CN111290357A - Intelligent fuel management and control system based on Internet of things and big data - Google Patents
Intelligent fuel management and control system based on Internet of things and big data Download PDFInfo
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- CN111290357A CN111290357A CN202010186204.4A CN202010186204A CN111290357A CN 111290357 A CN111290357 A CN 111290357A CN 202010186204 A CN202010186204 A CN 202010186204A CN 111290357 A CN111290357 A CN 111290357A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by quality surveillance of production
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32368—Quality control
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention relates to an intelligent fuel management and control system based on the Internet of things and big data, which comprises an operation overview module, an intelligent loading and unloading and stacking management module, a coal yard intelligent management module, a coal blending and burning intelligent management module, a fuel scheduling management module, a fuel acceptance management module, a coal purchasing guidance module, a coal cost analysis module, a diagnosis cab module and a system management module. According to the invention, through the application of automation equipment and information technology, the traditional fuel management mode is modified by means of mechanization, automation and informatization, the intellectualization is promoted around the key link of fuel management, and the working efficiency of the whole process of fuel management is improved.
Description
Technical Field
The invention relates to the technical field of power generation fuel, in particular to a fuel control system of a power plant, and specifically relates to an intelligent fuel control system based on the Internet of things and big data.
Background
Along with the progress of science and technology, mechanized sampling of coal entering a plant and coal entering a furnace is realized, and informatization technology is also applied to daily management work of a power plant in a large amount, such as an automatic identification system of the number of a coal entering the plant, a unified fuel settlement system, a digital coal yard and the like, so that the fuel management level and efficiency are continuously improved.
At present, each link of fuel management of a thermal power enterprise has some problems, and the problems seriously affect the fuel management efficiency of the enterprise. For example, further improvements are needed in the following links:
(1) and (3) a metering link: some fuel equipment of most thermal power enterprises need manual measurement, the efficiency of an intermediate link is very low, and the problem of data safety exists. Meanwhile, the weighing apparatus cannot automatically identify information such as vehicles, mine types and the like, and problems of repeated weighing or remote control of the weighing apparatus and the like can occur;
(2) a sampling link: and a manual sampling mode is adopted when a plurality of enterprise mechanical sampling devices are in failure. The sampling automation degree is not enough, and a vulnerability exists in the management aspect. The manual sampling has the conditions of over-high labor intensity, irregular flow, human errors and the like;
(3) a sample preparation link: at present, most enterprises adopt a manual off-line mode to prepare samples, and the sample preparation effect is uncontrollable, so that the samples cannot represent the characteristics of the whole batch of fuel;
(4) and (3) sample sending and storing links: during the transportation of the coal sample, the sealing means of the sample barrel or the sample bag is simple, the safety of the sample cannot be fully guaranteed, and the danger of sample pollution exists;
(5) and (3) assay link: in the process of testing a sample in a laboratory of a thermal power enterprise, various testing data are manually calculated and recorded, and the risk of human errors and changes exists;
(6) and (3) management links: the fuel management personnel still carries out the statistics of fuel measurement, chemical examination data using the manual means, the human error appears easily, and efficiency is lower, and the storage of subregion, branch heap, branch variety, branch quality still can not be accomplished at present to fuel stock management simultaneously, also can't accurately measure fuel parameter information, has brought very big difficulty for fuel blending co-combustion.
Disclosure of Invention
Aiming at the existing problems in each link of fuel management of a thermal power enterprise, the invention provides an intelligent fuel management and control system based on the Internet of things and big data for effectively improving the fuel management efficiency of the enterprise.
The invention is realized by the following technical scheme, and provides an intelligent fuel management and control system based on the Internet of things and big data, which comprises an operation overview module, an intelligent loading and unloading and stacking management module, a coal yard intelligent management module, a coal blending and burning intelligent management module, a fuel scheduling management module, a fuel acceptance management module, a coal burning purchase guidance module, a coal burning cost analysis module, a diagnosis cab module and a system management module, wherein the operation overview module comprises the whole process information from fuel loading to burning result feedback, and an ECharts visual chart library is adopted to display core indexes (including coal loading and unloading operation progress, fuel purchasing guidance suggestions, fuel acceptance statistics, coal yard coal storage analysis and coal burning real-time cost) related to coal burning, so that the production and operation conditions of enterprises are clearly and intuitively presented to users; the intelligent receiving and discharging stacking management module comprises receiving and discharging stacking management and receiving and discharging stacking equipment for monitoring two parts of contents in real time, a receiving and discharging stacking operation scheme is calculated according to a receiving and discharging stacking model before coal enters a plant and comprises a receiving and discharging path and a stacking position, the receiving and discharging stacking equipment performs work according to a machine instruction converted by the scheme, stores or loads fuel in a partition, stacking, variety and quality mode, and transmits and feeds back receiving and discharging stacking information in real time; the intelligent management module of the coal yard associates coal quality online detection data, mine coal quality data and test coal quality data through a bulk density analysis calculation model, a field loss analysis calculation model, a coal yard dynamic temperature field and an early warning model in combination with three-dimensional dynamic scanning and temperature environment monitoring of the coal yard, and comprehensively, dynamically displays the state of the coal yard in real time in a three-dimensional graph, wherein the state comprises the coal amount, the temperature, the heat value, the total moisture, the sulfur content, the price and the stockpiling time of different areas; the intelligent management module for blending coal generates a blending coal blending scheme with comprehensive optimal safety, economy and environmental protection indexes by combining factors including boiler design parameters, incoming coal information, current coal storage condition, coal-fired cost, blending coal blending feedback suggestion and equipment operation condition according to a blending coal blending optimization model, and also supports generation of a blending coal blending scheme with optimal single condition; the fuel scheduling management module forms a fire coal scheduling and transporting machine account according to a scheduling and transporting plan, a coming coal forecast, and receiving, unloading, storing and piling management of coal from a railway or a vehicle and a ship, automatically identifies the unique coal code and the weight to be matched with the coming coal forecast information by adding an identification device (such as a radio frequency card) at a factory (port), realizes the bidirectional identification of the factory (port) entrance and exit, and realizes the closed-loop management of each link of scheduling, vehicle receiving, factory entrance, sampling, weighing, unloading and leaving factory; the coal purchasing management module is used for planning the reasonable purchasing quantity of various heat value coal varieties according to the estimated coal quality entering the power plant when the power plant has the lowest power supply cost and by combining the historical co-combustion data and the inventory condition of the power plant in the same month, and finally generating the purchasing suggestion of the coal in the same month, wherein the purchasing suggestion comprises suggestions on suppliers, purchasing coal types and purchasing quantity, so that the purchasing optimizing management with the lowest comprehensive cost of the power plant is realized; the intelligent fuel acceptance management module comprises fuel entering equipment, weighing, coal unloading, peeling, delivery, sampling, sample separating, sample preparation and assay, standardizes the fuel acceptance process, improves the control and risk prevention and control capacity of the fuel acceptance process, realizes the acquisition, monitoring and early warning of field condition data by being tightly combined with fuel management bottom equipment, and performs dispersed data and centralized display on equipment in each link of remote fuel entering equipment management, metering and sample preparation; the coal-fired cost analysis module analyzes reasons and influence factors of fuel cost rise and fall, analyzes profit and loss trends of unit operation, measures profit and loss balance points, analyzes fuel consumption in the production process of a power plant, and displays change conditions and trends of coal-fired cost; the diagnosis cockpit module statistics summarize all alarm information in the platform, show with Echarts chart and Antd tabular form, can make statistics to various alarm information to later analysis, alarm information includes: receiving and unloading stacking equipment, sampling and testing equipment and weighing equipment are abnormal; the operator violates the operational procedures or specifications; alarming when the current coal storage time, temperature and environmental conditions are out of limit; an empirical formula is established by using historical data to judge that the measured data of the equipment deviates from a reasonable range; the system management module is used for managing and configuring various information parameters.
Preferably, the loading and unloading and stacking model comprises an operation model, a coal-fired stacking rule base and a coal conveying system process flow base, wherein the operation model is used for calculating and generating a coal loading and unloading and stacking operation scheme by using an optimization method according to the coal forecast information, the coal conveying equipment operation condition and the current coal storage condition in combination with the stacking rule, wherein the operation scheme comprises a coal unloading mode, a transfer path and a stacking position.
Preferably, the real-time monitoring of the loading and unloading and stacking device shows the field operation condition through an svg configuration diagram according to the real-time database data, and comprises the following steps: information of entering and leaving factories (ports) and overbalance information (including batch codes, overbalance time, coal varieties and weight) of vehicles (ships); the system comprises a tipper, a sampling machine, an iron remover, a ship unloader, a coal plough, a coal feeder and three-way equipment, wherein the running state, parameters and alarm information of the three-way equipment can be used for checking the equipment details of each equipment primitive of the single machine; vehicle (ship) queuing.
Preferably, the bulk density model comprises a bulk density database which records the bulk density change curves corresponding to different coal types, different working conditions and different stacking times.
Preferably, the field loss analysis calculation model calculates the field loss data and analyzes the field loss factors according to coal yard stacking data (including quantity, orientation, coal types and storage conditions), coal yard environment monitoring data, incoming and furnace coal quality inspection data and field loss management rules.
Preferably, the coal yard dynamic temperature field and the early warning model acquire the surface temperature value of the coal pile through an infrared scanner, acquire the internal temperature of the coal pile through a temperature measuring rod, establish the dynamic temperature field model aiming at the coal yard by using a function model of an expert in the coal temperature research aspect, and give an alarm when the temperature exceeds the early warning value.
In conclusion, the intelligent power station fuel management and control system based on the internet of things and big data transforms the traditional fuel management mode through the application of automation equipment and information technology and the mechanized, automatic and informatization means, completes the work of data collection, statistical analysis, operation optimization supervision, decision suggestion, comprehensive display and the like of a fuel system, realizes the perception, biological, operation automation, diagnosis, intelligence and decision intelligence in the links of fuel receiving, unloading, storage, blending, extraction, transportation, acceptance and the like, promotes the intelligence around the key link of fuel management, improves the work efficiency of the whole process of fuel management, and enables the fuel management of thermal power enterprises to be more intelligent.
Drawings
FIG. 1 is a schematic structural diagram of an intelligent fuel management and control system based on the Internet of things and big data in the invention;
FIG. 2 is a schematic diagram of a software architecture of an intelligent fuel management and control system based on the Internet of things and big data according to the present invention;
fig. 3 is a schematic diagram of a hardware connection architecture of an intelligent fuel management and control system based on the internet of things and big data in the invention.
Detailed Description
In order to clearly illustrate the technical features of the present invention, the present invention is further illustrated by the following detailed description with reference to the accompanying drawings.
As shown in fig. 1 to 3, an intelligent fuel management and control system based on internet of things and big data comprises an operation overview module, an intelligent loading and unloading and stacking management module, a coal yard intelligent management module, a coal blending intelligent management module, a fuel scheduling management module, a fuel acceptance management module, a coal purchasing guidance module, a coal cost analysis module, a diagnosis cockpit module and a system management module, wherein the operation overview module comprises the whole process information from fuel loading to combustion result feedback, and an ECharts visual chart library is adopted to display core indexes related to coal combustion (including coal loading and unloading operation progress, fuel purchasing guidance suggestions, fuel acceptance statistics, coal yard coal storage analysis and coal combustion real-time cost), so that enterprise production and operation conditions are clearly and intuitively presented to users; the intelligent receiving and discharging stacking management module comprises receiving and discharging stacking management and receiving and discharging stacking equipment for monitoring two parts of contents in real time, a receiving and discharging stacking operation scheme is calculated according to a receiving and discharging stacking model before coal enters a plant and comprises a receiving and discharging path and a stacking position, the receiving and discharging stacking equipment performs work according to a machine instruction converted by the scheme, stores or loads fuel in a partition, stacking, variety and quality mode, and transmits and feeds back receiving and discharging stacking information in real time; the coal yard intelligent management module associates coal quality online detection data, mine coal quality data and test coal quality data through a bulk density analysis calculation model, a field loss analysis calculation model, a coal yard dynamic temperature field and an early warning model in combination with coal yard three-dimensional dynamic scanning and temperature environment monitoring, and dynamically displays the coal yard state in a three-dimensional graph comprehensively in real time, wherein the three-dimensional graph comprises coal amount, temperature, heat value, total moisture, sulfur content, price and stockpiling time in different areas;
the intelligent management module for blending coal generates a blending coal blending scheme with comprehensive optimal safety, economy and environmental protection indexes by combining factors including boiler design parameters, incoming coal information, current coal storage condition, coal-fired cost, blending coal blending feedback suggestion and equipment operation condition according to a blending coal blending optimization model, and also supports generation of a blending coal blending scheme with optimal single condition; the fuel scheduling management module forms a fire coal scheduling and transporting machine account according to a scheduling and transporting plan, a coming coal forecast, and receiving, unloading, storing and piling management of coal from a railway or a vehicle and a ship, automatically identifies the unique coal code and the weight to be matched with the coming coal forecast information by adding an identification device (such as a radio frequency card) at a factory (port), realizes the bidirectional identification of the factory (port) entrance and exit, and realizes the closed-loop management of each link of scheduling, vehicle receiving, factory entrance, sampling, weighing, unloading and leaving factory; the coal purchasing management module is used for planning the reasonable purchasing quantity of various heat value coal varieties according to the estimated coal quality entering the power plant when the power plant has the lowest power supply cost and by combining the historical co-combustion data and the inventory condition of the power plant in the same month, and finally generating the purchasing suggestion of the coal in the same month, wherein the purchasing suggestion comprises suggestions on suppliers, purchasing coal types and purchasing quantity, so that the purchasing optimizing management with the lowest comprehensive cost of the power plant is realized; the intelligent fuel acceptance management module comprises fuel entering equipment, weighing, coal unloading, peeling, delivery, sampling, sample separating, sample preparation and assay, standardizes the fuel acceptance process, improves the control and risk prevention and control capacity of the fuel acceptance process, realizes the acquisition, monitoring and early warning of field condition data by being tightly combined with fuel management bottom equipment, and performs dispersed data and centralized display on equipment in each link of remote fuel entering equipment management, metering and sample preparation; the coal-fired cost analysis module analyzes reasons and influence factors of fuel cost rise and fall, analyzes profit and loss trends of unit operation, measures profit and loss balance points, analyzes fuel consumption in the production process of a power plant, and displays change conditions and trends of coal-fired cost;
the diagnosis cockpit module statistics summarize all alarm information in the platform, show with Echarts chart and Antd tabular form, can make statistics to various alarm information to later analysis, alarm information includes: receiving and unloading stacking equipment, sampling and testing equipment and weighing equipment are abnormal; the operator violates the operational procedures or specifications; alarming when the current coal storage time, temperature and environmental conditions are out of limit; an empirical formula is established by using historical data to judge that the measured data of the equipment deviates from a reasonable range; the system management module is used for managing and configuring various information parameters.
In this embodiment, the loading/unloading/stacking model includes an operation model, a coal-fired stacking rule base, and a coal transportation system process flow base, where the operation model generates a coal loading/unloading/stacking operation scheme by using an optimization method according to rules of coal forecast information, coal transportation equipment operation conditions, and current coal storage conditions in combination with stacking, where the operation scheme includes a coal unloading mode, a transfer path, and a stacking position, and the loading/unloading/stacking equipment monitors in real time to display field operation conditions through an svg configuration diagram according to real-time database data, and includes: information of entering and leaving factories (ports) and overbalance information (including batch codes, overbalance time, coal varieties and weight) of vehicles (ships); the system comprises a tipper, a sampling machine, an iron remover, a ship unloader, a coal plough, a coal feeder and three-way equipment, wherein the running state, parameters and alarm information of the three-way equipment can be used for checking the equipment details of each equipment primitive of the single machine; the condition of lining up of car (ship), the bulk density change curve that different coal types, different operating modes, different stack time correspond has been recorded including the bulk density database to the constitution of bulk density model, the field loss analysis calculation model with coal yard pile data (quantity, position, coal variety, storage condition), coal yard environmental monitoring data, income factory and the coal quality inspection data of firing and field loss management rule for the basis calculate the field loss data and to the analysis of field loss factor, coal yard dynamic temperature field and early warning model acquire coal pile surface temperature value through infrared scanner, acquire the inside temperature of coal pile through the temperature measuring pole, use the function model of the aspect of coal-fired temperature research to establish dynamic temperature field model to the coal yard, the suggestion of reporting to the police is just carried out when the temperature exceeds the early warning value.
Finally, it should be further noted that the above examples and descriptions are not limited to the above embodiments, and technical features of the present invention that are not described may be implemented by or using the prior art, and are not described herein again; the above embodiments and drawings are only for illustrating the technical solutions of the present invention and not for limiting the present invention, and the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that changes, modifications, additions or substitutions within the spirit and scope of the present invention may be made by those skilled in the art without departing from the spirit of the present invention, and shall also fall within the scope of the claims of the present invention.
Claims (6)
1. An intelligent fuel management and control system based on the Internet of things and big data is characterized by comprising an operation overview module, an intelligent loading and unloading and stacking management module, a coal yard intelligent management module, a coal blending and blending intelligent management module, a fuel scheduling management module, a fuel acceptance management module, a coal purchasing guidance module, a coal cost analysis module, a diagnosis cab module and a system management module, wherein,
the operation overview module comprises the information of the whole process from fuel entering a factory to combustion result feedback, and the ECharts visual chart library is adopted to show the core indexes related to the fire coal (the working progress of coal receiving and unloading, fuel purchasing guidance suggestion, the statistical condition of fuel acceptance, coal storage analysis in a coal yard and the real-time cost of the fire coal), so that the production and operation conditions of enterprises are clearly and intuitively presented to users;
the intelligent receiving and discharging stacking management module comprises receiving and discharging stacking management and receiving and discharging stacking equipment for monitoring two parts of contents in real time, a receiving and discharging stacking operation scheme is calculated according to a receiving and discharging stacking model before coal enters a plant and comprises a receiving and discharging path and a stacking position, the receiving and discharging stacking equipment performs work according to a machine instruction converted by the scheme, stores or loads fuel in a partition, stacking, variety and quality mode, and transmits and feeds back receiving and discharging stacking information in real time;
the intelligent management module of the coal yard associates coal quality online detection data, mine coal quality data and test coal quality data through a bulk density analysis calculation model, a field loss analysis calculation model, a coal yard dynamic temperature field and an early warning model in combination with three-dimensional dynamic scanning and temperature environment monitoring of the coal yard, and comprehensively, dynamically displays the state of the coal yard in real time in a three-dimensional graph, wherein the state comprises the coal amount, the temperature, the heat value, the total moisture, the sulfur content, the price and the stockpiling time of different areas;
the intelligent management module for blending coal generates a blending coal blending scheme with comprehensive optimal safety, economy and environmental protection indexes by combining factors including boiler design parameters, incoming coal information, current coal storage condition, coal-fired cost, blending coal blending feedback suggestion and equipment operation condition according to a blending coal blending optimization model, and also supports generation of a blending coal blending scheme with optimal single condition;
the fuel scheduling management module forms a fire coal scheduling and transporting machine account according to a scheduling and transporting plan, a coming coal forecast, and receiving, unloading, storing and piling management of coal from a railway or a vehicle and a ship, automatically identifies the unique coal code and the weight to be matched with the coming coal forecast information by adding an identification device (such as a radio frequency card) at a factory (port), realizes the bidirectional identification of the factory (port) entrance and exit, and realizes the closed-loop management of each link of scheduling, vehicle receiving, factory entrance, sampling, weighing, unloading and leaving factory;
the coal purchasing management module is used for planning the reasonable purchasing quantity of various heat value coal varieties according to the estimated coal quality entering the power plant when the power plant has the lowest power supply cost and by combining the historical co-combustion data and the inventory condition of the power plant in the same month, and finally generating the purchasing suggestion of the coal in the same month, wherein the purchasing suggestion comprises suggestions on suppliers, purchasing coal types and purchasing quantity, so that the purchasing optimizing management with the lowest comprehensive cost of the power plant is realized;
the intelligent fuel acceptance management module comprises fuel entering equipment, weighing, coal unloading, peeling, delivery, sampling, sample separating, sample preparation and assay, standardizes the fuel acceptance process, improves the control and risk prevention and control capacity of the fuel acceptance process, realizes the acquisition, monitoring and early warning of field condition data by being tightly combined with fuel management bottom equipment, and performs dispersed data and centralized display on equipment in each link of remote fuel entering equipment management, metering and sample preparation;
the coal-fired cost analysis module analyzes reasons and influence factors of fuel cost rise and fall, analyzes profit and loss trends of unit operation, measures profit and loss balance points, analyzes fuel consumption in the production process of a power plant, and displays change conditions and trends of coal-fired cost;
the diagnosis cockpit module statistics summarize all alarm information in the platform, show with Echarts chart and Antd tabular form, can make statistics to various alarm information to later analysis, alarm information includes: receiving and unloading stacking equipment, sampling and testing equipment and weighing equipment are abnormal; the operator violates the operational procedures or specifications; alarming when the current coal storage time, temperature and environmental conditions are out of limit; an empirical formula is established by using historical data to judge that the measured data of the equipment deviates from a reasonable range;
the system management module is used for managing and configuring various information parameters.
2. The intelligent fuel management and control system based on the internet of things and big data as claimed in claim 1, wherein the receiving, discharging and stacking model comprises an operational model, a coal-fired stacking rule base and a coal conveying system process flow base, and the operational model is used for generating a coal receiving, discharging and stacking operation scheme by using an optimization method according to coal forecast information, coal conveying equipment operation conditions and current coal storage conditions in combination with stacking rules, wherein the coal receiving, discharging and stacking operation scheme comprises a coal discharging mode, a transfer path and a stacking position.
3. The intelligent fuel management and control system based on the internet of things and big data according to claim 1, wherein the on-site operation condition of the loading and unloading and stacking equipment is monitored in real time through an svg configuration diagram according to real-time database data, and the system comprises: information of entering and leaving factories (ports) and overbalance information (including batch codes, overbalance time, coal varieties and weight) of vehicles (ships); the system comprises a tipper, a sampling machine, an iron remover, a ship unloader, a coal plough, a coal feeder and three-way equipment, wherein the running state, parameters and alarm information of the three-way equipment can be used for checking the equipment details of each equipment primitive of the single machine; vehicle (ship) queuing.
4. The intelligent fuel management and control system based on the internet of things and the big data as claimed in claim 1, wherein the bulk density model comprises a bulk density database which records bulk density change curves corresponding to different coal types, different working conditions and different stacking times.
5. The intelligent fuel management and control system based on the internet of things and big data as claimed in claim 1, wherein the site loss analysis and calculation model calculates the site loss data and analyzes the site loss factors based on coal yard storage data (including quantity, orientation, coal type and storage condition), coal yard environment monitoring data, incoming and as-fired coal quality inspection data and site loss management rules.
6. The intelligent fuel management and control system based on the internet of things and big data as claimed in claim 1, wherein the coal yard dynamic temperature field and early warning model obtains a coal pile surface temperature value through an infrared scanner, obtains a coal pile internal temperature through a temperature measuring rod, establishes a dynamic temperature field model for the coal yard by using a function model of an expert in coal temperature research, and gives an alarm when the temperature exceeds the early warning value.
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| CN112734208A (en) * | 2020-12-31 | 2021-04-30 | 华润电力技术研究院有限公司 | Fire coal acceptance monitoring device, method and equipment and readable storage medium |
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Denomination of invention: An intelligent fuel management and control system based on the Internet of Things and Big data Effective date of registration: 20230720 Granted publication date: 20230328 Pledgee: Qilu Bank Co.,Ltd. Jinan Science and Technology Innovation Financial Center Branch Pledgor: Shandong chuangde Intelligent Technology Co.,Ltd. Registration number: Y2023980049182 |