A big data power plant indicator assessment and analysis system based on electromagnetic monitoring

Abstract

The invention discloses a big data power plant index assessment and analysis system based on electromagnetic monitoring, comprising an electromagnetic monitoring module, an environmental monitoring module, a correction module, a database module, a data verification module, a data processing module, and a data output module; the correction module is used for analyzing real-time parameter information to correct real-time electromagnetic data; the data verification module determines abnormal conditions of the corrected electromagnetic data by analyzing historical data information; the data processing module is used for determining abnormal conditions of the electromagnetic field in the power plant; the invention first collects electromagnetic monitoring data in the power plant, corrects the monitoring data by analyzing the influence of the position of the monitoring point on its monitoring value; then verifies whether the corrected electromagnetic data has abnormalities, further improves the accuracy and reliability of the data, and finally further analyzes the electromagnetic environment in the power plant, determines the operating status of each device in the power plant, and assesses the governance effect of the power plant.

Description

Technical Field

[0001] The present invention relates to the field of data monitoring, and in particular to a big data power plant index assessment and analysis system based on electromagnetic monitoring. Background Art

[0002] The importance of electromagnetic monitoring of equipment in power plants lies in that it can promptly detect potential electromagnetic interference and pollution problems, ensuring the normal operation of power plant equipment and the safety and stability of the power system; however, the electromagnetic environment in power plants is complex, and electromagnetic monitoring data is affected by many factors, such as temperature, humidity, vibration, measurement deviation and other factors, which lead to large errors in electromagnetic analysis and make it difficult to provide accurate judgment basis for power plant management, which in turn leads to deviations in the electromagnetic analysis results of power plants and affects the scientific maintenance of power plants; therefore, a big data power plant indicator assessment and analysis system based on electromagnetic monitoring 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 big data power plant indicator assessment and analysis system based on electromagnetic monitoring 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, an environmental monitoring module, a correction module, a database module, a data verification module, a data processing module, and a data output module;

[0005] The electromagnetic monitoring module is used to monitor the electromagnetic field in the power plant and obtain real-time electromagnetic information;

[0006] Environmental monitoring module users monitor environmental parameters in the power plant and obtain real-time parameter information;

[0007] The database module is used to store historical data information, standard index base values ​​and monitoring point distribution data of plant equipment;

[0008] The correction module is used to receive real-time electromagnetic information and real-time parameter information, and correct the real-time electromagnetic data by analyzing the real-time parameter information to obtain corrected electromagnetic data;

[0009] The data verification module is used to receive historical data information, correct electromagnetic data, determine the abnormal situation of the corrected electromagnetic data through analysis of historical data information, issue an abnormal monitoring report, and feed back the abnormal monitoring report to the electromagnetic monitoring module;

[0010] The data processing module is used to receive and analyze the distribution data of monitoring points, the base values ​​of standard indicators, the corrected electromagnetic data of different monitoring points and real-time parameter information, determine the abnormal conditions of the electromagnetic field in the power plant, analyze the abnormal conditions, determine the completion of the electromagnetic governance assessment indicators and issue an analysis report;

[0011] The data output module is used to receive and output analysis reports.

[0012] Preferably, the real-time parameter information includes the real-time size information of the electromagnetic monitoring points, and the specific processing process of the correction module is:

[0013] The circumscribed sphere A1 is established based on the equipment to be monitored in the power plant;

[0014] Obtaining real-time electromagnetic information of each electromagnetic monitoring point and real-time dimension data of each electromagnetic monitoring point from the surface of sphere A1;

[0015] The real-time electromagnetic data of each electromagnetic monitoring point are: Q1, Q2, Q3, ..., Qn, and the real-time size data of each monitoring point from the surface of the sphere A1 are: L1, L2, L3, ..., Ln;

[0016] Calculate the correlation R between real-time electromagnetic data and real-time dimension data. The specific calculation process is:

[0017] ;

[0018] in, is the average value of multiple real-time size data. It is the average value of multiple real-time electromagnetic data;

[0019] When the correlation When <0.5, let the correction value of electromagnetic data Qr= To obtain corrected electromagnetic data;

[0020] When the correlation When ≥0.5, the linear regression equation Q=β1+β2·L of the real-time electromagnetic data Q and the real-time dimension data L is established;

[0021] Use the least squares method to calculate β1. The specific calculation process is:

[0022] ;

[0023] Let the correction value Qr of electromagnetic data = β1 to obtain corrected electromagnetic data.

[0024] Preferably, when the relevance When ≥0.5, the acquisition process of corrected electromagnetic data also includes:

[0025] Get the parameter information of sphere A1;

[0026] Taking the geometric center of the monitoring device as the origin, three virtual straight lines are established in the length direction, width direction and height direction of the monitoring device respectively;

[0027] Obtain the intersection points of the three virtual straight lines and the device surface respectively, and obtain the maximum line segment size Lr between the multiple intersection points and the sphere A1 respectively;

[0028] With the maximum line segment size Lr as the height and the plane A2 corresponding to the monitoring device and the maximum line segment as the bottom surface, a vertebral body A3 is established, and the intersection point A4 of the maximum line segment and the device is obtained;

[0029] Obtain the vertical dimensions of the intersection point A4 from the edge line of the monitoring bottom surface A2, which are Le1, Le2, ... Len respectively;

[0030] The formula tanθ=Lr / Len is used to calculate the inclination angle of each side of the vertebral body A3, and the minimum inclination angle θ1 is obtained;

[0031] When the minimum tilt angle θ1> the preset threshold W1, an inscribed sphere A5 of the monitoring device is established;

[0032] Calculate the radius Ra1 of sphere A1 and the radius Ra2 of sphere A5 respectively;

[0033] Correct the real-time dimension data Ln and set the correction value Ln`=Ln+1 / 2·(Ra1+Ra2).

[0034] Preferably, when the relevance When ≥0.5, the acquisition process of corrected electromagnetic data also includes:

[0035] Read the real-time dimension data Ln and real-time electromagnetic data Qn of the nth monitoring point;

[0036] A sphere A6 is established with the geometric center of the monitoring device as the origin and the real-time size data of the nth monitoring point as the radius;

[0037] Continuously acquire multiple electromagnetic monitoring data on sphere A6, namely Qe1, Qe2, Qe3, ...Qen;

[0038] Calculate the average value of multiple electromagnetic monitoring data ;

[0039] Then calculate the deviation degree E1 of the real-time electromagnetic data Qn. The specific calculation process is:

[0040] ;

[0041] When the deviation degree E1>preset threshold W2, the real-time electromagnetic data Qn is eliminated.

[0042] Preferably, the historical data information includes historical electromagnetic data of each monitoring point, and the specific processing process of the data verification module is:

[0043] Obtain historical electromagnetic data of the same monitoring device at the same time point t in recent period;

[0044] Calculate the historical corrected electromagnetic data Qr at each time point t respectively;

[0045] Establish the rectangular coordinate system of historical corrected electromagnetic data Qr and monitoring time t;

[0046] Marking multiple historical corrected electromagnetic data Qr in a rectangular coordinate system to establish a discrete graph of historical corrected electromagnetic data Qr and time node t;

[0047] Establish a rectangular area C1 in the discrete graph, and the rectangular area C1 includes all historical corrected electromagnetic data;

[0048] Read the real-time corrected electromagnetic data and mark it in the discrete graph to establish the reference point C0;

[0049] Establish a standard circle C2 through C0 with the geometric center of the rectangular area C1 as the origin;

[0050] Read the coordinate values ​​of each corner of the rectangular area C1 respectively to calculate the area S1 of the rectangular area C1;

[0051] Then read the coordinate value of the standard circle C2 along the direction parallel to the coordinate value to calculate the area S2 of the standard circle C2;

[0052] Calculate the real-time distribution value E2 of the corrected electromagnetic data. The specific calculation process is:

[0053] E2=S2 / S1;

[0054] When the distribution value E2>the preset threshold value W3, an abnormal monitoring report of electromagnetic monitoring is generated, and the abnormal monitoring report is fed back to the electromagnetic monitoring module.

[0055] Preferably, the process of establishing the rectangular area C1 further includes:

[0056] One of the side lines B1 of the rectangular area C1 is moved toward the center thereof by one coordinate unit to form a virtual line B2;

[0057] Count the number Y of historical corrected electromagnetic data between the virtual line B2 and the edge line B1;

[0058] Read the coordinate value of the edge line B1 and calculate the area S3 of the area between the virtual line B2 and the edge line B1;

[0059] Calculate the regional distribution density E3 of the historical corrected electromagnetic data in the area. The specific calculation process is:

[0060] E3=Y / S3;

[0061] When the area distribution density E3 is less than the preset threshold W4, the virtual line B2 is used as the edge line of the rectangular area C1.

[0062] Preferably, the analysis report is divided into an electromagnetic assessment compliance report, an electromagnetic assessment abnormality report, an electromagnetic assessment warning report, and a local abnormality warning report. The specific processing process of the data processing module is as follows:

[0063] Obtain the distribution data of monitoring points in the power plant and the corrected electromagnetic data of different monitoring points;

[0064] Import the base value of standard indicators to obtain the standard values ​​of electromagnetic data at different monitoring points;

[0065] Count the number of monitoring points M1;

[0066] The number of monitoring points M2 whose electromagnetic values ​​are greater than the standard value of the electromagnetic data of the point is counted;

[0067] Calculate the proportion of abnormal monitoring points E4. The specific calculation process is as follows:

[0068] E4=M2 / M1;

[0069] Then select the points where the real-time corrected electromagnetic data is greater than the standard value of the electromagnetic data of the corresponding monitoring point, and calculate the overscale E5 of the electromagnetic value of each point. The specific calculation process is:

[0070] ;

[0071] Among them, Qr` is the standard value of the electromagnetic data at the monitoring point;

[0072] Calculate the power plant electromagnetic monitoring assessment score G. The specific calculation process is as follows:

[0073] G=J1·E4+J2· ;

[0074] Among them, J1 is the correction value of the proportion of abnormal monitoring points E4, J2 is the correction value of the over-scale of electromagnetic value E5, is the average value of the overscale E5 of the electromagnetic value at each point, let J1+J2=1, and J1>J2;

[0075] When the assessment score G ≤ the preset threshold W5, the electromagnetic treatment effect of the power plant is good, and an electromagnetic assessment compliance report is generated;

[0076] When the preset threshold value W5 of the assessment score is less than or equal to the preset threshold value W6, the electromagnetic value of the power plant is abnormal, and an abnormal report of the electromagnetic assessment is generated;

[0077] When the assessment score G>the preset threshold W6, there are serious problems in the electromagnetic management of the power plant, and a warning report of the electromagnetic assessment is generated.

[0078] Preferably, the calculation process of the power plant electromagnetic monitoring assessment score G also includes:

[0079] The device U that obtains the real-time corrected electromagnetic data is greater than the electromagnetic data of the corresponding monitoring point;

[0080] Obtain multiple monitoring points of device U;

[0081] Import the corrected electromagnetic data of multiple monitoring points respectively, and count the number of monitoring points Z1;

[0082] Count the number of abnormal monitoring points Z2;

[0083] Use the formula P=Z2 / Z1 to calculate the proportion of abnormal monitoring points;

[0084] When P is less than the preset threshold W7, the data of the abnormal monitoring point is discarded.

[0085] Preferably, when P>preset threshold W7, the calculation process of the power plant electromagnetic monitoring assessment score G also includes:

[0086] Acquire multiple monitoring points of the device U and multiple abnormal monitoring points contained therein;

[0087] Establishing the first cubic area A7 including all monitoring points;

[0088] Establish a second cubic area A8 including all abnormal monitoring points;

[0089] Taking the unit size as a reference, obtain the size information area volume V1 of the first cubic area A7;

[0090] Then obtain the size information area volume V2 of the second cube area A8;

[0091] The concentration of abnormal monitoring points is calculated using the formula F=V2 / V1;

[0092] When F is less than the preset threshold value W8, the data of the abnormal monitoring point is retained and a warning report of local abnormality of the equipment is generated.

[0093] Compared with the prior art, the present invention has the following advantages: the system first collects electromagnetic monitoring data in the power plant, and corrects the monitoring data by analyzing the influence of the location of the monitoring point on its monitoring value; then, by analyzing the historical data, it is verified whether there are abnormalities in the corrected electromagnetic data, and the accuracy and reliability of the data are further improved. Finally, the electromagnetic environment in the power plant is further analyzed to determine the operating status of each equipment in the power plant to assess the governance effect of the power plant, and to determine abnormal situations, which can provide decision support for power plant managers, realize comprehensive monitoring and analysis of the electromagnetic environment of the power plant, optimize the monitoring process, and improve monitoring efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0094] Figure 1 It is the overall module diagram of the present invention. DETAILED DESCRIPTION

[0095] 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.

[0096] like Figure 1 As shown, this embodiment provides a technical solution: a big data power plant index assessment and analysis system based on electromagnetic monitoring, including an electromagnetic monitoring module, an environmental monitoring module, a correction module, a database module, a data verification module, a data processing module, and a data output module;

[0097] The electromagnetic monitoring module is used to monitor the electromagnetic field in the power plant and obtain real-time electromagnetic information;

[0098] Environmental monitoring module users monitor environmental parameters in the power plant and obtain real-time parameter information;

[0099] The database module is used to store historical data information, standard index base values ​​and monitoring point distribution data of plant equipment;

[0100] It should be noted that the base value of the standard index is the maximum normal value of the electromagnetic monitoring value of each equipment in the power plant, which is pre-made in advance according to the equipment in the power plant;

[0101] The correction module is used to receive real-time electromagnetic information and real-time parameter information, and correct the real-time electromagnetic data by analyzing the real-time parameter information to obtain corrected electromagnetic data;

[0102] The data verification module is used to receive historical data information, correct electromagnetic data, determine the abnormal situation of the corrected electromagnetic data through analysis of historical data information, issue an abnormal monitoring report, and feed back the abnormal monitoring report to the electromagnetic monitoring module;

[0103] The data processing module is used to receive and analyze the distribution data of monitoring points, the base values ​​of standard indicators, the corrected electromagnetic data of different monitoring points and real-time parameter information, determine the abnormal conditions of the electromagnetic field in the power plant, analyze the abnormal conditions, determine the completion of the electromagnetic governance assessment indicators and issue an analysis report;

[0104] The data output module is used to receive and output analysis reports.

[0105] The system first collects electromagnetic monitoring data from the power plant, and corrects the monitoring data by analyzing the impact of the location of the monitoring points on their monitoring values. It then verifies whether the corrected electromagnetic data has any anomalies by analyzing historical data, further improving the accuracy and reliability of the data. Finally, it further analyzes the electromagnetic environment in the power plant, determines the operating status of each device in the power plant to assess the power plant's governance effect, and makes judgments on abnormal situations. It can provide decision-making support for power plant managers, realize comprehensive monitoring and analysis of the power plant's electromagnetic environment, optimize the monitoring process, and improve monitoring efficiency.

[0106] Among them, the real-time parameter information includes the real-time size information of the electromagnetic monitoring points. The specific processing process of the correction module is as follows:

[0107] The circumscribed sphere A1 is established based on the equipment to be monitored in the power plant;

[0108] Obtaining real-time electromagnetic information of each electromagnetic monitoring point and real-time dimension data of each electromagnetic monitoring point from the surface of sphere A1;

[0109] The real-time electromagnetic data of each electromagnetic monitoring point are: Q1, Q2, Q3, ..., Qn, and the real-time size data of each monitoring point from the surface of the sphere A1 are: L1, L2, L3, ..., Ln;

[0110] Calculate the correlation R between real-time electromagnetic data and real-time dimension data. The specific calculation process is:

[0111] ;

[0112] in, is the average value of multiple real-time size data. It is the average value of multiple real-time electromagnetic data;

[0113] When the correlation When <0.5, let the correction value of electromagnetic data Qr= To obtain corrected electromagnetic data;

[0114] When the correlation When ≥0.5, the linear regression equation Q=β1+β2·L of the real-time electromagnetic data Q and the real-time dimension data L is established;

[0115] It should be noted that β1 is the electromagnetic value monitored when the distance between the monitoring point and the monitoring equipment is 0, which is the electromagnetic monitoring value of the monitoring equipment.

[0116] Use the least squares method to calculate β1. The specific calculation process is:

[0117] ;

[0118] Let the correction value Qr of electromagnetic data = β1 to obtain corrected electromagnetic data.

[0119] In this embodiment, the relationship between the electromagnetic monitoring value and the distance between the monitoring point and the monitoring equipment is first analyzed to determine whether there is a correlation between the two. When there is no correlation, the average value of the electromagnetic monitoring value is used to replace the electromagnetic value of the equipment; when there is a correlation between the two, the electromagnetic value of the monitoring equipment is calculated through a linear regression equation, which can effectively improve the accuracy of the electromagnetic monitoring value of the equipment and lay the foundation for the subsequent analysis process.

[0120] The above scheme calculates the electromagnetic value of the device based on the circumscribed sphere A1 of the device, that is, the electromagnetic value on the circumscribed sphere A1 is the electromagnetic value of the device. However, due to the diverse shapes of monitoring devices, the length, width and height of some devices vary greatly. Some monitoring positions on the circumscribed sphere A1 are far away from the device and cannot replace the electromagnetic value of the device. To solve this problem, the following preferred scheme is proposed:

[0121] Preferably, when the relevance When ≥0.5, the acquisition process of corrected electromagnetic data also includes:

[0122] Get the parameter information of sphere A1;

[0123] Taking the geometric center of the monitoring device as the origin, three virtual straight lines are established in the length direction, width direction and height direction of the monitoring device respectively;

[0124] Obtain the intersection points of the three virtual straight lines and the device surface respectively, and obtain the maximum line segment size Lr between the multiple intersection points and the sphere A1 respectively;

[0125] With the maximum line segment size Lr as the height and the plane A2 corresponding to the monitoring device and the maximum line segment as the bottom surface, a vertebral body A3 is established, and the intersection point A4 of the maximum line segment and the device is obtained;

[0126] Obtain the vertical dimensions of the intersection point A4 from the edge line of the monitoring bottom surface A2, which are Le1, Le2, ... Len respectively;

[0127] The formula tanθ=Lr / Len is used to calculate the inclination angle of each side of the vertebral body A3, and the minimum inclination angle θ1 is obtained;

[0128] When the minimum tilt angle θ1> the preset threshold W1, an inscribed sphere A5 of the monitoring device is established;

[0129] Calculate the radius Ra1 of sphere A1 and the radius Ra2 of sphere A5 respectively;

[0130] Correct the real-time dimension data Ln and set the correction value Ln`=Ln+1 / 2·(Ra1+Ra2).

[0131] First, the maximum distance of sphere A1 from the equipment in different directions is screened out, and then cone A3 is established based on the corresponding surface of the equipment. By calculating the inclination angles of each side of A3, it is determined whether there is a large difference in the inclination angles of each surface of cone A3 when the maximum distance exists; when the difference is large, it indicates that there is a large difference in the shape of the equipment, and the monitoring value needs to be adjusted. When the inclination angle is too large, the monitoring point on sphere A1 is far away from the equipment, and the monitoring value also needs to be adjusted. The equipment size is the largest at the minimum inclination angle, and it is also the farthest from sphere A1 at this time. By judging the size of this angle, the representativeness of the equipment monitoring value is inferred. When the angle is large, the size of sphere A1 is adjusted to reduce the error, thereby further improving the accuracy and representativeness of the equipment.

[0132] Furthermore, when the correlation When ≥0.5, the acquisition process of corrected electromagnetic data also includes:

[0133] Read the real-time dimension data Ln and real-time electromagnetic data Qn of the nth monitoring point;

[0134] A sphere A6 is established with the geometric center of the monitoring device as the origin and the real-time size data of the nth monitoring point as the radius;

[0135] Continuously acquire multiple electromagnetic monitoring data on sphere A6, namely Qe1, Qe2, Qe3, ...Qen;

[0136] Calculate the average value of multiple electromagnetic monitoring data ;

[0137] Then calculate the deviation degree E1 of the real-time electromagnetic data Qn. The specific calculation process is:

[0138] ;

[0139] When the deviation degree E1>preset threshold W2, the real-time electromagnetic data Qn is eliminated.

[0140] Collect multiple electromagnetic monitoring values ​​at locations equidistant from the equipment, determine whether there are any abnormalities in the electromagnetic values ​​at the monitoring points used to calculate the electromagnetic values ​​of the equipment, and process them.

[0141] Among them, the historical data information includes the historical electromagnetic data of each monitoring point, and the specific processing process of the data verification module is as follows:

[0142] Obtain historical electromagnetic data of the same monitoring device at the same time point t in recent period;

[0143] Calculate the historical corrected electromagnetic data Qr at each time point t respectively;

[0144] Establish the rectangular coordinate system of historical corrected electromagnetic data Qr and monitoring time t;

[0145] Marking multiple historical corrected electromagnetic data Qr in a rectangular coordinate system to establish a discrete graph of historical corrected electromagnetic data Qr and time node t;

[0146] Establish a rectangular area C1 in the discrete graph, and the rectangular area C1 includes all historical corrected electromagnetic data;

[0147] Read the real-time corrected electromagnetic data and mark it in the discrete graph to establish the reference point C0;

[0148] Establish a standard circle C2 through C0 with the geometric center of the rectangular area C1 as the origin;

[0149] Read the coordinate values ​​of each corner of the rectangular area C1 respectively to calculate the area S1 of the rectangular area C1;

[0150] Then read the coordinate value of the standard circle C2 along the direction parallel to the coordinate value to calculate the area S2 of the standard circle C2;

[0151] Calculate the real-time distribution value E2 of the corrected electromagnetic data. The specific calculation process is:

[0152] E2=S2 / S1;

[0153] When the distribution value E2>the preset threshold value W3, an abnormal monitoring report of electromagnetic monitoring is generated, and the abnormal monitoring report is fed back to the electromagnetic monitoring module.

[0154] It should be noted that due to the stable operation of the equipment in the short term, the electromagnetic monitoring values ​​at the same time point are slightly different and there is a small amount of scattered data. Therefore, a large amount of data is concentrated near the middle of the rectangular area C1. Therefore, the degree of deviation can be judged by the area ratio of the area where the real-time monitoring point is located to the entire rectangular area C1.

[0155] This embodiment first determines the basic range of equipment monitoring values ​​based on historical electromagnetic monitoring values, establishes a rectangular area based on the basic range, and then calculates the degree of deviation from the data set center area based on the location of the real-time corrected electromagnetic data. When the degree of deviation is large, it indicates that the data value is abnormal and needs to be reviewed.

[0156] Furthermore, the process of establishing the rectangular area C1 also includes:

[0157] One of the side lines B1 of the rectangular area C1 is moved toward the center thereof by one coordinate unit to form a virtual line B2;

[0158] Count the number Y of historical corrected electromagnetic data between the virtual line B2 and the edge line B1;

[0159] Read the coordinate value of the edge line B1 and calculate the area S3 of the area between the virtual line B2 and the edge line B1;

[0160] Calculate the regional distribution density E3 of the historical corrected electromagnetic data in the area. The specific calculation process is:

[0161] E3=Y / S3;

[0162] When the area distribution density E3 is less than the preset threshold W4, the virtual line B2 is used as the edge line of the rectangular area C1.

[0163] By calculating the number of local electromagnetic values ​​in the rectangular area C1, the size of the rectangular area C1 is adjusted to reduce the verification error of the corrected electromagnetic data.

[0164] Among them, the analysis report is divided into electromagnetic assessment compliance report, electromagnetic assessment abnormality report, electromagnetic assessment warning report and local abnormality warning report. The specific processing process of the data processing module is as follows:

[0165] Obtain the distribution data of monitoring points in the power plant and the corrected electromagnetic data of different monitoring points;

[0166] Import the base value of standard indicators to obtain the standard values ​​of electromagnetic data at different monitoring points;

[0167] Count the number of monitoring points M1;

[0168] The number of monitoring points M2 whose electromagnetic values ​​are greater than the standard value of the electromagnetic data of the point is counted;

[0169] Calculate the proportion of abnormal monitoring points E4. The specific calculation process is as follows:

[0170] E4=M2 / M1;

[0171] Then select the points where the real-time corrected electromagnetic data is greater than the standard value of the electromagnetic data of the corresponding monitoring point, and calculate the overscale E5 of the electromagnetic value of each point. The specific calculation process is:

[0172] ;

[0173] Among them, Qr` is the standard value of the electromagnetic data at the monitoring point;

[0174] Calculate the power plant electromagnetic monitoring assessment score G. The specific calculation process is as follows:

[0175] G=J1·E4+J2· ;

[0176] Among them, J1 is the correction value of the proportion of abnormal monitoring points E4, J2 is the correction value of the over-scale of electromagnetic value E5, is the average value of the overscale E5 of the electromagnetic value at each point, let J1+J2=1, and J1>J2;

[0177] When the assessment score G ≤ the preset threshold W5, the electromagnetic treatment effect of the power plant is good, and an electromagnetic assessment compliance report is generated;

[0178] When the preset threshold value W5 of the assessment score is less than or equal to the preset threshold value W6, the electromagnetic value of the power plant is abnormal, and an abnormal report of the electromagnetic assessment is generated;

[0179] When the assessment score G>the preset threshold W6, there are serious problems in the electromagnetic management of the power plant, and a warning report of the electromagnetic assessment is generated.

[0180] The operating status of the equipment inside the power plant is comprehensively judged by comprehensively considering the abnormal number and degree of electromagnetic monitoring values ​​of each equipment in the power plant. The management status of the equipment and environment inside the power plant is reflected according to the electromagnetic monitoring values. The management indicators are evaluated based on the electromagnetic management results, and the achievement of the evaluation is judged to provide decision support for power plant managers.

[0181] Furthermore, the calculation process of the power plant electromagnetic monitoring assessment score G also includes:

[0182] The device U that obtains the real-time corrected electromagnetic data is greater than the electromagnetic data of the corresponding monitoring point;

[0183] Obtain multiple monitoring points of device U;

[0184] Import the corrected electromagnetic data of multiple monitoring points respectively, and count the number of monitoring points Z1;

[0185] Count the number of abnormal monitoring points Z2;

[0186] Use the formula P=Z2 / Z1 to calculate the proportion of abnormal monitoring points;

[0187] When P is less than the preset threshold W7, the data of the abnormal monitoring point is discarded.

[0188] By analyzing the electromagnetic values ​​at different monitoring points of a single device, the probability of abnormality in the device is determined. When the probability is small, the data is eliminated to improve the actual use value and representativeness of the electromagnetic monitoring assessment score G.

[0189] When the electromagnetic monitoring values ​​of the equipment are abnormal, the equipment is abnormal, but it is impossible to provide valuable reference information on the abnormal situation of the equipment. Therefore, the following further technical solutions are proposed:

[0190] Furthermore, when P>preset threshold W7, the calculation process of the power plant electromagnetic monitoring assessment score G also includes:

[0191] Acquire multiple monitoring points of the device U and multiple abnormal monitoring points contained therein;

[0192] Establishing the first cubic area A7 including all monitoring points;

[0193] Establish a second cubic area A8 including all abnormal monitoring points;

[0194] Taking the unit size as a reference, obtain the size information area volume V1 of the first cubic area A7;

[0195] Then obtain the size information area volume V2 of the second cube area A8;

[0196] The concentration of abnormal monitoring points is calculated using the formula F=V2 / V1;

[0197] When F is less than the preset threshold value W8, the data of the abnormal monitoring point is retained and a warning report of local abnormality of the equipment is generated.

[0198] First determine the monitoring points of abnormal monitoring electromagnetic values, and then analyze the concentration of abnormal monitoring points. When the abnormal monitoring points are concentrated in a certain area of ​​the equipment, it indicates that there is an abnormality in this area of ​​the equipment, causing changes in the equipment's operating status, thereby improving the targeted use of the system.

[0199] 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.

[0200] 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.

[0201] 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 big data power plant index assessment and analysis system based on electromagnetic monitoring, characterized in that: It includes electromagnetic monitoring module, environmental monitoring module, correction module, database module, data verification module, data processing module and data output module; The electromagnetic monitoring module is used to monitor the electromagnetic field in the power plant and obtain real-time electromagnetic information; Environmental monitoring module users monitor environmental parameters in the power plant and obtain real-time parameter information; The database module is used to store historical data information, standard index base values ​​and monitoring point distribution data of plant equipment; The correction module is used to receive real-time electromagnetic information and real-time parameter information, and correct the real-time electromagnetic data by analyzing the real-time parameter information to obtain corrected electromagnetic data; The data verification module is used to receive historical data information, correct electromagnetic data, determine the abnormal situation of the corrected electromagnetic data through analysis of historical data information, issue an abnormal monitoring report, and feed back the abnormal monitoring report to the electromagnetic monitoring module; The data processing module is used to receive and analyze the distribution data of monitoring points, the base values ​​of standard indicators, the corrected electromagnetic data of different monitoring points and real-time parameter information, determine the abnormal conditions of the electromagnetic field in the power plant, analyze the abnormal conditions, determine the completion of the electromagnetic governance assessment indicators and issue an analysis report; The data output module is used to receive and output analysis reports; The real-time parameter information includes the real-time dimension information of the electromagnetic monitoring points. The specific processing process of the correction module is as follows: The circumscribed sphere A1 is established based on the equipment to be monitored in the power plant; Obtaining real-time electromagnetic information of each electromagnetic monitoring point and real-time dimension data of each electromagnetic monitoring point from the surface of sphere A1; The real-time electromagnetic data of each electromagnetic monitoring point are: Q1, Q2, Q3, ..., Qn, and the real-time size data of each monitoring point from the surface of the sphere A1 are: L1, L2, L3, ..., Ln; Calculate the correlation R between real-time electromagnetic data and real-time dimension data. The specific calculation process is: ； in, is the average value of multiple real-time size data. It is the average value of multiple real-time electromagnetic data; When the correlation When <0.5, let the correction value of electromagnetic data Qr= To obtain corrected electromagnetic data; When the correlation When ≥0.5, the linear regression equation Q=β1+β2·L of the real-time electromagnetic data Q and the real-time dimension data L is established; Use the least squares method to calculate β1. The specific calculation process is: ； Let the correction value of electromagnetic data Qr = β1 to obtain the corrected electromagnetic data; When the correlation When ≥0.5, the acquisition process of corrected electromagnetic data also includes: Get the parameter information of sphere A1; Taking the geometric center of the monitoring device as the origin, three virtual straight lines are established in the length direction, width direction and height direction of the monitoring device respectively; Obtain the intersection points of the three virtual straight lines and the device surface respectively, and obtain the maximum line segment size Lr between the multiple intersection points and the sphere A1 respectively; With the maximum line segment size Lr as the height and the plane A2 corresponding to the monitoring device and the maximum line segment as the bottom surface, a vertebral body A3 is established, and the intersection point A4 of the maximum line segment and the device is obtained; Obtain the vertical dimensions of the intersection point A4 from the edge line of the monitoring bottom surface A2, which are Le1, Le2, ... Len respectively; The formula tanθ=Lr / Len is used to calculate the inclination angle of each side of the vertebral body A3, and the minimum inclination angle θ1 is obtained; When the minimum tilt angle θ1>preset threshold W1, an inscribed sphere A5 of the monitoring device is established; Calculate the radius Ra1 of sphere A1 and the radius Ra2 of sphere A5 respectively; Correct the real-time dimension data Ln and set the correction value Ln`=Ln+1 / 2·(Ra1+Ra2).

2. According to the big data power plant index assessment and analysis system based on electromagnetic monitoring according to claim 1, it is characterized by: When the correlation When ≥0.5, the acquisition process of corrected electromagnetic data also includes: Read the real-time dimension data Ln and real-time electromagnetic data Qn of the nth monitoring point; A sphere A6 is established with the geometric center of the monitoring device as the origin and the real-time size data of the nth monitoring point as the radius; Continuously acquire multiple electromagnetic monitoring data on sphere A6, namely Qe1, Qe2, Qe3, ...Qen; Calculate the average value of multiple electromagnetic monitoring data ; Then calculate the deviation degree E1 of the real-time electromagnetic data Qn. The specific calculation process is: ； When the deviation degree E1>preset threshold W2, the real-time electromagnetic data Qn is eliminated.

3. According to the big data power plant index assessment and analysis system based on electromagnetic monitoring according to claim 1, it is characterized by: The historical data information includes the historical electromagnetic data of each monitoring point. The specific processing process of the data verification module is as follows: Obtain historical electromagnetic data of the same monitoring device at the same time point t in recent period; Calculate the historical corrected electromagnetic data Qr at each time point t respectively; Establish the rectangular coordinate system of historical corrected electromagnetic data Qr and monitoring time t; Marking multiple historical corrected electromagnetic data Qr in a rectangular coordinate system to establish a discrete graph of historical corrected electromagnetic data Qr and time node t; Establish a rectangular area C1 in the discrete graph, and the rectangular area C1 includes all historical corrected electromagnetic data; Read the real-time corrected electromagnetic data and mark it in the discrete graph to establish the reference point C0; Establish a standard circle C2 through C0 with the geometric center of the rectangular area C1 as the origin; Read the coordinate values ​​of each corner of the rectangular area C1 respectively to calculate the area S1 of the rectangular area C1; Then read the coordinate value of the standard circle C2 along the direction parallel to the coordinate value to calculate the area S2 of the standard circle C2; Calculate the real-time distribution value E2 of the corrected electromagnetic data. The specific calculation process is: E2=S2 / S1; When the distribution value E2>the preset threshold value W3, an abnormal monitoring report of electromagnetic monitoring is generated, and the abnormal monitoring report is fed back to the electromagnetic monitoring module.

4. The big data power plant index assessment and analysis system based on electromagnetic monitoring according to claim 3 is characterized by: The process of establishing the rectangular area C1 also includes: One of the side lines B1 of the rectangular area C1 is moved toward the center thereof by one coordinate unit to form a virtual line B2; Count the number Y of historical corrected electromagnetic data between the virtual line B2 and the edge line B1; Read the coordinate value of the edge line B1 and calculate the area S3 of the area between the virtual line B2 and the edge line B1; Calculate the regional distribution density E3 of the historical corrected electromagnetic data in the area. The specific calculation process is: E3=Y / S3; When the area distribution density E3 is less than the preset threshold W4, the virtual line B2 is used as the edge line of the rectangular area C1.

5. The big data power plant index assessment and analysis system based on electromagnetic monitoring according to claim 1 is characterized by: The analysis report is divided into electromagnetic assessment compliance report, electromagnetic assessment abnormality report, electromagnetic assessment warning report and local abnormality warning report. The specific processing process of the data processing module is as follows: Obtain the distribution data of monitoring points in the power plant and the corrected electromagnetic data of different monitoring points; Import the base value of standard indicators to obtain the standard values ​​of electromagnetic data at different monitoring points; Count the number of monitoring points M1; The number of monitoring points M2 whose electromagnetic values ​​are greater than the standard value of the electromagnetic data of the point is counted; Calculate the proportion of abnormal monitoring points E4. The specific calculation process is as follows: E4=M2 / M1; Then select the points where the real-time corrected electromagnetic data is greater than the standard value of the electromagnetic data of the corresponding monitoring point, and calculate the overscale E5 of the electromagnetic value of each point. The specific calculation process is: ； Among them, Qr` is the standard value of the electromagnetic data at the monitoring point; Calculate the power plant electromagnetic monitoring assessment score G. The specific calculation process is as follows: G=J1·E4+J2· ; Among them, J1 is the correction value of the proportion of abnormal monitoring points E4, J2 is the correction value of the over-scale of electromagnetic value E5, is the average value of the overscale E5 of the electromagnetic value at each point, let J1+J2=1, and J1>J2; When the assessment score G ≤ the preset threshold W5, the electromagnetic treatment effect of the power plant is good, and an electromagnetic assessment compliance report is generated; When the preset threshold value W5 of the assessment score is less than or equal to the preset threshold value W6, the electromagnetic value of the power plant is abnormal, and an abnormal report of the electromagnetic assessment is generated; When the assessment score G>the preset threshold W6, there are serious problems in the electromagnetic management of the power plant, and a warning report of the electromagnetic assessment is generated.

6. The big data power plant index assessment and analysis system based on electromagnetic monitoring according to claim 5 is characterized by: The calculation process of the power plant electromagnetic monitoring assessment score G also includes: The device U that obtains the real-time corrected electromagnetic data is greater than the electromagnetic data of the corresponding monitoring point; Obtain multiple monitoring points of device U; Import the corrected electromagnetic data of multiple monitoring points respectively, and count the number of monitoring points Z1; Count the number of abnormal monitoring points Z2; Use the formula P=Z2 / Z1 to calculate the proportion of abnormal monitoring points; When P is less than the preset threshold W7, the data of the abnormal monitoring point is discarded.

7. The big data power plant index assessment and analysis system based on electromagnetic monitoring according to claim 6 is characterized by: When P>preset threshold W7, the calculation process of the power plant electromagnetic monitoring assessment score G also includes: Acquire multiple monitoring points of the device U and multiple abnormal monitoring points contained therein; Establishing the first cubic area A7 including all monitoring points; Establish a second cubic area A8 including all abnormal monitoring points; Taking the unit size as a reference, obtain the size information area volume V1 of the first cubic area A7; Then obtain the size information area volume V2 of the second cube area A8; The concentration of abnormal monitoring points is calculated using the formula F=V2 / V1; When F is less than the preset threshold value W8, the data of the abnormal monitoring point is retained and a warning report of local abnormality of the equipment is generated.

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