Industrial heat source information expression and extraction method and device for industrial heat source objects

Abstract

The present application discloses an industrial heat source information expression extraction method for industrial heat source objects, the method comprising: obtaining multi-source long-time series thermal anomaly data and industrial heat source object data sets in a target area; constructing a complete industrial heat anomaly data set for industrial heat source objects based on the consistency of the spatiotemporal distribution of a single industrial heat source object in the multi-source long-time series thermal anomaly data; reconstructing / correcting the heat source information parameters of the complete industrial heat anomaly data set for industrial heat source objects based on the heat source information parameters of the initial multi-source long-time series thermal anomaly data set for industrial heat source objects; constructing an information expression feature descriptor for industrial heat source objects, and extracting the information expression features of industrial heat source objects based on the heat source information parameters of the complete industrial heat anomaly data set for industrial heat source objects. The present application is oriented to industrial heat source objects, designs its feature expression method, and improves the accuracy and reliability of information expression of industrial heat source objects in complex environments.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial heat source information expression extraction of industrial heat source objects, and in particular to an industrial heat source information expression extraction method and device for industrial heat source objects. Background Art

[0002] In the process of increasingly close economic globalization, the global industrial industry has made great progress, and a large number of industrial capacity clusters have emerged, which has greatly promoted the development of the global economy. However, to a certain extent, there have been structural isomorphism, uneven production capacity, and unreasonable layout and cooperation. At the same time, satellite remote sensing monitoring research has found that industrial heat emissions are the main source of regional air pollution and anthropogenic CO2 emissions. China has become a global industrial power and needs near-real-time industrial heat source spatiotemporal layout and heat emission parameter monitoring data to provide important scientific basis for my country to effectively promote "de-capacity, optimize structure", carbon tax domestic and foreign transactions, and promote international capacity cooperation. Therefore, how to balance development and emission needs, and grasp the spatiotemporal layout of my country's industrial heat sources and heat emission parameter monitoring data in real time, quickly and accurately, has become an important problem facing my country's future sustainable development.

[0003] At present, the industrial / mining enterprise data obtained through inventory methods such as statistics and field surveys are of poor timeliness, strong subjectivity, and often have large errors, which makes it difficult to meet the needs of real-time discovery of industrial heat source objects and monitoring of heat emission parameters in large areas. Recent studies have shown that thermal anomaly data obtained using remote sensing methods can characterize the production activities and production scale of industrial heat source objects, and is the most effective method for monitoring the spatiotemporal layout and changes of industrial heat sources in large areas. However, in the monitoring of industrial heat source objects based on remote sensing methods, there are still problems of inaccurate identification of industrial heat source objects and blank expression of industrial heat source information. Summary of the invention

[0004] Since the existing methods have the above-mentioned problems, the present application proposes an industrial heat source information expression and extraction method and device for industrial heat source objects.

[0005] In the first aspect, the present application proposes an industrial heat source information expression and extraction method for industrial heat source objects, including:

[0006] (1) Obtain multi-source long-term thermal anomaly data and industrial heat source object data sets in the target area;

[0007] (1-1) The multi-source long time series thermal anomaly data includes: NVNP14IMG thermal anomaly data, VNF thermal anomaly data and L8F thermal anomaly data;

[0008] (1-2) The industrial heat source object dataset is the “Ruby” industrial heat source object dataset.

[0009] (2) Based on the consistency of the spatiotemporal distribution of a single industrial heat source object in multi-source long-time series thermal anomaly data, a complete industrial thermal anomaly data set for the industrial heat source object is constructed, wherein the complete industrial thermal anomaly data set for the industrial heat source object includes an initial multi-source long-time series thermal anomaly data set for the industrial heat source object;

[0010] (2-1) constructing an initial multi-source long-time series thermal anomaly dataset for each industrial heat source object based on the regional range of the industrial heat source object dataset and the location of the multi-source long-time series thermal anomaly data;

[0011] (2-2) For each industrial heat source object, construct initial raster data with a preset temporal and spatial resolution;

[0012] (2-3) Based on the initial multi-source long-time series thermal anomaly data set for the industrial heat source object, and the preset corresponding spatiotemporal window size and the threshold value of the number of thermal anomaly data, the number of multi-source long-time series thermal anomaly data of the industrial heat source object is calculated grid by grid; if the number of multi-source long-time series thermal anomaly data within the preset corresponding spatiotemporal window in the grid unit is greater than the threshold value of the number of thermal anomaly data, the center point of the grid unit is determined to be the industrial thermal anomaly point of the industrial heat source object, and a complete industrial thermal anomaly data set for the industrial heat source object is constructed in this way in a cycle.

[0013] (3) reconstructing / correcting the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object;

[0014] (3-1) Based on the heat emission parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object, the initial heat emission parameter values ​​of the complete industrial heat anomaly data set for the industrial heat source object are calculated using the spatiotemporal kriging estimation method;

[0015] (3-2) Constructing a composite periodic function of heat emission parameters for industrial heat source objects, and reconstructing and correcting the initial heat emission parameter values ​​of the complete industrial thermal anomaly data set for the industrial heat source objects according to the composite periodic function.

[0016] In a possible implementation, the initial heat emission parameter value includes: temperature attribute parameter values ​​and / or thermal radiation attribute parameter values ​​of different multi-source long-time series thermal anomaly data sets.

[0017] (4) Based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set for industrial heat source objects and the constructed information expression feature descriptor for industrial heat source objects, the information expression features of the industrial heat source objects are extracted.

[0018] In a possible implementation, the information expression features include: location attribute features, spatiotemporal distribution attribute features, geometric attribute features, temperature attribute features, thermal radiation attribute features, and the like.

[0019] In a second aspect, the present application proposes an industrial heat source information expression and extraction device for industrial heat source objects, comprising:

[0020] The acquisition unit is used to acquire multi-source long-time series thermal anomaly data and industrial heat source object data set of the target area;

[0021] The processing unit is used to construct a complete industrial heat anomaly data set for the industrial heat source object based on the consistency of the spatiotemporal distribution of the multi-source long-time series thermal anomaly data of a single industrial heat source object, wherein the complete industrial heat anomaly data set for the industrial heat source object includes an initial multi-source long-time series thermal anomaly data set for the industrial heat source object;

[0022] The processing unit is used to reconstruct / correct the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object;

[0023] The processing unit is used to extract the information expression features of the industrial heat source object based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set oriented to the industrial heat source object and the constructed information expression feature descriptor oriented to the industrial heat source object.

[0024] In a possible implementation, the multi-source long-time series thermal anomaly data includes: NVNP14IMG thermal anomaly data, VNF thermal anomaly data and L8F thermal anomaly data; the industrial heat source object data set is the "Ruby" industrial heat source object data set.

[0025] In a possible implementation, the processing unit is specifically used to construct an initial multi-source long-time series thermal anomaly data set for each industrial heat source object based on the regional range of the industrial heat source object data set and the location of the multi-source long-time series thermal anomaly data; construct initial raster data with a preset spatiotemporal resolution for each industrial heat source object; based on the initial multi-source long-time series thermal anomaly data set for the industrial heat source object, as well as a preset corresponding spatiotemporal window size and a threshold value for the number of thermal anomaly data, calculate the number of multi-source long-time series thermal anomaly data of the industrial heat source object grid by grid; if the number of multi-source long-time series thermal anomaly data within a preset corresponding spatiotemporal window in a grid unit is greater than the threshold value for the number of thermal anomaly data, determine the center point of the grid unit as the industrial thermal anomaly point of the industrial heat source object, and construct a complete industrial thermal anomaly data set for the industrial heat source object in a cycle.

[0026] In a possible implementation, the heat source information parameter includes a heat discharge parameter.

[0027] In a possible implementation, the processing unit is specifically used to calculate the initial heat emission parameter values ​​of the complete industrial thermal anomaly data set for the industrial heat source object based on the heat emission parameters of the initial multi-source long-time series thermal anomaly data set for the industrial heat source object, using the spatiotemporal kriging estimation method; construct a composite periodic function of the heat emission parameters for the industrial heat source object, and reconstruct and correct the initial heat emission parameter values ​​of the complete industrial thermal anomaly data set for the industrial heat source object according to the composite periodic function.

[0028] In a possible implementation, the initial heat emission parameter value includes: temperature attribute parameter values ​​and / or thermal radiation attribute parameter values ​​of different multi-source long-time series thermal anomaly data sets.

[0029] In a third aspect, the present application also proposes a thermal anomaly data processing and feature extraction device, comprising at least one processor, wherein the processor is used to execute a program stored in a memory, and when the program is executed, the device executes the various steps in the first aspect and various possible implementations.

[0030] In a fourth aspect, the present application further proposes a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the various steps in the first aspect and various possible implementations.

[0031] It can be seen from the above technical solutions that this application organically combines the identification of industrial heat source objects with information expression. On the one hand, a complete industrial thermal anomaly data set can be constructed for industrial heat source objects, and the heat emission parameters of the complete industrial thermal anomaly data set for industrial heat source objects can be corrected, effectively improving the accuracy of the heat source information expression of industrial heat source objects; on the other hand, by taking advantage of the characteristics of short-term spatiotemporal continuity and long-term spatiotemporal fluctuations in the operation of industrial heat source objects, an information expression feature descriptor for industrial heat source objects is designed as a preset information expression feature descriptor for industrial heat source objects, which solves the problem of missing industrial heat source information expression and effectively improves the accuracy and reliability of industrial heat source object identification in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1A schematic diagram of a process flow of an industrial heat source information expression and extraction method for an industrial heat source object provided in an embodiment of the present application;

[0034] Figure 2 A schematic diagram of the structure of an industrial heat source information expression and extraction device for industrial heat source objects provided in an embodiment of the present application;

[0035] Figure 3 A schematic diagram of the structure of an industrial heat source information expression and extraction device for industrial heat source objects provided in an embodiment of the present application. DETAILED DESCRIPTION

[0036] The following will describe the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings in the embodiments of the present application. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application.

[0037] It should be noted that the term "and / or" in this application is only a description of the association relationship of associated objects, indicating that there may be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone. The terms "first" and "second" in the description and claims of the embodiments of this application are used to distinguish different objects, rather than to describe the specific order of objects. For example, the first geographic location data, the second geographic location data, and the third geographic location data are used to distinguish different geographic location data, rather than to describe the specific order of target objects. In the embodiments of this application, words such as "exemplary", "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design scheme described as "exemplary", "for example" or "for example" in the embodiments of this application should not be interpreted as having advantages over other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way. In the description of the embodiments of this application, unless otherwise specified, the meaning of "multiple" refers to two or more.

[0038] In one possible implementation, the heat emission data of industrial / factory and mining enterprises mainly rely on the emission inventory statistical method. This model has large uncertainty in statistical results at the regional scale and cannot support the quantitative estimation of heat emission indicators of large-scale industrial heat source objects.

[0039] To this end, the present application embodiment provides Figure 1 The flowchart of the industrial heat source information expression and extraction method for industrial heat source objects shown in the figure includes: S101-S104, specifically including:

[0040] S101, obtaining multi-source long-term thermal anomaly data and industrial heat source object data set of the target area.

[0041] In the embodiment of the present application, the target area may be China, for example. The target area described herein has first geographic location data. The first geographic location data is the description data of the administrative boundary of the target area. For example, the first geographic location data may be the longitude and latitude coordinates of each point on the administrative boundary line of China.

[0042] In an embodiment of the present application, exemplarily, the multi-source long-time series thermal anomaly data may be fire point data from multiple sources, such as NVNP14IMG (NPP VIIRS 375 active fire / hotspot data) thermal anomaly data downloaded from the NASA website, VNF (NPP VIIRS Nightfire Data) thermal anomaly data downloaded from the NASA website, and L8F (Fires product based on Landsat-8 Data of AIRCAS) thermal anomaly data downloaded from the Institute of Remote Sensing, Chinese Academy of Sciences. The multi-source long-time series thermal anomaly data has heat source information parameters and includes second geographic location data. The second geographic location data is the location description data of the thermal anomaly point. Exemplarily, the second geographic location data is the longitude and latitude coordinates of the thermal anomaly point corresponding to the multi-source long-time series thermal anomaly data.

[0043] In an embodiment of the present application, multi-source long-time series thermal anomaly data of a target area, such as China, is obtained. Specifically, multi-source long-time series thermal anomaly data of a larger area than China can be first obtained. Then, a first area cut is performed on it. Specifically, based on the second geographic location data in the multi-source long-time series thermal anomaly data of a larger area and the administrative boundaries of China, the thermal anomaly points corresponding to the multi-source long-time series thermal anomaly data falling within the administrative boundaries of China are determined, that is, the multi-source long-time series thermal anomaly data of China is determined.

[0044] In the embodiment of the present application, the industrial heat source object data set is a "Ruby" industrial heat source object data set. The "Ruby" industrial heat source object data set described herein may be third geographic location data. The third geographic location data is regional range description data of the industrial heat source object.

[0045] In an embodiment of the present application, a target area, such as a dataset of industrial heat source objects in China, is obtained. Specifically, a dataset of industrial heat source objects in a larger area than China can be first obtained. Then, a second area cut is performed on it. Specifically, based on the dataset of industrial heat source objects in a larger area and the administrative boundaries of China, the industrial heat source objects falling within the administrative boundaries of China are determined.

[0046] S102: Based on the consistency of the spatiotemporal distribution of a single industrial heat source object in multi-source long-term thermal anomaly data, a complete industrial thermal anomaly dataset for industrial heat source objects is constructed.

[0047] In an embodiment of the present application, based on the characteristics of spatiotemporal continuity of multi-source long-term thermal anomaly data in the industrial heat source object area, a complete industrial thermal anomaly data set for industrial heat source objects is constructed.

[0048] In the embodiment of the present application, the multi-source long-time series thermal anomaly data for industrial heat source objects is first constructed. Specifically, based on the regional range of the industrial heat source object data set and the location of the multi-source long-time series thermal anomaly data, an initial multi-source long-time series thermal anomaly data set for the industrial heat source object is constructed for each industrial heat source object. Exemplarily, if the location of a certain multi-source long-time series thermal anomaly data is within the regional range of the industrial heat source object data set, the multi-source long-time series thermal anomaly data is added to the initial multi-source long-time series thermal anomaly data set of the industrial heat source object.

[0049] In the embodiment of the present application, the initial multi-source long-time series thermal anomaly data set for industrial heat source objects is reconstructed to obtain a complete industrial thermal anomaly data set for industrial heat source objects. The spatiotemporal differences of multi-source long-time series thermal anomaly data are jointly analyzed, and the multi-source long-time series thermal anomaly data missing due to unexpected factors such as weather, geographical environment, surface coverage and satellite data reception are filled through spatiotemporal trends. Specifically, for each industrial heat source object, the initial raster data of the preset spatiotemporal resolution is constructed. Based on the initial multi-source long-time series thermal anomaly data set for industrial heat source objects, and the preset corresponding spatiotemporal window size and the number threshold of thermal anomaly data, the number of multi-source long-time series thermal anomaly data of industrial heat source objects is calculated grid by grid. If the number of multi-source long-time series thermal anomaly data in the corresponding spatiotemporal window preset in the grid unit is greater than the number threshold of thermal anomaly data, the center point of the grid unit is determined to be the industrial thermal anomaly point of the industrial heat source object, and the complete industrial thermal anomaly data set for industrial heat source objects is constructed in this way. Exemplarily, for each industrial heat source object, the initial raster data with a spatial resolution of 30m is constructed. If the number of multi-source long-time series thermal anomaly data within the 11×11 spatiotemporal window and ±5 days in the searched grid cell is greater than the threshold of the number of thermal anomaly data, the center point of the grid cell is determined to be the industrial thermal anomaly point of the industrial heat source object.

[0050] S103, reconstructing / correcting the heat source information parameters of the complete industrial heat anomaly dataset for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly dataset for the industrial heat source object.

[0051] In an embodiment of the present application, the heat source information parameter includes a heat emission parameter.

[0052] In an embodiment of the present application, based on the heat emission parameters of the initial multi-source long-time series thermal anomaly data set for industrial heat source objects, the spatiotemporal kriging estimation method is used to calculate the initial heat emission parameter values ​​of the complete industrial heat anomaly data set for industrial heat source objects. A composite periodic function of the heat emission parameters for industrial heat source objects is constructed. The composite periodic function described herein is composed of a linear function and an annual periodic function. Then, the initial heat emission parameter values ​​of the complete industrial heat anomaly data set for industrial heat source objects are reconstructed and corrected according to the composite periodic function. Specifically, fitting is performed according to the least squares principle to remove the annual growth trend of the heat emission parameters of the industrial heat source objects, and obtain the seasonal growth trend of the heat emission parameters of the industrial heat source objects, which effectively suppresses the influence of the quality and uncertainty of the multi-source long-time series thermal anomaly data, thereby constructing relatively stable heat emission parameters of the multi-source long-time series thermal anomaly data for industrial heat source objects. At this point, a complete industrial heat anomaly data set for industrial heat source objects with complete heat emission parameters is obtained.

[0053] S104, extracting information expression features of the industrial heat source object based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object and the constructed information expression feature descriptor for the industrial heat source object.

[0054] In the embodiment of the present application, the initial heat emission parameter value in S103 includes: temperature attribute parameter values ​​and / or thermal radiation attribute parameter values ​​of different multi-source long-time series thermal anomaly data sets.

[0055] In an embodiment of the present application, each attribute parameter value in the initial heat emission parameter value is input into each information expression feature descriptor constructed for the industrial heat source object to obtain each output; based on each output and the mapping relationship between each output and the information expression feature of each industrial heat source object, the information expression feature of each industrial heat source object is determined.

[0056] Specifically, by taking advantage of the fact that the operation of industrial heat source objects has short-term spatiotemporal continuity and long-term spatiotemporal fluctuation, an information expression feature descriptor for industrial heat source objects is designed as a preset information expression feature descriptor for industrial heat source objects, which solves the problem of missing information expression for industrial heat sources and effectively improves the accuracy and reliability of industrial heat source object recognition in complex environments. This application includes location attribute features, spatiotemporal distribution attribute features, geometric attribute features, temperature attribute features, and thermal radiation attribute features. Among them, the location attribute characteristics include the center point position and center of gravity position of the thermal anomaly data of multiple sources of the industrial heat source object; the spatiotemporal distribution attribute characteristics include the number of thermal anomaly data of multiple sources contained in the industrial heat source object, the density of thermal anomaly points of multiple sources per unit area, the starting detection time of the thermal anomaly point data of multiple sources, the final detection time of the thermal anomaly point data of multiple sources, and the mean and variance of the time interval of the thermal anomaly data of multiple sources sorted by date; the geometric attribute characteristics include the longest moment, shortest moment, and ratio of the maximum convex hull of the industrial heat source object; the temperature attribute characteristics include the brightness temperature of band 4 (bright_t i4) and band 5 (bright_t i5) of the thermal anomaly data of the industrial heat source object VNP14IMG. i5), the blackbody temperature (Temp_BB) and background temperature (Temp_Bkg) of VNF thermal anomaly data, and the surface temperature (t1) of L8F thermal anomaly data, and other related information; thermal radiation attribute characteristics, including the radiation power (FRP) of industrial heat source object VNP14IMG thermal anomaly data, thermal radiation (RH) and radiation density (RHI) of VNF thermal anomaly data, and the surface coverage area (area) of L8F thermal anomaly data, and other related information of temperature thermal radiation attribute information.

[0057] Finally, through sensitive factor analysis and other methods, the importance of information expression characteristics of industrial heat source objects can be quantitatively analyzed.

[0058] The technical solution provided by this application organically combines the identification of industrial heat source objects with information expression. On the one hand, a complete industrial heat anomaly data set can be constructed for industrial heat source objects, and the heat emission parameters of the complete industrial heat anomaly data set for industrial heat source objects can be corrected, effectively improving the accuracy of the heat source information expression of industrial heat source objects; on the other hand, by taking advantage of the characteristics of short-term spatiotemporal continuity and long-term spatiotemporal fluctuation in the operation of industrial heat source objects, an information expression feature descriptor for industrial heat source objects is designed as a preset information expression feature descriptor for industrial heat source objects, which solves the problem of missing information expression for industrial heat sources and effectively improves the accuracy and reliability of industrial heat source object identification in complex environments.

[0059] Figure 2A structural schematic diagram 200 of an industrial heat source information expression extraction device for an industrial heat source object provided in an embodiment of the present application, the structural schematic diagram 200 includes: an acquisition unit 201 and a processing unit 202;

[0060] The acquisition unit 201 is used to acquire multi-source long-time series thermal anomaly data and industrial heat source object data set of the target area;

[0061] The processing unit 202 is used to construct a complete industrial thermal anomaly data set for the industrial heat source object based on the consistency of the spatiotemporal distribution of the multi-source long-time series thermal anomaly data of a single industrial heat source object, wherein the complete industrial thermal anomaly data set for the industrial heat source object includes an initial multi-source long-time series thermal anomaly data set for the industrial heat source object;

[0062] The processing unit 202 is used to reconstruct / correct the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object;

[0063] The processing unit 202 is used to extract the information expression features of the industrial heat source object based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set oriented to the industrial heat source object and the constructed information expression feature descriptor oriented to the industrial heat source object.

[0064] In a possible implementation, the multi-source long-time series thermal anomaly data includes: NVNP14IMG thermal anomaly data, VNF thermal anomaly data and L8F thermal anomaly data; the industrial heat source object data set is the "Ruby" industrial heat source object data set.

[0065] In a possible implementation, the processing unit 202 is specifically used to construct an initial multi-source long-time series thermal anomaly dataset for each industrial heat source object based on the regional range of the industrial heat source object dataset and the location of the multi-source long-time series thermal anomaly data; construct initial raster data with a preset spatiotemporal resolution for each industrial heat source object; based on the initial multi-source long-time series thermal anomaly dataset for the industrial heat source object, as well as a preset corresponding spatiotemporal window size and a threshold value for the number of thermal anomaly data, calculate the number of multi-source long-time series thermal anomaly data of the industrial heat source object grid by grid; if the number of multi-source long-time series thermal anomaly data within the preset corresponding spatiotemporal window in the grid unit is greater than the threshold value for the number of thermal anomaly data, determine the center point of the grid unit as the industrial thermal anomaly point of the industrial heat source object, and construct a complete industrial thermal anomaly dataset for the industrial heat source object in a cycle.

[0066] In a possible implementation, the heat source information parameter includes a heat discharge parameter.

[0067] In a possible implementation, the processing unit 202 is specifically used to calculate the initial heat emission parameter values ​​of the complete industrial thermal anomaly data set for the industrial heat source object based on the heat emission parameters of the initial multi-source long-time series thermal anomaly data set for the industrial heat source object, using the spatiotemporal kriging estimation method; construct a composite periodic function of the heat emission parameters for the industrial heat source object, and reconstruct and correct the initial heat emission parameter values ​​of the complete industrial thermal anomaly data set for the industrial heat source object according to the composite periodic function.

[0068] In a possible implementation, the initial heat emission parameter value includes: temperature attribute parameter values ​​and / or thermal radiation attribute parameter values ​​of different multi-source long-time series thermal anomaly data sets.

[0069] Figure 3 A structural schematic diagram 300 of an industrial heat source information expression and extraction device for an industrial heat source object provided in an embodiment of the present application. The device 300 may be a chip system. In the embodiment of the present application, the chip system may be composed of chips, or may include chips and other discrete devices. The device 300 includes at least one processor 310 for implementing the method provided in the embodiment of the present application. The device 300 may also include a communication interface 320. In the embodiment of the present application, the communication interface 320 may be a transceiver, circuit, bus, module or other type of communication interface for communicating with other devices through a transmission medium.

[0070] The processor 310 can execute the functions executed by the processing unit 202 in the device 200 ; the communication interface 320 can be used to execute the functions executed by the acquisition unit 201 in the device 200 .

[0071] When the device 300 is used to execute the above method, the communication interface 320 is used to obtain multi-source long-time series thermal anomaly data and industrial heat source object data sets of the target area; the processor 310 is used to construct a complete industrial thermal anomaly data set for industrial heat source objects based on the consistency of the spatiotemporal distribution of a single industrial heat source object in the multi-source long-time series thermal anomaly data, wherein the complete industrial thermal anomaly data set for industrial heat source objects includes an initial multi-source long-time series thermal anomaly data set for industrial heat source objects; based on the heat source information parameters of the initial multi-source long-time series thermal anomaly data set for industrial heat source objects, the heat source information parameters of the complete industrial thermal anomaly data set for industrial heat source objects are reconstructed / corrected; based on the reconstructed / corrected heat source information parameters of the complete industrial thermal anomaly data set for industrial heat source objects and the constructed information expression feature descriptor for industrial heat source objects, the information expression features of the industrial heat source objects are extracted.

[0072] The communication interface 320 is also used to execute other steps or operations in the above method embodiment except the acquisition unit 201. The processor 310 can also be used to execute other steps or operations in the above method embodiment except the processing unit 202, which will not be described one by one here.

[0073] The device 300 may also include at least one memory 330 for storing program instructions and / or data. The memory 330 is coupled to the processor 310. The coupling in the embodiment of the present application is an indirect coupling or communication connection between devices, units or modules, which may be electrical, mechanical or other forms, and is used for information exchange between devices, units or modules. The processor 310 may operate in conjunction with the memory 330. The processor 310 may execute program instructions stored in the memory 330. In one possible implementation, at least one of the at least one memory may be integrated with the processor. In another possible implementation, the memory 330 is located outside the device 300.

[0074] The specific connection medium between the communication interface 320, the processor 310 and the memory 330 is not limited in the embodiment of the present application. Figure 3 In the embodiment, the memory 330, the processor 310 and the communication interface 320 are connected via a bus 340. Figure 3 The connections between the other components are shown in bold lines, which are only for illustration and are not intended to be limiting. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0075] Exemplarily, the processor 310 may be one or more central processing units (CPUs). When the processor 310 is a CPU, the CPU may be a single-core CPU or a multi-core CPU. The processor 410 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in conjunction with the embodiments of the present application may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0076] Exemplarily, the memory 330 may include, but is not limited to, non-volatile memories such as a hard disk drive (HDD) or a solid-state drive (SSD), random access memory (RAM), erasable programmable read-only memory (EPROM), read-only memory (ROM) or portable read-only memory (CD-ROM), etc. The memory is any other medium that can be used to carry or store a desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory in the embodiment of the present application can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0077] The present application provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0078] Obtain multi-source long-term thermal anomaly data and industrial heat source object data sets in the target area;

[0079] Based on the consistency of the spatiotemporal distribution of a single industrial heat source object in multi-source long-time series thermal anomaly data, a complete industrial thermal anomaly data set for the industrial heat source object is constructed, wherein the complete industrial thermal anomaly data set for the industrial heat source object includes an initial multi-source long-time series thermal anomaly data set for the industrial heat source object;

[0080] Reconstructing / correcting the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object;

[0081] Based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set for industrial heat source objects and the constructed information expression feature descriptor for industrial heat source objects, the information expression features of industrial heat source objects are extracted.

[0082] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0083] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution 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 ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0084] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for extracting industrial heat source information expression for industrial heat source objects, characterized in that: include: Obtain multi-source long-term thermal anomaly data and industrial heat source object data sets in the target area; Based on the consistency of the spatiotemporal distribution of a single industrial heat source object in multi-source long-time series thermal anomaly data, a complete industrial thermal anomaly data set for the industrial heat source object is constructed, wherein the complete industrial thermal anomaly data set for the industrial heat source object includes an initial multi-source long-time series thermal anomaly data set for the industrial heat source object; Reconstructing / correcting the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object; Based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set for industrial heat source objects and the constructed information expression feature descriptor for industrial heat source objects, the information expression features of industrial heat source objects are extracted; The method is based on the consistency of the spatiotemporal distribution of a single industrial heat source object in multi-source long-time series thermal anomaly data to construct a complete industrial thermal anomaly dataset for industrial heat source objects, including: Based on the regional range of the industrial heat source object data set and the location of the multi-source long time series thermal anomaly data, for each industrial heat source object, an initial multi-source long time series thermal anomaly data set for the industrial heat source object is constructed; For each industrial heat source object, construct the initial raster data with preset temporal and spatial resolution; Based on the initial multi-source long-time series thermal anomaly data set for the industrial heat source object, and the preset corresponding spatiotemporal window size and the number threshold of thermal anomaly data, the number of multi-source long-time series thermal anomaly data of the industrial heat source object is calculated grid by grid; if the number of multi-source long-time series thermal anomaly data in the corresponding spatiotemporal window preset in the grid unit is greater than the number threshold of thermal anomaly data, the center point of the grid unit is determined to be the industrial thermal anomaly point of the industrial heat source object, and a complete industrial thermal anomaly data set for the industrial heat source object is constructed in this way in a cycle; The heat source information parameters include temperature attribute parameter values ​​and / or thermal radiation attribute parameter values; The reconstructing / correcting the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object includes: Based on the heat emission parameters of the initial multi-source long-time series heat anomaly data set for industrial heat source objects, the initial heat emission parameter values ​​of the complete industrial heat anomaly data set for industrial heat source objects are calculated using the spatiotemporal kriging estimation method; A composite periodic function of heat emission parameters for industrial heat source objects is constructed, and initial heat emission parameter values ​​of the complete industrial thermal anomaly data set for the industrial heat source objects are reconstructed and corrected according to the composite periodic function.

2. The method according to claim 1, characterized in that: The multi-source long time series thermal anomaly data includes: NVNP14IMG thermal anomaly data, VNF thermal anomaly data and L8F thermal anomaly data; The industrial heat source object dataset is the "Ruby" industrial heat source object dataset.

3. The method according to claim 1, characterized in that The initial heat emission parameter values ​​include: temperature attribute parameter values ​​and / or thermal radiation attribute parameter values ​​of different multi-source long-time series thermal anomaly data sets.

4. An industrial heat source information expression and extraction device for industrial heat source objects, used to implement the method according to any one of claims 1 to 3, characterized in that: include: An acquisition unit, used to acquire multi-source long-time series thermal anomaly data and industrial heat source object data sets in a target area; A processing unit, for constructing a complete industrial thermal anomaly data set for an industrial heat source object based on the consistency of the spatiotemporal distribution of a single industrial heat source object in multi-source long-time series thermal anomaly data, wherein the complete industrial thermal anomaly data set for an industrial heat source object includes an initial multi-source long-time series thermal anomaly data set for the industrial heat source object; The processing unit is used to reconstruct / correct the heat source information parameters of the complete industrial heat anomaly data set for the industrial heat source object based on the heat source information parameters of the initial multi-source long-time series heat anomaly data set for the industrial heat source object; The processing unit is used to extract the information expression features of the industrial heat source object based on the reconstructed / corrected heat source information parameters of the complete industrial heat anomaly data set oriented to the industrial heat source object and the constructed information expression feature descriptor oriented to the industrial heat source object.

5. An industrial heat source information expression and extraction device for industrial heat source objects, characterized in that: The device comprises at least one processor, wherein the processor is configured to execute a program stored in a memory, and when the program is executed, the device executes: The method according to any one of claims 1 to 3.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 3 is implemented.

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