Operation and maintenance management method and device of intelligent switch cabinet, storage medium and electronic equipment

Abstract

The invention relates to an operation and maintenance management method and device of an intelligent switch cabinet, a storage medium and electronic equipment, and relates to the technical field of switch cabinets, and the method comprises the steps: obtaining the geographic position information of the intelligent switch cabinet; determining a suitable monitoring frequency corresponding to the environmental data of at least one dimension according to the geographical location information; according to each suitable monitoring frequency, obtaining at least one piece of environmental data of the corresponding dimension of the intelligent switch cabinet, and comparing each piece of environmental data with a corresponding environmental data threshold; and if the environment data exceeding the corresponding environment data threshold exists, determining the corresponding environment data as abnormal environment data, and adjusting the operation state of the intelligent switch cabinet based on the abnormal environment data so as to enable the intelligent switch cabinet to operate normally. The intelligent switch cabinet can be regulated and controlled in time.

Description

Technical Field

[0001] The present application relates to the technical field of switch cabinets, and in particular to an operation and maintenance management method, device, storage medium and electronic equipment of an intelligent switch cabinet. Background Art

[0002] Intelligent switchgear refers to power distribution equipment with high performance, high reliability, certain self-diagnosis and automatic control performance, and network communication capabilities. It combines modern electrical control technology and digital signal processing technology, and can realize multiple functions such as control, protection, measurement, communication and monitoring of power systems. Intelligent switchgear is of great significance to the power system. It not only improves the reliability of power supply, but also optimizes energy management and promotes the rapid development of smart grids. With the continuous development of modern information technology and the in-depth promotion of smart grid construction, the application prospects of intelligent switchgear are broader. In order for the intelligent switchgear to play its role better, one of the important prerequisites is operation and maintenance management. The operation and maintenance management of the intelligent switchgear refers to a management method that monitors the operation of the intelligent switchgear in real time, analyzes data, and warns of abnormalities to ensure the safe operation of the equipment.

[0003] At present, the common method for operation and maintenance management of smart switch cabinets is to set corresponding monitoring frequencies for each dimension of environmental data based on the operation and maintenance experience of the operation and maintenance managers, and monitor the environmental data of multiple dimensions of the smart switch cabinet according to the monitoring frequency, so as to achieve early warning of abnormal operation of the smart switch cabinet. Under this method, the operation and maintenance experience of the operation and maintenance managers is relatively high, the rationality of the monitoring frequency is difficult to ensure, and the accuracy of early warning of abnormal operation of the smart switch cabinet is low, resulting in the inability to timely regulate the smart switch cabinet to ensure normal operation. Summary of the invention

[0004] In order to timely regulate the intelligent switch cabinet, the present application provides an operation and maintenance management method, device, storage medium and electronic equipment of the intelligent switch cabinet.

[0005] In a first aspect of the present application, a method for operation and maintenance management of an intelligent switch cabinet is provided, which specifically includes: Obtain the geographical location information of the intelligent switch cabinet; Determining, based on the geographic location information, an appropriate monitoring frequency corresponding to environmental data of at least one dimension; According to each of the suitable monitoring frequencies, at least one environmental data of a corresponding dimension of the intelligent switch cabinet is acquired, and each of the environmental data is compared with a corresponding environmental data threshold; If there is environmental data exceeding the corresponding environmental data threshold, the corresponding environmental data is determined as abnormal environmental data, and based on the abnormal environmental data, the operating state of the intelligent switch cabinet is adjusted to enable the intelligent switch cabinet to operate normally.

[0006] By adopting the above technical solution, after obtaining the geographical location information of the intelligent switch cabinet, due to different geographical locations, the local meteorological data is different, the environment of the intelligent switch cabinet is also different, and the degree of influence on the operation of the intelligent switch cabinet is different. Therefore, according to the geographical location information, the appropriate monitoring frequency of the environmental data is determined, so that the environmental data corresponding to the intelligent switch cabinet can be monitored in a targeted manner in the future, thereby realizing accurate early warning of abnormal operation of the intelligent switch cabinet. Under the appropriate monitoring frequency, the abnormal environmental data is obtained, which can also more accurately reflect the abnormal situation of the intelligent switch cabinet. Finally, according to this abnormal environmental data, the intelligent switch cabinet is targetedly regulated, so that when the intelligent switch cabinet has abnormal operation problems, the intelligent switch cabinet can be regulated in time to enable it to operate normally.

[0007] Optionally, adjusting the operating state of the intelligent switch cabinet based on the abnormal environment data specifically includes: If the abnormal environment data is abnormal temperature data and abnormal humidity data in the intelligent switch cabinet, turning on the dehumidification device in the intelligent switch cabinet; Determine a first wind direction from a temperature abnormality location in the intelligent switch cabinet to a humidity abnormality location in the intelligent switch cabinet, and perform ventilation processing through a cooling fan in the intelligent switch cabinet according to the first wind direction; If the abnormal environment data is abnormal temperature data in the intelligent switch cabinet, the location with abnormal temperature is determined as a first key location, and based on at least one location in the intelligent switch cabinet where humidity is prone to abnormality, a second wind direction from the first key location to the location where humidity is prone to abnormality is determined, and based on the second wind direction, ventilation is performed by the cooling fan, and the location where humidity is prone to abnormality is a location in the intelligent switch cabinet where humidity is prone to abnormality; If the abnormal environmental data is abnormal humidity data in the intelligent switch cabinet, the location with abnormal humidity is determined as the second key location, and based on at least one location with easily abnormal temperature in the intelligent switch cabinet, a third wind direction from the second key location to the location with easily abnormal temperature is determined. Based on the third wind direction, ventilation is performed by the cooling fan, and the dehumidification device is turned on. The location with easily abnormal temperature is a location in the intelligent switch cabinet where abnormal temperature is likely to occur.

[0008] By adopting the above technical scheme, ventilation treatment is carried out through the first wind direction, which can not only effectively reduce the temperature of the temperature-abnormal part, but also blow part of the heat to the humidity-abnormal part, thereby assisting the dehumidification of the humidity-abnormal part; when ventilation treatment is carried out through the second wind direction, while achieving the cooling effect, it can also play a better preventive role in the humidity abnormality of the humidity-prone part; when ventilation treatment is carried out through the third wind direction, while assisting dehumidification, it can also play a better preventive role in the temperature abnormality of the temperature-prone part.

[0009] Optionally, the determining, based on at least one location in the intelligent switch cabinet where humidity is prone to abnormality, a second wind direction from the first key location to the location where humidity is prone to abnormality specifically includes: Obtain the first historical location where humidity abnormality occurs in the intelligent switch cabinet in the historical season, count the first occurrence times of each of the first historical locations, and select the first historical location with the first occurrence times from each of the first historical locations in descending order to determine it as the location prone to humidity abnormality, wherein the historical season is the same as the current season; Counting the first historical period in which humidity abnormality occurs in each of the humidity-prone abnormal parts, counting the second occurrence number of each first historical period, and selecting the first historical period with the second number from each of the first historical periods in descending order of the second occurrence number to determine as the humidity abnormality period of the corresponding humidity-prone abnormal part; Calculate the first weight of each of the humidity prone abnormal parts and the second weight of each of the corresponding humidity prone abnormal time periods, wherein the first weight is the ratio of the first occurrence number of each humidity prone abnormal part to the sum of the first occurrence numbers of all humidity prone abnormal parts, and the second weight is the ratio of the second occurrence number of a single humidity prone abnormal time period corresponding to the humidity prone abnormal part to the sum of the second occurrence numbers of all corresponding humidity prone abnormal time periods; Based on the first weight and the corresponding second weights, a second wind direction from the first key location to the location prone to abnormal humidity is determined.

[0010] By adopting the above technical solution, the greater the number of first occurrences, the more likely the corresponding first historical part is to have abnormal humidity, and thus the abnormal humidity part is determined; the greater the number of second occurrences, the more likely the abnormal humidity part is to have abnormal humidity in the corresponding first historical period, and thus the abnormal humidity period is determined. Finally, combining the first weight of the abnormal humidity part and the corresponding second weight of each abnormal humidity period, the situation of abnormal humidity in each abnormal humidity part is analyzed, and finally the more suitable second wind direction from the first key part to the abnormal humidity part is determined, so that when ventilation and cooling are performed according to this second wind direction, the abnormal humidity in the abnormal humidity part can be better prevented.

[0011] Optionally, determining the second wind direction from the first key location to the location prone to abnormal humidity based on the first weight and the corresponding second weights specifically includes: If the current time is within the humidity abnormality time period, the humidity abnormality time period at the current time is determined as the first key time period, and the humidity abnormality portion in the first key time period in each corresponding humidity abnormality time period is determined as the first key abnormal portion; Calculate the first product of the first weight of each of the first key abnormal parts and the second weight of the corresponding first key time period, determine the maximum first product from each of the first products, and determine the wind direction from the first key part to the first key abnormal part corresponding to the maximum first product as the second wind direction; If the current time is not within the humidity abnormality period, determine the target ventilation duration according to the temperature abnormality data of the first key part, and determine the ventilation period according to the target ventilation duration and the current time; Determine the humidity prone abnormal period in the ventilation period among the humidity prone abnormal period corresponding to each humidity prone abnormal part as the target abnormal period, and calculate the product of the first weight of each humidity prone abnormal part and the corresponding second weight of each target abnormal period and sum them to obtain the corresponding sum of the first products; The maximum sum of the first products is determined from the sums of the first products, and the wind direction from the first key location to the location with abnormal humidity corresponding to the maximum sum of the first products is determined as the second wind direction.

[0012] By adopting the above technical solution, the larger the first product is, the greater the possibility that the corresponding first key abnormal part will have humidity abnormality, and the wind direction from the first key part to the first key abnormal part corresponding to the maximum first product is determined as the second wind direction. The subsequent ventilation treatment according to this second wind direction can not only ventilate and cool the first key part with temperature abnormality, but also blow heat to the part with the greatest possibility of humidity abnormality at the current time. Once humidity abnormality occurs, the increase in humidity can be suppressed to a certain extent and auxiliary dehumidification can be carried out; the larger the sum of the first products is, the greater the possibility that the corresponding humidity-prone part will have humidity abnormality during the entire ventilation period, and the wind direction from the first key part to the humidity-prone part corresponding to the sum of the maximum first products is determined as the second wind direction, so that when ventilation and cooling are carried out according to this second wind direction, the humidity increase in the part with the greatest possibility of humidity abnormality during the entire ventilation period can be prevented to a certain extent.

[0013] Optionally, the determining, based on at least one temperature-prone location in the intelligent switch cabinet, a third wind direction from the second key location to the temperature-prone location specifically includes: Obtain the second historical position where the temperature abnormality occurs in the intelligent switch cabinet in the historical season, count the first occurrence frequency of each second historical position, and select the third second historical position from each second historical position in descending order of the first occurrence frequency to determine it as the temperature prone abnormal position, and the historical season is the same as the current season; Obtaining the second historical period in which the temperature abnormality occurs at each of the temperature-prone parts, counting the second occurrence frequency of each second historical period, and selecting the fourth number of second historical periods from each of the second historical periods in descending order of the second occurrence frequency to determine as the temperature abnormality period of the corresponding temperature abnormality part; Calculate the third weight of each of the temperature-prone abnormal parts and the fourth weight of each of the corresponding temperature-prone abnormal time periods, wherein the third weight is the ratio of the first occurrence frequency of each temperature-prone abnormal part to the sum of the first occurrence frequencies of all temperature-prone abnormal parts, and the fourth weight is the ratio of the second occurrence frequency of a single temperature-prone abnormal time period corresponding to the temperature-prone abnormal part to the sum of the second occurrence frequencies of all corresponding temperature-prone abnormal time periods; Based on the third weight and the corresponding fourth weights, a third wind direction from the second key location to the location prone to temperature abnormality is determined.

[0014] By adopting the above technical solution, the greater the first frequency of occurrence, the more likely the corresponding second historical part is to have temperature anomalies, and thus the temperature-prone part is determined; the greater the second frequency of occurrence, the more likely the temperature-prone part is to have temperature anomalies in the corresponding second historical period, and thus the temperature-prone period is determined. Finally, based on the third weight of each temperature-prone part and the corresponding fourth weight of each temperature-prone period, the third wind direction from the second key part to the temperature-prone part is determined, which reduces humidity and, when the temperature of the temperature-prone part rises, blows moisture into the air in time to cool it down.

[0015] Optionally, determining the third wind direction from the second key location to the location prone to abnormal temperature based on the third weight and the corresponding fourth weights specifically includes: Determine the temperature abnormality time period at the current time as the second key time period, and determine the temperature abnormality location at the second key time period in each corresponding temperature abnormality time period as the second key abnormal location; Calculate the second product of the third weight of each of the second key abnormal parts and the fourth weight of the corresponding second key time period, and select the maximum second product and the minimum second product from each of the second products; The wind direction from the second key position to the second key abnormal position corresponding to the minimum second product is determined as the first initial wind direction. If there is a dry position downstream of the second key abnormal position corresponding to the minimum second product under the first initial wind direction, the first initial wind direction is determined as the third wind direction. The dry position is a position in the intelligent switch cabinet where the humidity data is less than a preset dry-wet critical threshold, and the dry-wet critical threshold is a critical value for judging whether the position is dry. The wind direction from the second key position to the second key abnormal position corresponding to the maximum second product is determined as the second initial wind direction. If, under the second initial wind direction, there is a dry area between the second key abnormal position corresponding to the maximum second product and the second key position, the second initial wind direction is determined as the third wind direction.

[0016] By adopting the above technical scheme, the first initial wind direction is determined as the third wind direction, and ventilation treatment is subsequently performed through this third wind direction, which can not only take away part of the air moisture in the second key part and reduce the humidity to a certain extent, but also blow the air moisture to the dry part to increase the humidity of the part, avoid static electricity accumulation in the dry part, and affect the normal operation of the intelligent switch cabinet. At the same time, the upstream of the dry part in the third wind direction is the part with the least possibility of temperature abnormality, which can better avoid the temperature increase upstream of the dry part and affect the improvement effect of the drying problem; the second initial wind direction is determined as the third wind direction, and ventilation treatment is subsequently performed through this third wind direction, which can not only reduce the humidity of the second key part, but also blow the air moisture to the dry part and the part with the greatest possibility of temperature abnormality in turn, improve the air drying problem in the dry part, and when the temperature of the part with the greatest possibility of temperature abnormality is abnormal, part of the heat can be taken away in time by the blown air moisture to avoid the occurrence of temperature abnormality.

[0017] Optionally, the method further includes: Determine the next monitoring time of the environmental data of the temperature dimension in the intelligent switch cabinet according to the appropriate monitoring frequency corresponding to the temperature dimension; Calculate the product of the third weight of each of the temperature-prone abnormal parts and the corresponding fourth weight of each of the temperature-prone abnormal time periods to obtain a third product, and select the maximum third product from each of the third products; Determine the temperature abnormality time period corresponding to the maximum third product of each temperature abnormality-prone part as a reference abnormality time period, and count the number of time periods in which the reference abnormality time period exists at the next monitoring time; If the number of time periods is less than a preset number threshold, a monitoring frequency adjustment reminder is sent to the terminal of the operation and maintenance management personnel.

[0018] By adopting the above technical solution, the temperature abnormality period corresponding to the maximum third product of each temperature abnormality part can be understood as the period with the greatest possibility of temperature abnormality in each temperature abnormality part. If the number of time periods is less than the number threshold, it means that the reference abnormality period containing the next monitoring time is small, which means that the temperature abnormality part inside the smart switch cabinet cannot be well found when the environmental data of the temperature dimension is monitored next time, and the early warning effect for abnormal operation is poor. Then, a reminder to adjust the monitoring frequency is sent to the terminal of the operation and maintenance manager, so as to better manage the operation and maintenance of the smart switch cabinet.

[0019] In a second aspect of the present application, an operation and maintenance management device for an intelligent switch cabinet is provided, specifically comprising: An information acquisition module is used to obtain the geographical location information of the intelligent switch cabinet; A frequency determination module, used to determine an appropriate monitoring frequency corresponding to environmental data of at least one dimension according to the geographical location information; An environmental monitoring module, used to obtain at least one environmental data of a corresponding dimension of the intelligent switch cabinet according to each of the suitable monitoring frequencies, and compare each of the environmental data with a corresponding environmental data threshold; The operation and maintenance management module is used to determine the corresponding environmental data as abnormal environmental data if there is environmental data exceeding the corresponding environmental data threshold, and adjust the operating state of the intelligent switch cabinet based on the abnormal environmental data to enable the intelligent switch cabinet to operate normally.

[0020] By adopting the above technical solution, the information acquisition module obtains the geographic location information, and then the frequency determination module determines the appropriate monitoring frequency corresponding to the environmental data of at least one dimension. Then, the environmental monitoring module obtains the corresponding environmental data according to the appropriate monitoring frequency and compares it with the corresponding environmental data threshold. Finally, the operation and maintenance management module adjusts the operating status of the intelligent switch cabinet based on the abnormal environmental data.

[0021] In a third aspect of the present application, a computer-readable storage medium is provided, in which a computer program is stored. When the computer program is loaded and executed by a processor, the method steps described in any one of the first aspects are performed.

[0022] In a fourth aspect of the present application, an electronic device is provided, specifically comprising: A processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the processor is used to load and execute the computer program stored in the memory so that the electronic device performs the method as described in any one of the first aspects.

[0023] In summary, the present application includes at least one of the following beneficial technical effects: after obtaining the geographical location information of the intelligent switch cabinet, due to different geographical locations, the local meteorological data is different, the environment of the intelligent switch cabinet is also different, and the degree of influence on the operation of the intelligent switch cabinet is different. Therefore, according to the geographical location information, the appropriate monitoring frequency of the environmental data is determined, so that the environmental data corresponding to the intelligent switch cabinet can be monitored in a targeted manner in the future, thereby realizing accurate early warning of abnormal operation of the intelligent switch cabinet. Under the appropriate monitoring frequency, the abnormal environmental data is obtained, which can also more accurately reflect the abnormal situation of the intelligent switch cabinet. Finally, according to this abnormal environmental data, the intelligent switch cabinet is targetedly regulated, so that when the intelligent switch cabinet has abnormal operation problems, the intelligent switch cabinet can be regulated in time to enable it to operate normally. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flowchart of an operation and maintenance management method of an intelligent switch cabinet provided in an embodiment of the present application; Figure 2 It is a flowchart of another operation and maintenance management method of an intelligent switch cabinet provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an operation and maintenance management device of an intelligent switch cabinet provided in an embodiment of the present application; Figure 4 It is a structural diagram of another operation and maintenance management device of an intelligent switch cabinet provided in an embodiment of the present application.

[0025] Explanation of the accompanying drawings: 11. Information acquisition module; 12. Frequency determination module; 13. Environmental monitoring module; 14. Operation and maintenance management module; 15. Monitoring reminder module. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0028] In the description of the embodiments of the present application, the term "and / or" is only a kind of association relationship describing the associated objects, indicating that there may be three kinds of relationships, for example, A and / or B, which can represent: A exists alone, B exists alone, and A and B exist at the same time. In addition, unless otherwise specified, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are only used for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" can explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] See also Figure 1 The present application embodiment discloses a flowchart of an operation and maintenance management method for an intelligent switch cabinet, which can be implemented by a computer program or run on an operation and maintenance management device for an intelligent switch cabinet based on a von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S101: Obtain geographical location information of the intelligent switch cabinet.

[0030] Specifically, in an embodiment of the present application, the intelligent switch cabinet may be a switch cabinet in a substation or a distribution room of an electric power system. Geographical location information refers to the specific location information set by the intelligent switch cabinet. In addition, the execution subject of an operation and maintenance management method of an intelligent switch cabinet disclosed in the present application may be a server, and the server and the intelligent switch cabinet are connected through a wireless network. The server may be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers. In other embodiments, the execution subject of an operation and maintenance management method of an intelligent switch cabinet may be the intelligent switch cabinet itself. Furthermore, a feasible way to obtain the geographical location information of the intelligent switch cabinet is to obtain the geographical location information of the intelligent switch cabinet through Geographic Information System (GIS) technology. In other embodiments, the geographical location information of the intelligent switch cabinet may also be obtained through the GPS module built into the intelligent switch cabinet.

[0031] S102: Determine, based on the geographic location information, an appropriate monitoring frequency corresponding to environmental data of at least one dimension.

[0032] Specifically, after obtaining the geographical location information of the intelligent switch cabinet, the preset real-time meteorological interface is called, which may be a meteorological data unified service interface (Meteorological Unified Service Interface Community, MUSIC), to obtain the meteorological data of the area corresponding to the geographical location information, wherein the meteorological data includes but is not limited to air pressure, precipitation, sunshine and other data. Further, according to the obtained meteorological data, the appropriate monitoring frequency corresponding to the environmental data of at least one dimension in the area corresponding to the geographical location information is determined, and the dimensions of the environmental data are not limited to temperature, humidity, air pressure and other dimensions. The appropriate monitoring frequency refers to the monitoring frequency of personalized and targeted monitoring of environmental data of different dimensions corresponding to the intelligent switch cabinet based on the current geographical location information. The main reason is that different geographical location information has different local meteorological data, and the environmental data corresponding to the intelligent switch cabinet is also different, which has different degrees of influence on the operation of the intelligent switch cabinet. Therefore, for different geographical locations, it is necessary to monitor the environmental data corresponding to the intelligent switch cabinet in a targeted manner, so as to achieve accurate early warning of abnormal operation of the intelligent switch cabinet. It should be noted that in the embodiment of the present application, the environmental data of each dimension corresponding to the smart switch cabinet is the environmental data of the parts where different components are located inside the smart switch cabinet or the environmental data inside the smart switch cabinet. In other embodiments, it can also be the environmental data within a preset distance range outside the smart switch cabinet. The environmental conditions inside and outside the smart switch cabinet will affect the normal operation.

[0033] Furthermore, a feasible way to determine the appropriate monitoring frequency is: input the meteorological data obtained according to the geographical location information into the preset regional environmental characteristics prediction model to obtain the regional environmental characteristics corresponding to the geographical location information, and then match the appropriate monitoring frequency of the corresponding environmental data from the monitoring frequency matching table according to the regional environmental characteristics. The monitoring frequency matching table includes different regional environmental characteristics and the corresponding monitoring frequencies of environmental data. Among them, the regional environmental characteristics prediction model can be a trained convolutional neural network model or a recurrent neural network model. The training process is briefly described as follows: the model is trained by using historical meteorological data of other regions marked with regional environmental characteristics until the model converges. This is a prior art and will not be repeated here. For example, if the regional environmental characteristics of the area where the smart switch cabinet is located are high temperature and drought, the high temperature environment is likely to affect the normal operation of the smart switch cabinet. Therefore, the appropriate monitoring frequency corresponding to the temperature dimension needs to be increased, so as to better monitor the operating status of the smart switch cabinet.

[0034] S103: Acquire at least one environmental data of a corresponding dimension of the intelligent switch cabinet according to each suitable monitoring frequency, and compare each environmental data with a corresponding environmental data threshold.

[0035] Specifically, after the appropriate monitoring frequency of the environmental data of each dimension of the intelligent switch cabinet is determined, the corresponding environmental data of each part in the intelligent switch cabinet is obtained through a distributed sensor network according to the appropriate monitoring frequency of each dimension, wherein the distributed sensor network is a wireless sensor network composed of multiple sensor nodes, and these sensor nodes include but are not limited to temperature sensors, humidity sensors or air pressure sensors, etc., which are distributed in the parts where each device in the intelligent switch cabinet is located, and finally each environmental data is compared with the corresponding environmental data threshold. Exemplarily, the dimensions that the intelligent switch cabinet needs to detect are temperature and humidity. Then, the temperature data and humidity data of each part in the intelligent switch cabinet are obtained through the corresponding temperature sensor and humidity sensor, that is, at least one environmental data of the corresponding dimension of the intelligent switch cabinet. Further, the temperature data of each part is compared with the corresponding temperature threshold, and the humidity data of each part is compared with the corresponding humidity threshold, so as to determine whether the temperature and humidity of each part in the intelligent switch cabinet are abnormal.

[0036] S104: If there is environmental data exceeding the corresponding environmental data threshold, the corresponding environmental data is determined as abnormal environmental data, and based on the abnormal environmental data, the operating state of the intelligent switch cabinet is adjusted to enable the intelligent switch cabinet to operate normally.

[0037] Specifically, if there is environmental data that exceeds the corresponding environmental data threshold, then such environmental data is determined as abnormal environmental data, that is, environmental data that may affect the normal operation of the intelligent switch cabinet. Furthermore, based on the abnormal environmental data, the operating state of the intelligent switch cabinet is adjusted, thereby reducing the impact of the abnormal environmental data on the intelligent switch cabinet, and ensuring the normal operation of the intelligent switch cabinet to a certain extent. In an embodiment of the present application, a feasible adjustment method is: matching the adjustment scheme corresponding to this abnormal environmental data from a preset adjustment scheme matching table, and the adjustment scheme matching table includes different abnormal environmental data and corresponding adjustment schemes, which are all set based on the experience of the operation and maintenance management personnel. Finally, according to the matched adjustment scheme, the operating state of the intelligent switch cabinet is adjusted so that the intelligent switch cabinet operates normally. Among them, adjusting the operating state of the intelligent switch cabinet includes but is not limited to adjusting the load current of the intelligent switch cabinet, the internal dehumidification device, and the operating state of the cooling fan.

[0038] See also Figure 2 The present application embodiment discloses a flowchart of another operation and maintenance management method of an intelligent switch cabinet, which can be implemented by a computer program or run on an operation and maintenance management device of an intelligent switch cabinet based on a von Neumann system. The computer program can be integrated into an application or run as an independent tool application, specifically including: S201: Obtain geographical location information of the intelligent switch cabinet.

[0039] S202: Determine, based on the geographic location information, an appropriate monitoring frequency corresponding to environmental data of at least one dimension.

[0040] S203: Acquire at least one environmental data of a corresponding dimension of the intelligent switch cabinet according to each suitable monitoring frequency, and compare each environmental data with a corresponding environmental data threshold.

[0041] S204: If there is environmental data exceeding the corresponding environmental data threshold, the corresponding environmental data is determined as abnormal environmental data.

[0042] For details, please refer to steps S101-S104, which will not be described in detail here.

[0043] S205: If the abnormal environmental data is abnormal temperature data and abnormal humidity data in the intelligent switch cabinet, a dehumidification device in the intelligent switch cabinet is turned on.

[0044] S206: Determine a first wind direction from the temperature abnormality location in the intelligent switch cabinet to the humidity abnormality location in the intelligent switch cabinet, and perform ventilation processing through a cooling fan in the intelligent switch cabinet according to the first wind direction.

[0045] Specifically, if the abnormal environment data is abnormal temperature data and abnormal humidity data in the intelligent switch cabinet, it means that there are parts with abnormal temperature and parts with abnormal humidity in the intelligent switch cabinet, so it is necessary to perform cooling and dehumidification in time to avoid affecting the corresponding devices and causing abnormal operation of the intelligent switch cabinet. In the embodiment of the present application, a feasible processing method is: according to the distribution of the temperature sensor that detects the abnormal temperature data, the abnormal temperature part in the intelligent switch cabinet is determined, and according to the distribution of the humidity sensor that detects the abnormal humidity data, the abnormal humidity part in the intelligent switch cabinet is determined. When there is only one abnormal humidity part and one abnormal temperature part, the first wind direction from the abnormal temperature part to the abnormal humidity part is determined. Since at least one cooling fan and a dehumidification device are pre-installed in the intelligent switch cabinet, the cooling fan is turned on to ventilate and cool the inside of the intelligent switch cabinet, and the cooling fan is specifically controlled to ventilate in the first wind direction, and the internal dehumidification device is turned on at the same time. In other embodiments, ventilation can also be performed by a ventilation fan. Among them, ventilation treatment can not only effectively reduce the temperature of the temperature abnormal part, but also blow part of the heat to the humidity abnormal part, which plays an auxiliary effect on the dehumidification of the humidity abnormal part, and cooperates with the dehumidification device to achieve a better dehumidification effect on the humidity abnormal part. In other embodiments, according to the difference between the temperature abnormality data and the corresponding temperature threshold, the ventilation speed and ventilation time with better cooling effect are determined. The larger the difference, the larger the ventilation speed and ventilation time. Then the product of the ventilation speed and ventilation time is calculated to characterize the corresponding ventilation and dehumidification effect. The larger the product, the better the ventilation and dehumidification effect. Finally, according to this product, the gear of the dehumidification device is lowered to the target gear. The larger the product, the lower the target gear. Therefore, according to the auxiliary dehumidification effect brought by the ventilation blowing heat to the humidity abnormal part, the gear of the dehumidification device itself is reduced to ensure the dehumidification effect while saving energy.

[0046] Furthermore, if there are multiple temperature abnormality locations and a single humidity abnormality location, then the first wind direction from each temperature abnormality location to the humidity abnormality location is determined, and ventilation is performed in the order from large to small according to the difference in temperature between each temperature abnormality location and the temperature threshold.

[0047] S207: If the abnormal environmental data is abnormal temperature data in the intelligent switch cabinet, the location of the temperature abnormality is determined as the first key location, and based on at least one location in the intelligent switch cabinet where humidity is prone to abnormality, a second wind direction from the first key location to the location where humidity is prone to abnormality is determined, and based on the second wind direction, ventilation is performed through a cooling fan.

[0048] Specifically, if the abnormal environment data is abnormal temperature data in the smart switch cabinet, it means that there is currently a part with abnormal temperature in the smart switch cabinet, then the part with abnormal temperature is determined as the first key part, and at this time, it is only necessary to turn on the cooling fan for ventilation. Further, through the historical records of abnormal humidity in the smart switch cabinet, the first historical part where abnormal humidity occurs in the smart switch cabinet in the same historical season as the current season is obtained, and the first occurrence number of each first historical part is counted. The larger the first occurrence number, the more likely the corresponding first historical part is to have abnormal humidity. Then, in order of the first occurrence number from large to small, the first historical part with the first number is selected from each first historical part, and it is determined as the part prone to abnormal humidity, that is, the part prone to abnormal humidity in the smart switch cabinet. Furthermore, the first historical period in which humidity abnormality occurs in each humidity-prone abnormal part is counted, and the second occurrence number of each first historical period is counted. The larger the second occurrence number, the more likely the humidity-prone abnormal part is to have humidity abnormality in the corresponding first historical period. Finally, in descending order of the second occurrence number, the second number of first historical periods is selected from each first historical period, and determined as the humidity abnormality period of the corresponding humidity-prone abnormal part, that is, the period in which humidity abnormality is likely to occur in the humidity-prone abnormal part. The historical record of humidity abnormality includes but is not limited to the time when humidity abnormality occurred in the intelligent switch cabinet in history, and the location where it occurred.

[0049] Furthermore, the first weight of each humidity-prone part and the second weight of each corresponding humidity-prone time period are calculated, the first weight being the ratio of the first number of occurrences of each humidity-prone part to the sum of the first number of occurrences of all humidity-prone parts, and the second weight being the ratio of the second number of occurrences of a single humidity-prone time period corresponding to the humidity-prone part to the sum of the second number of occurrences of all corresponding humidity-prone time periods.

[0050] According to each first weight and the corresponding second weights, the second wind direction from the first key area to the humidity prone abnormal area is determined. A feasible implementation method is: judging whether the current time is in the humidity prone abnormal time period corresponding to each humidity prone abnormal area; if so, determining the humidity prone abnormal time period at the current time as the first key time period, and determining the humidity prone abnormal area in the corresponding humidity prone abnormal time period where this first key time period exists as the first key abnormal area.

[0051] Further, the product of the first weight of each first key abnormal part and the second weight of the corresponding first key time period is calculated, that is, the first product. The larger the first product, the greater the possibility of humidity abnormality in the corresponding first key abnormal part. Then determine the maximum first product among the first products, and determine the wind direction from the first key part to the first key abnormal part corresponding to this maximum first product as the second wind direction. Subsequent ventilation treatment according to this second wind direction can not only ventilate and cool the first key part with abnormal temperature, but also blow heat to the part with the greatest possibility of humidity abnormality. Once humidity abnormality occurs, the increase of humidity can be suppressed to a certain extent and auxiliary dehumidification can be carried out. This is because a large amount of heat is blown to the part with the greatest possibility of humidity abnormality. The wind blowing to this part is hot air. Once the humidity of this part increases, the effect of hot air dehumidification can be achieved. The technical principle of hot air dehumidification is a prior art and will not be repeated here.

[0052] If the current time is not in the period of abnormal humidity, then calculate the temperature anomaly data of the first key part, that is, the temperature difference between the temperature value of the part and the corresponding temperature threshold. The higher the temperature difference, the greater the degree of temperature anomaly. Then match the target ventilation time corresponding to this temperature difference from the preset ventilation parameter matching table. The ventilation parameter matching table includes different temperature difference ranges and corresponding ventilation times. The larger the temperature difference, the longer the ventilation time. For example, the ventilation parameter matching table includes: temperature difference range 0-5℃, corresponding ventilation time is 5 minutes; temperature difference range 5-10℃, corresponding ventilation time is 10 minutes, temperature difference range 10-15℃, corresponding ventilation time is 15 minutes, and so on. Then, add the current time to the target ventilation time to obtain the ventilation period for cooling the first key part.

[0053] Furthermore, the humidity prone abnormal period in each humidity prone abnormal period corresponding to each humidity prone abnormal part within this ventilation period is determined as the target abnormal period, and then the product of the first weight of each humidity prone abnormal part and the second weight of each corresponding target abnormal period is calculated and summed to obtain the corresponding sum of the first products. The larger the sum of the first products, the greater the possibility of humidity abnormality in the corresponding humidity prone abnormal part during the entire ventilation period. Finally, the maximum sum of the first products is determined from the sums of the first products, and the wind direction from the first key part to the humidity prone abnormal part corresponding to this maximum sum of the first products is determined as the second wind direction, so that when ventilation and cooling are performed according to this second wind direction, the humidity of the part with the greatest possibility of humidity abnormality can be prevented to a certain extent from increasing, which affects the operation of the intelligent switch cabinet. In other embodiments, the second wind direction from the first key part to each humidity prone abnormal part can also be determined, and ventilation treatment is performed in accordance with each second wind direction in turn.

[0054] S208: If the abnormal environmental data is abnormal humidity data in the intelligent switch cabinet, the location of the humidity abnormality is determined as the second key location, and based on at least one location in the intelligent switch cabinet where temperature is prone to abnormality, a third wind direction from the second key location to the location where temperature is prone to abnormality is determined. Based on the third wind direction, ventilation is performed through a cooling fan, and the dehumidification device is turned on.

[0055] Specifically, if the abnormal environmental data is abnormal humidity data in the smart switch cabinet, it means that there is currently a part with abnormal humidity in the smart switch cabinet, and then the part with abnormal humidity is determined as the second key part. Then, from the historical records of temperature abnormalities, obtain the second historical parts where temperature abnormalities occurred in the smart switch cabinet in the historical season, and select the second historical parts with the third number from each second historical part in order from large to small according to the first occurrence frequency of each second historical part, and determine them as parts prone to temperature abnormalities, that is, parts where temperature abnormalities are prone to occur in the smart switch cabinet. Among them, the greater the first occurrence frequency, the more likely the corresponding second historical part in the smart switch cabinet is to have temperature abnormalities. The historical records of temperature abnormalities include but are not limited to the time when temperature abnormalities occurred in the smart switch cabinet in history, and the location where they occurred.

[0056] Furthermore, the second historical period in which the temperature abnormality occurs in each temperature-prone abnormal part is obtained from the historical records, and the second occurrence frequency of each second historical period is counted. The greater the second occurrence frequency, the more likely the temperature abnormality occurs in the corresponding second historical period. In descending order of the second occurrence frequency, the fourth number of second historical periods is selected from each second historical period, and is determined as the temperature abnormality period of the corresponding temperature abnormality part, that is, the period in which the temperature abnormality part is more likely to have a temperature abnormality.

[0057] Calculate the third weight of each temperature-prone abnormal part and the fourth weight of each corresponding temperature-prone abnormal time period, the third weight is the ratio of the first occurrence frequency of each temperature-prone abnormal part to the sum of the first occurrence frequencies of all temperature-prone abnormal parts, and the fourth weight is the ratio of the second occurrence frequency of a single temperature-prone abnormal time period corresponding to the temperature-prone abnormal part to the sum of the second occurrence frequencies of all corresponding temperature-prone abnormal time periods.

[0058] Further, according to the third weight and the corresponding fourth weights, the third wind direction from the second key part to the part prone to temperature abnormality is determined. The specific process is: the temperature abnormality period at the current time is determined as the second key period, and the temperature abnormality part at the second key period in the corresponding temperature abnormality period is determined as the second key abnormal part. Further, the product of the third weight of each second key abnormal part and the fourth weight of the corresponding second key period is calculated, that is, the second product. The larger the second product, the greater the possibility that the corresponding second key abnormal part will have temperature abnormality after the current time. Then, the maximum second product and the minimum second product are selected from each second product. The wind direction from the second key position to the second key abnormal position corresponding to the minimum second product (the position with the least possibility of temperature abnormality after the current time) is determined as the first initial wind direction. If there is a dry position downstream of the second key abnormal position corresponding to the minimum second product under this first initial wind direction, then this first initial wind direction is determined as the final third wind direction. The subsequent ventilation treatment through this third wind direction can not only take away part of the air moisture in the second key position and reduce the humidity to a certain extent, but also blow the air moisture to the dry position to increase the humidity of the position, avoid static electricity accumulation in the dry position, and affect the normal operation of the intelligent switch cabinet. At the same time, the upstream of the dry position in the third wind direction is the position with the least possibility of temperature abnormality, which can better avoid the temperature increase upstream of the dry position and affect the improvement effect of the drying problem. Among them, the dry position is the position in the intelligent switch cabinet where the humidity data is less than the preset dry-wet critical threshold, and the dry-wet critical threshold is the critical value for judging whether the position is dry, which is less than the above-mentioned humidity threshold.

[0059] Furthermore, the wind direction from the second key part to the second key abnormal part corresponding to the maximum second product is determined as the second initial wind direction. If under this second initial wind direction, there is a dry part between the second key abnormal part corresponding to the maximum second product (the part with the greatest possibility of temperature abnormality after the current time) and the second key part, then this second initial wind direction is determined as the third wind direction. The subsequent ventilation treatment through this third wind direction can not only reduce the humidity of the second key part, but also blow the air moisture to the dry part and the second key abnormal part corresponding to the maximum second product in sequence, improve the air drying problem of the dry part, and when the temperature of the second key abnormal part corresponding to the maximum second product is abnormal, the air moisture can be blown away in time to avoid the occurrence of temperature abnormality. Finally, based on the third wind direction, ventilation treatment is carried out through the cooling fan, and the dehumidification device is turned on at the same time.

[0060] In one embodiment, according to the appropriate monitoring frequency corresponding to the temperature dimension, the next monitoring time of the environmental data of the temperature dimension in the intelligent switch cabinet can be determined, that is, the time of the next detection of the environmental data of the temperature dimension, and then the product of the third weight of the single temperature-prone abnormal part and the corresponding fourth weight of each temperature-prone abnormal period is calculated, that is, the third product. The larger the third product, the greater the possibility that the single temperature-prone abnormal part will have temperature abnormality in the corresponding temperature-prone abnormal period. Further, for the single temperature-prone abnormal part, the largest third product is selected from the corresponding third products. Then, the temperature-prone abnormal period corresponding to the maximum third product of each temperature-prone abnormal part is determined as the reference abnormal period, and it is judged whether the next monitoring time is within each reference abnormal period. If it is, it means that when the environmental data of the temperature dimension is detected at the next monitoring time, the temperature abnormality is likely to be detected. Then, the number of time periods in which there are reference abnormal periods in the next monitoring time is counted. If the number of time periods is less than the number threshold, it means that the number of reference abnormal periods including the next monitoring time is small, which means that the temperature abnormal parts inside the smart switch cabinet cannot be well found when the environmental data of the temperature dimension is monitored next time, and the warning effect for abnormal operation is poor. Then, a monitoring frequency adjustment reminder is sent to the terminal of the operation and maintenance management personnel, so as to better perform operation and maintenance management of the smart switch cabinet.

[0061] The implementation principle of the operation and maintenance management method of the smart switch cabinet of the embodiment of the present application is as follows: after obtaining the geographical location information of the smart switch cabinet, due to different geographical locations, the local meteorological data is different, the environment of the smart switch cabinet is also different, and the degree of influence on the operation of the smart switch cabinet is different. Therefore, according to the geographical location information, the appropriate monitoring frequency of the environmental data is determined, so that the environmental data corresponding to the smart switch cabinet is subsequently monitored in a targeted manner, thereby realizing accurate early warning of abnormal operation of the smart switch cabinet. Acquiring abnormal environmental data at an appropriate monitoring frequency can also more accurately reflect the abnormal situation of the smart switch cabinet. Finally, according to this abnormal environmental data, the smart switch cabinet is targetedly regulated, so that when the smart switch cabinet has abnormal operation problems, the smart switch cabinet is regulated in a timely manner so that it can operate normally.

[0062] The following is an embodiment of the device of the present application, which can be used to execute the embodiment of the method of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the embodiment of the method of the present application.

[0063] See also Figure 3, is a schematic diagram of the structure of the operation and maintenance management device of the intelligent switch cabinet provided in the embodiment of the present application. The operation and maintenance management device applied to the intelligent switch cabinet can be implemented as all or part of the device through software, hardware or a combination of both. The device includes an information acquisition module 11, a frequency determination module 12, an environment monitoring module 13 and an operation and maintenance management module 14.

[0064] The information acquisition module 11 is used to obtain the geographical location information of the intelligent switch cabinet; A frequency determination module 12, configured to determine an appropriate monitoring frequency corresponding to environmental data of at least one dimension according to geographical location information; The environment monitoring module 13 is used to obtain at least one environment data of the corresponding dimension of the intelligent switch cabinet according to each suitable monitoring frequency, and compare each environment data with the corresponding environment data threshold; The operation and maintenance management module 14 is used to determine the corresponding environmental data as abnormal environmental data if there is environmental data exceeding the corresponding environmental data threshold, and adjust the operating state of the intelligent switch cabinet based on the abnormal environmental data to make the intelligent switch cabinet operate normally.

[0065] Optionally, the operation and maintenance management module 14 is specifically used to: If the abnormal environmental data is abnormal temperature data and abnormal humidity data in the intelligent switch cabinet, the dehumidification device in the intelligent switch cabinet is turned on; Determine a first wind direction from a temperature abnormality location in the intelligent switch cabinet to a humidity abnormality location in the intelligent switch cabinet, and perform ventilation processing through a cooling fan in the intelligent switch cabinet according to the first wind direction; If the abnormal environment data is abnormal temperature data in the intelligent switch cabinet, the location with abnormal temperature is determined as the first key location, and based on at least one location with abnormal humidity in the intelligent switch cabinet, a second wind direction from the first key location to the location with abnormal humidity is determined, and based on the second wind direction, ventilation is performed by a cooling fan, and the location with abnormal humidity is a location in the intelligent switch cabinet where abnormal humidity is likely to occur; If the abnormal environmental data is abnormal humidity data in the smart switch cabinet, the location with abnormal humidity is determined as the second key location. Based on at least one location with easily abnormal temperature in the smart switch cabinet, the third wind direction from the second key location to the location with easily abnormal temperature is determined. Based on the third wind direction, ventilation is performed by a cooling fan, and the dehumidification device is turned on. The location with easily abnormal temperature is the location in the smart switch cabinet where abnormal temperature is likely to occur.

[0066] Optionally, the operation and maintenance management module 14 is specifically used to: Obtain the first historical location where humidity anomaly occurs in the intelligent switch cabinet in the historical season, count the first occurrence times of each first historical location, and select the first historical location with the first number from each first historical location in descending order of the first occurrence times to determine it as the location prone to humidity anomaly, and the historical season is the same as the current season; Count the first historical period in which humidity abnormality occurs in each humidity prone abnormal part, count the second occurrence number of each first historical period, and select the first historical period with the second number from each first historical period in descending order of the second occurrence number to determine it as the humidity prone abnormal period of the corresponding humidity prone abnormal part; Calculate the first weight of each humidity prone abnormal part and the second weight of each corresponding humidity prone abnormal time period, the first weight is the ratio of the first occurrence number of each humidity prone abnormal part to the sum of the first occurrence numbers of all humidity prone abnormal parts, and the second weight is the ratio of the second occurrence number of a single humidity prone abnormal time period corresponding to the humidity prone abnormal part to the sum of the second occurrence numbers of all corresponding humidity prone abnormal time periods; Based on the first weight and the corresponding second weights, a second wind direction from the first key location to the location prone to abnormal humidity is determined.

[0067] Optionally, the operation and maintenance management module 14 is specifically used to: If the current time is in the humidity abnormality time period, the humidity abnormality time period in the current time is determined as the first key time period, and the humidity abnormality portion in the first key time period in each corresponding humidity abnormality time period is determined as the first key abnormal portion; Calculate the first product of the first weight of each first key abnormal part and the second weight of the corresponding first key time period, determine the maximum first product from each first product, and determine the wind direction from the first key part to the first key abnormal part corresponding to the maximum first product as the second wind direction; If the current time is not within the period of abnormal humidity, the target ventilation time is determined according to the temperature abnormality data of the first key part, and the ventilation period is determined according to the target ventilation time and the current time; Determine the humidity prone abnormal period in the ventilation period among the humidity prone abnormal periods corresponding to each humidity prone abnormal part as the target abnormal period, and calculate the product of the first weight of each humidity prone abnormal part and the second weight of each corresponding target abnormal period and sum them to obtain the corresponding sum of the first products; The maximum sum of the first products is determined from the sums of the first products, and the wind direction from the first key location to the location with abnormal humidity corresponding to the maximum sum of the first products is determined as the second wind direction.

[0068] Optionally, the operation and maintenance management module 14 is specifically used to: Obtain the second historical parts where temperature anomalies occur in the intelligent switch cabinet in the historical season, count the first occurrence frequency of each second historical part, and select the third second historical part from each second historical part in descending order of the first occurrence frequency to determine it as the temperature prone abnormal part, and the historical season is the same as the current season; Obtain the second historical period in which the temperature abnormality occurs at each temperature-prone abnormal part, count the second occurrence frequency of each second historical period, and select the fourth second historical period from each second historical period in descending order of the second occurrence frequency to determine it as the temperature abnormality period of the corresponding temperature-prone abnormal part; Calculate the third weight of each temperature-prone abnormal part and the fourth weight of each corresponding temperature-prone abnormal time period, the third weight being the ratio of the first occurrence frequency of each temperature-prone abnormal part to the sum of the first occurrence frequencies of all temperature-prone abnormal parts, and the fourth weight being the ratio of the second occurrence frequency of a single temperature-prone abnormal time period corresponding to the temperature-prone abnormal part to the sum of the second occurrence frequencies of all corresponding temperature-prone abnormal time periods; Based on the third weight and the corresponding fourth weights, a third wind direction from the second key location to the location prone to abnormal temperature is determined.

[0069] Optionally, the operation and maintenance management module 14 is specifically used to: Determine the temperature abnormality time period at the current time as the second key time period, and determine the temperature abnormality location at the second key time period in each corresponding temperature abnormality time period as the second key abnormal location; Calculate the second product of the third weight of each second key abnormal part and the fourth weight of the corresponding second key time period, and select the maximum second product and the minimum second product from each second product; The wind direction from the second key position to the second key abnormal position corresponding to the minimum second product is determined as the first initial wind direction. If there is a dry position downstream of the second key abnormal position corresponding to the minimum second product under the first initial wind direction, the first initial wind direction is determined as the third wind direction. The dry position is a position in the intelligent switch cabinet where the humidity data is less than a preset dry-wet critical threshold. The dry-wet critical threshold is a critical value for judging whether the position is dry. The wind direction from the second key position to the second key abnormal position corresponding to the maximum second product is determined as the second initial wind direction. If, under the second initial wind direction, there is a dry area between the second key abnormal position corresponding to the maximum second product and the second key position, the second initial wind direction is determined as the third wind direction.

[0070] Optional, such as Figure 4 As shown, the device also includes a monitoring reminder module 15, which is specifically used for: According to the appropriate monitoring frequency corresponding to the temperature dimension, determine the next monitoring time of the environmental data of the temperature dimension in the intelligent switch cabinet; Calculate the product of the third weight of each temperature-prone abnormal location and the fourth weight of each corresponding temperature-prone abnormal time period to obtain a third product, and select the maximum third product from each third product; Determine the temperature abnormality time period corresponding to the maximum third product of each temperature abnormality location as the reference abnormality time period, and count the number of time periods of the reference abnormality time period in the next monitoring time; If the number of time periods is less than the preset number threshold, a monitoring frequency adjustment reminder is sent to the terminal of the operation and maintenance manager.

[0071] It should be noted that the operation and maintenance management device of an intelligent switch cabinet provided in the above embodiment only uses the division of the above functional modules as an example when executing the operation and maintenance management method of the intelligent switch cabinet. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the operation and maintenance management device of an intelligent switch cabinet provided in the above embodiment and the operation and maintenance management method embodiment of an intelligent switch cabinet belong to the same concept, and the implementation process thereof is detailed in the method embodiment, which will not be repeated here.

[0072] An embodiment of the present application further discloses a computer-readable storage medium, and the computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, an operation and maintenance management method of an intelligent switch cabinet of the above embodiment is adopted.

[0073] Among them, the computer program can be stored in a computer-readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or certain middleware, etc. The computer-readable medium includes any entity or device that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the computer-readable medium includes but is not limited to the above-mentioned components.

[0074] Among them, through this computer-readable storage medium, an operation and maintenance management method of an intelligent switch cabinet in the above embodiment is stored in a computer-readable storage medium, and is loaded and executed on a processor to facilitate the storage and application of the above method.

[0075] An embodiment of the present application further discloses an electronic device, in which a computer program is stored in a computer-readable storage medium. When the computer program is loaded and executed by a processor, the above-mentioned operation and maintenance management method of an intelligent switch cabinet is adopted.

[0076] The electronic device may be a desktop computer, a laptop computer, a cloud server or other electronic device, and the electronic device includes but is not limited to a processor and a memory. For example, the electronic device may also include input and output devices, a network access device, and a bus.

[0077] Among them, the processor can adopt a central processing unit (CPU). Of course, according to actual usage, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be adopted. The general-purpose processor can adopt a microprocessor or any conventional processor, etc., and this application does not impose any restrictions on this.

[0078] Among them, the memory can be an internal storage unit of the electronic device, such as a hard disk or memory of the electronic device, or it can be an external storage device of the electronic device, such as a plug-in hard disk, a smart memory card (SMC), a secure digital card (SD) or a flash memory card (FC) equipped on the electronic device. Moreover, the memory can also be a combination of an internal storage unit and an external storage device of the electronic device. The memory is used to store computer programs and other programs and data required by the electronic device. The memory can also be used to temporarily store data that has been output or is to be output, and this application does not impose any restrictions on this.

[0079] Among them, through this electronic device, an operation and maintenance management method of an intelligent switch cabinet in the above embodiment is stored in the memory of the electronic device, and is loaded and executed on the processor of the electronic device for easy use.

[0080] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. An operation and maintenance management method for an intelligent switch cabinet, characterized in that: The method comprises: Obtain the geographical location information of the intelligent switch cabinet; Determining, based on the geographic location information, an appropriate monitoring frequency corresponding to environmental data of at least one dimension; According to each of the suitable monitoring frequencies, at least one environmental data of a corresponding dimension of the intelligent switch cabinet is acquired, and each of the environmental data is compared with a corresponding environmental data threshold; If there is environmental data exceeding the corresponding environmental data threshold, the corresponding environmental data is determined as abnormal environmental data, and based on the abnormal environmental data, the operating state of the intelligent switch cabinet is adjusted to enable the intelligent switch cabinet to operate normally.

2. The operation and maintenance management method of the intelligent switch cabinet according to claim 1 is characterized in that: The adjusting the operating state of the intelligent switch cabinet based on the abnormal environment data specifically includes: If the abnormal environment data is abnormal temperature data and abnormal humidity data in the intelligent switch cabinet, turning on the dehumidification device in the intelligent switch cabinet; Determine a first wind direction from a temperature abnormality location in the intelligent switch cabinet to a humidity abnormality location in the intelligent switch cabinet, and perform ventilation processing through a cooling fan in the intelligent switch cabinet according to the first wind direction; If the abnormal environment data is abnormal temperature data in the intelligent switch cabinet, the location with abnormal temperature is determined as a first key location, and based on at least one location in the intelligent switch cabinet where humidity is prone to abnormality, a second wind direction from the first key location to the location where humidity is prone to abnormality is determined, and based on the second wind direction, ventilation is performed by the cooling fan, and the location where humidity is prone to abnormality is a location in the intelligent switch cabinet where humidity is prone to abnormality; If the abnormal environmental data is abnormal humidity data in the intelligent switch cabinet, the location with abnormal humidity is determined as the second key location, and based on at least one location with easily abnormal temperature in the intelligent switch cabinet, a third wind direction from the second key location to the location with easily abnormal temperature is determined. Based on the third wind direction, ventilation is performed by the cooling fan, and the dehumidification device is turned on. The location with easily abnormal temperature is a location in the intelligent switch cabinet where abnormal temperature is likely to occur.

3. The operation and maintenance management method of the intelligent switch cabinet according to claim 2 is characterized in that: The determining, based on at least one humidity prone abnormal location in the intelligent switch cabinet, a second wind direction from the first key location to the humidity prone abnormal location specifically includes: Obtain the first historical location where humidity abnormality occurs in the intelligent switch cabinet in the historical season, count the first occurrence times of each of the first historical locations, and select the first historical location with the first occurrence times from each of the first historical locations in descending order to determine it as the location prone to humidity abnormality, wherein the historical season is the same as the current season; Counting the first historical period in which humidity abnormality occurs in each of the humidity-prone abnormal parts, counting the second occurrence number of each first historical period, and selecting the first historical period with the second number from each of the first historical periods in descending order of the second occurrence number to determine as the humidity abnormality period of the corresponding humidity-prone abnormal part; Calculate the first weight of each of the humidity prone abnormal parts and the second weight of each of the corresponding humidity prone abnormal time periods, wherein the first weight is the ratio of the first occurrence number of each humidity prone abnormal part to the sum of the first occurrence numbers of all humidity prone abnormal parts, and the second weight is the ratio of the second occurrence number of a single humidity prone abnormal time period corresponding to the humidity prone abnormal part to the sum of the second occurrence numbers of all corresponding humidity prone abnormal time periods; Based on the first weight and the corresponding second weights, a second wind direction from the first key location to the location prone to abnormal humidity is determined.

4. The operation and maintenance management method of the intelligent switch cabinet according to claim 3 is characterized in that: The determining, based on the first weight and the corresponding second weights, the second wind direction from the first key location to the location prone to abnormal humidity specifically includes: If the current time is within the humidity abnormality time period, the humidity abnormality time period at the current time is determined as the first key time period, and the humidity abnormality portion in the first key time period in each corresponding humidity abnormality time period is determined as the first key abnormal portion; Calculate the first product of the first weight of each of the first key abnormal parts and the second weight of the corresponding first key time period, determine the maximum first product from each of the first products, and determine the wind direction from the first key part to the first key abnormal part corresponding to the maximum first product as the second wind direction; If the current time is not within the humidity abnormality period, determine the target ventilation duration according to the temperature abnormality data of the first key part, and determine the ventilation period according to the target ventilation duration and the current time; Determine the humidity prone abnormal period in the ventilation period among the humidity prone abnormal period corresponding to each humidity prone abnormal part as the target abnormal period, and calculate the product of the first weight of each humidity prone abnormal part and the corresponding second weight of each target abnormal period and sum them to obtain the corresponding sum of the first products; The maximum sum of the first products is determined from the sums of the first products, and the wind direction from the first key location to the location with abnormal humidity corresponding to the maximum sum of the first products is determined as the second wind direction.

5. The operation and maintenance management method of the intelligent switch cabinet according to claim 2 is characterized in that: The determining, based on at least one temperature-prone location in the intelligent switch cabinet, a third wind direction from the second key location to the temperature-prone location specifically includes: Obtain the second historical position where the temperature abnormality occurs in the intelligent switch cabinet in the historical season, count the first occurrence frequency of each second historical position, and select the third second historical position from each second historical position in descending order of the first occurrence frequency to determine it as the temperature prone abnormal position, and the historical season is the same as the current season; Obtaining the second historical period in which the temperature abnormality occurs at each of the temperature-prone parts, counting the second occurrence frequency of each second historical period, and selecting the fourth number of second historical periods from each of the second historical periods in descending order of the second occurrence frequency to determine as the temperature abnormality period of the corresponding temperature abnormality part; Calculate the third weight of each of the temperature-prone abnormal parts and the fourth weight of each of the corresponding temperature-prone abnormal time periods, wherein the third weight is the ratio of the first occurrence frequency of each temperature-prone abnormal part to the sum of the first occurrence frequencies of all temperature-prone abnormal parts, and the fourth weight is the ratio of the second occurrence frequency of a single temperature-prone abnormal time period corresponding to the temperature-prone abnormal part to the sum of the second occurrence frequencies of all corresponding temperature-prone abnormal time periods; Based on the third weight and the corresponding fourth weights, a third wind direction from the second key location to the location prone to temperature abnormality is determined.

6. The operation and maintenance management method of the intelligent switch cabinet according to claim 5, characterized in that: The determining, based on the third weight and the corresponding fourth weights, the third wind direction from the second key location to the location prone to abnormal temperature specifically includes: Determine the temperature abnormality time period at the current time as the second key time period, and determine the temperature abnormality location at the second key time period in each corresponding temperature abnormality time period as the second key abnormal location; Calculate the second product of the third weight of each of the second key abnormal parts and the fourth weight of the corresponding second key time period, and select the maximum second product and the minimum second product from each of the second products; The wind direction from the second key position to the second key abnormal position corresponding to the minimum second product is determined as the first initial wind direction. If there is a dry position downstream of the second key abnormal position corresponding to the minimum second product under the first initial wind direction, the first initial wind direction is determined as the third wind direction. The dry position is a position in the intelligent switch cabinet where the humidity data is less than a preset dry-wet critical threshold, and the dry-wet critical threshold is a critical value for judging whether the position is dry. The wind direction from the second key position to the second key abnormal position corresponding to the maximum second product is determined as the second initial wind direction. If, under the second initial wind direction, there is a dry area between the second key abnormal position corresponding to the maximum second product and the second key position, the second initial wind direction is determined as the third wind direction.

7. The operation and maintenance management method of the intelligent switch cabinet according to claim 5, characterized in that: The method further comprises: Determine the next monitoring time of the environmental data of the temperature dimension in the intelligent switch cabinet according to the appropriate monitoring frequency corresponding to the temperature dimension; Calculate the product of the third weight of each of the temperature-prone abnormal parts and the fourth weight of each of the corresponding temperature-prone abnormal time periods to obtain a third product, and select the maximum third product from the third weight products; Determine the temperature abnormality time period corresponding to the maximum third product of each temperature abnormality-prone part as a reference abnormality time period, and count the number of time periods in which the reference abnormality time period exists at the next monitoring time; If the number of time periods is less than a preset number threshold, a monitoring frequency adjustment reminder is sent to the terminal of the operation and maintenance management personnel.

8. An operation and maintenance management device for an intelligent switch cabinet, characterized in that: include: An information acquisition module (11) is used to acquire geographical location information of the intelligent switch cabinet; A frequency determination module (12), configured to determine, based on the geographic location information, an appropriate monitoring frequency corresponding to environmental data of at least one dimension; An environmental monitoring module (13) is used to obtain at least one environmental data of a corresponding dimension of the intelligent switch cabinet according to each of the suitable monitoring frequencies, and compare each of the environmental data with a corresponding environmental data threshold; The operation and maintenance management module (14) is used to determine the corresponding environmental data as abnormal environmental data if there is environmental data exceeding the corresponding environmental data threshold, and adjust the operating state of the intelligent switch cabinet based on the abnormal environmental data to enable the intelligent switch cabinet to operate normally.

9. A computer-readable storage medium having a computer program stored therein, characterized in that: When the computer program is loaded and executed by a processor, the method according to any one of claims 1 to 7 is adopted.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that: When the processor loads and executes the computer program, the method according to any one of claims 1 to 7 is adopted.

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