Coal mine enterprise regional power consumption abnormity grading early warning system based on space GIS

Abstract

The invention discloses a coal mine enterprise area power consumption abnormity grading early warning system based on a space GIS, and the system comprises an acquisition and analysis module which is used for collecting the related data of a coal mine enterprise area based on a space GIS technology, dividing the coal mine enterprise area, obtaining the data of a coal mine enterprise area group, and transmitting the data to other modules; the abnormity setting module is used for setting the standard power consumption condition of each coal mine enterprise area group based on the data of the coal mine enterprise area group in combination with the historical power consumption analysis characteristics; the condition acquisition module is used for acquiring power consumption data of the coal mine enterprise areas and obtaining the power consumption condition of each coal mine enterprise area group based on the standard power consumption condition; and the grading early warning module is used for determining grading early warning information of the coal mine enterprise area group and comprehensive early warning information of the coal mine enterprise area based on the power consumption condition of the coal mine enterprise area group. According to the invention, a coal mine enterprise can rapidly respond and take measures, multiple risks caused by abnormal power consumption are effectively restrained, and stable operation of a power system is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of electric power big data, and in particular to a spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system. Background Art

[0002] With the rapid development of the coal industry, coal mining enterprises, as an important pillar of energy supply, have a direct relationship with national energy security and economic development in terms of the stability and efficiency of their production and operation. However, while pursuing efficient production, coal mining enterprises are also facing the severe challenge of abnormal regional power consumption. Abnormal power consumption not only erodes the healthy operation of the power system, but also increases the risks of equipment damage, personnel safety and production safety, becoming a key factor restricting the sustainable development of coal mining enterprises. Therefore, building an efficient and accurate power consumption monitoring and analysis system to timely discover and solve abnormal power consumption problems has become an important issue that coal mining enterprises need to solve urgently.

[0003] Currently, existing technologies are designed to optimize electricity consumption configuration and reduce costs, but they still have obvious limitations in practical applications. Especially for coal mining enterprises, this method fails to accurately locate regional power consumption anomalies, resulting in a significant reduction in analysis efficiency and accuracy. The complexity and dynamics of regional power consumption require more sophisticated monitoring methods and analysis models to achieve rapid identification and precise intervention of power consumption anomalies. Therefore, existing technologies are still insufficient in meeting the actual needs of coal mining enterprises and improving the efficiency of power consumption management, and innovative breakthroughs are urgently needed. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system to solve the problem of lack of accurate positioning and classification management in coal mine enterprise regional power consumption abnormality monitoring and early warning.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides a spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system, comprising:

[0008] The collection and analysis module is used to collect data related to the coal mining enterprise area based on the spatial GIS technology, divide the coal mining enterprise area based on the relevant data, obtain the coal mining enterprise area group data and send it to the abnormal setting module, the situation acquisition module and the graded warning module;

[0009] The abnormal setting module is used to set the standard power consumption of each coal mine enterprise regional group based on the coal mine enterprise regional group data and the historical power consumption analysis characteristics and send it to the situation acquisition module;

[0010] The situation acquisition module is used to collect the electricity consumption data of the coal mining enterprise area, and based on the standard power consumption situation, obtain the power consumption situation of each coal mining enterprise area group and send it to the hierarchical early warning module;

[0011] The hierarchical warning module is used to determine the hierarchical warning information of the coal mine enterprise regional group and the comprehensive warning information of the coal mine enterprise region based on the power consumption of the coal mine enterprise regional group.

[0012] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system described in the present invention, wherein: the collection and analysis module includes:

[0013] Obtaining the initial cluster center through the center determination unit;

[0014] Using a judgment unit to perform cluster analysis on the coal mining enterprise region-related data according to the initial cluster center to obtain a target spatial data group;

[0015] Based on the corresponding relationship between the unique regional features and the standard spatial data, the coal mining enterprise area is divided by the division unit to obtain the coal mining enterprise area group corresponding to the target spatial data group.

[0016] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system described in the present invention, the abnormal setting module includes:

[0017] Based on the historical power consumption analysis characteristics, the normal range of historical power consumption and the abnormal range of historical power consumption are determined through the analysis unit, and the hazard type value under the abnormal range of historical power consumption is obtained;

[0018] Using a processing unit to average the normal range of historical power consumption, and setting a standard power consumption range according to the processing result;

[0019] The evaluation unit comprehensively evaluates the hazard type values ​​and sets the power consumption abnormality level according to the evaluation result.

[0020] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system described in the present invention, wherein: the evaluation unit includes a weight evaluation unit, a level division unit and a setting unit;

[0021] Assign a hazard impact weight to each hazard type through a weight assessment unit, and determine a comprehensive assessment value for all hazard types based on the hazard impact weight;

[0022] Based on the preset hazard level classification information, the comprehensive evaluation value is divided into a plurality of hazard level levels by using a level classification unit;

[0023] Based on the relationship between the comprehensive evaluation value and the historical power consumption abnormal range, combined with the hazard level, the power consumption abnormal level of the historical power consumption abnormal range is set using the setting unit.

[0024] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system described in the present invention, wherein: the situation acquisition module includes:

[0025] Acquire electricity consumption data of the coal mining enterprise area through a data processing unit, perform standardization processing on the electricity consumption data, and obtain target electricity consumption data;

[0026] Determining the power consumption of the coal mining enterprise regional group from the target power consumption data using the power consumption determination unit;

[0027] Based on the standard power consumption range and the power consumption range abnormal level, the power consumption situation corresponding to the power consumption of the regional group of the coal mining enterprise is determined by the situation determination unit.

[0028] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormal graded early warning system described in the present invention, the graded early warning module includes:

[0029] Based on the power consumption of all coal mining enterprise regional groups, an abnormality determination unit is used to determine the abnormality level of the actual power consumption range of the coal mining enterprise regional group;

[0030] Based on the location information of the coal mine enterprise regional group in the coal mine enterprise area, a regional group distribution map is established through a distribution determination unit, and the abnormal level of the actual power consumption range of the coal mine enterprise regional group is marked on the regional group distribution map, and an abnormal level distribution map is established according to the marking result;

[0031] Using a weight determination unit to obtain a first distribution feature of regions of the same type from the region group distribution map, obtain a second distribution feature between adjacent regions, and determine a group weight of the region group based on the first distribution feature, and determine a region weight of each region based on the second distribution feature;

[0032] Based on the target area weight and the level weight of each area, a warning level for each area is determined by a level determination unit;

[0033] The information determination unit integrates the warning level, the abnormal level of the actual power consumption range and the location information to establish graded warning information.

[0034] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system described in the present invention, wherein: the weight determination unit includes a difference determination unit and a regional weight determination unit,

[0035] A difference determination unit, configured to obtain a region group feature of a current region, obtain a region group feature of an adjacent region of the current region, and determine a group difference feature between the region group feature of the adjacent region and the region group feature of the current region;

[0036] The regional weight determination unit is used to determine the position of the inter-group difference feature in a preset difference feature range level, determine the difference feature range level, and determine the regional weight of each region based on the difference feature range level.

[0037] As a preferred solution of the spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system described in the present invention, it also includes:

[0038] The weight determination unit is further used to determine the target area weight of each area based on the group weight and the area weight;

[0039] The weight determination unit is further used to determine the level weight of each area based on the level distribution characteristics between adjacent areas of the abnormal level distribution diagram.

[0040] In a second aspect, the present invention provides a computing device, comprising:

[0041] Memory and processor;

[0042] The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions. When the computer executable instructions are executed by the processor, the steps of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system are implemented.

[0043] In a third aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system.

[0044] Compared with the prior art, the present invention has the following beneficial effects: the present invention integrates spatial GIS technology to systematically and accurately collect spatial data of coal mining enterprise areas, and realizes regional clustering and division in combination with enterprise information to form refined management of coal mining enterprise regional groups. Based on historical electricity consumption data, standard power consumption ranges and abnormal levels are tailored for each regional group, which realizes the accurate definition of abnormal power consumption. The system monitors the power consumption data of each region in real time, quickly compares the standard range, automatically determines the power consumption situation, and immediately triggers the graded early warning mechanism once an abnormality is found. This mechanism not only ensures the timeliness of the early warning, but also improves management efficiency and pertinence through graded processing, so that coal mining enterprises can respond quickly and take measures to effectively curb the multiple risks brought about by abnormal power consumption, ensure the stable operation of the power system, reduce equipment damage, and ensure personnel and production safety. At the same time, it reduces the difficulty of management and helps enterprises achieve a win-win situation of economic benefits and safe production. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0046] Figure 1 It is a schematic diagram of the overall process of a spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system according to an embodiment of the present invention;

[0047] Figure 2 A schematic diagram of the structure of a spatial GIS-based coal mining enterprise regional power consumption abnormality classification early warning system according to an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of a collection and analysis module of a spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system according to an embodiment of the present invention;

[0049] Figure 4 The present invention is a schematic diagram of an abnormality setting module of a spatial GIS-based coal mining enterprise regional power consumption abnormality classification early warning system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0051] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0052] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0053] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0054] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0055] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] Example 1

[0057] Reference Figure 1-4 , which is an embodiment of the present invention, provides a spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system, including:

[0058] S100: a collection and analysis module, which is used to collect data related to coal mine enterprise regions based on spatial GIS technology, divide coal mine enterprise regions based on the relevant data, obtain coal mine enterprise regional group data and send it to the abnormal setting module, the situation acquisition module and the graded warning module;

[0059] It should be noted that the data related to the coal mining enterprise area include the spatial data of the coal mining enterprise area and the enterprise information of the coal mining enterprise area, among which the enterprise information of the coal mining enterprise area includes, for example, information on coal mining faces, tunnels, surface coal preparation plants, coal mine power plants, coal mine substations, coal mine railways, etc.

[0060] Preferably, an initial cluster center is obtained by a center determination unit; a cluster analysis is performed on the coal mining enterprise region-related data according to the initial cluster center by a judgment unit to obtain a target spatial data group; based on the correspondence between the unique regional characteristics and the standard spatial data, the coal mining enterprise region is divided by a division unit to obtain a coal mining enterprise region group corresponding to the target spatial data group;

[0061] Specifically, the collection and analysis module includes a collection unit, an input unit, a mapping unit, a relationship determination unit, a system establishment unit, a center determination unit, a judgment unit, and a division unit;

[0062] The collection unit is used to collect geographic information data of the coal mining enterprise area based on spatial GIS technology;

[0063] An input unit, used for inputting geographic information data into a digital three-dimensional scene;

[0064] A mapping unit is used to coordinate map the geographic information data in a digital three-dimensional scene to obtain spatial data of the coal mining enterprise area;

[0065] A relationship determination unit is used to obtain the regional operation type from the enterprise information of the coal mining enterprise area, obtain the unique regional characteristics of the regional operation type, and establish a corresponding relationship between the unique regional characteristics and the standard spatial data;

[0066] A system establishment unit, used to establish the index range of the spatial data evaluation index of regional division based on the corresponding relationship, and to establish the spatial data evaluation index system of regional division in combination with the index attributes of the spatial data evaluation index;

[0067] A center determination unit is used to determine the number of cluster centers based on the regional operation type, and obtain the initial cluster centers of the number of cluster centers from the spatial data based on the spatial data evaluation index system;

[0068] A judgment unit, used to perform cluster analysis on the spatial data according to the initial cluster center to obtain multiple spatial data groups, determine the closest distance from the spatial data of each spatial data group to the initial cluster center, and judge whether the closest distance of each spatial data group is less than a preset distance;

[0069] If so, determine the initial cluster center as the target cluster center, and use the multiple spatial data groups as the target spatial data groups;

[0070] Otherwise, based on the difference between the nearest distance and the preset distance, the initial cluster center of the regional operation type whose nearest distance is not less than the preset distance is adjusted to obtain the latest cluster center, and based on the association relationship between the spatial data and the position of the latest cluster center, the initial cluster center of other regional operation types is adjusted to obtain the latest cluster center, and the spatial data is clustered based on the latest cluster center to obtain the target spatial data group;

[0071] The division unit is used to divide the coal mining enterprise area based on the corresponding relationship between the unique regional characteristics and the standard spatial data, and obtain the coal mining enterprise area group corresponding to the target spatial data group.

[0072] It should be noted that by combining the spatial information of coal mining enterprise areas with power consumption data through GIS technology, the coal mining enterprise areas are clustered and divided to obtain coal mining enterprise regional groups, thereby realizing the division of coal mining enterprise areas. This provides an accurate regional information basis for subsequent coal mining enterprise regional power consumption abnormal graded warning, and ensures the accuracy of the warning information for each determined area.

[0073] S102: an abnormality setting module, which is used to set the standard power consumption of each coal mine enterprise regional group based on the coal mine enterprise regional group data and in combination with the historical power consumption analysis characteristics and send it to the situation acquisition module;

[0074] Specifically, the abnormal setting module includes an analysis unit, a processing unit, and an evaluation unit;

[0075] Preferably, based on the historical power consumption analysis characteristics, the historical power consumption normal range and the historical power consumption abnormal range are determined by the analysis unit, and the hazard type value under the historical power consumption abnormal range is obtained; the historical power consumption normal range is averaged by the processing unit, and the standard power consumption range is set according to the processing result; the hazard type value is comprehensively evaluated by the evaluation unit, and the power consumption abnormal level is set according to the evaluation result;

[0076] Preferably, the evaluation unit includes a weight evaluation unit, a level division unit and a setting unit; the weight evaluation unit assigns a hazard impact weight to each hazard type, and determines a comprehensive evaluation value for all hazard types based on the hazard impact weight; based on preset hazard level classification information, the level division unit divides the comprehensive evaluation value into multiple hazard level levels; based on the relationship between the comprehensive evaluation value and the historical power consumption abnormal range, combined with the hazard level, the setting unit sets the power consumption abnormality level of the historical power consumption abnormal range;

[0077] It should be noted that by assigning a hazard impact weight to each hazard type, a comprehensive assessment value for all hazard types is determined based on the hazard impact weight, and based on the preset hazard level classification information, the comprehensive assessment value is divided into multiple hazard level levels. Based on the relationship between the comprehensive assessment value and the historical power consumption abnormal range, combined with the hazard level, the power consumption abnormality level of the historical power consumption abnormal range is set, providing a basis for further regional power consumption abnormality classification early warning of coal mining enterprises.

[0078] S104: a situation acquisition module, which is used to collect the electricity consumption data of the coal mining enterprise area, and based on the standard power consumption situation, obtain the power consumption situation of each coal mining enterprise area group and send it to the hierarchical early warning module;

[0079] Preferably, the power consumption data of the coal mining enterprise area is obtained by the data processing unit, and the power consumption data is standardized to obtain the target power consumption data; the power consumption determination unit is used to determine the power consumption of the coal mining enterprise regional group from the target power consumption data; based on the standard power consumption range and the power consumption range abnormal level, the power consumption situation corresponding to the power consumption of the coal mining enterprise regional group is determined by the situation determination unit;

[0080] The situation determination unit includes a selection unit and a matching unit.

[0081] A selection unit is used to select a target standard power consumption range and a target power consumption range abnormality level of the coal mining enterprise regional group from the standard power consumption range and the power consumption range abnormality level based on the regional type of the coal mining enterprise regional group;

[0082] The matching unit is used to determine the corresponding range of power consumption that meets the target standard power consumption range and the target power consumption range abnormal level as the power consumption situation of the coal mine enterprise regional group.

[0083] It should be noted that the power consumption situation includes normal power consumption or abnormal power consumption and their abnormal levels.

[0084] S106: A hierarchical warning module, used to determine hierarchical warning information of the coal mine enterprise regional group and comprehensive warning information of the coal mine enterprise region based on the power consumption of the coal mine enterprise regional group;

[0085] Preferably, based on the power consumption of all coal mining enterprise regional groups, an abnormality determination unit is used to determine the abnormality level of the actual power consumption range of the coal mining enterprise regional group; based on the location information of the coal mining enterprise regional group in the coal mining enterprise area, a regional group distribution map is established through a distribution determination unit, and the abnormality level of the actual power consumption range of the coal mining enterprise regional group is marked in the regional group distribution map, and an abnormality level distribution map is established according to the marking result;

[0086] Preferably, a weight determination unit is used to obtain a first distribution feature of regions of the same type from a region group distribution map, obtain a second distribution feature between adjacent regions, and determine a group weight of the region group based on the first distribution feature, and determine a region weight of each region based on the second distribution feature; a warning level for each region is determined by a level determination unit based on a target region weight and a level weight of each region; and a graded warning information is established by an information determination unit by integrating the warning level, the abnormal level of the actual power consumption range, and the location information;

[0087] Preferably, the weight determination unit includes a difference determination unit and a regional weight determination unit, the difference determination unit is used to obtain the regional group features of the current region, and obtain the regional group features of the adjacent regions of the current region, and determine the inter-group difference features between the regional group features of the adjacent regions and the regional group features of the current region; the regional weight determination unit is used to determine the position of the inter-group difference features in a preset difference feature range level, determine the difference feature range level, and determine the regional weight of each region based on the difference feature range level;

[0088] Preferably, the weight determination unit is further used to determine the target area weight of each area based on the group weight and the area weight; the weight determination unit is further used to determine the level weight of each area based on the level distribution characteristics between adjacent areas of the abnormal level distribution map;

[0089] In the embodiment of the present application, the hierarchical warning module further includes a sequence determination unit and an integration unit;

[0090] A sequence determination unit, for establishing a warning sequence based on the warning level in the hierarchical warning information of each area;

[0091] An integration unit is used to integrate the hierarchical warning information of each area according to the warning sequence to obtain comprehensive warning information of the coal mining enterprise area;

[0092] It should be noted that, based on the power consumption of all coal mine enterprise regional groups, the actual power consumption range abnormal level of the coal mine enterprise regional group is determined, based on the location information of the coal mine enterprise regional group in the coal mine enterprise area, a regional group distribution map is established, and the actual power consumption range abnormal level of the coal mine enterprise regional group is marked in the regional group distribution map, and an abnormal level distribution map is established according to the marking result, the first distribution feature of the same type of area is obtained from the regional group distribution map, the second distribution feature between adjacent areas is obtained, and the group weight of the regional group is determined based on the first distribution feature, the regional weight of each area is determined based on the second distribution feature, and the target area weight of each area is determined based on the group weight and the area weight, which is used to determine the level weight of each area based on the level distribution feature between adjacent areas of the abnormal level distribution map, and the warning level for each area is determined based on the target area weight and the level weight of each area, and the warning level, the actual power consumption range abnormal level and location information are used to establish graded warning information, and the spatial information of the coal mine enterprise area is combined with the power consumption data through GIS technology to monitor and analyze the power consumption of each area in real time. The system can automatically identify the power consumption abnormal area and give graded warning to the abnormality according to the preset classification standard, so as to ensure the normal operation of the coal mine enterprise.

[0093] The above is a schematic scheme of a spatial GIS-based coal mine enterprise regional power consumption abnormality classification warning system of this embodiment. It should be noted that the technical scheme of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification warning device and the above-mentioned spatial GIS-based coal mine enterprise regional power consumption abnormality classification warning system belong to the same concept. The details of the technical scheme of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification warning device that are not described in detail in this embodiment can all be referred to the description of the technical scheme of the spatial GIS-based coal mine enterprise regional power consumption abnormality classification warning system.

[0094] This embodiment also provides a computing device, which is applicable to the situation of abnormal graded warning of regional power consumption in coal mining enterprises based on spatial GIS, including:

[0095] Memory and processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system as proposed in the above embodiment.

[0096] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the spatial GIS-based coal mine enterprise regional power consumption abnormality classification early warning system is implemented as proposed in the above embodiment.

[0097] The storage medium proposed in this embodiment and the spatial GIS-based coal mine enterprise regional power consumption abnormality classification warning system proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0098] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ReadOnly, Memory, ROM), random access memory (RandomAccess Memory, RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform the methods of various embodiments of the present invention.

[0099] Example 2

[0100] Reference Figure 1 , which is an embodiment of the present invention, provides a spatial GIS-based coal mining enterprise regional power consumption abnormal classification early warning system. In order to verify its beneficial effects, the experimental parameters of the present invention are provided.

[0101] Firstly, based on spatial GIS technology, the spatial data of coal mining enterprise areas are collected through the collection and analysis module, and the coal mining enterprise areas are clustered and divided according to the enterprise information of the coal mining enterprise areas to obtain the coal mining enterprise area groups;

[0102] Specifically, the regional operation type is obtained, wherein the regional operation type includes coal mining area, transportation area and processing area, etc.; based on the regional operation type, the unique regional features are obtained, such as the unique regional features of the coal mining area are coal mining machines, the unique regional features of the transportation area are transportation vehicles, and the unique regional features of the processing area are processing equipment;

[0103] The corresponding relationship between the unique regional features and the standard spatial data is established through the relationship determination unit. The corresponding relationship between the unique regional features and the standard spatial data is the corresponding relationship between the features and the geographic data.

[0104] A spatial data evaluation index system for regional division is established through a system establishment unit; the index range of the spatial data evaluation index for regional division, for example, the evaluation index corresponding to the first spatial data is the number of coal mining machines, and the index range is 10 vehicles. The evaluation index is set according to the unique regional characteristics, and the index range can be dynamically set according to the actual situation; the spatial data evaluation index system is a standard for judging a type of spatial data composed of evaluation index ranges of multiple indicator attributes.

[0105] Cluster analysis is performed using these determination units, judgment units, and division units in the acquisition and analysis module. The initial cluster center of the regional operation type whose nearest distance is not less than the preset distance is adjusted in a way that can be an iterative optimization process based on the K-means algorithm, or in a more complex cluster analysis tool such as the cluster position adjustment mode of CiteSpace.

[0106] Secondly, based on the historical power consumption analysis characteristics, the abnormal setting module is used to set the standard power consumption range and power consumption abnormality level for each coal mining enterprise regional group;

[0107] Specifically, a hazard impact weight is assigned to each hazard type and is set according to the actual situation. For example, the hazard impact weight of equipment damage is 0.8, the hazard impact weight of personnel safety is 0.9, the hazard impact weight of production safety is 0.9, and the hazard impact weight of management impact is 0.7;

[0108] The comprehensive evaluation value of all hazard type values ​​is determined based on the hazard impact weights, for example, by accumulating the products of all hazard type values ​​and the corresponding hazard impact weights to obtain a comprehensive evaluation value.

[0109] Based on the relationship between the comprehensive assessment value and the historical power consumption abnormal range, combined with the hazard level, the power consumption abnormal level of the historical power consumption abnormal range is set. For example, the comprehensive assessment value is 4.5, and the corresponding historical power consumption abnormal range is 3-5; the comprehensive assessment value is 7.5, the hazard level is level two, and the corresponding historical power consumption abnormal range is 8-10; the hazard level is level five, and the historical power consumption abnormal range is unified to represent the degree, not the specific value. The determined historical power consumption abnormal range is 3-5, and the hazard level is level two; the historical power consumption abnormal range is 8-10, and the hazard level is level five.

[0110] Then, based on the historical power consumption analysis characteristics, the abnormal setting module is used to set the standard power consumption range and power consumption abnormality level for each coal mining enterprise regional group;

[0111] Finally, based on the power consumption of all coal mine enterprise regional groups, the hierarchical warning information of coal mine enterprise regional groups and the comprehensive warning information of coal mine enterprise regions are determined through the hierarchical warning module;

[0112] Specifically, obtaining the first distribution feature of the same type of area from the area group distribution map is, for example, obtaining the distribution feature of the coal mining area, the distribution feature including the abnormal power consumption level, obtaining the second distribution feature between adjacent areas, for example, the coal mining area and the transportation area are adjacent areas, and obtaining the distribution of the abnormal power consumption levels of the coal mining area and the transportation area;

[0113] Determine the group weight of the regional group based on the first distribution feature. For example, if the abnormal power consumption level distribution of the coal mining area is above 5, the group weight of the coal mining area is set to 0.8; if the abnormal power consumption level distribution of the transportation area is below 5, the group weight of the transportation area is set to 0.5;

[0114] The regional weight of each area is determined based on the second distribution feature. For example, among the adjacent coal mining areas and transportation areas, the abnormal power consumption level of the coal mining area is 6, and the abnormal power consumption level of the transportation area is 3. Then the regional weight of the coal mining area is set to 0.7, and the regional weight of the transportation area is set to 0.5.

[0115] The target area weight of each area is, for example, the sum of the group weight and the area weight. If the level difference between the level distribution characteristics of adjacent areas of the abnormal level distribution map is small, the level weight of each area is small, and if the level difference is large, the level weight of each area is large. The higher the target area weight and the level weight, the higher the corresponding warning level.

[0116] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A spatial GIS-based coal mining enterprise regional power consumption abnormal classification early warning system, characterized in that: include: The collection and analysis module is used to collect regional data related to coal mine enterprises based on spatial GIS technology, divide the coal mine enterprise regions based on the relevant data, obtain regional group data of coal mine enterprises and send it to the abnormal setting module, the situation acquisition module and the graded warning module; The abnormal setting module is used to set the standard power consumption of each coal mine enterprise regional group based on the coal mine enterprise regional group data and combined with the historical power consumption analysis characteristics and send it to the situation acquisition module; The situation acquisition module is used to collect the electricity consumption data of the coal mining enterprise area, and based on the standard power consumption situation, obtain the power consumption situation of each coal mining enterprise area group and send it to the hierarchical early warning module; The hierarchical warning module is used to determine the hierarchical warning information of the coal mine enterprise regional group and the comprehensive warning information of the coal mine enterprise region based on the power consumption of the coal mine enterprise regional group.

2. The spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system as claimed in claim 1 is characterized in that: The acquisition and analysis module includes: Obtaining the initial cluster center through the center determination unit; Using a judgment unit to perform cluster analysis on the coal mining enterprise region-related data according to the initial cluster center to obtain a target spatial data group; Based on the corresponding relationship between the unique regional features and the standard spatial data, the coal mining enterprise area is divided by the division unit to obtain the coal mining enterprise area group corresponding to the target spatial data group.

3. The spatial GIS-based coal mining enterprise regional power consumption abnormality classification early warning system as claimed in claim 1 or 2, characterized in that: The exception setting module includes: Based on the historical power consumption analysis characteristics, the normal range of historical power consumption and the abnormal range of historical power consumption are determined through the analysis unit, and the hazard type value under the abnormal range of historical power consumption is obtained; Using a processing unit to average the normal range of historical power consumption, and setting a standard power consumption range according to the processing result; The evaluation unit comprehensively evaluates the hazard type values ​​and sets the power consumption abnormality level according to the evaluation result.

4. The spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system as claimed in claim 3 is characterized in that: The evaluation unit includes a weight evaluation unit, a grade classification unit and a setting unit; Assign a hazard impact weight to each hazard type through a weight assessment unit, and determine a comprehensive assessment value for all hazard types based on the hazard impact weight; Based on the preset hazard level classification information, the comprehensive evaluation value is divided into a plurality of hazard level levels by using a level classification unit; Based on the relationship between the comprehensive evaluation value and the historical power consumption abnormal range, combined with the hazard level, the power consumption abnormal level of the historical power consumption abnormal range is set using the setting unit.

5. The spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system as claimed in claim 4 is characterized in that: The situation acquisition module includes: Acquire electricity consumption data of the coal mining enterprise area through a data processing unit, perform standardization processing on the electricity consumption data, and obtain target electricity consumption data; Determining the power consumption of the coal mining enterprise regional group from the target power consumption data using the power consumption determination unit; Based on the standard power consumption range and the power consumption range abnormal level, the power consumption situation corresponding to the power consumption of the regional group of the coal mining enterprise is determined by the situation determination unit.

6. The spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system as claimed in claim 5 is characterized in that: The hierarchical warning module includes: Based on the power consumption of all coal mining enterprise regional groups, an abnormality determination unit is used to determine the abnormality level of the actual power consumption range of the coal mining enterprise regional group; Based on the location information of the coal mine enterprise regional group in the coal mine enterprise area, a regional group distribution map is established through a distribution determination unit, and the abnormal level of the actual power consumption range of the coal mine enterprise regional group is marked on the regional group distribution map, and an abnormal level distribution map is established according to the marking result; Using a weight determination unit to obtain a first distribution feature of regions of the same type from the region group distribution map, obtain a second distribution feature between adjacent regions, and determine a group weight of the region group based on the first distribution feature, and determine a region weight of each region based on the second distribution feature; Based on the target area weight and the level weight of each area, a warning level for each area is determined by a level determination unit; The information determination unit integrates the warning level, the abnormal level of the actual power consumption range and the location information to establish graded warning information.

7. The spatial GIS-based coal mine enterprise regional power consumption abnormal classification early warning system as claimed in claim 6 is characterized in that: The weight determination unit includes a difference determination unit and a region weight determination unit, A difference determination unit, configured to obtain a region group feature of a current region, obtain a region group feature of an adjacent region of the current region, and determine a group difference feature between the region group feature of the adjacent region and the region group feature of the current region; The regional weight determination unit is used to determine the position of the inter-group difference feature in a preset difference feature range level, determine the difference feature range level, and determine the regional weight of each region based on the difference feature range level.

8. The spatial GIS-based coal mining enterprise regional power consumption abnormal classification early warning system as claimed in claim 7 is characterized in that: Also includes, The weight determination unit is further used to determine the target area weight of each area based on the group weight and the area weight; The weight determination unit is further used to determine the level weight of each area based on the level distribution characteristics between adjacent areas of the abnormal level distribution diagram.

9. An electronic device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the spatial GIS-based coal mining enterprise regional power consumption abnormality classification early warning system as described in any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the spatial GIS-based coal mining enterprise regional power consumption abnormality classification early warning system as described in any one of claims 1 to 8.

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