Inspection method, device and equipment for intelligent optical distribution network equipment

Abstract

The invention provides an inspection method, device and equipment for intelligent optical distribution network equipment. Comprising the following steps: for each intelligent optical distribution network device in a sub-region range, acquiring M data sets of the intelligent optical distribution network device in a preset time period; the data set comprises N pieces of data of environmental parameters corresponding to the data set in a preset time period; for each intelligent optical distribution network device in the sub-region range, determining health state information of the intelligent optical distribution network device according to the M data sets of the intelligent optical distribution network device, and for each intelligent optical distribution network device in the sub-region range, determining the health state information of the intelligent optical distribution network device according to the health state information of the intelligent optical distribution network device. Generating and outputting alarm information of the intelligent optical distribution network equipment, wherein the alarm information represents that the intelligent optical distribution network equipment is abnormal; and according to the alarm information, performing routing inspection on each intelligent optical distribution network device in the sub-region range. According to the invention, the inspection period is shortened and the inspection efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of optical communication, and in particular, to an inspection method, device, and equipment for intelligent optical distribution network equipment. Background Art

[0002] With the continuous development of science and technology, optical communication technology has been widely applied. The Optical Distribution Network (ODN) is a technology that uses optical fibers and equipment to transmit information at high speed and can transmit optical signals to different user terminals. Intelligent optical distribution network equipment is an important equipment that provides network services in the optical distribution network.

[0003] Intelligent optical distribution network equipment includes equipment such as intelligent optical fiber distribution frames, intelligent optical cable cross-connect boxes, and intelligent optical cable splitting boxes; intelligent optical distribution network equipment is used to complete functions such as intelligent optical fiber allocation and resource data collection. Currently, due to the large number and wide distribution of intelligent optical distribution network equipment, problems such as long inspection cycles and difficult fault location for intelligent optical distribution network equipment have occurred. Therefore, there is an urgent need for a method to complete the inspection of intelligent optical distribution network equipment to quickly inspect intelligent optical distribution network equipment. Summary of the Invention

[0004] This application provides an inspection method, device, and equipment for intelligent optical distribution network equipment to solve the technical problem of low inspection efficiency.

[0005] In a first aspect, this application provides an inspection method for intelligent optical distribution network equipment. A preset geographical area includes multiple sub-areas; at least one intelligent optical distribution network equipment is deployed within the scope of the sub-area; the method includes:

[0006] For each intelligent optical distribution network equipment within the scope of the sub-area, obtain M data sets of the intelligent optical distribution network equipment within a preset time period; where, N data of the environmental parameters corresponding to the data set within the preset time period are included in the data set, and the environmental parameters are used to indicate the environmental conditions of the environment where the intelligent optical distribution network equipment is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2;

[0007] For each intelligent optical distribution network equipment within the scope of the sub-area, determine the health status information of the intelligent optical distribution network equipment according to the M data sets of the intelligent optical distribution network equipment, where the health status information characterizes the hardware status of the intelligent optical distribution network equipment;

[0008] For each intelligent optical distribution network equipment within the scope of the sub-area, generate and output an alarm message of the intelligent optical distribution network equipment according to the health status information of the intelligent optical distribution network equipment, where the alarm message characterizes that the intelligent optical distribution network equipment has an abnormality;

[0009] According to the warning information, conduct inspections on each intelligent optical distribution network device within the sub-region.

[0010] Optionally, for each intelligent optical distribution network device within the sub-region, determine the health status information of the intelligent optical distribution network device according to M data sets of the intelligent optical distribution network device, including:

[0011] For each intelligent optical distribution network device within the sub-region, determine the health degree observation sequence of the intelligent optical distribution network device according to M data sets of the intelligent optical distribution network device; wherein, there are multiple health degrees in the health degree observation sequence, and the health degree is used to describe the health degree of the intelligent optical distribution network device.

[0012] For each intelligent optical distribution network device within the sub-region, determine the health status information of the intelligent optical distribution network device according to the health degree observation sequence of the intelligent optical distribution network device and a preset prediction model.

[0013] Optionally, for each intelligent optical distribution network device within the sub-region, determine the health status information of the intelligent optical distribution network device according to M data sets of the intelligent optical distribution network device, including:

[0014] For each intelligent optical distribution network device within the sub-region, determine the characteristic parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device; wherein, the characteristic parameter is used to indicate the abnormal situation of the intelligent optical distribution network device under the environmental parameter corresponding to the characteristic parameter.

[0015] For each intelligent optical distribution network device within the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the data set of the intelligent optical distribution network device.

[0016] Optionally, the M data sets include a data set of illuminance parameters; for each intelligent optical distribution network device within the sub-region, determine the characteristic parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device, including:

[0017] For each intelligent optical distribution network device within the sub-region, determine a first characteristic parameter according to the data set of the illuminance parameter of the intelligent optical distribution network device and a first preset threshold; wherein, the first preset threshold is used to indicate the threshold of the illuminance parameter; the first characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is closed.

[0018] For each intelligent optical distribution network device within the range of the sub-region, determine a second characteristic parameter according to the data set of the illuminance parameter of the intelligent optical distribution network device, a first preset threshold, and a second preset threshold; wherein, the second preset threshold is used to indicate the number of times the illuminance parameter exceeds the first preset threshold; the second characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is abnormally closed.

[0019] Optionally, the M data sets include a data set of humidity parameters; for each intelligent optical distribution network device within the range of the sub-region, determine the characteristic parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device, including:

[0020] For each intelligent optical distribution network device within the range of the sub-region, determine a third characteristic parameter according to the data set of the humidity parameter of the intelligent optical distribution network device and a third preset threshold; wherein, the third preset threshold is used to indicate the threshold of the humidity parameter; the third characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is water-injected.

[0021] Optionally, the M data sets include a data set of temperature parameters; for each intelligent optical distribution network device within the range of the sub-region, determine the characteristic parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device, including:

[0022] For each intelligent optical distribution network device within the range of the sub-region, determine a fourth characteristic parameter according to the data set of the temperature parameter of the intelligent optical distribution network device and a fourth preset threshold; wherein, the fourth preset threshold is used to indicate the threshold of the temperature parameter; the fourth characteristic parameter is used to indicate whether the temperature of the box body of the intelligent optical distribution network device is normal.

[0023] Optionally, for each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the data set of the intelligent optical distribution network device, including:

[0024] For each intelligent optical distribution network device within the range of the sub-region, determine the weight of the characteristic parameter corresponding to the data set of the intelligent optical distribution network device;

[0025] For each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the data set of the intelligent optical distribution network device and the weight of the characteristic parameter.

[0026] Optionally, for each intelligent optical distribution network device within the range of the sub-region, determining the weight of the characteristic parameter corresponding to the data set of the intelligent optical distribution network device includes:

[0027] For each intelligent optical distribution network device within the range of the sub-region, generate data matrix information of the intelligent optical distribution network device according to each data set of the intelligent optical distribution network device; wherein, the data matrix information includes data of each environmental parameter.

[0028] For each intelligent optical distribution network device within the range of the sub-region, use the principal component analysis method to process the data matrix information of the intelligent optical distribution network device to obtain the weights of the characteristic parameters corresponding to each data set of the intelligent optical distribution network device.

[0029] Optionally, for each intelligent optical distribution network device within the range of the sub-region, generate and output alarm information of the intelligent optical distribution network device according to the health status information of the intelligent optical distribution network device, including:

[0030] For each intelligent optical distribution network device within the range of the sub-region, if it is determined that the level characterized by the health status information of the intelligent optical distribution network device is lower than the preset health status level, generate and output the alarm information of the intelligent optical distribution network device.

[0031] Optionally, perform inspections on each intelligent optical distribution network device within the range of the sub-region according to the alarm information, including:

[0032] If it is determined that the number of alarm information of the intelligent optical distribution network devices within the range of the sub-region exceeds the fifth preset threshold, generate an inspection work order corresponding to the sub-region range, and perform inspections on each intelligent optical distribution network device within the range of the sub-region based on the inspection work order.

[0033] In a second aspect, the present application provides an inspection device for an intelligent optical distribution network device. A preset geographical area includes multiple sub-regions; at least one intelligent optical distribution network device is deployed within the range of the sub-region; the device includes:

[0034] An acquisition unit, configured to, for each intelligent optical distribution network device within the range of the sub-region, acquire M data sets of the intelligent optical distribution network device within a preset time period; wherein, the data sets include N data of environmental parameters corresponding to the data sets within the preset time period, and the environmental parameters are used to indicate the environmental conditions of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2.

[0035] A determination unit, configured to, for each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the M data sets of the intelligent optical distribution network device, wherein the health status information characterizes the hardware status of the intelligent optical distribution network device.

[0036] A generating unit, configured to generate and output an alarm message for each intelligent optical distribution network device within the range of the sub-region according to the health status information of the intelligent optical distribution network device, where the alarm message indicates that the intelligent optical distribution network device has an abnormality;

[0037] An inspection unit, configured to inspect each intelligent optical distribution network device within the range of the sub-region according to the alarm message.

[0038] In a third aspect, the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0039] The memory stores computer-executable instructions;

[0040] The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of the first aspects.

[0041] In a fourth aspect, the present application provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, they are used to implement the method according to any one of the first aspects.

[0042] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the method according to any one of the first aspects.

[0043] In a sixth aspect, the present application provides a chip, where a computer program is stored on the chip, and when the computer program is executed by the chip, it implements the method according to any one of the first aspects.

[0044] The inspection method, device, and equipment for the intelligent optical distribution network device provided by the present application can, by pre-dividing a preset geographical area into sub-regions, for each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device by using environmental parameters, generate an alarm message for the intelligent optical distribution network device by using the health status information, and inspect each intelligent optical distribution network device within the range of the sub-region according to the alarm messages of each intelligent optical distribution network device within the range of the sub-region. By this means, there is no need to regularly inspect each intelligent optical distribution network device within the range of the preset geographical area. It is only necessary to monitor the alarm messages of each intelligent optical distribution network device within the range of each sub-region, and inspect the intelligent optical distribution network devices within the range of the sub-region according to the alarm messages, reducing the inspection period each time, improving the inspection efficiency, and being able to quickly locate the corresponding intelligent optical distribution network device according to the alarm message for fault troubleshooting. Description of the Drawings

[0045] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0046] Figure 1 A schematic diagram of an application scenario provided for this application;

[0047] Figure 2 A schematic flowchart of an inspection method for an intelligent optical distribution network device provided for this application;

[0048] Figure 3 A schematic flowchart of an inspection method for an intelligent optical distribution network device provided for this application;

[0049] Figure 4 A schematic flowchart of an inspection method for an intelligent optical distribution network device provided for this application;

[0050] Figure 5 A schematic structural diagram of an inspection device for an intelligent optical distribution network device provided for this application;

[0051] Figure 6 A schematic structural diagram of an inspection device for an intelligent optical distribution network device provided for this application;

[0052] Figure 7 A schematic structural diagram of an electronic device provided for this application.

[0053] Through the above accompanying drawings, specific embodiments of this application have been shown, and there will be more detailed descriptions hereinafter. These drawings and textual descriptions are not intended to limit the scope of the concept of this application in any way, but to illustrate the concept of this application to those skilled in the art by referring to specific embodiments. Specific Embodiments

[0054] Here, exemplary embodiments will be described in detail, and the examples are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. On the contrary, they are merely examples of devices and methods consistent with some aspects of this application as detailed in the appended claims.

[0055] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards, and corresponding operation entrances are provided for users to choose to authorize or refuse.

[0056] Intelligent optical distribution network equipment is used to complete functions such as intelligent optical fiber allocation and resource data collection, and may include equipment such as intelligent optical fiber main distribution frames, intelligent optical cable cross-connect boxes, and intelligent optical cable fiber distribution boxes. Currently, it is usually to regularly inspect all intelligent optical distribution network equipment within a preset geographical area. However, due to the large number and wide distribution of intelligent optical distribution network equipment, for example, most intelligent optical cable fiber distribution boxes are installed on walls, there are problems such as long inspection cycles and difficult fault location for intelligent optical distribution network equipment.

[0057] In view of this, the present application provides an inspection method for intelligent optical distribution network equipment. First, the preset geographical area is divided into multiple sub-areas. For the intelligent optical distribution network equipment in the sub-areas, the environmental parameters of the intelligent optical distribution network equipment are used to determine whether the intelligent optical distribution network equipment is abnormal. Furthermore, it is possible to inspect the small area of the intelligent optical distribution network equipment that appears abnormal, without having to inspect all the intelligent optical distribution network equipment within the preset geographical area, improving the inspection efficiency, and being able to quickly locate the intelligent optical distribution network equipment with faults based on the abnormal information, facilitating fault troubleshooting.

[0058] Figure 1 It is a schematic diagram of an application scenario provided by the present application. As Figure 1 shown, it includes a management platform and multiple intelligent optical distribution network equipment. It should be noted that Figure 1 only for illustration with 3 intelligent optical distribution network equipment included.

[0059] The above management platform is used to manage the intelligent optical distribution network equipment. This management platform can be fully deployed in any environment, for example, fully deployed in a cloud environment; it can also be a distributed deployment, for example, part of it can be deployed in an edge environment and part in a cloud environment. The present application does not make a limitation here, and it can be specifically set according to actual needs. The execution subject of the present application can be this management platform.

[0060] It should be noted that the above intelligent optical distribution network equipment can be any of the foregoing intelligent optical distribution network equipment, or other intelligent optical distribution network equipment. The present application does not make a limitation here.

[0061] In one example, various functional sensors can be set in the above intelligent optical distribution network equipment. Such functional sensors can be, for example, a temperature sensor for obtaining temperature data, a humidity sensor for obtaining humidity data, an illuminance sensor for obtaining illuminance data, etc. It should be noted that the present application does not make a limitation on the quantity and types of the above functional sensors.

[0062] The above-mentioned preset geographical area includes multiple sub-areas. The preset geographical area can be an administrative area, such as a county, a village, etc., or a community, etc. The present application does not make any limitations here.

[0063] The above-mentioned sub-areas are partial areas of the above-mentioned preset geographical area. At least one intelligent optical distribution network device is deployed within the scope of the sub-area, and the intelligent optical distribution network devices within the scope of two adjacent sub-areas cannot be the same intelligent optical distribution network device.

[0064] Regarding how to divide the sub-areas, exemplarily, it can be divided based on a bounded area with a preset distance threshold. For example, a circle with a radius of 1 kilometer is made, and the geographical area within the circle is used as a sub-area; it can also be divided based on the geographical environment. For example, the area located on the east side of the river is used as a sub-area; it can also be divided based on the distance between intelligent optical distribution network devices. For example, starting from an intelligent optical distribution network device, the geographical area where all intelligent optical distribution network devices within 1 kilometer of this intelligent optical distribution network device are located is used as a sub-area. The present application does not limit the size and division method of the sub-area range, and can be specifically set according to actual needs.

[0065] The technical solution of the present application and how the technical solution of the present application solves the above technical problems will be described in detail below with specific embodiments. The following several specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0066] Figure 2 It is a schematic flow chart of an inspection method for an intelligent optical distribution network device provided by the present application. The preset geographical area includes multiple sub-areas, and the sub-areas are partial areas of the preset geographical area; at least one intelligent optical distribution network device is deployed within the scope of the sub-area; as Figure 3 shown, the method includes:

[0067] S101. For each intelligent optical distribution network device within the scope of the sub-area, obtain M data sets of the intelligent optical distribution network device within a preset time period.

[0068] Exemplarily, multiple intelligent optical distribution network devices are deployed within the above-mentioned sub-area range. It should be noted that the present application does not limit the quantity and type of the above-mentioned intelligent optical distribution network devices.

[0069] Exemplarily, the above dataset includes N data of environmental parameters corresponding to the dataset within a preset time period. The above preset time period can be, for example, one week, one month, etc., which is not limited in this application and can be specifically set according to actual needs. The above environmental parameters are used to indicate the environmental conditions of the environment where the intelligent optical distribution network device is located. The above environmental parameters can be, for example, temperature, humidity, illuminance, etc., which is not limited in this application and can be specifically set according to actual needs. The above N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2.

[0070] For example, taking the above M = 3 as an example, the dataset can be a dataset corresponding to temperature, a dataset corresponding to humidity, and a dataset corresponding to illuminance; and, the dataset corresponding to temperature includes N temperature data within a preset time period; the dataset corresponding to humidity includes N humidity data within a preset time period; the dataset corresponding to illuminance includes N illuminance data within a preset time period.

[0071] In one example, the above intelligent optical distribution network device can regularly report the environmental parameter data of the intelligent optical distribution network device to the management platform for storage, and the management platform can obtain M datasets of the intelligent optical distribution network device within a preset time period from the memory. In another example, M datasets of the intelligent optical distribution network device can be imported from an external device; or, M datasets of the intelligent optical distribution network device can be obtained by communicating with other electronic devices.

[0072] S102. For each intelligent optical distribution network device within the sub-region range, determine the health status information of the intelligent optical distribution network device according to the M datasets of the intelligent optical distribution network device.

[0073] Exemplarily, the above health status information characterizes the hardware status of the intelligent optical distribution network device. It should be understood that the above environmental parameters can reflect the hardware status of the intelligent optical distribution network device. For example, temperature can reflect whether the working temperature of the intelligent optical distribution network device is overheated, humidity can reflect whether the intelligent optical distribution network device has water ingress; illuminance can reflect whether the box body of the intelligent optical distribution network device is closed. Therefore, according to the M datasets, the health status information of the intelligent optical distribution network device can be determined. The above health status information can be the health status level of the intelligent optical distribution network device, for example, excellent, good, poor, etc. It should be noted that the division method and the number of divisions of the health status level are not limited in this application and can be specifically set according to actual needs.

[0074] In one example, the above M data sets can be input into a preset prediction model to output the health status information of the intelligent optical distribution network device. In another example, the weight values of the environmental parameters corresponding to each data set can be determined first, and then based on the weight values, the health status information of the intelligent optical distribution network device can be determined.

[0075] S103. For each intelligent optical distribution network device within the sub-region range, generate and output the alarm information of the intelligent optical distribution network device according to the health status information of the intelligent optical distribution network device.

[0076] Exemplarily, the above alarm information indicates that the intelligent optical distribution network device is abnormal. Optionally, the above alarm information may include the identifier of the intelligent optical distribution network device, the cause of the abnormality, etc. Optionally, the above alarm information may also include the alarm handling method of the intelligent optical distribution network device to help the staff handle the alarm.

[0077] In one example, as described above, the health status information can represent the health status level. It can be determined whether the health status level represented by the health status information of the intelligent optical distribution network device is lower than the preset health status level. If it is lower, the alarm information of the intelligent optical distribution network device is generated.

[0078] S104. Perform inspections on each intelligent optical distribution network device within the sub-region range according to the alarm information.

[0079] In one example, if the number of alarm information in the above sub-region is higher than the preset threshold, it indicates that the failure rate of each intelligent optical distribution network device within the sub-region range is relatively high, and it is necessary to check the intelligent optical distribution network devices within the sub-region range. Then, inspections are performed on each intelligent optical distribution network device within the sub-region range. If the number of alarm information in the above sub-region range is lower than the preset threshold, only the intelligent optical distribution network device that generates the alarm information can be inspected for troubleshooting.

[0080] In this embodiment, by pre-dividing a preset geographical area into sub-areas, for each intelligent optical distribution network device within the scope of the sub-area, the health status information of the intelligent optical distribution network device can be determined by using environmental parameters, and the alarm information of the intelligent optical distribution network device can be generated by using the health status information. According to the alarm information of each intelligent optical distribution network device within the scope of the sub-area, the inspection of each intelligent optical distribution network device within the scope of the sub-area is carried out. In this way, it is not necessary to regularly inspect each intelligent optical distribution network device within the scope of the preset geographical area. Only the alarm information of each intelligent optical distribution network device within the scope of each sub-area needs to be monitored, and the intelligent optical distribution network devices within the scope of the sub-area are inspected according to the alarm information, reducing the cycle of each inspection, improving the inspection efficiency, and quickly positioning the corresponding intelligent optical distribution network device according to the alarm information for fault troubleshooting.

[0081] Figure 3 It is a schematic flow chart of a method for inspecting an intelligent optical distribution network device provided by this application. The preset geographical area includes multiple sub-areas, and the sub-area is a partial area of the preset geographical area; at least one intelligent optical distribution network device is deployed within the scope of the sub-area; as Figure 3 shown, the method includes:

[0082] S201. For each intelligent optical distribution network device within the scope of the sub-area, obtain M data sets of the intelligent optical distribution network device within a preset time period.

[0083] The above data set includes N data of environmental parameters corresponding to the data set within a preset time period, and the above environmental parameters are used to indicate the environmental conditions of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2. It should be noted that the description of this step can refer to the foregoing step S101 and will not be elaborated here.

[0084] S202. For each intelligent optical distribution network device within the scope of the sub-area, determine the characteristic parameters corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device.

[0085] Exemplarily, the above characteristic parameters are used to indicate the abnormal conditions of the intelligent optical distribution network device under the environmental parameters corresponding to the characteristic parameters. It should be understood that as mentioned above, the above data set corresponds to the environmental parameters one by one, and thus the characteristic parameters used to characterize the abnormal conditions under the environmental parameters corresponding to the data set can be determined according to the data set. The characteristic parameters can be, for example, the number of times exceeding the preset temperature threshold, the number of times exceeding the preset humidity threshold, etc. This application does not make a limit here, and can be specifically set according to actual needs. It should be noted that one data set can correspond to one characteristic parameter or multiple characteristic parameters.

[0086] In one example, based on the dataset of the intelligent optical distribution network device and the preset threshold corresponding to the dataset, the characteristic parameters corresponding to the dataset of the intelligent optical distribution network device can be determined.

[0087] Exemplarily, according to the differences in the environmental parameters corresponding to the dataset of the intelligent optical distribution network device, this step may include the following situations:

[0088] The first situation: Among the above M datasets, there is a dataset including illuminance parameters; this step may include the following steps:

[0089] S2021. For each intelligent optical distribution network device within the sub-region range, based on the dataset of the illuminance parameters of the intelligent optical distribution network device and the first preset threshold, determine the first characteristic parameter.

[0090] Exemplarily, the above first preset threshold is used to indicate the threshold of the illuminance parameter. The above first characteristic parameter is used to indicate whether the cabinet of the intelligent optical distribution network device is closed. If the data in the dataset of the illuminance parameter exceeds the first preset threshold, it can be regarded that the cabinet of the intelligent optical distribution network device is not closed.

[0091] In one example, it can be determined whether the illuminance data in the dataset of the illuminance parameters of the intelligent optical distribution network device exceeds the first preset threshold. If it is determined that it exceeds the first preset threshold, then determine that the first characteristic parameter is the first preset value; if it is determined that it does not exceed the first preset threshold, then determine that the first characteristic parameter is the second preset value. Exemplarily, the first preset value can be 1 or other preset values, which can be set according to actual needs. The second preset value can be 0 or other preset values, which can be set according to actual needs, but the first preset value is different from the second preset value.

[0092] S2022. For each intelligent optical distribution network device within the sub-region range, based on the dataset of the illuminance parameters of the intelligent optical distribution network device, the first preset threshold, and the second preset threshold, determine the second characteristic parameter.

[0093] Exemplarily, the above second preset threshold is used to indicate the number of times the illuminance parameter exceeds the first preset threshold. The second characteristic parameter is used to indicate whether the cabinet of the intelligent optical distribution network device is abnormally closed. If the number of times the illuminance parameter exceeds the first preset threshold exceeds the second preset threshold, it can be regarded that the cabinet of the intelligent optical distribution network device is abnormally closed.

[0094] In one example, the number of times the illuminance data in the dataset of the illuminance parameter of the intelligent optical distribution network device exceeds the first preset threshold can be determined. If it is determined that the number of times exceeds the second preset threshold, the second characteristic parameter is determined to be the third preset value; if it is determined that the number of times does not exceed the second preset threshold, the second characteristic parameter is determined to be the fourth preset value. Exemplarily, the third preset value can be 1 or other preset values, which can be set according to actual requirements. The fourth preset value can be 0 or other preset values, which can be set according to actual requirements, but the third preset value is different from the fourth preset value.

[0095] The second case: Among the above M datasets, there are datasets including humidity parameters; this step may include the following steps:

[0096] For each intelligent optical distribution network device within the sub-region range, according to the dataset of the humidity parameter of the intelligent optical distribution network device and the third preset threshold, the third characteristic parameter is determined.

[0097] Exemplarily, the above third preset threshold is used to indicate the threshold of the humidity parameter. The above third characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is flooded. If the humidity parameter exceeds the third preset threshold, it can be regarded as the box body of the intelligent optical distribution network device being flooded.

[0098] In one example, it can be determined whether the humidity data in the dataset of the humidity parameter of the intelligent optical distribution network device exceeds the third preset threshold. If it is determined that it exceeds the third preset threshold, the third characteristic parameter is determined to be the fifth preset value; if it is determined that it does not exceed the third preset threshold, the third characteristic parameter is determined to be the sixth preset value. Exemplarily, the fifth preset value can be 1 or other preset values, which can be set according to actual requirements. The sixth preset value can be 0 or other preset values, which can be set according to actual requirements, but the fifth preset value is different from the sixth preset value.

[0099] The third case: Among the above M datasets, there are datasets including temperature parameters; this step may include the following steps:

[0100] For each intelligent optical distribution network device within the sub-region range, according to the dataset of the temperature parameter of the intelligent optical distribution network device and the fourth preset threshold, the fourth characteristic parameter is determined.

[0101] Exemplarily, the above fourth preset threshold is used to indicate the threshold of the temperature parameter. The above fourth characteristic parameter is used to indicate whether the temperature of the box body of the intelligent optical distribution network device is normal. If the temperature parameter exceeds the fourth preset threshold, it can be regarded as the temperature of the box body of the intelligent optical distribution network device being abnormal.

[0102] In one example, it can be determined whether the temperature data in the dataset of the temperature parameter of the intelligent optical distribution network device exceeds the fourth preset threshold. If it is determined that the fourth preset threshold is exceeded, the fourth characteristic parameter is determined to be the seventh preset value; if it is determined that the fourth preset threshold is not exceeded, the fourth characteristic parameter is determined to be the eighth preset value. Exemplarily, the seventh preset value can be 1 or other preset values, which can be set according to actual needs. The eighth preset value can be 0 or other preset values, which can be set according to actual needs, but the seventh preset value is different from the eighth preset value.

[0103] S203. For each intelligent optical distribution network device within the sub-region range, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the dataset of the intelligent optical distribution network device.

[0104] In one example, the characteristic parameter corresponding to the dataset of the above intelligent optical distribution network device and a preset prediction model are used to determine the health status information of the intelligent optical distribution network device. The preset prediction model can be, for example, a convolutional neural network model or a recurrent neural network model, which is not limited in this application.

[0105] In another example, the weight of the characteristic parameter can be determined according to the characteristic parameter corresponding to the dataset, and then the health status information of the intelligent optical distribution network device can be obtained according to the weight of the characteristic parameter. Specifically, the following steps can be included:

[0106] S2031. For each intelligent optical distribution network device within the sub-region range, determine the weight of the characteristic parameter corresponding to the dataset of the intelligent optical distribution network device.

[0107] In one example, the weight of the characteristic parameter corresponding to the dataset of the intelligent optical distribution network device is preset; in another example, the weight of the characteristic parameter corresponding to the dataset of the intelligent optical distribution network device can be determined according to the principal component analysis method.

[0108] Specifically, for each intelligent optical distribution network device within the sub-region range, according to each dataset of the intelligent optical distribution network device, generate the data matrix information of the intelligent optical distribution network device. Then, use the principal component analysis method to process the data matrix information of the intelligent optical distribution network device to obtain the weight of the characteristic parameter corresponding to each dataset of the intelligent optical distribution network device. Among them, the above data matrix information includes the data of each environmental parameter.

[0109] For example, each column of data in the above data matrix information represents an environmental parameter, and an N*M-dimensional data matrix information can be obtained; then, the data in the above data matrix information are standardized to obtain the standardized data matrix information; furthermore, the covariance matrix information of the standardized data matrix information is calculated based on the standardized data matrix information, and the covariance matrix information is an M*M-dimensional matrix; furthermore, M eigenvalues of the covariance matrix and the eigenvectors corresponding to each eigenvalue can be determined; furthermore, according to a preset contribution rate threshold and M eigenvalues, the number P of principal components is determined, where P is an integer greater than or equal to 1; furthermore, according to P, the coefficient matrix of each principal component is determined, and the score coefficient of each principal component is obtained, and the score coefficients of each principal component are normalized to obtain the weight of the principal component. At the same time, the weight of the principal component is determined as the weight of the characteristic parameter of the environmental parameter corresponding to the principal component.

[0110] It should be noted that if the above characteristic parameters include the above first characteristic parameter and the second characteristic parameter, the first characteristic parameter and the second characteristic parameter commonly correspond to the same principal component. The ratio of the first characteristic parameter and the ratio of the second characteristic parameter can be preset to determine the weight of the first characteristic parameter and the weight of the second characteristic parameter according to their respective ratios and the weight of the principal component. For example, if the weight of the principal component corresponding to the illuminance parameter is 0.5, the weight of the first characteristic parameter can be 0.5a, and the weight of the second characteristic parameter is (1 - a)*0.5.

[0111] This step is beneficial to determining the weights of the characteristic parameters of the intelligent optical distribution network device for different intelligent optical distribution network devices, making the determined health status of the intelligent optical distribution network device more accurate.

[0112] S2032. For each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameters of the intelligent optical distribution network device corresponding to the data set and the weights of the characteristic parameters.

[0113] In one example, the health degree of the intelligent optical distribution network device can be calculated according to the characteristic parameters of the intelligent optical distribution network device corresponding to the data set and the weights of the characteristic parameters, and the health status information of the intelligent optical distribution network device is determined according to the health degree. The above health degree is used to describe the health degree of the intelligent optical distribution network device.

[0114] Specifically, a mapping relationship among the health degree, the characteristic parameters, and the weights of the characteristic parameters can be preset, and the health degree of the intelligent optical distribution network device can be calculated according to this mapping relationship. Meanwhile, a mapping relationship between the health degree and the health status information is preset, and the health status information of the intelligent optical distribution network device is determined according to the health degree of the intelligent optical distribution network device. For example, the mapping relationship between the health degree and the health status information can be as shown in Table 1. It should be noted that Table 1 is only for illustration, and the present application is not limited thereto.

[0115] Table 1

[0116] Health level Health status information [0.9,100] Excellent [60,90) Good (0,60) Poor

[0117] S204. For each intelligent optical distribution network device within the sub-region range, if it is determined that the level characterized by the health status information of the intelligent optical distribution network device is lower than the preset health status level, an alarm message of the intelligent optical distribution network device is generated and output.

[0118] Exemplarily, referring to Table 1, if the level characterized by the health status information of the above intelligent optical distribution network device is lower than the good level, an alarm message of the intelligent optical distribution network device is generated and output. It should be noted that the present application does not limit the specific implementation manner of generating the alarm message, and the prior art can be specifically referred to. In one example, the above alarm message can be output in the form of an audible and visual alarm or in the form of a text pop-up window, and the present application is not limited thereto.

[0119] S205. If it is determined that the number of alarm messages of the intelligent optical distribution network devices within the sub-region range exceeds the fifth preset threshold, an inspection work order corresponding to the sub-region range is generated to inspect each intelligent optical distribution network device within the sub-region range based on the inspection work order.

[0120] Exemplarily, the above inspection work order is used to instruct the operation and maintenance personnel to inspect each intelligent optical distribution network device within the sub-region range corresponding to the inspection work order. It should be noted that the present application does not limit the specific implementation manner of generating the inspection work order, and the prior art can be specifically referred to. Optionally, the above management platform can send the inspection work order to the electronic device of the operation and maintenance personnel to prompt the operation and maintenance personnel that an inspection is required; or, a message for generating the inspection work order can be sent to the electronic device of the operation and maintenance personnel to prompt the operation and maintenance personnel to log in to the client of the management platform to view the inspection work order.

[0121] In this embodiment, for each intelligent optical distribution network device within the sub-region range, based on the environmental parameters of the intelligent optical distribution network device, the characteristic parameters of the intelligent optical distribution network device are determined, and the weights of the characteristic parameters are determined. Based on the weights of the characteristic parameters, the health status information of the intelligent optical distribution network device is determined. Then, the alarm information of the intelligent optical distribution network device is determined, and whether to perform a patrol inspection on the intelligent optical distribution network devices within the sub-region range is determined according to the number of alarm information of the intelligent optical distribution network devices within the sub-region range. This method uses the weights of the characteristic parameters to determine the health status information of the intelligent optical distribution network device, making the determined alarm information more accurate. And based on the number of alarm information, it is determined whether to perform a patrol inspection on each intelligent optical distribution network device in the sub-region, which can reduce the patrol inspection period and improve the patrol inspection efficiency.

[0122] Figure 4 It is a schematic flowchart of a patrol inspection method for an intelligent optical distribution network device provided by this application. A preset geographical area includes multiple sub-regions, and a sub-region is a partial area of the preset geographical area; at least one intelligent optical distribution network device is deployed within the sub-region range; as Figure 4 shown, the method includes:

[0123] S301. For each intelligent optical distribution network device within the sub-region range, obtain M data sets of the intelligent optical distribution network device within a preset time period.

[0124] Exemplarily, the above data sets include N data of environmental parameters corresponding to the data sets within a preset time period, and the environmental parameters are used to indicate the environmental conditions of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2. It should be noted that the description of this step can refer to the foregoing step S101 and will not be elaborated here.

[0125] S302. For each intelligent optical distribution network device within the sub-region range, determine the health degree observation sequence of the intelligent optical distribution network device according to the M data sets of the intelligent optical distribution network device.

[0126] Exemplarily, there are multiple health degrees in the above health degree observation sequence, and the health degree is used to describe the health degree of the intelligent optical distribution network device.

[0127] In one example, the determination method of the health degree described in the foregoing step S2032 can be used to determine the historical health degree of the intelligent optical distribution network device, and the health degree observation sequence of the intelligent optical distribution network device is obtained.

[0128] S303. For each intelligent optical distribution network device within the sub-region range, determine the health status information of the intelligent optical distribution network device according to the health degree observation sequence of the intelligent optical distribution network device and a preset prediction model.

[0129] Exemplarily, the above prediction model may be the Viterbi algorithm based on the Hidden Markov Model. By using the health observation sequence, the future health status information of the intelligent optical distribution network device can be predicted. It should be noted that this application does not limit the specific implementation manner of how to predict the health status information based on the observation sequence and the preset prediction model, and reference can be made to the existing technology specifically.

[0130] S304. For each intelligent optical distribution network device within the sub-region range, generate and output the alarm information of the intelligent optical distribution network device according to the health status information of the intelligent optical distribution network device.

[0131] Exemplarily, the above alarm information indicates that the intelligent optical distribution network device is abnormal. If the health status level characterized by the health status information of the intelligent optical distribution network device is lower than the preset health status level, it indicates that the intelligent optical distribution network device may malfunction in the future. Then generate and output the alarm information of the intelligent optical distribution network device so that the operation and maintenance personnel can perform fault troubleshooting based on the alarm information and prevent faults in advance.

[0132] S305. Perform inspections on each intelligent optical distribution network device within the sub-region range according to the alarm information.

[0133] Exemplarily, if the number of alarm information within the above sub-region is higher than the preset value, it indicates that the future failure rate of each intelligent optical distribution network device within the sub-region is relatively high, and it is necessary to perform inspections on the intelligent optical distribution network devices within the sub-region range to prevent faults in advance and ensure communication connections.

[0134] In this embodiment, for each intelligent optical distribution network device within the sub-region range, the health observation sequence of the intelligent optical distribution network device is determined through the environmental parameters of the intelligent optical distribution network device. Then, based on the health observation sequence of the intelligent optical distribution network device, the future health status information of the intelligent optical distribution network device is predicted, and the alarm information of the intelligent optical distribution network device is determined according to the future health status information of the intelligent optical distribution network device. If the number of alarm information within the sub-region range exceeds the preset value, inspections are performed on the intelligent optical distribution network devices within the sub-region range. This method can predict the future health status information of the intelligent optical distribution network device, so that alarm information can be generated when the health status information of the intelligent optical distribution network device is poor, and fault inspections and troubleshooting of the intelligent optical distribution network device can be performed in advance to ensure communication connections.

[0135] Figure 5 This is a schematic structural diagram of an inspection device for an intelligent optical distribution network device provided by the present application. As Figure 5 shown, the device 40 includes:

[0136] An acquisition unit 41, configured to obtain, for each intelligent optical distribution network device within the range of the sub-region, M data sets of the intelligent optical distribution network device within a preset time period; wherein, each data set includes N data of environmental parameters corresponding to the data set within the preset time period, and the environmental parameters are used to indicate the environmental condition of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2;

[0137] A determination unit 42, configured to determine, for each intelligent optical distribution network device within the range of the sub-region, the health status information of the intelligent optical distribution network device according to the M data sets of the intelligent optical distribution network device, wherein the health status information characterizes the hardware status of the intelligent optical distribution network device;

[0138] A generation unit 43, configured to generate and output an alarm message of the intelligent optical distribution network device according to the health status information of the intelligent optical distribution network device for each intelligent optical distribution network device within the range of the sub-region, wherein the alarm message characterizes that the intelligent optical distribution network device has an abnormality;

[0139] An inspection unit 44, configured to inspect each intelligent optical distribution network device within the range of the sub-region according to the alarm message.

[0140] The inspection device for an intelligent optical distribution network device provided by the present application can execute the inspection method for an intelligent optical distribution network device in the above method embodiment, and its implementation principle and technical effect are similar, which will not be elaborated here.

[0141] Figure 6 It is a schematic structural diagram of an inspection device for an intelligent optical distribution network device provided by the present application. As Figure 6 shown, the device 50 includes:

[0142] An acquisition unit 51, configured to obtain, for each intelligent optical distribution network device within the range of the sub-region, M data sets of the intelligent optical distribution network device within a preset time period; wherein, each data set includes N data of environmental parameters corresponding to the data set within the preset time period, and the environmental parameters are used to indicate the environmental condition of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2;

[0143] A determination unit 52, configured to determine, for each intelligent optical distribution network device within the range of the sub-region, the health status information of the intelligent optical distribution network device according to the M data sets of the intelligent optical distribution network device, wherein the health status information characterizes the hardware status of the intelligent optical distribution network device;

[0144] A generating unit 53, configured to generate and output an alarm message for each intelligent optical distribution network device within the range of the sub-region according to the health status information of the intelligent optical distribution network device, where the alarm message indicates that the intelligent optical distribution network device has an abnormality;

[0145] An inspection unit 54, configured to inspect each intelligent optical distribution network device within the range of the sub-region according to the alarm message.

[0146] In one example, the determining unit 52 is specifically configured to, for each intelligent optical distribution network device within the range of the sub-region, determine a health degree observation sequence of the intelligent optical distribution network device according to M data sets of the intelligent optical distribution network device; where multiple health degrees in the health degree observation sequence are used to describe the health degree of the intelligent optical distribution network device; for each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the health degree observation sequence of the intelligent optical distribution network device and a preset prediction model.

[0147] In one example, the determining unit 52 includes:

[0148] A first determining module 521, configured to, for each intelligent optical distribution network device within the range of the sub-region, determine a feature parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device; where the feature parameter is used to indicate an abnormality of the intelligent optical distribution network device under the environmental parameter corresponding to the feature parameter;

[0149] A second determining module 522, configured to, for each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the feature parameter corresponding to the data set of the intelligent optical distribution network device.

[0150] In one example, the data set in the M data sets includes a data set of illuminance parameters; the first determining module 521 is specifically configured to, for each intelligent optical distribution network device within the range of the sub-region, determine a first feature parameter according to the data set of the illuminance parameters of the intelligent optical distribution network device and a first preset threshold; where the first preset threshold is used to indicate the threshold of the illuminance parameter; the first feature parameter is used to indicate whether the box body of the intelligent optical distribution network device is closed; for each intelligent optical distribution network device within the range of the sub-region, determine a second feature parameter according to the data set of the illuminance parameters of the intelligent optical distribution network device, the first preset threshold, and a second preset threshold; where the second preset threshold is used to indicate the number of times that the illuminance parameter exceeds the first preset threshold; the second feature parameter is used to indicate whether the box body of the intelligent optical distribution network device is abnormally closed.

[0151] In one example, the M data sets include the data set of humidity parameters; the first determination module 521 is specifically configured to, for each intelligent optical distribution network device within the range of the sub-region, determine a third characteristic parameter according to the data set of the humidity parameters of the intelligent optical distribution network device and a third preset threshold; wherein, the third preset threshold is used to indicate the threshold of the humidity parameter; the third characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is flooded with water.

[0152] In one example, the M data sets include the data set of temperature parameters; the first determination module 521 is specifically configured to, for each intelligent optical distribution network device within the range of the sub-region, determine a fourth characteristic parameter according to the data set of the temperature parameters of the intelligent optical distribution network device and a fourth preset threshold; wherein, the fourth preset threshold is used to indicate the threshold of the temperature parameter; the fourth characteristic parameter is used to indicate whether the temperature of the box body of the intelligent optical distribution network device is normal.

[0153] In one example, the second determination module 522 includes:

[0154] The first determination sub-module 5221 is configured to, for each intelligent optical distribution network device within the range of the sub-region, determine the weight of the characteristic parameter corresponding to the data set of the intelligent optical distribution network device.

[0155] The second determination sub-module 5222 is configured to, for each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the data set of the intelligent optical distribution network device and the weight of the characteristic parameter.

[0156] In one example, the first determination sub-module 5221 is specifically configured to, for each intelligent optical distribution network device within the range of the sub-region, generate the data matrix information of the intelligent optical distribution network device according to the data sets of the intelligent optical distribution network device; wherein, the data matrix information includes the data of each environmental parameter; for each intelligent optical distribution network device within the range of the sub-region, the principal component analysis method is used to process the data matrix information of the intelligent optical distribution network device to obtain the weight of the characteristic parameter corresponding to each data set of the intelligent optical distribution network device.

[0157] In one example, the generating unit 53 is specifically configured to, for each intelligent optical distribution network device within the range of the sub-region, if it is determined that the level characterized by the health status information of the intelligent optical distribution network device is lower than the preset health status level, generate and output the alarm information of the intelligent optical distribution network device.

[0158] In one example, the above-mentioned inspection unit 54 is specifically configured to generate an inspection work order corresponding to the sub-region range if it is determined that the number of alarm messages of the intelligent optical distribution network devices within the sub-region range exceeds the fifth preset threshold, so as to inspect each intelligent optical distribution network device within the sub-region range based on the inspection work order.

[0159] The inspection device for intelligent optical distribution network devices provided by this application can execute the inspection method for intelligent optical distribution network devices in the above method embodiments. The implementation principles and technical effects are similar and will not be elaborated here.

[0160] Figure 7 It is a schematic structural diagram of an electronic device provided by this application. As Figure 7 shown, the electronic device 600 may include: at least one processor 601 and a memory 602. The electronic device may be a device with processing capabilities such as a terminal, a server, a computer device, etc.

[0161] The memory 602 is used to store programs. Specifically, the program may include program code, and the program code includes computer operation instructions.

[0162] The memory 602 may contain a high-speed RAM memory and may also include non-volatile memory, such as at least one disk memory.

[0163] The processor 601 is used to execute the computer execution instructions stored in the memory 602 to implement the inspection method for intelligent optical distribution network devices described in the foregoing method embodiments. Among them, the processor 601 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or a specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0164] The electronic device 600 may further include a communication interface 603, and through the communication interface 603, it can communicate and interact with external devices. External devices may be, for example, mobile phones, tablets, etc.

[0165] In specific implementation, if the communication interface 603, the memory 602, and the processor 601 are implemented independently, the communication interface 603, the memory 602, and the processor 601 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0166] Optionally, in specific implementation, if the communication interface 603, the memory 602, and the processor 601 are integrated on a chip, the communication interface 603, the memory 602, and the processor 601 can communicate through an internal interface.

[0167] This application also provides a computer-readable storage medium, which may include: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc. Specifically, program instructions are stored in the computer-readable storage medium, and the program instructions are used for the method in the foregoing embodiments.

[0168] This application also provides a program product, which includes execution instructions stored in a readable storage medium. At least one processor of the electronic device 600 can read the execution instructions from the readable storage medium, and the at least one processor executes the execution instructions to enable the electronic device 600 to implement the inspection method of the intelligent optical distribution network device provided by the foregoing various embodiments.

[0169] This application also provides a chip, on which a computer program is stored. When the computer program is executed by the chip, the inspection method of the intelligent optical distribution network device provided by various embodiments is implemented.

[0170] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0171] It should be further noted that although the steps in the flowchart are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least some of the sub-steps or stages of other steps or other steps.

[0172] It should be understood that the above-described device embodiments are merely illustrative, and the devices of the present application can also be implemented in other ways. For example, the division of units / modules in the above embodiments is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0173] In addition, unless otherwise specified, in each embodiment of the present application, each functional unit / module can be integrated in one unit / module, or each unit / module can exist physically alone, or two or more units / modules can be integrated together. The above integrated unit / module can be implemented in the form of hardware or in the form of a software program module.

[0174] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as falling within the scope described in this specification.

[0175] Those skilled in the art will readily think of other implementation schemes of the present application after considering the specification and practicing the invention disclosed herein. The present application aims to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include the common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and embodiments are only regarded as exemplary, and the true scope and spirit of the present application are pointed out by the following claims.

[0176] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A patrol inspection method for an intelligent optical distribution network device, characterized in that, A preset geographical area includes multiple sub - areas; at least one intelligent optical distribution network device is deployed within the scope of each sub - area; the method includes: For each intelligent optical distribution network device within the scope of the sub - area, obtain M data sets of this intelligent optical distribution network device within a preset time period; wherein, each data set includes N data of environmental parameters corresponding to the data set within the preset time period, and the environmental parameters are used to indicate the environmental condition of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2; For each intelligent optical distribution network device within the scope of the sub - area, determine the health status information of this intelligent optical distribution network device according to the M data sets of this intelligent optical distribution network device; wherein, the health status information characterizes the hardware status of the intelligent optical distribution network device; For each intelligent optical distribution network device within the scope of the sub - area, generate and output the alarm information of this intelligent optical distribution network device according to the health status information of this intelligent optical distribution network device; wherein, the alarm information characterizes that the intelligent optical distribution network device has an abnormality; According to the alarm information, conduct inspections on each intelligent optical distribution network device within the scope of the sub - area.

2. The method according to claim 1, characterized in that, For each intelligent optical distribution network device within the scope of the sub - area, determining the health status information of this intelligent optical distribution network device according to the M data sets of this intelligent optical distribution network device includes: For each intelligent optical distribution network device within the scope of the sub - area, determine the health degree observation sequence of this intelligent optical distribution network device according to the M data sets of this intelligent optical distribution network device; wherein, there are multiple health degrees in the health degree observation sequence, and the health degree is used to describe the health degree of the intelligent optical distribution network device; For each intelligent optical distribution network device within the scope of the sub - area, determine the health status information of this intelligent optical distribution network device according to the health degree observation sequence of this intelligent optical distribution network device and a preset prediction model.

3. The method according to claim 1, characterized in that For each intelligent optical distribution network device within the scope of the sub - area, determining the health status information of this intelligent optical distribution network device according to the M data sets of this intelligent optical distribution network device includes: For each intelligent optical distribution network device within the scope of the sub - area, determine the characteristic parameters corresponding to the data set of this intelligent optical distribution network device according to the data set of this intelligent optical distribution network device; wherein, the characteristic parameters are used to indicate the abnormal conditions of the intelligent optical distribution network device under the environmental parameters corresponding to the characteristic parameters; For each intelligent optical distribution network device within the scope of the sub - area, determine the health status information of this intelligent optical distribution network device according to the characteristic parameters corresponding to the data set of this intelligent optical distribution network device.

4. The method according to claim 3, characterized in that, The M data sets include a data set of illuminance parameters; for each intelligent optical distribution network device within the scope of the sub - area, determining the characteristic parameters corresponding to the data set of this intelligent optical distribution network device according to the data set of this intelligent optical distribution network device includes: For each intelligent optical distribution network device within the range of the sub-region, determine a first characteristic parameter according to the data set of the illuminance parameter of the intelligent optical distribution network device and a first preset threshold; wherein, the first preset threshold is used to indicate the threshold of the illuminance parameter; the first characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is closed. For each intelligent optical distribution network device within the range of the sub-region, determine a second characteristic parameter according to the data set of the illuminance parameter of the intelligent optical distribution network device, the first preset threshold, and a second preset threshold; wherein, the second preset threshold is used to indicate the number of times the illuminance parameter exceeds the first preset threshold; the second characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is abnormally closed.

5. The method according to claim 3, wherein The M data sets include the data set of the humidity parameter; for each intelligent optical distribution network device within the range of the sub-region, determine the characteristic parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device, including: For each intelligent optical distribution network device within the range of the sub-region, determine a third characteristic parameter according to the data set of the humidity parameter of the intelligent optical distribution network device and a third preset threshold; wherein, the third preset threshold is used to indicate the threshold of the humidity parameter; the third characteristic parameter is used to indicate whether the box body of the intelligent optical distribution network device is water-injected.

6. The method according to claim 3, characterized in that, The M data sets include the data set of the temperature parameter; for each intelligent optical distribution network device within the range of the sub-region, determine the characteristic parameter corresponding to the data set of the intelligent optical distribution network device according to the data set of the intelligent optical distribution network device, including: For each intelligent optical distribution network device within the range of the sub-region, determine a fourth characteristic parameter according to the data set of the temperature parameter of the intelligent optical distribution network device and a fourth preset threshold; wherein, the fourth preset threshold is used to indicate the threshold of the temperature parameter; the fourth characteristic parameter is used to indicate whether the temperature of the box body of the intelligent optical distribution network device is normal.

7. The method according to claim 3, wherein For each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the data set of the intelligent optical distribution network device, including: For each intelligent optical distribution network device within the range of the sub-region, determine the weight of the characteristic parameter corresponding to the data set of the intelligent optical distribution network device. For each intelligent optical distribution network device within the range of the sub-region, determine the health status information of the intelligent optical distribution network device according to the characteristic parameter corresponding to the data set of the intelligent optical distribution network device and the weight of the characteristic parameter.

8. The method according to claim 7, wherein For each intelligent optical distribution network device within the range of the sub-region, determine the weight of the characteristic parameter corresponding to the data set of the intelligent optical distribution network device, including: For each intelligent optical distribution network device within the range of the sub-region, generate the data matrix information of the intelligent optical distribution network device according to the data sets of the intelligent optical distribution network device; wherein, the data matrix information includes the data of each environmental parameter. For each intelligent optical distribution network device within the scope of the sub-region, use the principal component analysis method to process the data matrix information of the intelligent optical distribution network device, and obtain the weights of the characteristic parameters corresponding to each data set of the intelligent optical distribution network device.

9. The method according to any one of claims 1-8, characterized in that, For each intelligent optical distribution network device within the scope of the sub-region, generate and output the alarm information of the intelligent optical distribution network device according to the health status information of the intelligent optical distribution network device, including: For each intelligent optical distribution network device within the scope of the sub-region, if it is determined that the level characterized by the health status information of the intelligent optical distribution network device is lower than the preset health status level, generate and output the alarm information of the intelligent optical distribution network device.

10. The method according to any one of claims 1-8, characterized in that, According to the alarm information, perform inspections on each intelligent optical distribution network device within the scope of the sub-region, including: If it is determined that the number of alarm information of the intelligent optical distribution network devices within the scope of the sub-region exceeds the fifth preset threshold, generate an inspection work order corresponding to the sub-region scope, and perform inspections on each intelligent optical distribution network device within the scope of the sub-region based on the inspection work order.

11. An inspection device for an intelligent optical distribution network device, characterized in that, A preset geographical area includes multiple sub-regions; at least one intelligent optical distribution network device is deployed within the scope of the sub-region; including: An acquisition unit, configured to, for each intelligent optical distribution network device within the scope of the sub-region, acquire M data sets of the intelligent optical distribution network device within a preset time period; wherein, the data set includes N data of environmental parameters corresponding to the data set within the preset time period, and the environmental parameters are used to indicate the environmental conditions of the environment where the intelligent optical distribution network device is located; N is a positive integer greater than or equal to 1; M is a positive integer greater than or equal to 2; A determination unit, configured to, for each intelligent optical distribution network device within the scope of the sub-region, determine the health status information of the intelligent optical distribution network device according to the M data sets of the intelligent optical distribution network device, wherein the health status information characterizes the hardware status of the intelligent optical distribution network device; A generation unit, configured to, for each intelligent optical distribution network device within the scope of the sub-region, generate and output the alarm information of the intelligent optical distribution network device according to the health status information of the intelligent optical distribution network device, wherein the alarm information characterizes that the intelligent optical distribution network device has an abnormality; An inspection unit, configured to perform inspections on each intelligent optical distribution network device within the scope of the sub-region according to the alarm information.

12. An electronic device, characterized in that, Including: A processor, and a memory communicatively connected to the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method according to any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, Computer execution instructions are stored in the computer-readable storage medium, and when the computer execution instructions are executed by the processor, they are used to implement the method according to any one of claims 1 to 10.

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