Electric power pipe gallery risk early warning processing method, computer equipment, readable storage medium and program product

Abstract

The invention relates to an electric power pipe gallery risk early warning processing method, computer equipment, a readable storage medium and a program product, and is applied to the technical field of big data, and the method comprises the steps: obtaining target pipe gallery data of a target electric power pipe gallery, and multiple pieces of normal pipe gallery data of the target electric power pipe gallery under a normal operation condition, the pipe gallery data is used for representing at least one of the environment condition of the electric power pipe gallery and the operation state of the electric power pipe gallery; according to matching conditions between the target pipe gallery data and the plurality of normal pipe gallery data, potential risks of the target electric power pipe gallery are identified, and a pipe gallery risk identification result is obtained; and carrying out risk early warning processing on the target electric power pipe gallery according to the pipe gallery risk identification result. By adopting the method, the accuracy of electric power pipe gallery risk early warning processing can be improved.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and particularly to a method for processing risk early warning of a power pipe gallery, a computer device, a computer-readable storage medium, and a computer program product. Background Art

[0002] A power pipe gallery is a tunnel or pipeline specifically used to accommodate cables and other power infrastructure, mainly for power transmission and distribution. These pipe galleries are usually located underground in cities and sometimes may also be set in other areas, such as industrial facilities. The main purpose of the power pipe gallery is to protect the cables from the external environment and at the same time facilitate the maintenance and management of the power system. Burying the power transmission cables in the power pipe gallery can not only improve the urban image and realize the rational utilization of land resources but also ensure the stable transmission of the power system. To ensure the normal operation of the power system, there is an urgent need for a way to conduct risk early warning for the power pipe gallery.

[0003] Currently, manual inspection is relied on to conduct risk early warning for the power pipe gallery. However, this method has a large workload and low efficiency. In addition, with the construction of power lines, the distribution of power pipe galleries is becoming wider and wider, and the involved landforms are becoming more and more complex and changeable. It is difficult for inspection personnel to reach the distribution areas of the power pipe galleries, resulting in the inability to detect potential risks in some distribution areas by the manual inspection method, and further leading to a low accuracy in the processing of risk early warning for the power pipe gallery. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium, and computer program product for processing risk early warning of a power pipe gallery that can improve the accuracy of risk early warning processing for the power pipe gallery.

[0005] In a first aspect, the present application provides a method for processing risk early warning of a power pipe gallery, including:

[0006] Obtain target pipe gallery data of a target power pipe gallery and a plurality of normal pipe gallery data corresponding to the target power pipe gallery under normal operating conditions, where the pipe gallery data is used to represent at least one of the environmental conditions and the operating state of the power pipe gallery;

[0007] Identify potential risks of the target power pipe gallery according to the matching status between the target pipe gallery data and the plurality of normal pipe gallery data respectively, and obtain a pipe gallery risk identification result;

[0008] Perform risk early warning processing on the target power pipe gallery according to the pipe gallery risk identification result.

[0009] In a second aspect, the present application further provides a device for processing risk early warning of a power pipe gallery, including:

[0010] An acquisition module, configured to acquire target corridor data of a target power corridor, and a plurality of normal corridor data corresponding to the target power corridor under normal operating conditions, wherein the corridor data is used to characterize at least one of the environmental conditions and the operating state of the power corridor;

[0011] An identification module, configured to identify potential risks of the target power corridor according to the matching conditions between the target corridor data and the plurality of normal corridor data, and obtain a corridor risk identification result;

[0012] A processing module, configured to perform risk early warning processing on the target power corridor according to the corridor risk identification result.

[0013] In a third aspect, the present application further provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0014] Acquire target corridor data of a target power corridor, and a plurality of normal corridor data corresponding to the target power corridor under normal operating conditions, wherein the corridor data is used to characterize at least one of the environmental conditions and the operating state of the power corridor;

[0015] Identify potential risks of the target power corridor according to the matching conditions between the target corridor data and the plurality of normal corridor data, and obtain a corridor risk identification result;

[0016] Perform risk early warning processing on the target power corridor according to the corridor risk identification result.

[0017] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0018] Acquire target corridor data of a target power corridor, and a plurality of normal corridor data corresponding to the target power corridor under normal operating conditions, wherein the corridor data is used to characterize at least one of the environmental conditions and the operating state of the power corridor;

[0019] Identify potential risks of the target power corridor according to the matching conditions between the target corridor data and the plurality of normal corridor data, and obtain a corridor risk identification result;

[0020] Perform risk early warning processing on the target power corridor according to the corridor risk identification result.

[0021] In a fifth aspect, the present application further provides a computer program product, including a computer program, which when executed by a processor, implements the following steps:

[0022] Obtain the target duct data of the target power duct, and a plurality of normal duct data corresponding to the target power duct under normal operating conditions, where the duct data is used to characterize at least one of the environmental conditions and operating status of the power duct;

[0023] Identify the potential risks of the target power duct according to the matching status between the target duct data and the plurality of normal duct data respectively, and obtain a duct risk identification result;

[0024] Perform risk early warning processing on the target power duct according to the duct risk identification result.

[0025] For the above power duct risk early warning processing method, device, computer device, computer-readable storage medium and computer program product, by obtaining the target duct data of the target power duct, and a plurality of normal duct data corresponding to the target power duct under normal operating conditions, where the duct data is used to characterize at least one of the environmental conditions and operating status of the power duct; identify the potential risks of the target power duct according to the matching status between the target duct data and the plurality of normal duct data respectively, and obtain a duct risk identification result; perform risk early warning processing on the target power duct according to the duct risk identification result. In this way, through the target duct data, the impact of the environmental conditions of the target power duct on the operation of the target power duct and the impact of the operating status of the target power duct on the operation of the target power duct can be accurately determined, and a plurality of normal duct data corresponding to the target power duct under normal operating conditions are used as the matching basis for the target duct data, so that the potential risks of the target power duct can be identified, a duct risk identification result can be obtained, and then based on the duct risk identification result, risk early warning processing is performed. Therefore, the accuracy of power duct risk early warning processing is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following will briefly introduce the drawings required for use in the description of the embodiments of the present application or related technologies. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0027] Figure 1 It is an application environment diagram of the power duct risk early warning processing method in an embodiment;

[0028] Figure 2 It is a schematic flowchart of a method for risk early warning and processing of a power pipe gallery in an embodiment;

[0029] Figure 3 It is a schematic flowchart of a step of identifying potential risks of the target power pipe gallery according to the matching status between the target pipe gallery data and the multiple normal pipe gallery data respectively in an embodiment, and obtaining a pipe gallery risk identification result;

[0030] Figure 4 It is a schematic flowchart of a step of performing risk early warning and processing on the target power pipe gallery according to the pipe gallery risk identification result in an embodiment;

[0031] Figure 5 It is a structural block diagram of a power pipe gallery risk early warning and processing device in an embodiment;

[0032] Figure 6 It is an internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0033] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0034] It should be noted that the information and data involved in the present application (including but not limited to data for analysis, stored data, displayed data, etc.) are all information and data authorized by users or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data all comply with the relevant regulations of national laws and regulations. For the content pushed to users (such as target pipe gallery data, pipe gallery risk identification results, results after performing risk early warning and processing on the target power pipe gallery, etc.), users can refuse or can conveniently refuse content push, etc. In the embodiments of the present application, some industry-existing solutions such as certain software, components, models, etc. may be mentioned, and they should be regarded as exemplary. The purpose is only to illustrate the feasibility in the implementation of the technical solutions of the present application, but it does not mean that the applicant has already or necessarily used this solution.

[0035] The power pipe gallery risk early warning and processing method provided by the embodiments of the present application can be applied to, for example Figure 1In the application environment shown. Among them, the data acquisition component 102, the target power pipe gallery 104, and the terminal 106 communicate with the server 108 respectively. The data acquisition component 102 is deployed in the target power pipe gallery 104, and the data acquisition component 102 is used to collect the target pipe gallery data of the target power pipe gallery 104. The data storage system can store the data that the server 108 needs to process. The data storage system can be integrated on the server 108, or can be placed on the cloud or other network servers. The server 108 obtains the target pipe gallery data of the target power pipe gallery 104 collected by the data acquisition component 102, and obtains a plurality of normal pipe gallery data corresponding to the target power pipe gallery 104 under normal operating conditions, where the pipe gallery data is used to characterize at least one of the environmental conditions and the operating state of the power pipe gallery; according to the matching status between the target pipe gallery data and the plurality of normal pipe gallery data respectively, identify the potential risks of the target power pipe gallery 104 to obtain a pipe gallery risk identification result; according to the pipe gallery risk identification result, perform a risk warning process on the target power pipe gallery 104. The server 108 can push at least one of the target pipe gallery data, the pipe gallery risk identification result, and the result after performing the risk warning process on the target power pipe gallery to the terminal 106. Among them, the terminal 106 can be but is not limited to various personal computers, laptop computers, smart phones, tablet computers, Internet of Things devices, and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. The portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The head-mounted devices can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server 108 can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0036] The power pipe gallery risk early warning processing method provided by the embodiments of this application can also be applied to the following application environments. Among them: The data acquisition component 102 and the terminal 106 are respectively in communication with the target power pipe gallery 104. The data acquisition component 102 is deployed in the target power pipe gallery 104, and the data acquisition component 102 is used to collect the target pipe gallery data of the target power pipe gallery 104. The target power pipe gallery 104 obtains the target pipe gallery data of the target power pipe gallery 104 collected by the data acquisition component 102, and obtains a plurality of normal pipe gallery data corresponding to the target power pipe gallery 104 under normal operating conditions. Among them, the pipe gallery data is used to characterize at least one of the environmental conditions and the operating state of the power pipe gallery; according to the matching status between the target pipe gallery data and the plurality of normal pipe gallery data; according to the matching status between the target pipe gallery data and the plurality of normal pipe gallery data, identify the potential risks of the target power pipe gallery 104 to obtain a pipe gallery risk identification result; according to the pipe gallery risk identification result, perform risk early warning processing on the target power pipe gallery 104. The target power pipe gallery 104 can push at least one of the target pipe gallery data, the pipe gallery risk identification result, and the result after performing risk early warning processing on the target power pipe gallery to the terminal 106.

[0037] In an exemplary embodiment, as Figure 2 shown, a power pipe gallery risk early warning processing method is provided. Taking the application of this method to Figure 1 the server 108 in as an example and described in an abbreviated form of the main body, it includes the following steps 202 to step 206. Among them:

[0038] Step 202, obtain the target pipe gallery data of the target power pipe gallery, and a plurality of normal pipe gallery data corresponding to the target power pipe gallery under normal operating conditions. Among them, the pipe gallery data is used to characterize at least one of the environmental conditions and the operating state of the power pipe gallery.

[0039] Among them, the target pipe gallery data in step 202 includes at least one of target environmental data, target pipe gallery operation data, and target pipe gallery structure data. The environmental data involved throughout the text (including the above-mentioned target environmental data and normal environmental data) includes at least one of environmental temperature data, environmental humidity data, environmental water level data, and gas concentration data. The pipe gallery operation data involved throughout the text (including the above-mentioned target pipe gallery operation data and normal pipe gallery operation data) includes at least one of pipe gallery cable current data, pipe gallery voltage data, and pipe gallery cable temperature. The target pipe gallery structure data includes at least one of pipe gallery structure, vent data, pipe gallery cable data, pipe gallery location data, pipe gallery interface data, and pipe gallery support location data. The pipe gallery cable data includes at least one of pipe gallery cable length, pipe gallery cable routing, and pipe gallery cable bending radius.

[0040] As an embodiment, obtaining target corridor data of a target power corridor includes: obtaining target corridor data of the target power corridor collected by a data collection component.

[0041] Among them, the data collection component includes at least one of a sensor and a camera component. The sensor includes at least one of a temperature sensor, a humidity sensor, a water level sensor, and a gas concentration sensor. The temperature sensor is used to collect at least one of the ambient temperature data of the target power corridor and the temperature of the corridor cable in the target power corridor. The camera component is used to collect the corridor image of the target power corridor, and the corridor image is used to represent the target corridor structure data.

[0042] Among them, the data collection component communicates with the target power corridor, and the data collection component receives at least one of the corridor cable current data and the corridor voltage data sent by the target power corridor.

[0043] In this way, for the power corridor with complex and changeable landforms involved, and the distribution area of the power corridor that is difficult for general inspection personnel to reach, the corridor data collection of the power corridor can also be realized by deploying the data collection component.

[0044] As an embodiment, obtaining multiple normal corridor data corresponding to the target power corridor under normal operating conditions includes: obtaining the historical corridor data of the target power corridor, and screening the historical target corridor data corresponding to the target power corridor when it is under normal operating conditions from the historical corridor data; determining the historical target corridor data as the multiple normal corridor data corresponding to the target power corridor under normal operating conditions.

[0045] As another embodiment, obtaining multiple normal corridor data corresponding to the target power corridor under normal operating conditions includes: obtaining the similar corridor data of the power corridor of the same type as the target power corridor, and screening the similar target corridor data corresponding to the power corridor of the same type when it is under normal operating conditions from the similar corridor data; determining the similar target corridor data as the multiple normal corridor data corresponding to the target power corridor under normal operating conditions. Specifically, in the case that the power corridor and the target power corridor belong to the same corridor architecture, it is determined that the power corridor and the target power corridor belong to the same type, where the corridor architecture includes at least one of the corridor structure and the corridor size.

[0046] In this way, the data richness of the corridor data set for matching can be guaranteed, so that various scenarios can be included, and further, the potential risks of the power corridor can be recognized in a timely manner under various rich scenarios.

[0047] Step 204, identify the potential risks of the target power corridor according to the matching status between the target corridor data and multiple normal corridor data, and obtain the corridor risk identification result.

[0048] Exemplarily, step 204 includes: identifying potential risks of the target power pipe gallery based on the matching status between the target pipe gallery data and multiple normal pipe gallery data in the environmental dimension and the operation dimension, to obtain a pipe gallery risk identification result.

[0049] Step 206, perform a risk early warning process on the target power pipe gallery according to the pipe gallery risk identification result.

[0050] Exemplarily, step 206 includes: if the pipe gallery risk identification result indicates that there are risks in the target power pipe gallery, then evaluate the potential risks of the target power pipe gallery according to the pipe gallery risk identification result to obtain an evaluation result; perform a risk early warning process on the target power pipe gallery according to the evaluation result; if the pipe gallery risk identification result indicates that there are no risks in the target power pipe gallery, then return to execute the step of collecting the target pipe gallery data of the target power pipe gallery.

[0051] In this way, when the pipe gallery risk identification result indicates that there are no risks in the target power pipe gallery, the collection of the target pipe gallery data of the target power pipe gallery can be continuously performed, so as to ensure that the potential risks of the target power pipe gallery can be predicted in time; when the pipe gallery risk identification result indicates that there are risks in the target power pipe gallery, corresponding early warning processing can be performed in time, so as to avoid risks such as damage to the target power pipe gallery when not processed.

[0052] Optionally, the method further includes: determining at least one of the target pipe gallery data and the pipe gallery risk identification result as the display data corresponding to the target power pipe gallery; determining the status importance information respectively corresponding to the display data that characterizes the status of the target power pipe gallery, and determining the acquisition time information corresponding to the display data; evaluating the priority of the display data according to the status importance information and the acquisition time information respectively corresponding to the display data, to obtain the display priority of the display data; displaying the display data according to the display priority of the display data.

[0053] Among them, the higher the importance characterized by the status importance information corresponding to the display data, the higher the priority of the display data; the later the acquisition time characterized by the acquisition time information corresponding to the display data, the higher the priority of the display data; the higher the display priority of the display data, the better the display effect of the display data. Specifically, the longer the display time and the more prominent the display position, the better the display effect.

[0054] As an embodiment, determining the status importance information corresponding to the display data for characterizing the status of the target power pipe gallery includes: for each display data, if the display data includes target pipe gallery data, determining the degree of influence of the target pipe gallery data on the operation of the target power pipe gallery as the status importance information corresponding to the display data for characterizing the status of the target power pipe gallery. Among them, the greater the degree of influence on the operation of the target power pipe gallery, the higher the importance represented by the status importance information corresponding to the display data for characterizing the status of the target power pipe gallery; if the display data includes the pipe gallery risk identification result, determining the risk severity level represented by the pipe gallery risk identification result as the status importance information corresponding to the display data for characterizing the status of the target power pipe gallery. Among them, the higher the risk severity level represented by the pipe gallery risk identification result, the higher the importance represented by the status importance information corresponding to the display data for characterizing the status of the target power pipe gallery.

[0055] As an embodiment, evaluating the priority corresponding to the display data based on the status importance information and the acquisition time information corresponding to the display data respectively to obtain the display priority of the display data includes: for each display data, performing weighted processing on the status importance information corresponding to the display data according to the first preset weight corresponding to the status importance information to obtain status importance weighted information; and performing weighted processing on the acquisition time information corresponding to the display data according to the second preset weight corresponding to the acquisition time information to obtain acquisition time weighted information; fusing the status importance weighted information and the acquisition time weighted information to obtain the priority corresponding to the display data, where the first preset weight and the second preset weight can be set by the user as needed, and the information fusion methods include addition and multiplication, which are not limited here.

[0056] Optionally, the method further includes: constructing a digital twin model of the target power pipe gallery according to the target pipe gallery data; performing risk marking on the digital twin model according to the pipe gallery risk identification result to obtain a pipe gallery risk identification model, and visually displaying the pipe gallery risk identification model.

[0057] As an embodiment, constructing a digital twin model of the target power pipe gallery according to the target pipe gallery data includes: simulating the environment where the target power pipe gallery is located according to the target environment data to obtain an environment simulation model; simulating the operation state of the target power pipe gallery according to the target pipe gallery operation data and the target pipe gallery structure data to obtain a pipe gallery simulation model; combining the environment simulation model and the pipe gallery simulation model to obtain a digital twin model.

[0058] As an embodiment, according to the risk identification result of the utility tunnel, the digital twin model is marked with risks to obtain the utility tunnel risk identification model, including: if the risk identification result of the utility tunnel indicates that there is a risk in the target power utility tunnel, then according to the risk identification result of the utility tunnel, the potential risks of the target power utility tunnel are located to obtain risk location information, and the position corresponding to the risk location information in the digital twin model is marked to obtain the utility tunnel risk identification model.

[0059] Optionally, the utility tunnel risk identification model can be updated as the target tunnel data and the utility tunnel risk identification result are updated.

[0060] In this way, it is ensured that the utility tunnel risk identification model can represent the real-time condition of the target power utility tunnel.

[0061] Optionally, after collecting the target tunnel data of the target power utility tunnel, the method further includes: performing data processing on the target tunnel data, where the data processing methods include at least one of data cleaning method, data deduplication method, and data integration method.

[0062] Optionally, the method can also be applied to the power utility tunnel platform, which includes a data acquisition layer, a data processing layer, a digital twin layer, and a logic processing layer. The target tunnel data of the target power utility tunnel is collected through the data acquisition layer; the target tunnel data is processed through the data processing layer; the target power utility tunnel is subjected to risk warning processing according to the utility tunnel risk identification result through the logic processing layer; the digital twin model of the target power utility tunnel is constructed according to the target tunnel data through the digital twin layer; according to the utility tunnel risk identification result, the digital twin model is marked with risks to obtain the utility tunnel risk identification model, and the utility tunnel risk identification model is visually displayed.

[0063] Optionally, the method further includes: displaying the utility tunnel risk identification model according to the data importance degree in the utility tunnel risk identification model, where the higher the data importance degree, the better the corresponding data display effect.

[0064] In this way, it is ensured that the user can timely view the relatively important data.

[0065] In the above power pipe gallery risk early warning processing method, by obtaining the target pipe gallery data of the target power pipe gallery and multiple normal pipe gallery data corresponding to the target power pipe gallery under normal operating conditions, where the pipe gallery data is used to characterize at least one of the environmental conditions and the operating state of the power pipe gallery; according to the matching conditions between the target pipe gallery data and the multiple normal pipe gallery data respectively, identify the potential risks of the target power pipe gallery to obtain a pipe gallery risk identification result; according to the pipe gallery risk identification result, perform risk early warning processing on the target power pipe gallery. In this way, through the target pipe gallery data, the impact of the environmental conditions of the target power pipe gallery on the operation of the target power pipe gallery and the impact of the operating state of the target power pipe gallery on the operation of the target power pipe gallery can be accurately determined, so that the potential risks of the target power pipe gallery can be identified to obtain a pipe gallery risk identification result, and then based on the pipe gallery risk identification result, risk early warning processing is performed. Therefore, the accuracy of the power pipe gallery risk early warning processing is improved.

[0066] In an exemplary embodiment, as Figure 3 shown, a method for accurately identifying the potential risks of the target power pipe gallery is provided. According to the matching conditions between the target pipe gallery data and the multiple normal pipe gallery data respectively, identifying the potential risks of the target power pipe gallery to obtain a pipe gallery risk identification result includes steps 302 to 304. Among them:

[0067] Step 302, if there is no matching environmental data in the multiple normal environmental data that matches the target environmental data, then according to the matching conditions between the target pipe gallery operation data and the normal pipe gallery operation data of the multiple normal pipe gallery operation data, identify the potential risks of the target power pipe gallery to obtain a pipe gallery risk identification result.

[0068] Optionally, the method further includes: for each environmental dimension in each normal environmental data (where the environmental dimensions include at least one of the temperature dimension, humidity dimension, water level dimension, and gas concentration dimension), fuse the data under this environmental dimension in the multiple groups of normal environmental data to obtain the environmental data range corresponding to this environmental dimension. If the data under this environmental dimension in the target environmental data is not within the environmental data range, it is determined that there is no matching environmental data in the multiple normal environmental data that matches the target environmental data of this environmental dimension. If the data under this environmental dimension in the target environmental data is within the environmental data range, there is matching environmental data in the multiple normal environmental data that matches the target environmental data of this environmental dimension.

[0069] Further, as an embodiment, fusing the data of this environmental dimension in multiple normal environmental data to obtain the environmental data range corresponding to this environmental dimension, including: determining the maximum data of this environmental dimension in multiple groups of normal environmental data as the maximum value of the environmental data range corresponding to this environmental dimension, and determining the minimum data of this environmental dimension in multiple groups of normal environmental data as the minimum value of the environmental data range corresponding to this environmental dimension; determining the environmental data range corresponding to this environmental dimension according to the maximum value and the minimum value of the environmental data range corresponding to this environmental dimension.

[0070] As another embodiment, the method further includes: determining a first range correction value corresponding to this environmental dimension, and according to the first range correction value, correcting the maximum data of this environmental dimension in multiple normal environmental data to obtain the maximum value of the environmental data range corresponding to this environmental dimension; according to the first range correction value, correcting the minimum data of this environmental dimension in multiple normal environmental data to obtain the minimum value of the environmental data range corresponding to this environmental dimension.

[0071] In this way, considering that there are different data difference tolerance degrees for different environmental dimensions, therefore, based on the first range correction value corresponding to the environmental dimension, the maximum data and the minimum data of this environmental dimension in multiple normal environmental data are corrected respectively to avoid misjudgment of the matching of the environmental data of this environmental dimension.

[0072] Among them, the higher the degree of influence of the environmental dimension on the operation of the target power pipe gallery, the smaller the determined first range correction value.

[0073] In this way, it is ensured that for the environmental dimension with a higher degree of influence on the operation of the target power pipe gallery, the difference between the target environmental data corresponding to this environmental dimension and the normal environmental data is smaller, thereby avoiding misjudgment of the matching of the environmental data of this environmental dimension.

[0074] As an embodiment, the method further includes: if each environmental dimension in the target environmental data corresponds and matches multiple normal environmental data, determining that there is matching environmental data in multiple normal environmental data that matches the target environmental data, and determining the data in multiple normal environmental data that is closest to the target environmental data as the matching environmental data; if each environmental dimension in the target environmental data does not all correspond and match multiple normal environmental data, determining that there is no matching environmental data in multiple normal environmental data that matches the target environmental data. Specifically, for the case of multiple environmental dimensions, according to the difference degree corresponding to each environmental dimension in each normal environmental data, determining the data in multiple normal environmental data that is closest to the target environmental data, where the lower the difference degree between the normal environmental data and the target environmental data, the closer the normal environmental data is to the target environmental data, and the difference degree can be a difference value.

[0075] It can be understood that there may be a need to adopt a specific operation mode for the target power pipe gallery in a certain special environment. If the general operation mode is still adopted for the target power pipe gallery in the special environment, it may occur that the operation of the power pipe gallery is improper (not matching the special environment), resulting in the situation that there are risks in the operation of the target power pipe gallery.

[0076] As an embodiment, according to the matching status between the target pipe gallery operation data and the normal pipe gallery operation data of multiple normal pipe galleries, the potential risks of the target power pipe gallery are identified to obtain the pipe gallery risk identification result, including: if there is matching pipe gallery operation data in the multiple normal pipe gallery operation data that matches the target pipe gallery operation data, the environmental anomaly risk is determined as the pipe gallery risk identification result; if there is no matching pipe gallery operation data in the multiple normal pipe gallery operation data that matches the target pipe gallery operation data, the pipe gallery operation anomaly risk and the environmental anomaly risk are jointly determined as the pipe gallery risk identification result.

[0077] Optionally, the method further includes: for each operation dimension in the normal pipe gallery operation data (where the operation dimensions include at least one of the cable current dimension, voltage dimension, and cable temperature dimension), the data of this operation dimension in the multiple normal pipe gallery operation data are fused to obtain the operation data range corresponding to this operation dimension. If the data of this operation dimension in the target pipe gallery operation data is not within the operation data range, it is determined that there is no matching pipe gallery operation data in the multiple normal pipe gallery operation data that matches the target pipe gallery operation data of this operation dimension. If the data of this operation dimension in the target environment data is within the operation data range, it is determined that there is matching pipe gallery operation data in the multiple normal pipe gallery operation data that matches the target pipe gallery operation data of this operation dimension.

[0078] Further, as an embodiment, fusing the data of this operation dimension in the multiple normal pipe gallery operation data to obtain the operation data range corresponding to this operation dimension includes: determining the maximum data of this operation dimension in the multiple normal pipe gallery operation data as the maximum value of the operation data range corresponding to this operation dimension, and determining the minimum data of this operation dimension in the multiple normal pipe gallery operation data as the minimum value of the operation data range corresponding to this environment dimension; according to the maximum value and the minimum value of the operation data range corresponding to this operation dimension, determining the operation data range corresponding to this operation dimension.

[0079] As another embodiment, the method further includes: determining a second range correction value corresponding to the operation dimension; correcting the maximum data in the operation dimension among the multiple normal utility tunnel operation data according to the second range correction value to obtain the maximum value of the operation data range corresponding to the operation dimension; and correcting the minimum data in the operation dimension among the multiple normal utility tunnel operation data according to the second range correction value to obtain the minimum value of the operation data range corresponding to the operation dimension.

[0080] In this way, considering that there are different degrees of tolerance for data differences in different operation dimensions, the maximum data and the minimum data in the operation dimension among the multiple normal utility tunnel operation data are respectively corrected based on the second range correction value corresponding to the operation dimension, so as to avoid misjudgment in the matching of the operation data of this operation dimension.

[0081] Among them, the higher the degree of influence of the operation dimension on the operation of the target power utility tunnel, the smaller the determined second range correction value.

[0082] In this way, it is ensured that for the operation dimension with a higher degree of influence on the operation of the target power utility tunnel, the difference between the target operation data corresponding to this operation dimension and the normal operation data is smaller, thereby avoiding misjudgment in the matching of the operation data of this operation dimension.

[0083] As an embodiment, the method further includes: if each operation dimension in the target utility tunnel operation data corresponds and matches with the multiple normal utility tunnel operation data, determining that there is matching utility tunnel operation data in the multiple normal utility tunnel operation data that matches the target utility tunnel operation data, and determining the data in the multiple normal utility tunnel operation data that is closest to the target utility tunnel operation data as the matching utility tunnel operation data; if each operation dimension in the target utility tunnel operation data does not all correspond and match with the multiple normal utility tunnel operation data, determining that there is no matching utility tunnel operation data in the multiple normal utility tunnel operation data that matches the target utility tunnel operation data. Specifically, for the case of multiple operation dimensions, according to the difference degree corresponding to each operation dimension in each normal utility tunnel operation data, determining the data in multiple groups of normal utility tunnel operation data that is closest to the target utility tunnel operation data, where the lower the difference degree between the normal utility tunnel operation data and the target utility tunnel operation data, the closer the normal utility tunnel operation data is to the target utility tunnel operation data, and the difference degree can be the difference value.

[0084] Step 304, if there is matching environment data in the multiple normal environment data that matches the target environment data, when the target utility tunnel operation data does not match the normal utility tunnel operation data corresponding to the matching environment data, determining the utility tunnel operation abnormal risk as the utility tunnel risk identification result.

[0085] In this embodiment, by matching the target power pipe gallery with the pipe gallery dataset under normal operating conditions, and separately matching it with the two dimensions of environment and pipe gallery operation, considering two situations: some environments will affect the normal operation of the target power pipe gallery, and in some environments, special operating methods are required to ensure the normal operation of the target power pipe gallery, so as to ensure that the potential risks of the target power pipe gallery can be accurately identified.

[0086] In an exemplary embodiment, as Figure 4 shown, a method for accurately performing risk early warning processing on a target power pipe gallery is provided. According to the pipe gallery risk identification result, performing risk early warning processing on the target power pipe gallery includes steps 402 to 406. Among them:

[0087] Step 402, if the pipe gallery risk identification result indicates that there is a risk in the target power pipe gallery, then according to the pipe gallery risk identification result, identify the risk type of the potential risk of the target power pipe gallery to obtain the pipe gallery risk type, and evaluate the severity of the risk characterized by the pipe gallery risk identification result to obtain the risk assessment result.

[0088] Optionally, the method further includes: when the pipe gallery risk identification result includes the risk of abnormal pipe gallery operation or the risk of abnormal environment, determining that the pipe gallery risk identification result indicates that there is a risk in the target power pipe gallery; when the pipe gallery risk identification result does not include the risk of abnormal pipe gallery operation or the risk of abnormal environment, determining that the pipe gallery risk identification result indicates that there is no risk in the target power pipe gallery.

[0089] Exemplarily, according to the pipe gallery risk identification result, identifying the risk type of the potential risk of the target power pipe gallery to obtain the pipe gallery risk type includes at least one of the following: if the environmental dimension corresponding to multiple sets of normal environmental data in the target environmental data does not match includes the humidity dimension, then determine that the pipe gallery risk type includes the humidity risk type; if the environmental dimension corresponding to multiple sets of normal environmental data in the target environmental data does not match includes the temperature dimension, then determine that the pipe gallery risk type includes the temperature risk type; if the environmental dimension corresponding to multiple sets of normal environmental data in the target environmental data does not match includes the gas concentration dimension and the corresponding gas type includes the combustible gas type, then determine that the pipe gallery risk type includes the high concentration risk type of combustible gas; if the environmental dimension corresponding to multiple sets of normal environmental data in the target environmental data does not match includes the gas concentration dimension and the corresponding gas type includes the oxygen type, then determine that the pipe gallery risk type includes the low concentration risk type of combustible oxygen; if the environmental dimension corresponding to multiple sets of normal environmental data in the target environmental data does not match includes the water level dimension, then determine that the pipe gallery risk type includes the water level risk type.

[0090] Exemplarily, based on the risk identification result of the utility tunnel, the risk types of the potential risks of the target power utility tunnel are identified to obtain the utility tunnel risk types, including at least one of the following: If the operation dimensions corresponding to multiple groups of normal utility tunnel operation data in the target tunnel operation data include the cable current dimension or the cable temperature dimension, it is determined that the utility tunnel risk type includes the utility tunnel cable overload risk type; if the operation dimensions corresponding to multiple groups of normal utility tunnel operation data in the target tunnel operation data include the voltage dimension, it is determined that the utility tunnel risk type includes the utility tunnel cable voltage fluctuation risk type.

[0091] Exemplarily, the risk severity characterized by the utility tunnel risk identification result is evaluated to obtain the risk assessment result, including: determining the damage degree expected by the utility tunnel risk identification result to the target power utility tunnel, and evaluating the risk severity characterized by the utility tunnel risk identification result according to the damage degree expected by the utility tunnel risk identification result to the target power utility tunnel to obtain the risk assessment result, wherein the higher the damage degree expected by the utility tunnel risk identification result to the target power utility tunnel, the higher the risk severity characterized by the utility tunnel risk identification result.

[0092] Step 404, in the case where the risk assessment result characterizes the first type of severity, if the utility tunnel risk type belongs to the utility tunnel environmental risk type, the environmental intervention system corresponding to the target power utility tunnel is controlled according to the utility tunnel risk type, and if the utility tunnel risk type belongs to the utility tunnel operation risk type, the target power utility tunnel is controlled according to the utility tunnel risk type.

[0093] As an embodiment, the environmental intervention system includes an exhaust system, a temperature control system, a humidity control system, and a drainage system; controlling the environmental intervention system corresponding to the target power utility tunnel according to the utility tunnel risk type includes at least one of the following: If the utility tunnel risk type includes the high concentration of combustible gas risk type or the low oxygen concentration risk, the exhaust system corresponding to the target power utility tunnel is controlled; if the utility tunnel risk type includes the temperature risk type, the temperature control system corresponding to the target power utility tunnel is controlled; if the utility tunnel risk type includes the humidity risk type, the humidity control system corresponding to the target power utility tunnel is controlled; if the utility tunnel risk type includes the high water level risk type, the drainage system corresponding to the target power utility tunnel is controlled.

[0094] As an embodiment, the method further includes: If the utility tunnel risk type includes the high concentration of combustible gas risk type, controlling the exhaust system corresponding to the target power utility tunnel to exhaust; if the utility tunnel risk type includes the low oxygen concentration risk, controlling the exhaust system corresponding to the target power utility tunnel to ventilate.

[0095] As an embodiment, according to the risk types of the pipe gallery, the target power pipe gallery is controlled, including at least one of the following: If the risk type of the pipe gallery includes the risk type of voltage fluctuation of the pipe gallery cable, the abnormal waveform of the target power pipe gallery is located according to the target pipe gallery data to obtain abnormal waveform information, and the target power pipe gallery is controlled according to the abnormal waveform information; If the risk type of the pipe gallery includes the risk type of cable overload of the pipe gallery, a load reduction control is performed on the target power pipe gallery.

[0096] Step 406, when the risk assessment result represents the second level of severity, generate a pipe gallery risk warning information according to the risk type of the pipe gallery, and display the pipe gallery risk warning information.

[0097] In this embodiment, when the risk identification result of the pipe gallery indicates that there is a risk in the target power pipe gallery, the risk type and risk severity of the target power pipe gallery are evaluated. Then, when the potential risk of the target power pipe gallery is relatively serious, based on the risk type of the pipe gallery, a pipe gallery risk warning information is generated and the pipe gallery risk warning information is displayed, so as to enable relatively fast manual intervention; When the potential risk of the target power pipe gallery is not so serious, an automatic warning process is performed on the target power pipe gallery according to the risk type of the pipe gallery, so as to achieve relatively fast risk avoidance. Therefore, the efficiency of power pipe gallery risk handling is improved.

[0098] As a detailed embodiment, obtain the target pipe gallery data of the target power pipe gallery, and multiple normal pipe gallery data corresponding to the target power pipe gallery under normal operating conditions, where the pipe gallery data is used to represent at least one of the environmental conditions of the power pipe gallery and the operating state of the power pipe gallery; Obtain the pipe gallery data set corresponding to the target power pipe gallery under normal operating conditions, where the pipe gallery data set includes multiple groups of normal pipe gallery data, and each group of normal pipe gallery data includes normal environmental data and normal pipe gallery operating data collected during normal operation of the pipe gallery; If there is no matching environmental data in the multiple groups of normal pipe gallery data that matches the target environmental data, then if there is matching pipe gallery operating data in the multiple groups of normal pipe gallery data that matches the target pipe gallery operating data, determine the environmental anomaly risk as the pipe gallery risk identification result; If there is no matching pipe gallery operating data in the multiple groups of normal pipe gallery data that matches the target pipe gallery operating data, jointly determine the pipe gallery operating anomaly risk and the environmental anomaly risk as the pipe gallery risk identification result; If there is matching environmental data in the multiple groups of normal pipe gallery data that matches the target environmental data, when the target pipe gallery operating data does not match the normal pipe gallery operating data corresponding to the matching environmental data, determine the pipe gallery operating anomaly risk as the pipe gallery risk identification result.

[0099] Further, if the risk identification result of the utility tunnel indicates that there is a risk in the target power utility tunnel, then according to the risk identification result of the utility tunnel, identify the risk type of the potential risk of the target power utility tunnel to obtain the utility tunnel risk type, and evaluate the severity of the risk characterized by the risk identification result of the utility tunnel to obtain the risk assessment result; in the case where the risk assessment result indicates the first level of severity, if the utility tunnel risk type belongs to the utility tunnel environmental risk type, then if the utility tunnel risk type includes the combustible gas high concentration risk type or the oxygen low concentration risk type, control the exhaust system corresponding to the target power utility tunnel; if the utility tunnel risk type includes the temperature risk type, control the temperature regulation system corresponding to the target power utility tunnel; if the utility tunnel risk type includes the humidity risk type, control the humidity regulation system corresponding to the target power utility tunnel; if the utility tunnel risk type includes the high water level risk type, control the drainage system corresponding to the target power utility tunnel; if the utility tunnel risk type belongs to the utility tunnel operation risk type, then if the utility tunnel risk type includes the utility tunnel cable voltage fluctuation risk type, locate the abnormal waveform of the target power utility tunnel according to the target tunnel data to obtain the abnormal waveform information, and control the target power utility tunnel according to the abnormal waveform information; if the utility tunnel risk type includes the utility tunnel cable overload risk type, perform a load reduction control on the target power utility tunnel; in the case where the risk assessment result indicates the second level of severity, generate a utility tunnel risk warning information according to the utility tunnel risk type, and display the utility tunnel risk warning information.

[0100] In this way, by obtaining the target tunnel data of the target power utility tunnel and multiple normal tunnel data corresponding to the target power utility tunnel under normal operating conditions, where the tunnel data is used to characterize at least one of the environmental conditions and the operating state of the power utility tunnel; according to the matching status between the target tunnel data and the multiple normal tunnel data respectively, identify the potential risks of the target power utility tunnel to obtain the tunnel risk identification result; perform risk warning processing on the target power utility tunnel according to the tunnel risk identification result. In this way, through the target tunnel data, the impact of the environmental conditions of the target power utility tunnel on the operation of the target power utility tunnel and the impact of the operating state of the target power utility tunnel on the operation of the target power utility tunnel can be accurately determined, so that the potential risks of the target power utility tunnel can be identified to obtain the tunnel risk identification result, and then based on the tunnel risk identification result, risk warning processing is carried out. Therefore, the accuracy of the risk warning processing of the power utility tunnel is improved.

[0101] Further, by matching the target power pipe gallery with the pipe gallery data set under normal operating conditions and separately matching it with the two dimensions of the environment and pipe gallery operation, considering the two situations that certain environments will affect the normal operation of the target power pipe gallery and that special operating methods are required to ensure the normal operation of the target power pipe gallery in certain environments, so as to ensure that the potential risks of the target power pipe gallery can be accurately identified; and, when the pipe gallery risk identification result indicates that there are risks in the target power pipe gallery, evaluating the risk type and risk severity of the target power pipe gallery, and then, when the potential risks of the target power pipe gallery are relatively serious, generating a pipe gallery risk warning message based on the pipe gallery risk type and displaying the pipe gallery risk warning message, so as to enable faster manual intervention; when the potential risks of the target power pipe gallery are not so serious, performing automatic warning processing on the target power pipe gallery according to the pipe gallery risk type, so as to achieve faster risk avoidance. Therefore, the efficiency of power pipe gallery risk handling is improved.

[0102] It should be understood that although the steps in the flowcharts involved in the above embodiments are shown in sequence according to the arrows, these steps do not necessarily have to be executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages. These steps or stages do not necessarily have to be executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential either, but can be executed alternately or in turn with at least some of the steps or stages in other steps or other steps.

[0103] Based on the same inventive concept, an embodiment of the present application also provides a power pipe gallery risk warning processing device for implementing the power pipe gallery risk warning processing method involved above. The solution provided by this device to solve the problem is similar to the solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of the power pipe gallery risk warning processing device provided below can refer to the limitations on the power pipe gallery risk warning processing method in the above text, and will not be repeated here.

[0104] In an exemplary embodiment, as Figure 5 shown, a power pipe gallery risk warning processing device 500 is provided, including: an acquisition module 502, an identification module 504, and a processing module 506, where:

[0105] An acquisition module 502, configured to acquire target duct data of a target power duct corridor, as well as a plurality of normal duct data corresponding to the target power duct corridor under normal operating conditions, where the duct data is used to characterize at least one of the environmental conditions and the operating state of the power duct corridor;

[0106] An identification module 504, configured to identify potential risks of the target power duct corridor according to the matching conditions between the target duct data and the plurality of normal duct data, and obtain a duct risk identification result;

[0107] A processing module 506, configured to perform risk warning processing on the target power duct corridor according to the duct risk identification result.

[0108] In one embodiment, the target duct data includes target environmental data and target duct operation data, and the normal duct data includes normal environmental data and normal duct operation data; the identification module 504 is further configured to, if there is no matching environmental data that matches the target environmental data among the plurality of normal environmental data, identify potential risks of the target power duct corridor according to the matching conditions between the target duct operation data and the normal duct operation data among the plurality of normal duct operation data, and obtain a duct risk identification result; if there is matching environmental data that matches the target environmental data among the plurality of normal environmental data, when the target duct operation data does not match the normal duct operation data corresponding to the matching environmental data, determine the duct operation anomaly risk as the duct risk identification result.

[0109] In one embodiment, the identification module 504 is further configured to, if there is matching duct operation data that matches the target duct operation data among the plurality of normal duct operation data, determine the environmental anomaly risk as the duct risk identification result; if there is no matching duct operation data that matches the target duct operation data among the plurality of normal duct operation data, jointly determine the duct operation anomaly risk and the environmental anomaly risk as the duct risk identification result.

[0110] In one embodiment, the processing module 506 is further configured to, if the risk identification result of the utility tunnel indicates that there is a risk in the target power utility tunnel, identify the risk type of the potential risk of the target power utility tunnel according to the risk identification result of the utility tunnel to obtain the utility tunnel risk type, and evaluate the severity of the risk indicated by the risk identification result of the utility tunnel to obtain the risk assessment result; in the case where the risk assessment result indicates the first level of severity, if the utility tunnel risk type belongs to the utility tunnel environmental risk type, control the environmental intervention system corresponding to the target power utility tunnel according to the utility tunnel risk type, and if the utility tunnel risk type belongs to the utility tunnel operation risk type, control the target power utility tunnel according to the utility tunnel risk type; in the case where the risk assessment result indicates the second level of severity, generate a utility tunnel risk warning message according to the utility tunnel risk type and display the utility tunnel risk warning message.

[0111] In one embodiment, the environmental intervention system includes an exhaust system, a temperature control system, a humidity control system, and a drainage system; the processing module 506 is further configured to perform at least one of the following: if the utility tunnel risk type includes a high concentration of combustible gas risk type or a low concentration of oxygen risk type, control the exhaust system corresponding to the target power utility tunnel; if the utility tunnel risk type includes a temperature risk type, control the temperature control system corresponding to the target power utility tunnel; if the utility tunnel risk type includes a humidity risk type, control the humidity control system corresponding to the target power utility tunnel; if the utility tunnel risk type includes a high water level risk type, control the drainage system corresponding to the target power utility tunnel.

[0112] In one embodiment, the processing module 506 is further configured to perform at least one of the following: if the utility tunnel risk type includes a utility tunnel cable voltage fluctuation risk type, locate the abnormal waveform of the target power utility tunnel according to the target tunnel data to obtain the abnormal waveform information, and control the target power utility tunnel according to the abnormal waveform information; if the utility tunnel risk type includes a utility tunnel cable overload risk type, perform a load reduction control on the target power utility tunnel.

[0113] In one embodiment, the device further includes: a display module, configured to determine at least one of the target tunnel data and the risk identification result of the utility tunnel as the display data corresponding to the target power utility tunnel; determine the status importance information respectively corresponding to the display data and representing the status of the target power utility tunnel, and determine the acquisition time information corresponding to the display data; evaluate the priority of the display data according to the status importance information and the acquisition time information respectively corresponding to the display data to obtain the display priority of the display data; and display the display data according to the display priority of the display data.

[0114] Each module in the above-mentioned power pipe gallery risk early warning processing device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor of a computer device in hardware form or be independent of it, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0115] In an exemplary embodiment, a computer device is provided. This computer device can be a terminal, and its internal structure diagram can be as Figure 6 shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of this computer device is used to provide computing and control capabilities. The memory of this computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of this computer device is used to exchange information between the processor and external devices. The communication interface of this computer device is used to communicate with external terminals in a wired or wireless manner. The wireless manner can be achieved through WIFI, a mobile cellular network, near field communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a power pipe gallery risk early warning processing method. The display unit of this computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of this computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0116] Those skilled in the art can understand that Figure 6 the structure shown in

[0117] is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have a different component layout.

[0118] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0119] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0120] Those of ordinary skill in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above method embodiments. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, artificial intelligence (AI) processors, etc., without limitation.

[0121] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise 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 the scope recorded in this application.

[0122] The above embodiments only express several implementation manners of this application, and their descriptions are relatively specific and detailed, but they should not be construed as a limitation on the patent scope of this application. It should be noted that for those of ordinary skill in the art, without departing from the concept of this application, several deformations and improvements can still be made, and these all belong to the protection scope of this application. Therefore, the protection scope of this application should be subject to the appended claims.

Claims

1. A method for risk early warning and handling of a power pipe gallery, characterized in that, The method includes: Obtaining target duct data of a target power duct gallery, and a plurality of normal duct data corresponding to the target power duct gallery under normal operating conditions, where the duct data is used to characterize at least one of the environmental conditions and the operating state of the power duct gallery; Identifying potential risks of the target power duct gallery based on the matching conditions between the target duct data and the plurality of normal duct data respectively, to obtain a duct risk identification result; Performing risk early warning processing on the target power duct gallery according to the duct risk identification result.

2. The method according to claim 1, characterized in that, The target duct data includes target environmental data and target duct operating data, and the normal duct data includes normal environmental data and normal duct operating data; The identifying potential risks of the target power duct gallery based on the matching conditions between the target duct data and the plurality of normal duct data respectively, to obtain a duct risk identification result, includes: If there is no matching environmental data that matches the target environmental data among the plurality of normal environmental data, then identifying potential risks of the target power duct gallery based on the matching conditions between the target duct operating data and the normal duct operating data of the plurality of normal duct operating data, to obtain a duct risk identification result; If there is matching environmental data that matches the target environmental data among the plurality of normal environmental data, then when the target duct operating data does not match the normal duct operating data corresponding to the matching environmental data, determining the duct operating anomaly risk as the duct risk identification result.

3. The method according to claim 2, characterized in that, The identifying potential risks of the target power duct gallery based on the matching conditions between the target duct operating data and the normal duct operating data of the plurality of normal duct operating data, to obtain a duct risk identification result, includes: If there is matching duct operating data that matches the target duct operating data among the plurality of normal duct operating data, then determining the environmental anomaly risk as the duct risk identification result; If there is no matching duct operating data that matches the target duct operating data among the plurality of normal duct operating data, then jointly determining the duct operating anomaly risk and the environmental anomaly risk as the duct risk identification result.

4. The method according to claim 1, wherein The performing risk early warning processing on the target power duct gallery according to the duct risk identification result, includes: If the duct risk identification result indicates that the target power duct gallery has risks, then based on the duct risk identification result, identifying the risk type of the potential risks of the target power duct gallery, to obtain a duct risk type, and evaluating the severity of the risks indicated by the duct risk identification result, to obtain a risk assessment result; In the case where the risk assessment result indicates the first severity level, if the duct risk type belongs to the duct environmental risk type, then controlling the environmental intervention system corresponding to the target power duct gallery according to the duct risk type, and if the duct risk type belongs to the duct operating risk type, then controlling the target power duct gallery according to the duct risk type; When the risk assessment result characterizes the second level of severity, generate a risk warning message for the utility tunnel according to the type of utility tunnel risk, and display the risk warning message for the utility tunnel.

5. The method according to claim 4, characterized in that, The environmental intervention system includes an exhaust system, a temperature control system, a humidity control system, and a drainage system; the control of the environmental intervention system corresponding to the target power utility tunnel according to the type of utility tunnel risk includes at least one of the following: If the type of utility tunnel risk includes a high concentration of combustible gas risk type or a low concentration of oxygen risk type, control the exhaust system corresponding to the target power utility tunnel; If the type of utility tunnel risk includes a temperature risk type, control the temperature control system corresponding to the target power utility tunnel; If the type of utility tunnel risk includes a humidity risk type, control the humidity control system corresponding to the target power utility tunnel; If the type of utility tunnel risk includes a high water level risk type, control the drainage system corresponding to the target power utility tunnel.

6. The method according to claim 4, wherein The control of the target power utility tunnel according to the type of utility tunnel risk includes at least one of the following: If the type of utility tunnel risk includes a risk type of voltage fluctuation of utility tunnel cables, locate the abnormal waveform of the target power utility tunnel according to the target tunnel data to obtain abnormal waveform information, and control the target power utility tunnel according to the abnormal waveform information; If the type of utility tunnel risk includes a risk type of overload of utility tunnel cables, perform a load reduction control on the target power utility tunnel.

7. The method according to any one of claims 1 to 6, characterized in that The method further includes: Determine at least one of the target tunnel data and the tunnel risk identification result as the display data corresponding to the target power utility tunnel; Determine the status importance information respectively corresponding to the display data to characterize the status of the target power utility tunnel, and determine the acquisition time information corresponding to the display data; Evaluate the priority of the display data according to the status importance information and the acquisition time information respectively corresponding to the display data to obtain the display priority of the display data; Display the display data according to the display priority of the display data.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 7.

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