A method and device for monitoring and early warning of a hydropower station

Abstract

This application discloses a monitoring and early warning method and device for hydropower stations. The monitoring and early warning method includes: obtaining the limit-exceeding result of the first operating parameter based on a first operating parameter of the hydropower station and a dynamic threshold of the first operating parameter; and triggering corresponding early warning information based on the limit-exceeding result. The dynamic threshold is obtained based on a baseline operating condition value and a safety margin. The baseline operating condition value is obtained from a second operating parameter and a regression coefficient. The regression coefficient is obtained from historical operating data of the second operating parameter and historical operating data of the first operating parameter. This application can solve the problem in related technologies where manual data analysis is usually performed retrospectively, making timely early warning difficult.

Description

Technical Field

[0001] This application relates to the field of hydropower station automation monitoring technology, and in particular to a hydropower station monitoring and early warning method and device. Background Technology

[0002] In the operation and management of hydropower stations, operators need to manually record a large number of key operating parameters on the monitoring screen in the central control room periodically (usually every 4 hours), such as the bearing temperature of various parts of the unit, the flow and pressure of the technical water supply, the transformer winding temperature, and the pressure of the hydraulic system. Currently, this work is entirely done manually, which has the following significant drawbacks: (1) Inefficient and requires a lot of manpower: Meter reading is tedious and boring, and operators need to spend a lot of time recording repetitive data, making it impossible to focus on equipment status analysis and fault prediction.

[0003] (2) Prone to errors and poor reliability: During manual copying, calculation and comparison, human errors such as misreading, misrecording or omission are very likely to occur, affecting the accuracy of the operation record.

[0004] (3) Lagging analysis and insufficient early warning capability: Manual data analysis is usually done after the fact, making it difficult to detect slow abnormal trends or abnormal correlations of parameters in a timely manner, and unable to provide effective early warning in the early stage of a fault.

[0005] (4) Data isolation makes it difficult to utilize in depth: It is difficult to form electronic records from handwritten data, which is not conducive to the tracing of historical data, statistical analysis, and in-depth mining for optimizing unit operation.

[0006] While existing hydropower station monitoring systems can display data in real time, they generally lack dedicated tools that integrate automatic data recording, intelligent analysis, and one-click alarm confirmation to meet operational needs. Some newly built power stations may have advanced application functions, but for the large number of older, closed-system power stations already in operation, upgrading and retrofitting them is prohibitively expensive. Summary of the Invention

[0007] This application provides a method and device for monitoring and early warning of hydropower stations, in order to solve the problem that manual data analysis in related technologies is usually done after the fact, making it difficult to provide timely early warning.

[0008] In a first aspect, embodiments of this application provide a method for monitoring and early warning of a hydropower station, the method comprising: Based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter, the result of exceeding the limit of the first operating parameter is obtained; Based on the aforementioned limit violation result, a corresponding early warning message is triggered; The dynamic threshold is obtained based on the operating condition baseline value and the safety margin. The operating condition baseline value is obtained from the second operating parameter and the regression coefficient. The regression coefficient is obtained from the historical operating data of the second operating parameter and the historical operating data of the first operating parameter.

[0009] In conjunction with the first aspect, in one embodiment, the first operating parameter includes at least one of the following: bearing bearing temperature, unit stator temperature, transformer winding temperature, real-time pressure of the main technical water supply pipe, technical water supply flow rate, and hydraulic device pressure.

[0010] In conjunction with the first aspect, in one embodiment, when the first operating parameter includes the bearing pad temperature, the second operating parameter corresponding to the bearing pad temperature includes the real-time active power of the unit, the technical water supply inlet temperature, and the real-time ambient temperature of the plant where the unit is located. And / or, when the first operating parameter includes the stator temperature of the generator set, the second operating parameter corresponding to the stator temperature of the generator set includes the real-time active power of the generator set, the inlet water temperature of the stator cooling system, and the real-time ambient temperature of the generator floor. And / or, when the first operating parameter includes the transformer winding temperature, the second operating parameter corresponding to the transformer winding temperature includes the real-time active power transmitted by the transformer, the transformer cooler inlet air temperature, and the real-time ambient temperature of the transformer room. And / or, when the first operating parameter includes the real-time pressure of the main technical water supply pipe, the second operating parameter corresponding to the real-time pressure of the main technical water supply pipe includes the real-time active power of the unit and the real-time flow rate of the main technical water supply pipe. And / or, when the first operating parameter includes the technical water supply flow rate, the second operating parameter corresponding to the technical water supply flow rate includes the real-time active power of the unit, the real-time pressure of the technical water supply main pipe, and the real-time pressure difference between the inlet and outlet of the cooler; And / or, when the first operating parameter includes the pressure of the hydraulic device, the second operating parameter corresponding to the pressure of the hydraulic device includes the real-time opening degree of the unit guide vanes and the real-time ambient temperature at the location of the hydraulic device.

[0011] In conjunction with the first aspect, in one embodiment, the method further includes: The communication data packets are parsed and read using standard communication protocols to obtain the first and / or second operating parameters of the hydropower station. And / or, acquire screen images of the hydropower station's industrial control computer, perform image positioning and character recognition on the screen images, and obtain the first operating parameters and / or second operating parameters of the hydropower station.

[0012] In conjunction with the first aspect, in one implementation, obtaining the limit-exceeding result of the first operating parameter based on a first operating parameter of the hydropower station and a dynamic threshold of the first operating parameter includes: Compare the first operating parameter with the dynamic threshold of the first operating parameter; If the first operating parameter exceeds the dynamic threshold of the first operating parameter, then the result of exceeding the limit is that the first operating parameter exceeds the limit; Otherwise, the result of exceeding the limit is that the first operating parameter did not exceed the limit.

[0013] In conjunction with the first aspect, in one implementation, after determining that the first operating parameter has not exceeded the limit, the method further includes: Based on the first operating parameter of the current calculation cycle, the first operating parameter of the previous calculation cycle, the dynamic threshold of the first operating parameter, and the change rate limit of the first operating parameter, the trend information of the first operating parameter is obtained, and the trend information includes the rise and fall and the change rate exceeding the limit. Based on the trend information of the first operating parameter over a continuous preset number of calculation cycles, obtain the trend prediction result of the first operating parameter.

[0014] In conjunction with the first aspect, in one implementation, the trend prediction result of the first operating parameter is obtained based on the trend information of the first operating parameter for a continuous preset number of calculation cycles, including: if the trend information of the first operating parameter is all increasing and the rate of change exceeds the standard, or all decreasing and the rate of change exceeds the standard, then the trend prediction result of the first operating parameter is an abnormal trend; otherwise, the trend prediction result of the first operating parameter is a normal trend. And / or, the calculation cycle is synchronized with the acquisition cycle of the first operating parameter and the second operating parameter.

[0015] In conjunction with the first aspect, in one implementation, if the limit violation result is that the first operating parameter exceeds the limit, based on the limit violation result, a corresponding warning message is triggered, including: The degree of exceeding the limit of the first operating parameter is obtained based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter; The corresponding warning information is triggered based on the degree of violation of the first operating parameter, wherein the higher the degree of violation, the higher the level of the corresponding warning information; And / or, if the limit violation result is that the first operating parameter does not exceed the limit, based on the limit violation result, a corresponding warning message is triggered, including: Obtain the trend prediction result of the first operating parameter; Based on the trend prediction results, the trend anomaly alert for the first operating parameter may or may not be triggered.

[0016] In conjunction with the first aspect, in one implementation, if the limit violation result is that the first operating parameter exceeds the limit, the method further includes: Based on the warning information level, the warning-related information that triggers the warning information includes anomaly location and handling suggestions.

[0017] Secondly, embodiments of this application provide a hydropower station monitoring and early warning device, the hydropower station monitoring and early warning device comprising: The limit exceedance result acquisition module is used to acquire the limit exceedance result of the first operating parameter based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter; The early warning information triggering module is used to trigger corresponding early warning information based on the exceeded limit result; The dynamic threshold is obtained based on the operating condition baseline value and the safety margin. The operating condition baseline value is obtained from the second operating parameter and the regression coefficient. The regression coefficient is obtained from the historical operating data of the second operating parameter and the historical operating data of the first operating parameter.

[0018] The beneficial effects of the technical solution provided in this application include: This application provides a method and device for monitoring and early warning of hydropower stations. This embodiment explores the correlation between first and second operating parameters, uses historical operating data to fit regression coefficients, and constructs a dynamic threshold model that changes with the operating parameters of the hydropower station. This model is more consistent with the actual operating status of the equipment. The first operating parameter is compared with the dynamic threshold in real time to obtain the operating status of the hydropower station, thereby triggering corresponding early warning information. This solves the problem that hydropower station monitoring and early warning in related technologies rely on manual post-event analysis, which makes it difficult to automatically identify and effectively warn. This improves the real-time performance and accuracy of monitoring and ensures the safe operation of the unit. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating an embodiment of the hydropower station monitoring and early warning method of this application; Figure 2 This is a schematic diagram of the functional modules of an embodiment of the hydropower station monitoring and early warning device of this application. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] In one aspect, embodiments of this application provide a method for monitoring and early warning of hydropower stations.

[0023] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the hydropower station monitoring and early warning method of this application. Figure 1 As shown, the monitoring and early warning methods for hydropower stations include: 101: Based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter, obtain the limit exceedance result of the first operating parameter; wherein, the dynamic threshold is obtained based on the operating condition benchmark value and the safety margin, the operating condition benchmark value is obtained from the second operating parameter and the regression coefficient, and the regression coefficient is obtained from the historical operating data of the second operating parameter and the historical operating data of the first operating parameter.

[0024] In step 101, data acquisition can be performed using a data acquisition gateway. Specifically, the data acquisition gateway can be deployed in the central control room monitoring network to automatically obtain raw operating parameter data from the existing monitoring systems of the hydropower station (such as computer monitoring systems, auxiliary equipment control systems, etc.). The acquired operating parameters are core parameters used in the subsequent intelligent analysis and alarm handling process, including but not limited to: ① Core operating parameters of the unit: real-time active power of the unit; ② Unit status parameters: bearing temperature of various parts of the unit, stator temperature of the unit; ③ Auxiliary system operating parameters: real-time pressure of the main technical water supply pipe, technical water supply flow rate, technical water supply temperature; ④ Main transformer equipment status parameters: transformer winding temperature; ⑤ Hydraulic system operating parameters: hydraulic device pressure; ⑥ Environmental auxiliary parameters: ambient temperature at the power station site. Other operating parameters can be added as needed.

[0025] Understandably, after collecting the raw data, it is necessary to perform verification, filtering, and formatting to remove invalid data with abnormal jumps, unify the data format and timestamps, and provide a standardized data source for subsequent analysis.

[0026] 102: Based on the aforementioned limit violation result, trigger the corresponding warning information.

[0027] In this embodiment, by mining the correlation between the first and second operating parameters and fitting regression coefficients using historical operating data, a dynamic threshold model that changes with the operating parameters of the hydropower station is constructed. This is more consistent with the actual operating status of the equipment. The first operating parameter is compared with the dynamic threshold in real time to obtain the operating status of the hydropower station, thereby triggering corresponding early warning information. This solves the problem that hydropower station monitoring and early warning rely on manual post-event analysis in related technologies, making it difficult to automatically identify and effectively warn. It improves the real-time performance and accuracy of monitoring and ensures the safe operation of the unit.

[0028] The first operating parameters of the hydropower station include at least one of the following: bearing temperature, generator stator temperature, transformer winding temperature, real-time pressure of the main technical water supply pipe, technical water supply flow rate, and hydraulic pressure device pressure.

[0029] It is understandable that, since the above parameters directly reflect the status of the core components of the unit and are sensitive to faults, abnormalities can easily lead to accidents. Therefore, in this embodiment of the application, the first operating parameter is monitored as a key parameter to ensure equipment safety.

[0030] It is understood that in this application, the dynamic threshold is obtained by a two-step method of first calculating the operating condition baseline value and then generating the dynamic threshold.

[0031] Specifically, the general calculation formula framework is as follows: (1) Formula for calculating the reference value of the working condition:

[0032] (2) Formula for calculating dynamic threshold: Dynamic upper limit threshold:

[0033] Dynamic lower threshold:

[0034] in, This is the baseline value for the first operating parameter under the current operating conditions; A second operating parameter that affects the real-time operation of the first operating parameter; For the constant term of the regression model, The regression coefficients for each second operating parameter are obtained by fitting the historical operating data of the second operating parameter with the historical operating data of the first operating parameter during the same period. Automatic iteration and optimization can be automatically performed at a certain time, such as every quarter, every half year, or every month. n is the number of second operating parameters. To provide an upper safety margin, The lower limit safety margin is determined based on the manufacturer's specifications, power station operating procedures, and historical fault data of the equipment (the equipment is the core monitoring equipment / system / component in the hydropower station that directly corresponds to each first operating parameter, and is the carrier equipment of each first operating parameter). Different first operating parameters correspond to different safety margins. and These are the dynamic upper and lower thresholds under the current operating conditions, serving as the basis for comparison in actual alarm judgment.

[0035] The specific principle behind the above fitting is as follows: Historically available operating parameters for the hydropower station, including the first and second operating parameters, are used. Both are known quantities. A regression model is constructed based on the aforementioned baseline calculation formula. and All of these are unknowns to be determined, and can be calculated using multiple regression. and .

[0036] It is understandable that the first and second operating parameters for the same historical period both use the operating data of the hydropower station. If unstable data appears, it is removed and replaced with the average of the data before and after the unstable data, or the average of the data before or after the unstable data, or other existing outlier handling methods are used.

[0037] For different first operating parameters of a hydropower station, the corresponding second operating parameters may differ, and consequently, the baseline operating conditions will also differ. As an example, the following calculation can be used as a reference: (1) When the first operating parameter includes the bearing pad temperature, the second operating parameter corresponding to the bearing pad temperature includes the real-time active power of the unit, the technical water supply inlet temperature and the real-time ambient temperature of the plant where the unit is located.

[0038] Formula for calculating the reference value of the working condition:

[0039] Dynamic upper limit threshold: (Monitoring limit only) in, This is the baseline value for the bearing bearing temperature under current operating conditions; This refers to the real-time active power of the generator unit. For the technical water supply inlet temperature; The real-time ambient temperature of the plant where the generator unit is located; These are the constant term and regression coefficients of the regression model; This is the upper limit safety margin for bearing pad temperature; This is the dynamic upper limit threshold for bearing bearing temperature under the current operating conditions.

[0040] (2) When the first operating parameter includes the stator temperature of the generator set, the second operating parameter corresponding to the stator temperature of the generator set includes the real-time active power of the generator set, the inlet water temperature of the stator cooling system and the real-time ambient temperature of the generator layer.

[0041] Formula for calculating the reference value of the working condition:

[0042] Dynamic upper limit threshold: (Monitoring limit only) in, This is the reference value for the stator temperature of the unit under current operating conditions; This refers to the real-time active power of the generator unit. This refers to the inlet water temperature of the stator cooling system. This refers to the real-time ambient temperature of the generator floor. These are the constant term and regression coefficients of the regression model; This is the safety margin for the upper limit of the stator temperature of the unit; This is the dynamic upper limit threshold for the stator temperature of the unit under the current operating conditions.

[0043] (3) When the first operating parameter includes the transformer winding temperature, the second operating parameter corresponding to the transformer winding temperature includes the real-time active power transmitted by the transformer, the air inlet temperature of the transformer cooler, and the real-time ambient temperature of the transformer room.

[0044] For transformer winding temperature, the above bearing bearing temperature or generator stator temperature can be referenced to obtain the operating condition reference value and dynamic upper limit threshold of transformer winding temperature.

[0045] Among them, only the upper limit of transformer winding temperature is monitored.

[0046] (4) When the first operating parameter includes the real-time pressure of the main technical water supply pipe, the second operating parameter corresponding to the real-time pressure of the main technical water supply pipe includes the real-time active power of the unit and the real-time flow rate of the main technical water supply pipe.

[0047] For the real-time pressure of the main technical water supply pipe, the operating condition benchmark value, dynamic upper limit threshold, and dynamic lower limit threshold of the real-time pressure of the main technical water supply pipe can be obtained by referring to the bearing bearing temperature or the stator temperature of the unit.

[0048] Among them, the upper and lower limits of real-time pressure monitoring for the main water supply pipe are specified.

[0049] (5) When the first operating parameter includes the technical water supply flow rate, the second operating parameter corresponding to the technical water supply flow rate includes the real-time active power of the unit, the real-time pressure of the technical water supply main pipe, and the real-time pressure difference between the inlet and outlet of the cooler.

[0050] For the technical water supply flow rate, the operating condition benchmark value and dynamic upper limit threshold of the technical water supply flow rate can be obtained by referring to the above-mentioned bearing bearing temperature or unit stator temperature.

[0051] Among them, the technical water supply flow rate is only monitored at the lower limit.

[0052] It should be noted that the cooler mentioned in the real-time pressure difference between the inlet and outlet of the cooler belongs to the technical water supply system of the hydropower station unit. This system is the core auxiliary system of the hydropower station, which is specifically designed to provide cooling water for the core components of the unit (the bearings of various parts of the unit, including the thrust bearing, the upper guide bearing, the bearing cooler of the water guide bearing, the stator air cooler, etc.). It is a key supporting equipment to ensure the normal operation of the unit. On the other hand, the transformer cooler mentioned in the inlet air temperature of the transformer cooler belongs to the independent cooling system of the transformer.

[0053] (6) When the first operating parameter includes the pressure of the hydraulic device, the second operating parameter corresponding to the pressure of the hydraulic device includes the real-time opening degree of the unit guide vanes and the real-time ambient temperature at the location of the hydraulic device.

[0054] For the pressure of the hydraulic device, the operating reference value, dynamic upper limit threshold, and dynamic lower limit threshold of the hydraulic device pressure can be obtained by referring to the above-mentioned bearing bearing temperature or unit stator temperature.

[0055] Among them, the upper and lower limits of pressure monitoring for hydraulic devices.

[0056] Because meter reading is a tedious and repetitive task, operators need to spend a lot of time recording repetitive data, making it impossible for them to focus on equipment status analysis and fault prediction. This results in low efficiency, consumes a large amount of manpower, and is prone to human errors such as misreading, misrecording, or omissions during manual recording, calculation, and comparison, affecting the accuracy of the operation records. To solve this problem, the data acquisition gateway in this application adopts a dual-mode adaptation acquisition mechanism when collecting data: (1) Protocol parsing mode: For systems that support standard communication protocols (such as IEC 60870-5-104, Modbus TCP), communication data packets are parsed and read through the standard communication protocol to obtain the first and / or second operating parameters of the hydropower station.

[0057] (2) Visual recognition mode: For closed or old systems, screen information capture technology based on machine vision is used to collect screen images of the hydropower station's industrial control computer, perform image positioning and character recognition on the screen images, and periodically capture parameter information of a specified area on the monitoring screen to obtain the first operating parameters and / or the second operating parameters of the hydropower station.

[0058] This application employs a dual-mode adaptive data acquisition mechanism, compatible with both standard and legacy systems, enabling automatic data collection. This avoids errors such as misreading and omissions that can occur with manual data recording, improving data accuracy. Simultaneously, it frees up manpower, allowing operators to focus on equipment analysis and fault prediction, significantly improving work efficiency and effectively reducing maintenance costs.

[0059] Furthermore, in one embodiment, obtaining the limit-exceeding result of the first operating parameter based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter includes: 201: Compare the first operating parameter with the dynamic threshold of the first operating parameter.

[0060] 202: If the first operating parameter exceeds the dynamic threshold of the first operating parameter, then the limit-breaking result is that the first operating parameter has exceeded the limit; otherwise, the limit-breaking result is that the first operating parameter has not exceeded the limit.

[0061] This embodiment automatically outputs out-of-limit results by comparing parameters with dynamic thresholds in real time, achieving standardized judgment. Dynamic thresholds adapt to operating conditions, significantly reducing false alarms and missed alarms compared to fixed thresholds. This ensures timely detection of anomalies, improves the accuracy and timeliness of early warnings, effectively guarantees the safe and stable operation of hydropower station units, and achieves automated monitoring.

[0062] In step 202 above, after determining that the first operating parameter has not exceeded the limit, the method further includes: 301: Based on the first operating parameter of the current calculation cycle, the first operating parameter of the previous calculation cycle, the dynamic threshold of the first operating parameter, and the change rate limit of the first operating parameter, obtain the trend information of the first operating parameter, which includes the rise and fall and the change rate exceeding the limit.

[0063] It is understood that in step 301, the calculation cycle is synchronized with the acquisition cycle of the first operating parameter and the second operating parameter, for example, the default setting is 1 time / minute, which can be adjusted according to the power plant's operating needs.

[0064] The formula for calculating the rate of change of the first operating parameter is as follows:

[0065] in, This represents the rate of change of the first operating parameter during the current calculation period; a positive value indicates an increase, and a negative value indicates a decrease. This is the real-time collected value of the first operating parameter during the current calculation period t; The real-time collected value of the first operating parameter in the previous calculation cycle t-1; and These are the dynamic upper and lower threshold values ​​under the current operating conditions. For different actual monitoring needs of the first operating parameter of the hydropower station, if only the upper limit of the first operating parameter is monitored and there is no need for a lower limit alarm, then the following values ​​are assigned: =0, the denominator in the rate of change calculation formula is taken as the dynamic upper limit threshold under the current operating condition. The absolute value of the value is assigned if the first running parameter only monitors the lower limit. =0, the denominator in the rate of change calculation formula is taken as the dynamic lower limit threshold under the current operating condition. The absolute value of.

[0066] like If the change rate of the first operating parameter exceeds the limit, it indicates that the change rate of the first operating parameter does not exceed the limit; otherwise, the change rate of the first operating parameter does not exceed the limit.

[0067] like and If the change rate is greater than 0, it is determined that the rate of change of the first operating parameter is "rapidly increasing". and If the value is less than 0, the rate of change of the first operating parameter is determined to be "rapidly decreasing".

[0068] The change rate limit for the first operating parameter is a fixed percentage value. The change rate limit for different first operating parameters can be different, and is set according to the equipment operating characteristics and power plant operating procedures corresponding to the first operating parameter.

[0069] 302: Obtain the trend prediction result of the first operating parameter based on the trend information of the first operating parameter over a continuous preset number of calculation cycles.

[0070] If the trend information of the first operating parameter is all upward and the rate of change exceeds the limit, or all downward and the rate of change exceeds the limit, then the trend prediction result of the first operating parameter is an abnormal trend. In the former case, the trend is an abnormal upward trend, and in the latter case, the trend is an abnormal downward trend. At this time, the trend abnormality reminder of the first operating parameter is triggered. Otherwise, the trend prediction result of the first operating parameter is a normal trend, and at this time, the trend abnormality reminder of the first operating parameter does not need to be triggered.

[0071] Understandably, the above preset quantity can be set as needed. For example, as an example, the preset quantity is set to 3, which means that if the trend information of three consecutive calculation cycles is all rising and the rate of change exceeds the standard, or all of them are falling and the rate of change exceeds the standard, it indicates that the first operating parameter has a continuous and rapid abnormal trend of rising or falling, and an early warning needs to be issued.

[0072] In this embodiment, when the limit is not exceeded, the trend is further analyzed, and abnormal rises, falls, and rates are identified by comparing the parameter change rates. Combined with continuous periodic prediction, the early signs of rapid rises or falls can be detected in a timely manner. This can compensate for the inadequacy of a single threshold, provide early warning of potential risks, improve the foresight of monitoring, prevent parameter mutations, and ensure the stable operation of the unit.

[0073] In step 202 above, after determining that the limit violation result is the first operating parameter exceeding the limit, based on the limit violation result, corresponding early warning information is triggered, including: 401: The degree of exceeding the limit of the first operating parameter is obtained based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter.

[0074] 402: Trigger corresponding early warning information based on the degree of exceeding the limit of the first operating parameter, wherein the higher the degree of exceeding the limit, the higher the level of the corresponding early warning information.

[0075] For example, if the dynamic upper limit threshold is 100, the dynamic lower limit threshold is 50, and the first operating parameter is 140, then the first operating parameter exceeds the limit, and the degree of exceeding the limit is (140-100) / 100=40%. If the threshold for judging the degree of exceeding the limit of the dynamic upper limit threshold is 10%, then a red warning is issued if it is higher than 10%, and an orange warning is issued if it is lower than 10% but higher than 0%. Since 40%>10%, a red warning should be triggered at this time. If the first operating parameter is 105, the degree of exceeding the limit is (105-100) / 100=5%. Since 5%<10%, an orange warning should be triggered at this time.

[0076] As can be seen, multiple thresholds for judging the level of exceeding the limit can be defined, and the degree of exceeding the limit can be compared with multiple thresholds to obtain the corresponding level of warning information.

[0077] This embodiment triggers early warnings by calculating the degree of limit violation, achieving tiered early warning management. The higher the degree of limit violation, the higher the warning level, helping operators quickly identify the severity of faults and prioritize handling urgent issues. This avoids alarm overload, improves operational response efficiency, ensures timely handling of key risks, and enhances safety management.

[0078] Furthermore, if the limit violation result is that the first operating parameter exceeds the limit, the method further includes: triggering the warning association information of the warning information according to the warning information level, wherein the warning association information includes anomaly location and handling suggestions.

[0079] This application's embodiments incorporate an expert knowledge base, which includes the warning association information of the aforementioned warning information. This association information is based on the operating mechanism of hydropower station equipment, industry standards and specifications, and years of operational experience of power stations. It defines the causal relationship logic between parameters and adopts a standardized format of "IF trigger condition AND association verification condition THEN alarm level + anomaly location + handling suggestion." Through multi-parameter linkage and composite judgment, it distinguishes between single parameter fluctuations and systemic faults, accurately locating the root cause of the fault. The core association rules include the following: Rule 1: If the real-time pressure of the main technical water supply pipe exceeds its dynamic threshold lower limit or the real-time pressure of the main technical water supply pipe shows an abnormal downward trend, and the temperature rise rate of any bearing bearing within a preset time is >0.5℃ / min, then an orange associated alarm is triggered. The anomaly is identified as "abnormal real-time pressure of the main technical water supply pipe leading to insufficient bearing cooling capacity," and the following handling suggestions are generated: check the operating status of the technical water supply pump and the filter differential pressure, and notify the on-site inspection team. The preset time can be set according to actual needs, such as 10 minutes.

[0080] Rule 2: If the stator temperature exceeds its dynamic threshold or shows an abnormal upward trend, AND the stator cooling system inlet water temperature is normal, AND the stator cooling water flow rate falls below the lower limit or shows an abnormal downward trend, then an orange alarm is triggered. The anomaly is identified as "insufficient flow rate in the stator cooling system leading to abnormal temperature rise," and the recommended actions are: check the status of the stator cooling water circuit valves and filter blockage, and strengthen temperature monitoring. The stator cooling system inlet water temperature will be compared with the set temperature range. If it is within the range, it is normal; otherwise, it is abnormal. This temperature range can be set as needed.

[0081] The logic for determining stator cooling water flow rate is as follows: Step 1: Using the dynamic threshold calculation method described above, with stator cooling water flow rate as the first operating parameter, and the real-time active power of the unit, the inlet water pressure of the stator cooling system, and the pressure difference between the inlet and outlet of the stator cooler as the second operating parameters, a multivariate regression method is used to fit the operating condition baseline value of the stator cooling water flow rate. Combined with the stator cooling system design specifications, manufacturer requirements, and historical fault data of the power plant, a lower limit safety margin is set to obtain the dynamic threshold of the stator cooling water flow rate. (The stator cooling water flow rate is only monitored at the lower limit; there is no upper limit alarm requirement).

[0082] Step 2: Calculate the rate of change of the stator cooling water flow rate using the previously defined rate of change formula V.

[0083] Step 3: When the condition "stator cooling water flow rate does not exceed the limit" is met, "When V < 0", it is determined that the single-cycle decrease rate of stator cooling water flow exceeds the standard; follow steps 301-302 to determine whether it is abnormal.

[0084] Rule 3: If the transformer winding temperature exceeds its dynamic threshold or shows an abnormal upward trend, AND the transformer room ambient temperature is normal, AND the cooling fan operation is abnormal or the cooler inlet air temperature rises abnormally, then an orange associated alarm is triggered. The anomaly is identified as "Transformer cooling system failure causing abnormal winding temperature," and the recommended actions are: check the cooling fan power supply and operating status, clean the cooler filter, and, if necessary, request a reduction in transformer load. The transformer room ambient temperature will be compared with the set temperature range. If it is within the range, it is normal; otherwise, it is abnormal. This temperature range can be set as needed.

[0085] In Rule 3, the operating status of the cooling fan is an auxiliary monitoring parameter, collected by the data acquisition gateway through the two methods mentioned above. If the cooling fan control system supports standard communication protocols such as IEC 60870-5-104 and Modbus TCP, the "run / stop / fault" status signal of the fan is directly acquired through protocol parsing mode. If it is an older fan (without a standard communication interface), the fan operating status indicator light and fan blade rotation are captured through visual recognition mode, and the operating status is determined by combining OCR recognition. Judgment criteria: When any of the following conditions are acquired: "fan fault signal", "fan stopped running (not manually stopped)", or "abnormal fan speed", the cooling fan is determined to be in an abnormal operating state.

[0086] The logic for determining the cooler inlet air temperature is as follows: Step 1: Using the dynamic threshold calculation method described above, with the cooler inlet air temperature as the first operating parameter, the real-time active power transmitted by the transformer and the ambient temperature of the cooler as the second operating parameters, a multivariate regression method is used for fitting, and combined with the upper limit safety margin, the dynamic upper limit threshold can be obtained (only the upper limit of the cooler inlet air temperature is monitored, and there is no need for a lower limit alarm).

[0087] Step 2: Calculate the rate of change of the cooler inlet air temperature using the previously defined rate of change formula V.

[0088] Step 3: When the condition "cooler inlet air temperature does not exceed the limit, but..." is met... If the temperature rise rate of the cooler intake air exceeds the standard, then follow steps 301-302 to determine if there is an abnormality.

[0089] Rule 4: IF The technical water supply flow rate exceeds its dynamic threshold lower limit or the technical water supply flow rate shows an abnormal downward trend AND The real-time pressure of the technical water supply main exceeds its dynamic threshold lower limit or the real-time pressure of the technical water supply main shows an abnormal downward trend AND The pressure difference between the inlet and outlet of the cooler exceeds the upper limit THEN triggers a yellow associated alarm, the anomaly is located as "cooler filter screen blockage leads to a decrease in water supply flow capacity", and the handling suggestion is: arrange to switch coolers and clean the blocked filter screen.

[0090] In Rule 4, the pressure difference between the inlet and outlet of the cooler is considered an auxiliary monitoring parameter.

[0091] The logic for determining the pressure difference between the inlet and outlet of the cooler is as follows: Step 1: The pressure difference between the inlet and outlet of the cooler is taken as the first operating parameter, and the technical water supply flow rate, the real-time pressure of the technical water supply main pipe, and the real-time active power of the unit are taken as the second operating parameters. These three are the core variables affecting the pressure difference between the inlet and outlet of the cooler. Changes in flow rate / pressure directly lead to the flow resistance and pressure difference fluctuations of the cooler. The unit load determines the cooling water supply demand and is strongly correlated with the pressure difference. The operating baseline value of the pressure difference between the inlet and outlet of the cooler is fitted by multiple regression. The upper limit safety margin is set by combining the cooler equipment manufacturer's specifications, power plant operation procedures and historical fault data to obtain the dynamic upper limit threshold of the pressure difference between the inlet and outlet of the cooler (only the upper limit is monitored, there is no need for lower limit alarm, and there is no need to set a lower limit safety margin and dynamic lower limit threshold).

[0092] Step 2: Calculate the rate of change of pressure difference between the inlet and outlet of the cooler using the previously defined rate of change formula V.

[0093] Step 3: When the "real-time collected value of the pressure difference between the inlet and outlet of the cooler is greater than the dynamic upper limit threshold under the current operating conditions" is met, it is directly determined that "the pressure difference between the inlet and outlet of the cooler exceeds the upper limit"; follow steps 301-302 to determine whether it is abnormal.

[0094] Rule 5: IF The hydraulic pressure exceeds its dynamic threshold lower limit or the hydraulic pressure shows an abnormal downward trend AND the hydraulic pump continues to run AND the guide vane relay has no action command THEN triggers a red associated alarm, the abnormality is located as "the hydraulic system has a leakage fault", and the following handling suggestions are generated: Immediately notify the on-site inspection of the hydraulic system, urgently start the backup hydraulic pump, and apply for shutdown if necessary.

[0095] Rule 6: If the real-time active power of the unit fluctuates significantly AND the guide vane opening fluctuates significantly AND the hydraulic pressure fluctuates abnormally, then a red alarm is triggered. The anomaly is identified as "abnormal adjustment of the governor system causing load fluctuations". The recommended action is to immediately switch the governor to manual control and notify maintenance personnel to troubleshoot the governor system.

[0096] The three-step logic for determining significant fluctuations in the unit's real-time active power is as follows: Step 1: Calculation of dynamic baseline value Using the unit's real-time active power as the first operating parameter, and the unit's AGC or dispatch-given active power and real-time net water head as the second operating parameters, a multiple regression model is used to fit and obtain the operating condition baseline value of the unit's real-time active power. ; Based on the power plant operation procedures, governor regulation quality requirements, and historical fault data, configurable thresholds are set: (1) Margin for small fluctuations The maximum allowable deviation during normal adjustment (e.g., rated active power) (±3%), anything exceeding this is considered an abnormal fluctuation; (2) Margin for determining large fluctuations : Threshold for large fluctuations (such as rated active power) (±8%), anything exceeding this is directly judged as a significant fluctuation; (3) Permissible rate of change for small fluctuations : The maximum permissible rate of change per single period under normal regulation (e.g., 3% / s); (4) Permissible rate of change for large fluctuations : Threshold for the rate of change of large fluctuations (e.g., 8% / s).

[0097] Step 2: Calculation of the rate of change Formula for calculating the real-time active power change rate of the unit:

[0098] Parameter description: : The relative rate of change of the real-time active power of the unit in the current calculation period (positive number indicates an increase, negative number indicates a decrease). Current period Real-time active power data of the generating units; Previous cycle Real-time active power data of the generating units; The dynamic reference value of the unit's real-time active power under the current operating conditions; The calculation cycle is synchronized with the speed controller adjustment cycle, with a default of 1 second / cycle, which can be adjusted as needed.

[0099] Step 3: Determining Significant Fluctuations (1) First determine whether there are abnormal fluctuations (excluding normal adjustment). An abnormal fluctuation (abnormal adjustment) in the real-time active power of a generator unit is determined when any of the following conditions are met: ① Absolute value of the deviation between real-time active power and the reference value (Exceeding the allowable margin for minor fluctuations); ② Absolute value of the rate of change in a single period (Exceeding the allowable rate of change for small fluctuations).

[0100] (2) Further determine whether it is a large fluctuation (distinguish between small and large abnormal fluctuations) If abnormal fluctuations have already been identified, and any of the following conditions are met, the unit's real-time active power will be ultimately determined to have experienced significant fluctuations: ① Absolute value of the deviation between real-time active power and the reference value (Exceeding the margin for judging large fluctuations); ② Absolute value of the rate of change in a single period (Exceeding the allowable rate of change for large fluctuations); ③ For multiple consecutive calculation cycles (3 by default, configurable), the condition of abnormal fluctuations is continuously met (small fluctuations accumulate into large fluctuations).

[0101] Three-step judgment logic for "synchronous large fluctuations" in guide vane opening Step 1: Calculation of dynamic baseline value Using the real-time guide vane opening as the first operating parameter, and the real-time active power and real-time net water head of the unit as the second operating parameters, a multiple regression model was used to fit the baseline value of the guide vane opening under operating conditions. ; Based on the power plant operation procedures, governor regulation quality requirements, and historical fault data, configurable thresholds are set: (1) Margin for small fluctuations The maximum allowable deviation during normal adjustment (e.g., rated opening). (±3%) (2) Margin for determining large fluctuations Thresholds with large fluctuations (such as rated opening) (±8%) (3) Permissible rate of change for small fluctuations : The maximum permissible rate of change per single period under normal regulation (e.g., 3% / s); (4) Permissible rate of change for large fluctuations : Threshold for the rate of change of large fluctuations (e.g., 8% / s); (5) Allowable deviation of synchronization time : The maximum allowable time difference between the fluctuations of the two parameters (default 1s, matching the speed controller response time).

[0102] Step 2: Calculation of the rate of change Formula for calculating the rate of change of guide vane opening:

[0103] Parameter description: : The relative rate of change of guide vane opening in the current calculation cycle (positive number indicates large opening, negative number indicates small closing); Current period Real-time acquisition value of guide vane opening; Previous cycle Real-time acquisition value of guide vane opening; The dynamic reference value of the guide vane opening under the current operating conditions; The calculation cycle is fully synchronized with the real-time active power of the unit (1 second / cycle) to ensure the accuracy of synchronization determination.

[0104] Step 3: Identify significant synchronous fluctuations (distinguishing between independent and correlated fluctuations) (1) First determine the large fluctuation of the guide vane opening itself. The logic is consistent with the real-time active power of the generator set: ① First, determine if there are abnormal fluctuations: or ; ② Further determine significant fluctuations, satisfying any one of the following: , The abnormal fluctuations continued for three consecutive cycles.

[0105] (2) Further determine synchronization with the real-time active power of the unit (verify abnormal speed governor linkage) Based on the fact that the unit's real-time active power and guide vane opening have both been determined to be fluctuating significantly, if all of the following conditions are met, it will be ultimately determined that the guide vane opening fluctuates significantly synchronously: ① Consistent fluctuation direction: Within the same calculation period, and When the positive and negative signs are the same (i.e., active power increases → guide vane opens wider, active power decreases → guide vane closes narrower); ②Synchronization of fluctuation time: The time difference between the start of large fluctuations in the two parameters is ≤ (Within 1 second, ensure that the fluctuations are caused by the same adjustment action, rather than independent random fluctuations.) ③ Fluctuation amplitude matching: Within the same cycle, the ratio of the change amplitude of the unit's real-time active power to the change amplitude of the guide vane opening should be within the allowable deviation range of the active power-opening characteristic curve under the current head of the unit (e.g., ±20%, excluding independent fluctuations caused by non-regulation).

[0106] The above information can be displayed through a human-machine interface, allowing operators to perform graphical operations. The human-machine interface centrally displays a parameter overview, real-time / historical trend curves, alarm lists, confirmation panels, and device settings.

[0107] (1) Graded alarm: Alarms are divided into different grades according to the severity of the anomaly, the rate of change and the scope of impact, such as red (urgent, needs to be dealt with immediately), orange (important, needs to be dealt with as soon as possible) and yellow (warning, needs to be paid attention to).

[0108] (2) Generation of handling suggestions: Connect to the expert knowledge base to provide possible causes and preliminary handling suggestions for each type of alarm (such as "strengthen monitoring", "notify on-site inspection", "request load adjustment" etc.).

[0109] (3) One-click confirmation and feedback: Operators can confirm alarms through the human-machine interface and select the actual operation to be performed from a preset list. The feedback information is recorded and used to optimize subsequent alarm models.

[0110] (4) Automatic generation of operation logs: Automatically generate standardized electronic operation logs from alarm events, parameter snapshots, confirmed personnel, time and handling selections, and support export and archiving.

[0111] Compared with the prior art, this application has the following outstanding advantages: (1) Completely liberate manpower: Free up operators from repetitive manual meter reading every 4 hours, saving more than 90% of related working hours, allowing them to focus more on inspection, operation and advanced analysis.

[0112] (2) Enhance safety early warning capabilities: Through dynamic thresholds that adapt to operating conditions, trend analysis of quantitative standards, and multi-parameter correlation diagnosis, potential equipment faults can be detected earlier and more accurately, transforming "post-event handling" into "pre-event early warning", significantly reducing the false alarm rate and improving the safety of power plant operation.

[0113] (3) Achieve knowledge accumulation and closed loop: The handling experience of operators is structured through the "confirmation-feedback" mechanism, and alarm rules, analysis models and handling suggestion library are continuously optimized, realizing the digital accumulation and inheritance of tacit knowledge.

[0114] (4) Flexible deployment and strong compatibility: The dual-mode data acquisition solution does not require deep modification of the existing monitoring system or opening of the underlying database. It is compatible with both newly built power plants that support standard protocols and closed old power plants that have already been put into operation. The implementation cost is low and the risk is small.

[0115] (5) Standardized management: The automatically generated standardized electronic logs fully record alarm events and the entire handling process, which facilitates traceability, auditing and analysis, and improves the standardization and refinement of operation management.

[0116] Secondly, this application also provides a hydropower station monitoring and early warning device.

[0117] In one embodiment, reference is made to Figure 2 , Figure 2 This is a schematic diagram of the functional modules of an embodiment of the hydropower station monitoring and early warning device of this application. Figure 2 As shown, the hydropower station monitoring and early warning device includes: The limit exceedance result acquisition module is used to acquire the limit exceedance result of the first operating parameter based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter; The early warning information triggering module is used to trigger corresponding early warning information based on the exceeded limit result; The dynamic threshold is obtained based on the operating condition baseline value and the safety margin. The operating condition baseline value is obtained from the second operating parameter and the regression coefficient. The regression coefficient is obtained from the historical operating data of the second operating parameter and the historical operating data of the first operating parameter.

[0118] Furthermore, in one embodiment, the hydropower station monitoring and early warning device also includes a data acquisition gateway, used to parse and read communication data packets through a standard communication protocol to obtain the first operating parameters and / or the second operating parameters of the hydropower station.

[0119] Furthermore, in one embodiment, the hydropower station monitoring and early warning device also includes a visual recognition module, which acquires the screen image of the hydropower station's industrial control computer, performs image positioning and character recognition on the screen image, and obtains the first operating parameters and / or the second operating parameters of the hydropower station.

[0120] Furthermore, in one embodiment, the limit-exceeding result acquisition module acquires the limit-exceeding result of the first operating parameter based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter, including: Compare the first operating parameter with the dynamic threshold of the first operating parameter; If the first operating parameter exceeds the dynamic threshold of the first operating parameter, then the result of exceeding the limit is that the first operating parameter exceeds the limit; Otherwise, the result of exceeding the limit is that the first operating parameter did not exceed the limit.

[0121] Furthermore, in one embodiment, after determining that the first operating parameter has not exceeded the limit, the limit-exceeding result acquisition module is further configured to: Based on the first operating parameter of the current calculation cycle, the first operating parameter of the previous calculation cycle, the dynamic threshold of the first operating parameter, and the change rate limit of the first operating parameter, the trend information of the first operating parameter is obtained, and the trend information includes the rise and fall and the change rate exceeding the limit. Based on the trend information of the first operating parameter over a continuous preset number of calculation cycles, obtain the trend prediction result of the first operating parameter.

[0122] Furthermore, in one embodiment, the over-limit result acquisition module acquires the trend prediction result of the first operating parameter based on the trend information of the first operating parameter for a consecutive preset number of calculation cycles, including: if the trend information of the first operating parameter is all increasing and the rate of change exceeds the standard, or all decreasing and the rate of change exceeds the standard, then the trend prediction result of the first operating parameter is an abnormal trend; otherwise, the trend prediction result of the first operating parameter is a normal trend.

[0123] Furthermore, in one embodiment, the early warning information triggering module triggers corresponding early warning information based on the limit violation result, including: The degree of exceeding the limit of the first operating parameter is obtained based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter; The corresponding warning information is triggered based on the degree of violation of the first operating parameter, wherein the higher the degree of violation, the higher the level of the corresponding warning information; And / or, the warning information triggering module triggers corresponding warning information based on the exceeded limit result, including: Obtain the trend prediction result of the first operating parameter; Based on the trend prediction results, the trend anomaly alert for the first operating parameter may or may not be triggered.

[0124] Furthermore, in one embodiment, if the limit violation result is that the first operating parameter exceeds the limit, the warning information triggering module is further configured to: Based on the warning information level, the warning-related information that triggers the warning information includes anomaly location and handling suggestions.

[0125] The functions of each module in the aforementioned hydropower station monitoring and early warning device correspond to the steps in the aforementioned hydropower station monitoring and early warning method embodiment, and their functions and implementation processes will not be described in detail here.

[0126] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0127] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0128] In the description of the embodiments in this application, terms such as "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0129] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0130] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0131] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0132] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for monitoring and early warning of hydropower stations, characterized in that, The hydropower station monitoring and early warning methods include: Based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter, the result of exceeding the limit of the first operating parameter is obtained; Based on the aforementioned limit violation result, a corresponding early warning message is triggered; The dynamic threshold is obtained based on the operating condition baseline value and the safety margin. The operating condition baseline value is obtained from the second operating parameter and the regression coefficient. The regression coefficient is obtained from the historical operating data of the second operating parameter and the historical operating data of the first operating parameter.

2. The hydropower station monitoring and early warning method as described in claim 1, characterized in that, The first operating parameter includes at least one of the following: bearing bearing temperature, unit stator temperature, transformer winding temperature, real-time pressure of the main technical water supply pipe, technical water supply flow rate, and hydraulic device pressure.

3. The hydropower station monitoring and early warning method as described in claim 2, characterized in that, When the first operating parameter includes the bearing pad temperature, the second operating parameter corresponding to the bearing pad temperature includes the real-time active power of the unit, the technical water supply inlet temperature, and the real-time ambient temperature of the plant where the unit is located. And / or, when the first operating parameter includes the stator temperature of the generator set, the second operating parameter corresponding to the stator temperature of the generator set includes the real-time active power of the generator set, the inlet water temperature of the stator cooling system, and the real-time ambient temperature of the generator floor. And / or, when the first operating parameter includes the transformer winding temperature, the second operating parameter corresponding to the transformer winding temperature includes the real-time active power transmitted by the transformer, the transformer cooler inlet air temperature, and the real-time ambient temperature of the transformer room. And / or, when the first operating parameter includes the real-time pressure of the main technical water supply pipe, the second operating parameter corresponding to the real-time pressure of the main technical water supply pipe includes the real-time active power of the unit and the real-time flow rate of the main technical water supply pipe. And / or, when the first operating parameter includes the technical water supply flow rate, the second operating parameter corresponding to the technical water supply flow rate includes the real-time active power of the unit, the real-time pressure of the technical water supply main pipe, and the real-time pressure difference between the inlet and outlet of the cooler; And / or, when the first operating parameter includes the pressure of the hydraulic device, the second operating parameter corresponding to the pressure of the hydraulic device includes the real-time opening degree of the unit guide vanes and the real-time ambient temperature at the location of the hydraulic device.

4. The hydropower station monitoring and early warning method as described in claim 1, characterized in that, The method further includes: The communication data packets are parsed and read using standard communication protocols to obtain the first and / or second operating parameters of the hydropower station. And / or, acquire screen images of the hydropower station's industrial control computer, perform image positioning and character recognition on the screen images, and obtain the first operating parameters and / or second operating parameters of the hydropower station.

5. The hydropower station monitoring and early warning method as described in claim 1, characterized in that, Based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter, the result of exceeding the limit of the first operating parameter is obtained, including: Compare the first operating parameter with the dynamic threshold of the first operating parameter; If the first operating parameter exceeds the dynamic threshold of the first operating parameter, then the result of exceeding the limit is that the first operating parameter exceeds the limit; Otherwise, the result of exceeding the limit is that the first operating parameter did not exceed the limit.

6. The hydropower station monitoring and early warning method as described in claim 5, characterized in that, After determining that the first operating parameter has not exceeded the limit, the method further includes: Based on the first operating parameter of the current calculation cycle, the first operating parameter of the previous calculation cycle, the dynamic threshold of the first operating parameter, and the change rate limit of the first operating parameter, the trend information of the first operating parameter is obtained, and the trend information includes the rise and fall and the change rate exceeding the limit. Based on the trend information of the first operating parameter over a continuous preset number of calculation cycles, obtain the trend prediction result of the first operating parameter.

7. The hydropower station monitoring and early warning method as described in claim 6, characterized in that, Based on the trend information of the first operating parameter for a continuous preset number of calculation cycles, the trend prediction result of the first operating parameter is obtained, including: if the trend information of the first operating parameter is all rising and the rate of change exceeds the standard, or all falling and the rate of change exceeds the standard, then the trend prediction result of the first operating parameter is an abnormal trend; otherwise, the trend prediction result of the first operating parameter is a normal trend. And / or, the calculation cycle is synchronized with the acquisition cycle of the first operating parameter and the second operating parameter.

8. The hydropower station monitoring and early warning method as described in claim 1, characterized in that, If the limit violation result is that the first operating parameter exceeds the limit, based on the limit violation result, corresponding early warning information is triggered, including: The degree of exceeding the limit of the first operating parameter is obtained based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter; The corresponding warning information is triggered based on the degree of violation of the first operating parameter, wherein the higher the degree of violation, the higher the level of the corresponding warning information; And / or, if the limit violation result is that the first operating parameter does not exceed the limit, based on the limit violation result, a corresponding warning message is triggered, including: Obtain the trend prediction result of the first operating parameter; Based on the trend prediction results, the trend anomaly alert for the first operating parameter may or may not be triggered.

9. The hydropower station monitoring and early warning method as described in claim 8, characterized in that, If the result of the exceeding the limit is that the first running parameter exceeds the limit, the method further includes: Based on the warning information level, the warning-related information that triggers the warning information includes anomaly location and handling suggestions.

10. A monitoring and early warning device for a hydropower station, characterized in that, The hydropower station monitoring and early warning device includes: The limit exceedance result acquisition module is used to acquire the limit exceedance result of the first operating parameter based on the first operating parameter of the hydropower station and the dynamic threshold of the first operating parameter; The early warning information triggering module is used to trigger corresponding early warning information based on the exceeded limit result; The dynamic threshold is obtained based on the operating condition baseline value and the safety margin. The operating condition baseline value is obtained from the second operating parameter and the regression coefficient. The regression coefficient is obtained from the historical operating data of the second operating parameter and the historical operating data of the first operating parameter.

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