Method for monitoring the application of system automation technology in power engineering

Abstract

The application relates to the technical field of application monitoring, and discloses an application monitoring system and method of system automation technology in electric power engineering, which realizes comprehensive equipment state monitoring by collecting multi-dimensional data of electric power equipment, including electric power monitoring, environment monitoring, sensor data and power monitoring and the like. Through comprehensive analysis of the data and in combination with weight and correction constant adjustment, a comprehensive change coefficient is obtained. This makes the system more accurately evaluate the running state of the electric power equipment, thereby effectively identifying abnormal fluctuations in electric power, environment and power, finding potential problems in advance, analyzing the electric power, environment and power fluctuation difference according to the set alarm standard, and realizing fine abnormality judgment. The system can also automatically shut down abnormal equipment and send data to the server, providing necessary parameters for subsequent repair, so as to minimize the equipment damage risk and ensure stable operation of the system.

Description

Technical Field

[0001] This invention relates to the field of application monitoring technology, specifically to application monitoring methods for system automation technology in power engineering. Background Technology

[0002] In power engineering, the application of system automation technology and monitoring methods is a key technology, which aims to monitor the operating status of power equipment in real time to ensure the stable operation of the power system.

[0003] In power engineering, the stable operation of equipment is crucial to the normal operation of the entire power system. However, the operating status of power equipment is affected by a variety of factors. Therefore, when equipment malfunctions, it is particularly important to distinguish the causes of the malfunction.

[0004] However, typical monitoring mechanisms can only detect abnormalities in equipment, but cannot distinguish the source of the abnormality. This leads to the monitoring equipment simply and crudely executing alarm mechanisms, making it difficult to identify the cause of the abnormality.

[0005] Moreover, some monitoring mechanisms can only monitor a single data point. However, the operating status of equipment is affected by a variety of factors. Monitoring only a single data point can easily lead to misjudgment by the monitoring system, causing the equipment to be in an abnormal working state without triggering an alarm, resulting in unnecessary losses. Summary of the Invention

[0006] This invention provides a monitoring method for the application of system automation technology in power engineering. It has the beneficial effects of multi-item detection, automated monitoring, and automated equipment shutdown. It solves the problems mentioned in the background technology, such as only being able to identify equipment abnormalities but not being able to distinguish the source of the abnormality, and some monitoring mechanisms being able to monitor only a certain data.

[0007] This invention provides the following technical solution: a monitoring method for the application of system automation technology in power engineering, characterized by comprising the following steps:

[0008] S1. Install automated central monitoring equipment in the power equipment to monitor the equipment operation status. The automated central monitoring equipment includes power monitoring equipment, environmental monitoring equipment, sensors and power monitoring equipment.

[0009] The automated total monitoring equipment obtains the first data set through the power monitoring equipment, the second data set through the environmental monitoring equipment, the third data set through the sensor, the power parameter GLX of the equipment through the power monitoring equipment, and the operating parameter CZX by accessing and analyzing the equipment's work log.

[0010] S2. Calculate the comprehensive change coefficient ZHX by calculating the first data group and the second data group. The specific calculation formula is as follows:

[0011] ZHX = {a * (DLX + HJX) + b * GLX + c * CZX} * A

[0012] In the formula, DLX is the power coefficient, representing the influence coefficient of power on the equipment, and its value is obtained by calculating the first data group. HJX is the environmental coefficient, representing the influence coefficient of the environment on the equipment, and its value is obtained by calculating the second data group and the third data group;

[0013] a is the weight value of the combination of the power coefficient DLX and the environmental coefficient HJX, and 0 < a < 1. b is the weight value of the power parameter GLX, and 0 < b < 1. c is the weight value of the operation parameter CZX, and 0 < c < 1. Among them, a + b + c = 1. A is a correction constant, and the specific values of A, a, b, and c are selected and set by the customer;

[0014] S3. Obtain the power fluctuation coefficient DBX by combining and calculating the power coefficient DLX and the comprehensive change coefficient ZHX, and then obtain the power fluctuation difference DLZ by combining and calculating the power coefficient DLX and the power fluctuation coefficient DBX;

[0015] Obtain the environmental fluctuation coefficient HBX by combining and calculating the environmental coefficient HJX and the comprehensive change coefficient ZHX, and then obtain the environmental fluctuation difference HLZ by combining and calculating the environmental coefficient HJX and the environmental fluctuation coefficient HBX;

[0016] Obtain the power fluctuation coefficient GBX by combining and calculating the power parameter GLX and the comprehensive change coefficient ZHX, and then obtain the power fluctuation difference GLZ by combining and calculating the power parameter GLX and the power fluctuation coefficient GBX;

[0017] S4. Compare the power fluctuation difference DLZ, the environmental fluctuation difference HLZ, and the power fluctuation difference GLZ obtained in the above steps with their corresponding alarm standards respectively to complete the analysis of the equipment status;

[0018] S5. When one or more of the above fluctuation values are in an abnormal state, the monitoring device will shut down the equipment and send data to the server to provide necessary parameters for subsequent repair operations of the equipment.

[0019] As an alternative solution to the application monitoring method of the system automation technology in the power engineering described in the present invention, wherein: in the step S1, the first data group includes a voltage coefficient DYS and a current coefficient DLS, the second data group includes a temperature coefficient WDS and a humidity coefficient SDS, and the third data group includes a pressure coefficient YLS and a gas system coefficient QTS.

[0020] As an alternative solution to the application monitoring method of the system automation technology in the power engineering described in the present invention, wherein: the power coefficient DLX in the step S2 is obtained by calculation through the following formula:

[0021] DLX = (d * DYS + e * DLS) * B

[0022] In the formula, d is the weight value of the voltage coefficient DYS, e is the weight value of the current coefficient DLS, and 0 < d < 1, 0 < e < 1. At the same time, d + e = 1. B is a correction constant, and the values of d, e, and B are selected and set by the customer.

[0023] As an alternative solution to the application monitoring method of the system automation technology in the power engineering described in the present invention, wherein: the environment coefficient HJX in the step S2 is obtained by calculation through the following formula:

[0024]

[0025] In the formula, f is the weight value of the temperature coefficient WDS, g is the weight value of the humidity coefficient SDS, YLS represents the pressure coefficient, QTS represents the gas system coefficient, and 0 < f < 1, 0 < g < 1. At the same time, f + g = 1. C and D are both correction constants, and the values of f, g, C, and D are selected and set by the customer.

[0026] As an alternative solution to the application monitoring method of the system automation technology in the power engineering described in the present invention, wherein: the power fluctuation coefficient DBX, the environment fluctuation coefficient HBX, and the power fluctuation coefficient GBX in the step S3 are respectively obtained by calculation through the following formulas;

[0027] DBX = DLX * ZHX * E

[0028] HBX = HJX * ZHX * F

[0029] GBX = (GLX * S * Tm) * ZHX * G

[0030] In the formula, DLX is the power coefficient, HJX is the environment coefficient, GLX is the power parameter, ZHX is the comprehensive change coefficient, S is the normal power attenuation value of the device, Tm is the usage time of the device, and E, F, and G are all correction exponents, and the values of E, F, and G are selected and set by the customer.

[0031] As an optional solution for the application monitoring method of system automation technology in power engineering described in this invention, wherein: in step S3, the power fluctuation difference DLZ, environmental fluctuation difference HLZ, and power fluctuation difference GLZ are calculated and obtained by the following formula;

[0032] DLZ = DLX - DBX

[0033] HLZ = HJX - HBX

[0034] GLZ = GLX - GBX

[0035] In the formula, DLX is the power coefficient, HJX is the environmental coefficient, HLX is the power parameter, DBX is the power fluctuation coefficient, HJX is the environmental fluctuation coefficient, and GBL is the power fluctuation coefficient.

[0036] As an optional solution to the application monitoring method of system automation technology in power engineering described in this invention, the alarm criteria in step S4 include the power safety threshold DYQZ and the power safety threshold DYYZ, and the specific steps are as follows:

[0037] When the power fluctuation difference DLZ ≤ the power safety threshold DYQZ, it indicates that the power coefficient is stable;

[0038] When the power safety threshold DYQZ < power fluctuation difference DLZ < power safety threshold DYYZ, it indicates that the power coefficient has a slight anomaly.

[0039] When the power fluctuation difference DLZ is greater than or equal to the power safety threshold DYYZ, it indicates that the power coefficient is highly abnormal.

[0040] As an optional solution for the application monitoring method of system automation technology in power engineering described in this invention, the alarm criteria in step S4 further include the environmental safety threshold DEQZ and the environmental safety threshold DRQZ.

[0041] When the environmental fluctuation difference HLZ ≤ the environmental safety threshold DEQZ, it indicates that the environmental coefficient is stable;

[0042] When the environmental safety threshold DEQZ < the environmental fluctuation difference HLZ < the environmental safety threshold DRQZ, it indicates that the environmental coefficient has a slight anomaly.

[0043] When the environmental fluctuation difference HLZ is greater than or equal to the environmental safety threshold DRQZ, it indicates that the environmental coefficient is highly abnormal.

[0044] As an optional solution to the application monitoring method of system automation technology in power engineering described in this invention, wherein: the alarm criteria in step S4 further include the power safety threshold DSQZ and the power safety threshold DSQZ:

[0045] When the power fluctuation difference GLZ ≤ the power safety threshold DSQZ, it indicates that the power coefficient is stable;

[0046] When the power safety threshold DSQZ < the power fluctuation difference GLZ < and the power safety threshold DSQZ, it indicates that the power coefficient has a slight abnormality.

[0047] When the power fluctuation difference GLZ is greater than or equal to the power safety threshold DSQZ, it indicates that the power coefficient is highly abnormal.

[0048] This invention also provides an application monitoring system for system automation technology in power engineering, including the application monitoring method for system automation technology in power engineering mentioned in the above specification. It includes an information acquisition module, a comprehensive calculation module, a data analysis module, and an automatic processing module. The specific system architecture is as follows:

[0049] The information acquisition module is responsible for collecting data related to monitoring, including data from power detection equipment, environmental monitoring equipment, sensors, power detectors, and query devices.

[0050] The power detection equipment is responsible for acquiring power parameter data from the power monitoring equipment to form the first data group; the environmental detection equipment collects environmental-related data from the environmental monitoring equipment to form the second data group; the sensor acquires sensor data to form the third data group; the power detector acquires power parameter data from the power monitoring equipment; and the query equipment extracts operating parameter data by accessing the equipment's work log.

[0051] The calculation module performs weighted calculations on the first data group, the second data group, the third data group, the power parameters, and the operating parameters according to the calculation formula recorded by the system to obtain the comprehensive change coefficient. Furthermore, based on the calculated power coefficient DLX and comprehensive change coefficient ZHX, as well as the environmental coefficient HJX and power parameter GLX, the module calculates the power fluctuation coefficient DBX, the environmental fluctuation coefficient HBX, and the power fluctuation coefficient GBX, respectively.

[0052] The analysis module compares the power fluctuation difference (DLZ), environmental fluctuation difference (HLZ), and power fluctuation difference (GLZ) with preset alarm standards. If any fluctuation difference exceeds the set threshold, the system will determine that the equipment is in an abnormal state.

[0053] The automatic processing module will trigger an alarm and shut down the equipment when the analysis module detects an abnormal device status to prevent potential problems from worsening. At the same time, the system will send relevant data and alarm information to the server for subsequent repair work.

[0054] The present invention has the following beneficial effects:

[0055] 1. The system automation technology used in this power engineering project employs a monitoring method that collects multi-dimensional data from power equipment, including power monitoring, environmental monitoring, sensor data, and power monitoring, to achieve comprehensive equipment status monitoring. By comprehensively analyzing this data and adjusting weights and correction constants, a comprehensive variation coefficient is obtained. This enables the system to more accurately assess the operating status of power equipment, effectively identify abnormal fluctuations in power, environment, and output, and detect potential problems in advance.

[0056] 2. The application of system automation technology in this power engineering project utilizes a monitoring method that analyzes power, environmental, and power fluctuation differences based on predefined alarm standards, achieving refined anomaly detection. This alarm mechanism categorizes fluctuation differences into stable, slightly abnormal, and highly abnormal levels, providing targeted real-time early warning information. Furthermore, the system can automatically shut down malfunctioning equipment and send data to the server, providing necessary parameters for subsequent repairs to minimize equipment damage risks and ensure stable system operation. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the structure of the present invention.

[0058] Figure 2 This is a schematic diagram of the structure of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] Example 1

[0061] Please see Figure 1-2 A monitoring method for the application of system automation technology in power engineering, characterized by the following steps:

[0062] S1. Install automated central monitoring equipment in the power equipment to monitor the equipment operation status. The automated central monitoring equipment includes power monitoring equipment, environmental monitoring equipment, sensors and power monitoring equipment.

[0063] Among them, the automated total monitoring device obtains the first data set through the power monitoring device, obtains the second data set through the environmental monitoring device, obtains the third data set through the sensor, obtains the power parameter GLX of the device through the power monitoring device, and the automated total monitoring device also analyzes and obtains the operation parameter CZX by accessing the device work log;

[0064] S2. Calculate the comprehensive change coefficient ZHX by calculating the first data set and the second data set. The specific calculation formula is as follows:

[0065] ZHX = {a*(DLX + HJX) + b*GLX + c*CZX}*A

[0066] In the formula, DLX is the power coefficient, representing the influence coefficient of power on the device, and its value is obtained by calculating the first data set. HJX is the environmental coefficient, representing the influence coefficient of the environment on the device, and its value is obtained by calculating the second data set and the third data set;

[0067] a is the weight value of the combination of the power coefficient DLX and the environmental coefficient HJX, and 0 < a < 1. b is the weight value of the power parameter GLX, and 0 < b < 1. c is the weight value of the operation parameter CZX, and 0 < c < 1. Among them, a + b + c = 1. A is the correction constant, and the specific values of A, a, b, and c are selected and set by the customer;

[0068] S3. Obtain the power fluctuation coefficient DBX by combining and calculating the power coefficient DLX and the comprehensive change coefficient ZHX, and then obtain the power fluctuation difference DLZ by combining and calculating the power coefficient DLX and the power fluctuation coefficient DBX;

[0069] Obtain the environmental fluctuation coefficient HBX by combining and calculating the environmental coefficient HJX and the comprehensive change coefficient ZHX, and then obtain the environmental fluctuation difference HLZ by combining and calculating the environmental coefficient HJX and the environmental fluctuation coefficient HBX;

[0070] Obtain the power fluctuation coefficient GBX by combining and calculating the power parameter GLX and the comprehensive change coefficient ZHX, and then obtain the power fluctuation difference GLZ by combining and calculating the power parameter GLX and the power fluctuation coefficient GBX;

[0071] S4. Compare the power fluctuation difference DLZ, the environmental fluctuation difference HLZ, and the power fluctuation difference GLZ obtained in the above steps with their corresponding alarm standards respectively to complete the analysis of the device status;

[0072] S5. When one or more of the above fluctuation values ​​are in an abnormal state, the monitoring equipment will shut down the equipment and send data to the server to provide the necessary parameters for subsequent equipment repair work.

[0073] In this embodiment: By setting up power monitoring equipment, environmental monitoring equipment, sensors and power monitoring equipment, the system can obtain multi-faceted data of the equipment in real time, including power, environmental and power parameters, thereby gaining a comprehensive understanding of the equipment's working status and achieving the goal of fully automated monitoring.

[0074] Meanwhile, by calculating the comprehensive change coefficient ZHX of various data, and combining different weight values ​​and correction constant A, the system can more accurately reflect the impact of factors such as electricity, environment and power on equipment status, and realize comprehensive data analysis.

[0075] By combining power coefficient, environmental coefficient, and comprehensive change coefficient, the system calculates the power fluctuation difference (DLZ), environmental fluctuation difference (HLZ), and fluctuation difference (GLZ), which can quantitatively assess the degree of fluctuation in equipment status and more accurately detect abnormal situations.

[0076] By comparing fluctuation differences with set alarm standards, the system can determine whether the equipment status is abnormal. When fluctuations in power, environmental, or energy levels exceed the set thresholds, the monitoring equipment will automatically trigger an alarm, promptly notifying maintenance personnel to take measures and thus preventing further escalation of equipment failure.

[0077] When the equipment is in an abnormal state, the monitoring equipment can automatically shut down the equipment and send relevant data to the server to provide necessary parameters for subsequent maintenance work. This helps to quickly locate the problem and reduce maintenance costs and downtime.

[0078] By transmitting data to the server, maintenance personnel can remotely monitor equipment status, make timely decisions and take actions, thereby improving maintenance efficiency and response speed.

[0079] By continuously monitoring equipment status, the system can detect potential problems early, implement preventative maintenance, reduce the risk of sudden failures, and improve the reliability and stability of the equipment.

[0080] The application of system automation technology in this power project enables comprehensive monitoring and analysis of the status of power equipment through integrated data analysis, fluctuation difference assessment, and alarm protection. This improves the stability, reliability, and security of the power system, while also optimizing maintenance processes and reducing maintenance costs and downtime.

[0081] Example 2

[0082] Please see Figure 1-2, in the S1 step, the first data set includes a voltage coefficient DYS and a current coefficient DLS, the second data set includes a temperature coefficient WDS and a humidity coefficient SDS, and the third data set includes a pressure coefficient YLS and a gas system coefficient QTS.

[0083] In this embodiment: The first data set in the S1 step includes a voltage coefficient DYS and a current coefficient DLS. These coefficients can not only reflect the voltage and current conditions of the power system, but also be used to determine whether the equipment is operating within a safe range. By real-time monitoring and analysis of these key parameters, the system can quickly identify any abnormal situations, and thus take timely measures to avoid potential failures.

[0084] The second data set includes a temperature coefficient WDS and a humidity coefficient SDS. These coefficients reflect the influence of environmental factors on the performance of power equipment. Temperature and humidity fluctuations may cause problems such as equipment overheating and insulation damage. By monitoring these coefficients, the system can predict potential thermal problems and take appropriate cooling measures to ensure the stable operation of the equipment.

[0085] The third data set includes a pressure coefficient YLS and a gas system coefficient QTS. These parameters are usually applied to liquid-insulated equipment and gas-insulated equipment in power engineering. For liquid-insulated equipment, changes in pressure may affect the state of the insulating liquid, so it needs to be closely monitored. In gas-insulated equipment, the composition and pressure of the gas are also key factors that may affect the insulation performance.

[0086] Through real-time monitoring of multiple data combinations, it can help engineers better understand the state of the equipment, predict potential problems, and thus take timely measures to ensure the efficient, safe and reliable operation of the power system. The introduction of such a system will undoubtedly improve the efficiency of power engineering, reduce maintenance costs, and ultimately benefit from sustainable energy supply.

[0087] Embodiment 3

[0088] Please refer to Figure 1-2 , the power coefficient DLX in the S2 step is calculated and obtained through the following formula:

[0089] DLX = (d * DLS + e * DLS) * B

[0090] In the formula, d is the weight value of the voltage coefficient DYS, e is the weight value of the current coefficient DLS, and 0 < d < 1, 0 < e < 1. At the same time, d + e = 1, B is a correction constant, and the values of d, e, and B are selected and set by the customer.

[0091] In this embodiment: It reflects the impact of voltage and current on the system performance in the power system. By adjusting the weights of d and e, a suitable balance can be found between voltage and current to optimize the efficiency and performance of the system. When different weight values are selected, the power coefficient DLX value will change accordingly, which may affect the stability, load distribution, and energy consumption of the power system.

[0092] B is used as a correction constant to adjust the amplitude of the power coefficient DLX. The selection of this value may be affected by system characteristics, environmental conditions, and customer requirements. By appropriately adjusting the value of B, it can be ensured that the calculation result of the power coefficient DLX is within a reasonable range to adapt to different application scenarios.

[0093] The calculation formula of the power coefficient DLX in step S2 provides a powerful tool for power system optimization. By weighing the impacts of voltage and current, and combining the weights and correction constants selected by the customer, the optimization of the power system performance can be achieved, thereby improving efficiency, reducing energy consumption, and meeting specific application requirements.

[0094] Embodiment 4

[0095] Please refer to Figure 1-2 , the environmental coefficient HJX in step S2 is calculated and obtained through the following formula:

[0096]

[0097] In the formula, f is the weight value of the temperature coefficient WDS, g is the weight value of the humidity coefficient SDS, YLS represents the combined pressure coefficient, QTS represents the gas coefficient, and 0 < f < 1, 0 < g < 1. At the same time, f + g = 1. Both C and D are correction constants, and the values of f, g, C, and D are selected and set by the customer.

[0098] In this embodiment: Through the coefficients of temperature and humidity, combined with the combined pressure coefficient and gas coefficient, the impact of the environment on the system can be comprehensively considered. By weighing the weights of temperature and humidity, the value of the environmental coefficient HJX can be adjusted under different environmental conditions, thereby optimizing the operation performance of the system.

[0099] In the formula, C and D are used as correction constants to adjust the value of the environmental coefficient HJX, which can ensure that the calculation result of the environmental coefficient HJX is within a reasonable range to adapt to different environmental changes.

[0100] The calculation formula of the environmental coefficient HJX provides an important tool for system optimization considering environmental factors. By combining the impacts of temperature, humidity, combined pressure, and gas coefficients, and combining the weights and correction constants selected by the customer, the optimal performance of the system under different environments can be achieved to meet specific application requirements.

[0101] Embodiment 5

[0102] Please see Figure 1-2 In step S3, the power fluctuation coefficient DBX, environmental fluctuation coefficient HBX, and power fluctuation coefficient GBX are calculated using the following formulas respectively.

[0103] DBX = DLX * ZHX * E

[0104] HBX = HJX * ZHX * F

[0105] GBX=(GLX*S*Tm)*ZHX*G

[0106] In the formula, DLX is the power coefficient, HJX is the environmental coefficient, GLX is the power parameter, ZHX is the comprehensive variation coefficient, S is the normal power attenuation value of the equipment, Tm is the usage time of the equipment, and E, F and G are all correction indices, and the values ​​of E, F and G are selected and set by the customer.

[0107] In this embodiment: The above formula reflects the impact of different factors on system volatility. Taking into account the influence of multiple factors, the values ​​of the correction indices E, F and G are adjusted by the customer according to specific needs, so as to better adapt to the actual situation.

[0108] The volatility coefficient calculation formula combines multiple factors such as electricity, environment, and power, providing an effective tool for system volatility analysis. By weighing the impact of various coefficients and adjusting the correction index according to customer choices, system volatility can be predicted and optimized more accurately to meet different operating requirements.

[0109] Example 6

[0110] Please see Figure 1-2 In step S3, the power fluctuation difference DLZ, environmental fluctuation difference HLZ, and power fluctuation difference GLZ are calculated using the following formulas.

[0111] DLZ = DLX - DBX

[0112] HLZ = HJX - HBX

[0113] GLZ = GLX - GBX

[0114] In the formula, DLX is the power coefficient, HJX is the environmental coefficient, HLX is the power parameter, DBX is the power fluctuation coefficient, HJX is the environmental fluctuation coefficient, and GBL is the power fluctuation coefficient.

[0115] In this embodiment: the fluctuations in electricity, environment and power can be quantified by calculation, and the difference between the coefficients can be calculated to more clearly understand the difference between the actual value and the predicted value. The calculation results of the power fluctuation difference DLZ, environmental fluctuation difference HLZ and power fluctuation difference GLZ can be used to evaluate the stability and adaptability of system performance, as well as possible improvement measures.

[0116] The formula for calculating the fluctuation difference provides an important indicator for system performance analysis. By comparing the differences between different coefficients, we can better understand the volatility of the system and provide valuable information for further optimization and adjustment of the system.

[0117] Example 7

[0118] Please see Figure 1-2 The alarm criteria in step S4 include the power safety threshold DYQZ and the power safety threshold DYYZ. The specific steps are as follows:

[0119] When the power fluctuation difference DLZ ≤ the power safety threshold DYQZ, it indicates that the power coefficient is stable;

[0120] When the power safety threshold DYQZ < power fluctuation difference DLZ < power safety threshold DYYZ, it indicates that the power coefficient has a slight anomaly.

[0121] When the power fluctuation difference DLZ is greater than or equal to the power safety threshold DYYZ, it indicates that the power coefficient is highly abnormal.

[0122] The alarm criteria in step S4 also include the environmental safety threshold DEQZ and the environmental safety threshold DRQZ.

[0123] When the environmental fluctuation difference HLZ ≤ the environmental safety threshold DEQZ, it indicates that the environmental coefficient is stable;

[0124] When the environmental safety threshold DEQZ < the environmental fluctuation difference HLZ < the environmental safety threshold DRQZ, it indicates that the environmental coefficient has a slight anomaly.

[0125] When the environmental fluctuation difference HLZ ≥ the environmental safety threshold DSQZ, it indicates that the environmental coefficient is highly abnormal. The alarm criteria in step S4 also include the power safety threshold DSQZ and the power safety threshold DSQZ:

[0126] When the power fluctuation difference GLZ ≤ the power safety threshold DSQZ, it indicates that the power coefficient is stable;

[0127] The alarm criteria in step S4 also include the power safety threshold DSQZ and the power safety threshold DSQZ:

[0128] When the power fluctuation difference GLZ ≤ the power safety threshold DSQZ, it indicates that the power coefficient is stable;

[0129] When the power safety threshold DSQZ < the power fluctuation difference GLZ < and the power safety threshold DSQZ, it indicates that the power coefficient has a slight abnormality.

[0130] When the power fluctuation difference GLZ is greater than or equal to the power safety threshold DSQZ, it indicates that the power coefficient is highly abnormal.

[0131] In this embodiment, through these detailed alarm standards, the system can accurately identify different levels of abnormal situations and take corresponding measures in a timely manner to ensure the stability and safety of power engineering, effectively improve system reliability, and reduce potential risks and losses.

[0132] This invention also provides an application monitoring system for system automation technology in power engineering, including the application monitoring method for system automation technology in power engineering mentioned in the above specification. It includes an information acquisition module, a comprehensive calculation module, a data analysis module, and an automatic processing module. The specific system architecture is as follows:

[0133] The information acquisition module is responsible for collecting data related to monitoring, including data from power detection equipment, environmental monitoring equipment, sensors, power detectors, and query devices.

[0134] The power detection equipment is responsible for acquiring power parameter data from the power monitoring equipment to form the first data group; the environmental detection equipment collects environmental-related data from the environmental monitoring equipment to form the second data group; the sensor acquires sensor data to form the third data group; the power detector acquires power parameter data from the power monitoring equipment; and the query equipment extracts operating parameter data by accessing the equipment's work log.

[0135] The calculation module performs weighted calculations on the first data group, the second data group, the third data group, the power parameters, and the operating parameters according to the calculation formula recorded by the system to obtain the comprehensive change coefficient. Furthermore, based on the calculated power coefficient DLX and comprehensive change coefficient ZHX, as well as the environmental coefficient HJX and power parameter GLX, the module calculates the power fluctuation coefficient DBX, the environmental fluctuation coefficient HBX, and the power fluctuation coefficient GBX, respectively.

[0136] The analysis module compares the power fluctuation difference (DLZ), environmental fluctuation difference (HLZ), and power fluctuation difference (GLZ) with preset alarm standards. If any fluctuation difference exceeds the set threshold, the system will determine that the equipment is in an abnormal state.

[0137] The automatic processing module will trigger an alarm and shut down the equipment when the analysis module detects an abnormal device status to prevent potential problems from worsening. At the same time, the system will send relevant data and alarm information to the server for subsequent repair work.

[0138] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0139] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A monitoring method for the application of system automation technology in power engineering, characterized by: It includes the following steps: S1. Set up an automated total monitoring device inside the power equipment to monitor the operation status of the equipment. The automated total monitoring device includes a power monitoring device, an environmental monitoring device, sensors, and a power monitoring device; Among them, the automated total monitoring device obtains the first data group through the power monitoring device, obtains the second data group through the environmental monitoring device, obtains the third data group through the sensors, obtains the power parameter GLX of the equipment through the power monitoring device, and the automated total monitoring device also analyzes and obtains the operation parameter CZX by accessing the equipment work log; S2. Calculate the comprehensive change coefficient ZHX by combining the first data group and the second data group. The specific calculation formula is as follows: ZHX = {a * (DLX + HJX) + b * GLX + c * CZX} * A In the formula, DLX is the power coefficient, representing the influence coefficient of power on the equipment, and its value is obtained by calculating the first data group. HJX is the environmental coefficient, representing the influence coefficient of the environment on the equipment, and its value is obtained by calculating the second data group and the third data group; a is the weight value of the combination of the power coefficient DLX and the environmental coefficient HJX, and 0 < a < 1. b is the weight value of the power parameter GLX, and 0 < b < 1. c is the weight value of the operation parameter CZX, and 0 < c < 1. Among them, a + b + c = 1. A is a correction constant, and the specific values of A, a, b, and c are selected and set by the customer; S3. Calculate the power fluctuation coefficient DBX by combining and calculating the power coefficient DLX and the comprehensive change coefficient ZHX, and then calculate the power fluctuation difference DLZ by combining and calculating the power coefficient DLX and the power fluctuation coefficient DBX; Calculate the environmental fluctuation coefficient HBX by combining and calculating the environmental coefficient HJX and the comprehensive change coefficient ZHX, and then calculate the environmental fluctuation difference HLZ by combining and calculating the environmental coefficient HJX and the environmental fluctuation coefficient HBX; Calculate the power fluctuation coefficient GBX by combining and calculating the power parameter parameter GLX and the comprehensive change coefficient ZHX, and then calculate the power fluctuation difference GLZ by combining and calculating the power parameter GLX and the power fluctuation coefficient GBX; S4. Compare the power fluctuation difference DLZ, the environmental fluctuation difference HLZ, and the power fluctuation difference GLZ calculated in the above steps with their corresponding alarm standards respectively to complete the analysis of the equipment status; S5. When one or more of the above fluctuation values are in an abnormal state, the monitoring device will shut down the equipment and send data to the server to provide necessary parameters for subsequent equipment repair operations.

2. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: In the S1 step, the first data group includes a voltage coefficient DYS and a current coefficient DLS, the second data group includes a temperature coefficient WDS and a humidity coefficient SDS, and the third data group includes a pressure coefficient YLS and a gas system coefficient QTS.

3. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: In the S2 step, the power coefficient DLX is obtained by calculating through the following formula: DLX = (d * DYS + e * DLS) * B Where d is the weight value of the voltage coefficient DYS, e is the weight value of the current coefficient DLS, and 0 < d < 1, 0 < e < 1. At the same time, d + e = 1, B is a correction constant, and the values of d, e, and B are selected and set by the customer.

4. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: In the S2 step, the environmental coefficient HJX is obtained through the following formula: Where f is the weight value of the temperature coefficient WDS, g is the weight value of the humidity coefficient SDS, YLS represents the combined pressure coefficient, QTS represents the gas system coefficient, and 0 < f < 1, 0 < g < 1. At the same time, f + g = 1, C and D are both correction constants, and the values of f, g, C, and D are selected and set by the customer.

5. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: In the S3 step, the power fluctuation coefficient DBX, the environmental fluctuation coefficient HBX, and the power fluctuation coefficient GBX are respectively obtained through the following formula; DBX = DLX * ZHX * E HBX = HJX * ZHX * F GBX = (GLX * S * Tm) * ZHX * G Where DLX is the power coefficient, HJX is the environmental coefficient, GLX is the power parameter, ZHX is the comprehensive change coefficient, S is the normal power attenuation value of the device, Tm is the usage time of the device, and E, F, and G are all correction exponents, and the values of E, F, and G are selected and set by the customer.

6. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: In the S3 step, the power fluctuation difference DLZ, the environmental fluctuation difference HLZ, and the power fluctuation difference GLZ are obtained through the following formula; DLZ = DLX - DBX HLZ = HJX - HBX GLZ = GLX - GBX Where DLX is the power coefficient, HJX is the environmental coefficient, GLX is the power parameter, DBX is the power fluctuation coefficient, HJX is the environmental fluctuation coefficient, and GBX is the power fluctuation coefficient.

7. The application monitoring method for system automation technology in power engineering according to claim 1, characterized in that: The alarm criteria in the S4 step include the power safety threshold DYQZ and the power safety threshold DYYZ. The specific steps are as follows: When the power fluctuation difference DLZ ≤ the power safety threshold DYQZ, it means that the power coefficient is stable; When the power safety threshold DYQZ < the power fluctuation difference DLZ < the power safety threshold DYYZ, it means that the power coefficient has a mild anomaly; When the power fluctuation difference DLZ ≥ the power safety threshold DYYZ, it means that the power coefficient has a high anomaly.

8. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: The alarm criteria in the S4 step also include the environmental safety threshold DEQZ and the environmental safety threshold DRQZ; When the environmental fluctuation difference HLZ ≤ the environmental safety threshold DEQZ, it means that the power coefficient is stable; When the environmental safety threshold DEQZ < the environmental fluctuation difference HLZ < the environmental safety threshold DRQZ, it means that the power coefficient has a mild anomaly; When the environmental fluctuation difference HLZ ≥ the environmental safety threshold DRQZ, it means that the power coefficient has a high anomaly.

9. The method for monitoring the application of system automation technology in power engineering according to claim 1, characterized in that: The alarm criteria in the S4 step also include the power safety threshold DSQZ and the power safety threshold DSYZ: When the power fluctuation difference GLZ ≤ the power safety threshold DSQZ, it means that the power coefficient is stable; When the power safety threshold DSQZ < the power fluctuation difference GLZ < the power safety threshold DSYZ, it means that the power coefficient has a mild anomaly; When the power fluctuation difference GLZ is greater than or equal to the power safety threshold DSYZ, it indicates that the power coefficient is highly abnormal.

10. A monitoring system for the application of system automation technology in power engineering, comprising the monitoring method for the application of system automation technology in power engineering as described in any one of claims 1 to 9, comprising an information acquisition module, a comprehensive calculation module, a data analysis module, and an automatic processing module, characterized in that: The specific system architecture is as follows: The information acquisition module is responsible for collecting data related to monitoring, including data from power detection equipment, environmental monitoring equipment, sensors, power detectors, and query devices. The power detection equipment is responsible for acquiring power parameter data from the power monitoring equipment to form the first data group; the environmental detection equipment collects environmental-related data from the environmental monitoring equipment to form the second data group; the sensor acquires sensor data to form the third data group; the power detector acquires power parameter data from the power monitoring equipment; and the query equipment extracts operating parameter data by accessing the equipment's work log. The calculation module performs weighted calculations on the first data group, the second data group, the third data group, the power parameters, and the operating parameters according to the calculation formula recorded by the system to obtain the comprehensive change coefficient. Furthermore, based on the calculated power coefficient DLX and comprehensive change coefficient ZHX, as well as the environmental coefficient HJX and power parameter GLX, the module calculates the power fluctuation coefficient DBX, the environmental fluctuation coefficient HBX, and the power fluctuation coefficient GBX, respectively. The analysis module compares the power fluctuation difference (DLZ), environmental fluctuation difference (HLZ), and power fluctuation difference (GLZ) with preset alarm standards. If any fluctuation difference exceeds the set threshold, the system will determine that the equipment is in an abnormal state. The automatic processing module will trigger an alarm and shut down the equipment when the analysis module detects an abnormal device status to prevent potential problems from worsening. At the same time, the system will send relevant data and alarm information to the server for subsequent repair work.

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