison change data. This solution determines defect detection conditions based on the information category of the first collected information and the suspected defect, and considers more comprehensive factors, which can improve the accuracy and rationality of detection.

[0064] Figure 3A flowchart of a method for determining defect information of a cable to be evaluated provided by an embodiment of the present invention, such as Figure 3 As shown, specifically including:

[0065] Step S301: when it is detected that there is a suspected defect in first collected information of a cable to be evaluated, determine the information category of the first collected information, and determine a plurality of auxiliary evaluation information associated with the first collected information based on the information category.

[0066] Step S302: Determine a defect detection condition associated with the suspected defect.

[0067] Step S303: Detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determine whether the cable to be evaluated has a cable defect according to the information detection result.

[0068] Step S304: When it is determined that the cable defect exists, the suspected defect is determined as the main defect of the cable to be evaluated; when the information category is an image category, the defect information of the cable to be evaluated is determined based on the main defect and the auxiliary evaluation information that meets the defect detection condition; when the information category is a parameter category, the secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection condition, and the main defect and the secondary defect are determined as the defect information of the cable to be evaluated.

[0069] Wherein, in the case where it is determined that there is a cable defect, the suspected defect is determined as the main defect of the cable to be evaluated, and in the case where the information category of the first collected information is an image category, the defect information of the cable to be evaluated is determined based on the main defect and the auxiliary evaluation information that meets the defect detection conditions. Optionally, the sum of the first collected information and the auxiliary evaluation information is determined as the total information quantity, the sum of the first collected information and the auxiliary evaluation information that meets the defect detection conditions is determined as the defect information quantity, the ratio of the defect information quantity to the total information quantity is calculated, the defect degree of the main defect is determined according to the ratio, and the main defect and the defect degree are determined as the defect information. In the case where the information category of the first collected information is a parameter category, the secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection conditions, and the main defect and the secondary defect are determined as the defect information of the cable to be evaluated. In one embodiment, it is determined that there is a cable defect, the information category of the first collected information is the image category, the suspected defect is that the thickness of the insulation layer is too small, the number of auxiliary evaluation information is 4, and the number of auxiliary evaluation information that meets the defect detection conditions is 3. Then the sum of the first collected information and the number of auxiliary evaluation information is 5, and the sum of the first collected information and the number of auxiliary evaluation information that meets the defect detection conditions is 4, that is, the total number of information is 5, the number of defect information is 4, and the ratio is 4 / 5. The ratio is converted into a defect degree of 80% for the main defect, and the insulation layer thickness is too small and the defect degree is 80% as defect information. In another embodiment, it is determined that there is a cable defect, the information category of the first collected information is the parameter category, the suspected defect is that the extrusion temperature is too high, that is, the main defect is that the extrusion temperature is too high, and the auxiliary evaluation information that meets the corresponding defect detection conditions is the extrusion speed, that is, the secondary defect is that the extrusion speed is too fast, and the main defect of the extrusion temperature is too high and the secondary defect of the extrusion speed is too fast are determined as the defect information of the cable to be evaluated.

[0070] From the above, it can be seen that when it is determined that there is a cable defect, the suspected defect is determined as the main defect of the cable to be evaluated. When the information category of the first collected information is an image category, the defect information of the cable to be evaluated is determined based on the main defect and the auxiliary evaluation information that meets the defect detection conditions. When the information category of the first collected information is a parameter category, the secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection conditions, and the main defect and the secondary defect are determined as the defect information of the cable to be evaluated. This solution determines the defect information of the cable to be evaluated associated with different categories of first collected information according to different methods, and can collect multi-dimensional parameter data to detect and identify cable defects, thereby improving the accuracy of defect identification.

[0071] Figure 4The module structure block diagram of a cable defect detection system based on comprehensive information evaluation provided by an embodiment of the present invention is used to execute the cable defect detection method based on comprehensive information evaluation provided by the above embodiment, and has the corresponding functional modules and beneficial effects of the execution method. Figure 4 As shown, the system specifically includes:

[0072] A category determination module 101 is used to determine the information category of the first collected information of the cable to be evaluated when it is detected that there is a suspected defect in the first collected information;

[0073] An evaluation information determination module 102, configured to determine a plurality of auxiliary evaluation information associated with the first collected information based on the information category;

[0074] An information detection module 103 is used to determine a defect detection condition associated with the suspected defect, and detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result;

[0075] The defect judgment module 104 is used to determine whether the cable to be evaluated has a cable defect according to the information detection result.

[0076] The defect information determination module 105 is used to determine the defect information of the cable to be evaluated based on the suspected defect and the information detection result when it is determined that the cable defect exists.

[0077] It can be seen from the above scheme that when it is detected that the first collected information of the cable to be evaluated has a suspected defect, the information category of the first collected information of the cable to be evaluated is determined, and multiple auxiliary evaluation information associated with the first collected information of the cable to be evaluated is determined based on the information category, and the defect detection conditions associated with the suspected defect are determined. Based on the defect detection conditions, multiple auxiliary evaluation information is detected to obtain information detection results, and it is determined whether the cable to be evaluated has a cable defect based on the information detection results. When it is determined that the cable to be evaluated has a cable defect, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection results. This scheme solves the problem that the discrimination mechanism in the existing cable defect detection technology is relatively single, which is easy to cause misjudgment and cannot more accurately determine the cable defect situation by further defect evaluation on the associated information of the suspected defect information. It can collect multi-dimensional parameter data to detect and identify cable defects and improve the accuracy of defect identification.

[0078] In a possible embodiment, the evaluation information determination module 102 is specifically configured to:

[0079] In the case where the information category is an image category, determining a first photographing device for collecting the first information, and determining images photographed by a plurality of second photographing devices associated with the first photographing device as auxiliary evaluation information;

[0080] In the case where the information category is a parameter category, a plurality of influencing parameters and influencing parameter values ​​of the first collected information are determined, and the influencing parameters and influencing parameter values ​​are determined as auxiliary evaluation information.

[0081] In a possible embodiment, the information detection module 103 is specifically used to:

[0082] In the case where the information category is an image category, determining a comparison image and a similarity threshold based on the suspected defect, and generating a defect detection condition according to the comparison image and the similarity threshold;

[0083] In the case where the information category is a parameter category, comparison change data corresponding to the multiple influencing parameters are determined based on the suspected defect, and corresponding defect detection conditions are generated according to the comparison change data.

[0084] In a possible embodiment, the information detection module 103 is further used to:

[0085] In the case where the information category is an image category, determining a defect parameter and an associated evaluation threshold based on the suspected defect, and generating a defect detection condition according to the defect parameter and the evaluation threshold;

[0086] In the case where the information category is a parameter category, a parameter value comparison range corresponding to the multiple influencing parameters is determined based on the suspected defect, and a corresponding defect detection condition is generated according to the parameter value comparison range.

[0087] In a possible embodiment, the defect judgment module 104 is specifically used to:

[0088] In the case where the information category is an image category, determining a quantity ratio of the auxiliary evaluation information that meets the defect detection condition, and determining whether the cable to be evaluated has a cable defect according to the quantity ratio;

[0089] When the information category is a parameter category, it is determined whether the auxiliary evaluation information satisfies the corresponding defect detection condition. If so, it is determined that the cable to be evaluated has a cable defect. If not, it is determined that the cable to be evaluated does not have a cable defect.

[0090] In a possible embodiment, the defect information determination module 105 is specifically configured to:

[0091] Determine the suspected defect as the main defect of the cable to be evaluated, and when the information category is an image category, determine the defect information of the cable to be evaluated based on the main defect and the auxiliary evaluation information that meets the defect detection condition;

[0092] In the case where the information category is a parameter category, a secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection condition, and the main defect and the secondary defect are determined as defect information of the cable to be evaluated.

[0093] In a possible embodiment, the defect information determination module 105 is further configured to:

[0094] Determine the sum of the first collected information and the auxiliary evaluation information as the total information quantity, and determine the sum of the first collected information and the auxiliary evaluation information that meets the defect detection condition as the defect information quantity;

[0095] The ratio of the defect information quantity to the total information quantity is calculated, the defect degree of the main defect is determined according to the ratio, and the main defect and the defect degree are determined as defect information.

[0096] Figure 5 A schematic diagram of the structure of a cable defect detection device based on comprehensive information evaluation provided by an embodiment of the present invention, such as Figure 5 As shown, the device includes a processor 201, a memory 202, an input device 203 and an output device 204; the number of processors 201 in the device can be one or more. Figure 5 A processor 201 is taken as an example; the processor 201, memory 202, input device 203 and output device 204 in the device can be connected by a bus or other means. Figure 5 In the example, the connection through the bus is taken. The memory 202, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions or modules corresponding to the cable defect detection method based on comprehensive information evaluation in the embodiment of the present invention. The processor 201 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 202, that is, realizes the above-mentioned cable defect detection method based on comprehensive information evaluation. The input device 203 can be used to receive input digital or character information, and generate key signal input related to user settings and function control of the device. The output device 204 may include a display device such as a display screen.

[0097] An embodiment of the present invention further provides a storage medium containing computer executable instructions, wherein the computer executable instructions are used to execute a cable defect detection method based on comprehensive information evaluation when executed by a computer processor, the method comprising:

[0098] In the case where it is detected that there is a suspected defect in the first collected information of the cable to be evaluated, determining the information category of the first collected information, and determining a plurality of auxiliary evaluation information associated with the first collected information based on the information category;

[0099] Determine a defect detection condition associated with the suspected defect, detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determine whether the cable to be evaluated has a cable defect according to the information detection result;

[0100] In the case where it is determined that the cable defect exists, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection result.

[0101] It is worth noting that in the above-mentioned embodiment of the cable defect detection method system based on comprehensive information evaluation, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present invention.

[0102] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the embodiments of the present invention are not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the embodiments of the present invention. Therefore, although the embodiments of the present invention are described in more detail through the above embodiments, the embodiments of the present invention are not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.

Claims

1. A cable defect detection method based on comprehensive information evaluation, characterized in that: include: In the case where it is detected that there is a suspected defect in the first collected information of the cable to be evaluated, determining the information category of the first collected information, and determining a plurality of auxiliary evaluation information associated with the first collected information based on the information category; Determine a defect detection condition associated with the suspected defect, detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result, and determine whether the cable to be evaluated has a cable defect according to the information detection result; In the case where it is determined that the cable defect exists, the defect information of the cable to be evaluated is determined based on the suspected defect and the information detection result.

2. The cable defect detection method based on comprehensive information evaluation according to claim 1 is characterized in that: The determining, based on the information category, a plurality of auxiliary evaluation information associated with the first collected information includes: In the case where the information category is an image category, determining a first photographing device for collecting the first information, and determining images photographed by a plurality of second photographing devices associated with the first photographing device as auxiliary evaluation information; In the case where the information category is a parameter category, a plurality of influencing parameters and influencing parameter values ​​of the first collected information are determined, and the influencing parameters and influencing parameter values ​​are determined as auxiliary evaluation information.

3. The cable defect detection method based on comprehensive information evaluation according to claim 1 is characterized in that: The determining of the defect detection condition associated with the suspected defect includes: In the case where the information category is an image category, determining a comparison image and a similarity threshold based on the suspected defect, and generating a defect detection condition according to the comparison image and the similarity threshold; In the case where the information category is a parameter category, comparison change data corresponding to the multiple influencing parameters are determined based on the suspected defect, and corresponding defect detection conditions are generated according to the comparison change data.

4. The cable defect detection method based on comprehensive information evaluation according to claim 3 is characterized in that: The determining of the defect detection condition associated with the suspected defect further includes: In the case where the information category is an image category, determining a defect parameter and an associated evaluation threshold based on the suspected defect, and generating a defect detection condition according to the defect parameter and the evaluation threshold; In the case where the information category is a parameter category, a parameter value comparison range corresponding to the multiple influencing parameters is determined based on the suspected defect, and a corresponding defect detection condition is generated according to the parameter value comparison range.

5. The cable defect detection method based on comprehensive information evaluation according to any one of claims 1 to 4, characterized in that: The determining, according to the information detection result, whether the cable to be evaluated has a cable defect includes: In the case where the information category is an image category, determining a quantity ratio of the auxiliary evaluation information that meets the defect detection condition, and determining whether the cable to be evaluated has a cable defect according to the quantity ratio; When the information category is a parameter category, it is determined whether the auxiliary evaluation information satisfies the corresponding defect detection condition. If so, it is determined that the cable to be evaluated has a cable defect. If not, it is determined that the cable to be evaluated does not have a cable defect.

6. The cable defect detection method based on comprehensive information evaluation according to any one of claims 1 to 5, characterized in that: The determining the defect information of the cable to be evaluated based on the suspected defect and the information detection result includes: Determine the suspected defect as the main defect of the cable to be evaluated, and when the information category is an image category, determine the defect information of the cable to be evaluated based on the main defect and the auxiliary evaluation information that meets the defect detection condition; In the case where the information category is a parameter category, a secondary defect is determined based on the auxiliary evaluation information that meets the corresponding defect detection condition, and the main defect and the secondary defect are determined as defect information of the cable to be evaluated.

7. The cable defect detection method based on comprehensive information evaluation according to claim 6 is characterized in that: The determining the defect information of the cable to be evaluated based on the main defect and the auxiliary evaluation information satisfying the defect detection condition includes: Determine the sum of the first collected information and the auxiliary evaluation information as the total information quantity, and determine the sum of the first collected information and the auxiliary evaluation information that meets the defect detection condition as the defect information quantity; The ratio of the defect information quantity to the total information quantity is calculated, the defect degree of the main defect is determined according to the ratio, and the main defect and the defect degree are determined as defect information.

8. Cable defect detection system based on comprehensive information evaluation, characterized in that: include: A category determination module, configured to determine the information category of the first collected information when a suspected defect is detected in the first collected information of the cable to be evaluated; An evaluation information determination module, configured to determine a plurality of auxiliary evaluation information associated with the first collected information based on the information category; An information detection module, used to determine a defect detection condition associated with the suspected defect, and detect the auxiliary evaluation information based on the defect detection condition to obtain an information detection result; The defect judgment module is used to determine whether the cable to be evaluated has a cable defect according to the information detection result. A defect information determination module is used to determine the defect information of the cable to be evaluated based on the suspected defect and the information detection result when it is determined that the cable defect exists.

9. A cable defect detection device based on comprehensive information evaluation, the device comprising: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the cable defect detection method based on comprehensive information evaluation as described in any one of claims 1-7.

10. A storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the cable defect detection method based on comprehensive information evaluation as described in any one of claims 1 to 7 when executed by a computer processor.

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