Coal-fired power plant operation efficiency optimization management system based on electromagnetic sensing

Abstract

The invention discloses a coal-fired power plant operation efficiency optimization management system based on electromagnetic sensing. The system comprises an electromagnetic monitoring module, a data acquisition module, a database module, a preprocessing module, a detection module, a data processing module and a data output module. The detection module is used for judging the operation state of each device in the power plant and generating a device operation report; the data processing module is used for judging the efficiency of the power plant and generating an efficiency monitoring report and a power plant optimization scheme; according to the method, the electromagnetic data in the power plant and the real-time data of equipment operation are collected and screened to ensure the validity and scientificity of the data, an effective judgment basis is provided for efficiency optimization of the power plant, the operation state of the equipment is judged according to the electromagnetic data, and on the basis of ensuring normal operation of the equipment, the efficiency of the power plant is improved. Furthermore, a reasonable optimization scheme is screened out through analysis of historical efficiency data, stable operation of the power plant can be guaranteed, and the stability of power supply of the power plant is improved.

Description

Technical Field

[0001] The present invention relates to the field of data optimization management, and in particular to an electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system. Background Art

[0002] Coal-fired power plants are an important part of my country's power supply and are of great importance. With the rapid development of computer technology and high-speed communication technology, intelligent monitoring technology has gradually been fully applied to equipment monitoring in power plants to assist in the optimization and management of power plants. The existing electromagnetic optimization work focuses on improving the efficiency of power plants. According to the existing power plant efficiency, the operating parameters of each equipment are adjusted to improve the efficiency of the power plant, but there is a lack of real-time monitoring and analysis of the equipment. Due to the diversity of equipment inside the power plant, adjusting parameters according to the power plant efficiency will cause some equipment to overload or operate inefficiently, resulting in large fluctuations in power plant efficiency, unstable production capacity, and inability to supply energy scientifically and stably. For this reason, a coal-fired power plant operation efficiency optimization management system based on electromagnetic sensing is proposed. Summary of the invention

[0003] The technical problem to be solved by the present invention is: how to solve the problem that the existing safety protection system has a single protection type, resulting in poor protection effect and bringing certain impacts on the use of the safety protection system. A coal-fired power plant operation efficiency optimization management system based on electromagnetic sensing is provided.

[0004] The present invention solves the above technical problems through the following technical solutions, and the present invention includes an electromagnetic monitoring module, a data acquisition module, a database module, a preprocessing module, a detection module, a data processing module, and a data output module; The electromagnetic monitoring module is used to monitor the real-time electromagnetic data of various equipment inside the power plant; The data acquisition module is used to collect real-time data information of power plant operation; The preprocessing module is used to process real-time electromagnetic data and real-time data information, and delete abnormal data; The database module is used to store historical data information and standard electromagnetic data; The detection module is used to receive real-time electromagnetic data, historical data information and standard electromagnetic data, determine the operating status of each device in the power plant, and generate an equipment operation report. If the equipment operating status is abnormal, a warning report will be generated; The data processing module is used to receive equipment operation reports, real-time data information and historical data information. When the equipment is in normal operation, the performance of the power plant is judged and a performance monitoring report is generated by analyzing the real-time data information and historical data information. The performance monitoring report is then analyzed in combination with the real-time data information and historical data information to produce a power plant optimization plan. The data output module is used to receive and output the power plant optimization plan.

[0005] Preferably, the processing process of the preprocessing module is: Obtain real-time electromagnetic data and real-time data information; A set of real-time electromagnetic data and real-time data information is randomly selected; Use the first rule to verify the real-time electromagnetic data and real-time data information, and delete abnormal data; The first rule is: Extract a set of data A1, A2, A3, ..., An; Calculate the distribution state S of the data. The specific calculation process is: ;

[0006] in, is the average of multiple data; when When >3, the data is considered abnormal and will be deleted.

[0007] Preferably, the equipment operation report includes a normal operation report and a warning report, and the specific processing process of the detection module is: Obtain real-time electromagnetic data of a group of equipment in the power plant, namely Q1, Q2, Q3, ..., Qn; Calculate the average electromagnetic data of the device ; Then import the standard electromagnetic data Qr of the equipment; When the average electromagnetic data ≤ standard electromagnetic data Qr, generate a normal operation report; When the average electromagnetic data >standard electromagnetic data Qr, a warning report is generated.

[0008] Preferably, the historical data information includes historical electromagnetic data. ≤ standard electromagnetic data Qr, the processing process of the detection module further includes: Obtain a set of historical electromagnetic data of equipment in the power plant and calculate the average value Qa of the historical electromagnetic data; Importing Averaged EM Data ; Calculate the long-term electromagnetic fluctuation K1 of the equipment. The specific calculation process is: ;

[0009] Acquire a set of real-time electromagnetic data Q1`, Q2`, Q3`, ..., Qn` continuously in equal time periods; Calculate the short-term electromagnetic fluctuation K2 of the real-time electromagnetic data in each time period respectively; the specific calculation process is: ;

[0010] Among them, t1 is the time interval of equal time periods; Extract the maximum value K2` of the short-term electromagnetic fluctuation K2; Calculate the comprehensive fluctuation K3 of the electromagnetic data of the equipment. The specific calculation process is: K3=e1*K1+e2*K2`; Among them, e1 is the weight of the long-term electromagnetic fluctuation K1, e2 is the weight of the short-term electromagnetic fluctuation K2, e1+e2=1 and e1<e2; When the comprehensive fluctuation K3>the preset threshold W1, a warning report is generated.

[0011] Preferably, when the comprehensive fluctuation K3 ≤ the preset threshold W1, the processing process of the detection module further includes: Obtain the short-term electromagnetic fluctuation K2 in each time period t1, and import the node time of each time period; When the short-term electromagnetic fluctuation K2>preset threshold W2, it is marked to obtain a plurality of marked electromagnetic fluctuations K4; Obtain all marked electromagnetic fluctuations K4; Then read the node time at both ends of each short-term electromagnetic fluctuation K2 respectively; The rear node time of each period is defined as the reference node time, and the reference node time difference C of any marked electromagnetic fluctuation K4 is calculated; Use the formula N=C / t1 to calculate the number N1 of short-term electromagnetic fluctuations K2 that occur within the time difference C of any reference node; When the number N2 of marked electromagnetic fluctuations K4 within the reference node time difference C is equal to N1, and C≥3t1, a warning report is generated.

[0012] Preferably, the real-time data information includes real-time coal consumption data, real-time electricity production data, real-time temperature data and real-time pressure data in the boiler, and the performance monitoring report includes a good performance report and an insufficient performance report. The generation process of the performance monitoring report is: Obtain real-time pressure data, real-time temperature data, real-time coal consumption data and real-time electricity production data in the power plant; Calculate the efficiency G of the power plant under the conditions of real-time pressure data P' and real-time temperature data H' of the boiler. The specific calculation process is: G=L` / V`; Among them, L` is the real-time electricity production data, and V` is the real-time coal consumption data; When the efficiency G ≥ the preset threshold W3, the power plant efficiency is good and a good efficiency report is generated; When the efficiency G is less than the preset threshold W3, the power plant efficiency is insufficient and an efficiency deficiency report is generated.

[0013] Preferably, the historical data information also includes historical efficiency data, historical temperature data and historical pressure data in the boiler, and the process of issuing the power plant optimization plan is: When the efficiency G is less than the preset threshold W3, the historical efficiency data Ge of the boiler is imported; When the historical performance data Ge≥W3, the historical performance data is marked; Sort the marked historical performance data Ge and obtain the maximum historical performance data Ge`; Obtain the historical temperature data H` and the historical pressure data P` of the maximum historical efficiency data Ge`; Then obtain a set of historical performance data when the historical temperature data is H' and the historical pressure data is P', which are Gr1, Gr2, Gr3, ..., Grn respectively; Calculate the stability F of historical performance data. The specific calculation process is: ;

[0014] in, is the average historical performance data; When the stability F>preset threshold W4, the data is cleared, the maximum historical efficiency Ge` is reselected, and the historical temperature data and historical pressure data under the maximum historical efficiency Ge` are used as optimization reference data, and a power plant optimization plan is issued.

[0015] Preferably, when the stability F>preset threshold W4, the process of issuing the power plant optimization plan further includes: Obtain the historical performance data of the maximum historical performance Ge` when the historical temperature data is H` and the historical pressure data is P, which are Gr1, Gr2, Gr3, ..., Grn respectively; Calculate the abnormality J of historical performance data. The specific calculation process is as follows; ;

[0016] When the abnormality J> the preset threshold W5, it indicates that the data is abnormal, which is abnormal performance data; Count the total amount of historical performance data B1; Then count the number of abnormal performance data B2; Calculate the abnormal data ratio B3. The specific calculation process is as follows: B3=B2 / B1; When B3 is less than the preset threshold value W6, the data of the maximum historical performance Ge` is retained and an equipment inspection report is generated.

[0017] Preferably, the historical data information also includes the total energy consumption of auxiliary equipment, and the process of issuing the power plant optimization plan also includes: The total energy consumption U of the auxiliary equipment under the maximum historical performance Ge` state is obtained. When the total energy consumption U of the auxiliary equipment is greater than the preset threshold W7, the data of the maximum historical performance Ge` is cleared.

[0018] Preferably, the system further comprises an early warning module and a service platform module, wherein the early warning module is used to receive an alarm report and generate an alarm action, and the service platform module is used to receive and display an efficiency monitoring report and a power plant optimization plan.

[0019] Compared with the prior art, the present invention has the following advantages: the system first collects electromagnetic data inside the power plant and real-time data on equipment operation, and screens the data to ensure the validity and scientificity of the data, providing an effective judgment basis for the efficiency optimization of the power plant, and then judges the operating status of the equipment by the electromagnetic data. On the basis of ensuring the normal operation of the equipment, further reasonable optimization solutions are screened out through analysis of historical performance data, which can ensure the stable operation of the power plant and improve the stability of the power plant's energy supply; at the same time, abnormal data is screened out in a targeted manner to provide targeted data support for maintenance personnel and power plant managers, so as to assist the power plant in making solutions in advance to avoid causing large economic losses, improve the economy of power plant operation, and make the system more worthy of promotion and use. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is the overall module diagram of the present invention. DETAILED DESCRIPTION

[0021] The following is a detailed description of an embodiment of the present invention. This embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiment.

[0022] like Figure 1 As shown, this embodiment provides a technical solution: an electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system, including an electromagnetic monitoring module, a data acquisition module, a database module, a preprocessing module, a detection module, a data processing module, and a data output module; The electromagnetic monitoring module is used to monitor the real-time electromagnetic data of various equipment inside the power plant; The data acquisition module is used to collect real-time data information of power plant operation; The preprocessing module is used to process real-time electromagnetic data and real-time data information, and delete abnormal data; The database module is used to store historical data information and standard electromagnetic data; Standard electromagnetic data is pre-made based on the electromagnetic data of each device in the power plant when it is working normally; The detection module is used to receive real-time electromagnetic data, historical data information and standard electromagnetic data, determine the operating status of each device in the power plant, and generate an equipment operation report. If the equipment operating status is abnormal, a warning report will be generated; The data processing module is used to receive equipment operation reports, real-time data information and historical data information. When the equipment is in normal operation, the performance of the power plant is judged and a performance monitoring report is generated by analyzing the real-time data information and historical data information. The performance monitoring report is then analyzed in combination with the real-time data information and historical data information to produce a power plant optimization plan. The data output module is used to receive and output the power plant optimization plan.

[0023] The system first collects electromagnetic data and real-time data on equipment operation inside the power plant, and screens them to ensure the validity and scientificity of the data, providing an effective judgment basis for the efficiency optimization of the power plant, and then judges the operating status of the equipment through the electromagnetic data. On the basis of ensuring the normal operation of the equipment, it further screens out reasonable optimization plans through analysis of historical performance data, which can ensure the stable operation of the power plant and improve the stability of the power plant's energy supply. At the same time, it specifically screens out abnormal data to provide targeted data support for maintenance personnel and power plant managers, so as to assist the power plant in making solutions in advance to avoid causing large economic losses, improve the economy of power plant operation, and make the system more worthy of promotion and use.

[0024] Among them, the processing process of the preprocessing module is: Obtain real-time electromagnetic data and real-time data information; A set of real-time electromagnetic data and real-time data information is randomly selected; Use the first rule to verify the real-time electromagnetic data and real-time data information, and delete abnormal data; The first rule is: Extract a set of data A1, A2, A3, ..., An; Calculate the distribution state S of the data. The specific calculation process is: ;

[0025] in, is the average of multiple data; when When >3, the data is abnormal and will be deleted.

[0026] The standard score of the data is determined by the mean and standard deviation of the data. When the distance between the data and the mean is outside 3 standard deviations, the data is judged as abnormal data and the data is cleared.

[0027] Among them, the equipment operation report includes normal operation report and warning report. The specific processing process of the detection module is as follows: Obtain real-time electromagnetic data of a group of equipment in the power plant, namely Q1, Q2, Q3, ..., Qn; Calculate the average electromagnetic data of the device ; Then import the standard electromagnetic data Qr of the equipment; When the average electromagnetic data ≤ standard electromagnetic data Qr, generate a normal operation report; When the average electromagnetic data >standard electromagnetic data Qr, a warning report is generated.

[0028] By calculating the average electromagnetic data of the equipment in the power plant and comparing it with the standard electromagnetic data of the equipment, it is determined whether the operating status of the equipment is abnormal, and the use status of the equipment is monitored to ensure the stability of the equipment in the power plant.

[0029] Furthermore, the historical data information includes historical electromagnetic data, when the average electromagnetic data When the value is less than or equal to the standard electromagnetic data Qr, the processing of the detection module also includes: Obtain a set of historical electromagnetic data of equipment in the power plant and calculate the average value Qa of the historical electromagnetic data; Importing Averaged EM Data ; Calculate the long-term electromagnetic fluctuation K1 of the equipment. The specific calculation process is: ;

[0030] Acquire a set of real-time electromagnetic data Q1`, Q2`, Q3`, ..., Qn` continuously in equal time periods; Calculate the short-term electromagnetic fluctuation K2 of the real-time electromagnetic data in each time period respectively; the specific calculation process is: ;

[0031] Among them, t1 is the time interval of equal time periods; Extract the maximum value K2` of the short-term electromagnetic fluctuation K2; Calculate the comprehensive fluctuation K3 of the electromagnetic data of the equipment. The specific calculation process is: K3=e1*K1+e2*K2`; Among them, e1 is the weight of the long-term electromagnetic fluctuation K1, e2 is the weight of the short-term electromagnetic fluctuation K2, e1+e2=1 and e1<e2; When the comprehensive fluctuation K3>the preset threshold W1, a warning report is generated.

[0032] When the power plant equipment is in operation, its electromagnetic monitoring data fluctuates. When the long-term electromagnetic fluctuation data of the equipment is too large, it indicates that the operating status of the equipment has declined and the equipment needs to be maintained or repaired. When the short-term electromagnetic fluctuation data of the equipment is too large, it indicates that there is damage inside the equipment and the operating status is unstable, requiring timely maintenance. By comprehensively analyzing the electromagnetic changes of the equipment and conducting comprehensive monitoring and analysis of the operating status of the equipment, the potential operating risks of the equipment can be discovered in time, and the staff can be reminded to deal with and prevent them in time, further improving the scientific nature and stability of the power plant operation.

[0033] During the use of the equipment, the electromagnetic monitoring value of normal equipment is in a stable state. When the comprehensive fluctuation value is within the normal range, but there are abnormal conditions in the equipment operation state, it is difficult to screen potential risks. Therefore, the following preferred solutions are proposed: Preferably, when the comprehensive fluctuation K3 ≤ the preset threshold W1, the processing process of the detection module further includes: Obtain the short-term electromagnetic fluctuation K2 in each time period t1, and import the node time of each time period; When the short-term electromagnetic fluctuation K2>preset threshold W2, it is marked to obtain a plurality of marked electromagnetic fluctuations K4; Obtain all marked electromagnetic fluctuations K4; Then read the node time at both ends of each short-term electromagnetic fluctuation K2 respectively; The rear node time of each period is defined as the reference node time, and the reference node time difference C of any marked electromagnetic fluctuation K4 is calculated; Use the formula N=C / t1 to calculate the number N1 of short-term electromagnetic fluctuations K2 that occur within the time difference C of any reference node; When the number N2 of marked electromagnetic fluctuations K4 within the reference node time difference C is equal to N1, and C≥3t1, a warning report is generated.

[0034] Real-time monitoring of the electromagnetic data of the equipment, marking of electromagnetic data with obvious abnormalities, and further determination of the duration of abnormal electromagnetic data. When abnormal electromagnetic data persists for too long, it indicates that there is a potential risk in the equipment and that it needs to be checked to prevent abnormal operation of the power plant, thus improving the practicality and reliability of the system.

[0035] Among them, the real-time data information includes real-time coal consumption data, real-time electricity production data, real-time temperature data and real-time pressure data in the boiler. The efficiency monitoring report includes a good efficiency report and an insufficient efficiency report. The generation process of the efficiency monitoring report is as follows: Obtain real-time pressure data, real-time temperature data, real-time coal consumption data and real-time electricity production data in the power plant; Calculate the efficiency G of the power plant under the conditions of real-time pressure data P' and real-time temperature data H' of the boiler. The specific calculation process is: G=L` / V`; Among them, L` is the real-time electricity production data, and V` is the real-time coal consumption data; When the efficiency G ≥ the preset threshold W3, the power plant efficiency is good and a good efficiency report is generated; When the efficiency G is less than the preset threshold W3, the power plant efficiency is insufficient and an efficiency deficiency report is generated.

[0036] Furthermore, the historical data information also includes historical efficiency data, historical temperature data in the boiler, and historical pressure data. The process of issuing the power plant optimization plan is as follows: When the efficiency G is less than the preset threshold W3, the historical efficiency data Ge of the boiler is imported; When the historical performance data Ge≥W3, the historical performance data is marked; Sort the marked historical performance data Ge and obtain the maximum historical performance data Ge`; Obtain the historical temperature data H` and the historical pressure data P` of the maximum historical efficiency data Ge`; Then obtain a set of historical performance data when the historical temperature data is H' and the historical pressure data is P', which are Gr1, Gr2, Gr3, ..., Grn respectively; Calculate the stability F of historical performance data. The specific calculation process is: ;

[0037] in, Average historical performance data When the stability F>preset threshold W4, the data is cleared, the maximum historical efficiency Ge` is reselected, and the historical temperature data and historical pressure data under the maximum historical efficiency Ge` are used as optimization reference data, and a power plant optimization plan is issued.

[0038] When the efficiency of a power plant is insufficient, good performance data of the power plant is obtained through historical data to ensure that the data matches the performance of the power plant equipment and can be realized; then the pressure and temperature under the efficiency are checked; finally, the historical data is filtered out to see if the power plant can achieve a stable performance under the temperature and pressure. When the power plant performance is stable, an indication of the operating temperature and pressure of the boiler is issued. At this time, the operating parameters of the auxiliary equipment are adjusted to achieve the operating temperature and pressure of the boiler to improve the efficiency of the power plant.

[0039] It should be noted that auxiliary equipment includes feed water pumps, circulating water pumps, condensate pumps, etc. They are mainly used for water circulation and transportation. Although these equipment require electric drive, their function is to support the operation of the main equipment.

[0040] Furthermore, when the stability F> the preset threshold W4, the process of issuing the power plant optimization plan also includes: Obtain the historical performance data of the maximum historical performance Ge` when the historical temperature data is H` and the historical pressure data is P, which are Gr1, Gr2, Gr3, ..., Grn respectively; Calculate the abnormality J of historical performance data. The specific calculation process is as follows; ;

[0041] When the abnormality J> the preset threshold W5, it indicates that the data is abnormal, which is abnormal performance data; Count the total number of historical performance data B1; Then count the number of abnormal performance data B2; Calculate the abnormal data ratio B3. The specific calculation process is as follows: B3=B2 / B1; When B3 is less than the preset threshold value W6, the data of the maximum historical performance Ge` is retained and an equipment inspection report is generated.

[0042] When the power plant's performance stability is insufficient, further check the abnormal performance data under the operating temperature and pressure. When the number of abnormal data accounts for a small proportion, it indicates that the value of the abnormal data deviates greatly from the average performance data. Under this performance, there are major hidden dangers in the equipment in the power plant, which need to be checked to eliminate risks.

[0043] Furthermore, the historical data information also includes the total energy consumption of auxiliary equipment. The process of issuing the power plant optimization plan also includes: The total energy consumption U of the auxiliary equipment under the maximum historical performance Ge` state is obtained. When the total energy consumption U of the auxiliary equipment is greater than the preset threshold W7, the data of the maximum historical performance Ge` is cleared.

[0044] The system also includes an early warning module and a service platform module. The early warning module is used to receive warning reports and generate warning actions, and the service platform module is used to receive and display efficiency monitoring reports and power plant optimization plans.

[0045] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0046] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0047] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A coal-fired power plant operation efficiency optimization management system based on electromagnetic sensing, characterized in that: It includes electromagnetic monitoring module, data acquisition module, database module, preprocessing module, detection module, data processing module and data output module; The electromagnetic monitoring module is used to monitor the real-time electromagnetic data of various equipment inside the power plant; The data acquisition module is used to collect real-time data information of power plant operation; The preprocessing module is used to process real-time electromagnetic data and real-time data information, and delete abnormal data; The database module is used to store historical data information and standard electromagnetic data; The detection module is used to receive real-time electromagnetic data, historical data information and standard electromagnetic data, determine the operating status of each device in the power plant, and generate an equipment operation report. If the equipment operating status is abnormal, a warning report will be generated; The data processing module is used to receive equipment operation reports, real-time data information and historical data information. When the equipment is in normal operation, the performance of the power plant is judged and a performance monitoring report is generated by analyzing the real-time data information and historical data information. The performance monitoring report is then analyzed in combination with the real-time data information and historical data information to produce a power plant optimization plan. The data output module is used to receive and output the power plant optimization plan.

2. According to claim 1, a coal-fired power plant operation efficiency optimization management system based on electromagnetic sensing is characterized by: The processing process of the preprocessing module is: Obtain real-time electromagnetic data and real-time data information; A set of real-time electromagnetic data and real-time data information is randomly selected; Use the first rule to verify the real-time electromagnetic data and real-time data information, and delete abnormal data; The first rule is: Extract a set of data A1, A2, A3, ..., An; Calculate the distribution state S of the data. The specific calculation process is: ； in, is the average of multiple data; when When >3, the data is considered abnormal and will be deleted.

3. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 1, characterized in that: The equipment operation report includes a normal operation report and a warning report. The specific processing process of the detection module is as follows: Obtain real-time electromagnetic data of a group of equipment in the power plant, namely Q1, Q2, Q3, ..., Qn; Calculate the average electromagnetic data of the device ; Then import the standard electromagnetic data Qr of the equipment; When the average electromagnetic data ≤ standard electromagnetic data Qr, generate a normal operation report; When the average electromagnetic data >standard electromagnetic data Qr, a warning report is generated.

4. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 3 is characterized by: The historical data information includes historical electromagnetic data, when the average electromagnetic data ≤ standard electromagnetic data Qr, the processing process of the detection module further includes: Obtain a set of historical electromagnetic data of equipment in the power plant and calculate the average value Qa of the historical electromagnetic data; Importing Averaged EM Data ; Calculate the long-term electromagnetic fluctuation K1 of the equipment. The specific calculation process is: ； Acquire a set of real-time electromagnetic data Q1`, Q2`, Q3`, ..., Qn` continuously in equal time periods; Calculate the short-term electromagnetic fluctuation K2 of the real-time electromagnetic data in each time period respectively; the specific calculation process is: ； Among them, t1 is the time interval of equal time periods; Extract the maximum value K2` of the short-term electromagnetic fluctuation K2; Calculate the comprehensive fluctuation K3 of the electromagnetic data of the equipment. The specific calculation process is: K3=e1*K1+e2*K2`; Among them, e1 is the weight of the long-term electromagnetic fluctuation K1, e2 is the weight of the short-term electromagnetic fluctuation K2, e1+e2=1 and e1<e2; When the comprehensive fluctuation K3>the preset threshold W1, a warning report is generated.

5. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 4 is characterized by: When the comprehensive fluctuation K3 ≤ the preset threshold W1, the processing process of the detection module further includes: Obtain the short-term electromagnetic fluctuation K2 in each time period t1, and import the node time of each time period; When the short-term electromagnetic fluctuation K2>preset threshold W2, it is marked to obtain a plurality of marked electromagnetic fluctuations K4; Obtain all marked electromagnetic fluctuations K4; Then read the node time at both ends of each short-term electromagnetic fluctuation K2 respectively; The rear node time of each period is defined as the reference node time, and the reference node time difference C of any marked electromagnetic fluctuation K4 is calculated; Use the formula N=C / t1 to calculate the number N1 of short-term electromagnetic fluctuations K2 that occur within the time difference C of any reference node; When the number N2 of marked electromagnetic fluctuations K4 within the reference node time difference C is equal to N1, and C≥3t1, a warning report is generated.

6. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 1, characterized in that: The real-time data information includes real-time coal consumption data, real-time electricity production data, real-time temperature data and real-time pressure data in the boiler. The performance monitoring report includes a good performance report and an insufficient performance report. The generation process of the performance monitoring report is as follows: Obtain real-time pressure data, real-time temperature data, real-time coal consumption data and real-time electricity production data in the power plant; Calculate the efficiency G of the power plant under the conditions of real-time pressure data P' and real-time temperature data H' of the boiler. The specific calculation process is: G=L` / V`; Among them, L` is the real-time electricity production data, and V` is the real-time coal consumption data; When the efficiency G ≥ the preset threshold W3, the power plant efficiency is good and a good efficiency report is generated; When the efficiency G is less than the preset threshold W3, the power plant efficiency is insufficient and an efficiency deficiency report is generated.

7. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 6, characterized in that: The historical data information also includes historical efficiency data, historical temperature data and historical pressure data in the boiler. The process of issuing the power plant optimization plan is as follows: When the efficiency G is less than the preset threshold W3, the historical efficiency data Ge of the boiler is imported; When the historical performance data Ge≥W3, the historical performance data is marked; Sort the marked historical performance data Ge and obtain the maximum historical performance data Ge`; Obtain the historical temperature data H` and the historical pressure data P` of the maximum historical efficiency data Ge`; Then obtain a set of historical performance data when the historical temperature data is H' and the historical pressure data is P', which are Gr1, Gr2, Gr3, ..., Grn respectively; Calculate the stability F of historical performance data. The specific calculation process is: ； in, is the average historical performance data; When the stability F>preset threshold W4, the data is cleared, the maximum historical efficiency Ge` is reselected, and the historical temperature data and historical pressure data under the maximum historical efficiency Ge` are used as optimization reference data, and a power plant optimization plan is issued.

8. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 7, characterized in that: When the stability F> the preset threshold W4, the process of issuing the power plant optimization plan further includes: Obtain the historical performance data of the maximum historical performance Ge` when the historical temperature data is H` and the historical pressure data is P, which are Gr1, Gr2, Gr3, ..., Grn respectively; Calculate the abnormality J of historical performance data. The specific calculation process is as follows; ； When the abnormality J> the preset threshold W5, it indicates that the data is abnormal, which is abnormal performance data; Count the total number of historical performance data B1; Then count the number of abnormal performance data B2; Calculate the abnormal data ratio B3. The specific calculation process is as follows: B3=B2 / B1: When B3 is less than the preset threshold value W6, the data of the maximum historical performance Ge` is retained and an equipment inspection report is generated.

9. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 7 or 8, characterized in that: The historical data information also includes the total energy consumption of auxiliary equipment. The process of issuing the power plant optimization plan also includes: The total energy consumption U of the auxiliary equipment under the maximum historical performance Ge` state is obtained. When the total energy consumption U of the auxiliary equipment is greater than the preset threshold W7, the data of the maximum historical performance Ge` is cleared.

10. The electromagnetic sensing-based coal-fired power plant operation efficiency optimization management system according to claim 1, characterized in that: It also includes an early warning module and a service platform module. The early warning module is used to receive warning reports and generate warning actions, and the service platform module is used to receive and display efficiency monitoring reports and power plant optimization plans.

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