CN118149927B - Method, system, equipment and medium for early warning of abnormal oil level of hydraulic oil system of hydropower station - Google Patents
Method, system, equipment and medium for early warning of abnormal oil level of hydraulic oil system of hydropower station Download PDFInfo
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- 239000003921 oil Substances 0.000 title claims abstract description 301
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- 238000000034 method Methods 0.000 title claims abstract description 33
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- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/80—Arrangements for signal processing
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Abstract
The invention relates to the technical field of pumped storage unit equipment, in particular to a method, a system, equipment and a medium for early warning of abnormal oil level of a hydraulic oil system of a hydropower station, which comprises the following steps: acquiring input data, wherein the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level; calculating an oil level predicted value of the oil return tank based on the oil level of the pressure oil tank; based on the equipment parameters, determining the state of the hydroelectric generating set, and based on the state of the hydroelectric generating set, searching a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state from a characteristic database; and determining whether the oil level of the hydraulic oil system of the hydro-power unit is abnormal according to the difference value between the oil level of the oil return tank and the predicted value of the oil level of the oil return tank and a linear regression curve, and carrying out abnormality early warning under the condition that the oil level of the hydraulic oil system of the hydro-power unit is abnormal. According to the invention, the characteristic database is established, and the oil level prediction difference value of the oil return tank is compared with the linear regression curve, so that the running risk of the oil pressing system is reduced, and the alarm efficiency is improved.
Description
Technical Field
The invention relates to the technical field of pumped storage unit equipment, in particular to a method, a system, equipment and a medium for early warning of abnormal oil level of a hydraulic oil system of a hydropower station.
Background
The hydraulic oil system plays a vital role in a hydropower station, and is a hydraulic oil supply system used by hydraulic actuators of a unit adjusting system, a control system, a jigger device and other equipment, and comprises an oil pump, an oil filter, a valve, a pipeline and other parts. The hydraulic oil system is responsible for providing necessary hydraulic oil for a hydraulic adjustment or electrohydraulic adjustment system so as to meet various adjustment and control requirements, and the normal operation of the hydraulic oil system has important significance for ensuring the stable operation and efficient power generation of the hydropower station.
In hydropower stations, the units need to be frequently adjusted to adapt to different operating conditions, and the hydraulic oil system provides a stable and reliable hydraulic oil source for the adjustment processes. In a hydropower station, parameters such as the rotating speed, the load and the like of a unit need to be adjusted in real time, and the response speed and the stability of a pressure oil system directly influence the adjusting effect of the parameters, so that the accuracy and the rapidity of unit adjustment are directly influenced. Therefore, monitoring oil level and oil quantity information of the oil pressing system is important to ensuring safe operation and power generation efficiency of the hydropower station.
The traditional oil level monitoring method of the oil pressure system adopts an alarm mode that the fixed threshold value of the pressure oil tank and the oil return tank is out of limit, is mainly concentrated on oil level monitoring of the pressure oil tank, and pumps oil from the oil return tank to the pressure oil tank through an oil pump when the oil level of the pressure oil tank is reduced, and the whole circulation oil loop and the operation oil loop are abnormal such as leaked oil and run oil in the circulation operation process, so that the problem cannot be found by monitoring the oil level of the pressure oil tank, the whole system has potential safety hazard, the oil pressure system cannot timely operate to supplement oil, and therefore, an abnormal accident of the oil pressure system occurs when the power grid is stopped, and unstable factors are brought to the operation of the power grid.
Disclosure of Invention
The invention aims to solve the problem that oil leakage and oil running cannot be found in time by adopting an alarm mode that a fixed threshold value of a pressure oil tank and an oil return tank is out of limit in the traditional method, and provides an abnormal oil level early warning method, system, equipment and medium for a hydraulic oil system of a hydropower station.
The embodiment of the invention is realized by the following technical scheme: the early warning method for the abnormal oil level of the hydraulic oil system of the hydropower station comprises the following steps:
Acquiring input data, wherein the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level;
Calculating an oil level predicted value of an oil return tank based on the pressure oil tank oil level;
Based on the equipment parameters, determining the state of the hydroelectric generating set, and based on the state of the hydroelectric generating set, searching a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state from a characteristic database;
And determining whether the oil level of the hydro-power unit system is abnormal according to the difference value between the oil level of the oil return tank and the oil level predicted value of the oil return tank and the linear regression curve, and carrying out abnormality early warning under the condition that the oil level of the hydro-power unit system is abnormal.
According to a preferred embodiment, the method further comprises performing validity processing and filtering processing on the input data and filtering the abnormal data before calculating the predicted oil level value of the oil return tank.
According to a preferred embodiment, the abnormal data is data whose adjacent time changes are greater than a first preset threshold value, which is determined empirically by an expert, and which has a jump.
According to a preferred embodiment, the feature database is generated as follows:
Periodically extracting a pressure oil tank oil level curve and an oil return tank oil level curve under the working conditions of shutdown and operation from a computer monitoring system;
Screening the curves, removing the curves in the oil pump operation interval, the curves of the hydropower unit in which accident shutdown occurs, the curves of the oil level exceeding the threshold value of the computer monitoring system, the curves of the oil level with bad quality and the curves of the oil level change larger than a second preset threshold value and jump at adjacent moments, wherein the second preset threshold value is determined by expert experience;
performing data reorganization on curves under shutdown and operation conditions at each moment to form a characteristic state matrix;
And calculating a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank by adopting a partial least square regression algorithm based on the characteristic state matrix, and generating a characteristic database.
According to a preferred embodiment, the determining whether the oil level of the hydro-power generating unit system is abnormal according to the difference value between the oil level of the oil return tank and the predicted value of the oil level of the oil return tank and the linear regression curve specifically includes:
and acquiring the difference value in a long period, storing the difference value into temporary storage, and judging the abnormal oil level of the hydroelectric generating set system based on the difference value in the temporary storage.
According to a preferred embodiment, the conditions for judging the abnormal oil level of the hydro-power generating unit system are as follows:
When the difference between adjacent moments in the temporary storage is larger than the confidence interval of the linear regression curve, the judging condition is satisfied;
When N confidence intervals with difference values larger than the linear regression curve exist in the temporary storage, the judgment condition is met, and N is determined by expert experience.
According to a preferred embodiment, all differences in the temporary storage are cleared when the hydroelectric generating set is in a non-stop condition during the acquisition of the differences over a long period.
The invention also provides an oil level abnormality early warning system of the hydraulic oil system of the hydropower station, which comprises the following components:
the data acquisition module is used for acquiring input data, wherein the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level;
the calculation module is used for calculating an oil level predicted value of the oil return tank based on the oil level of the pressure oil tank;
the searching module is used for determining the state of the hydroelectric generating set based on the equipment parameters, and searching a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state from the characteristic database based on the state of the hydroelectric generating set;
And the judging module is used for determining whether the oil level of the hydro-power generating unit system is abnormal according to the difference value between the oil level of the oil return tank and the oil level predicted value of the oil return tank and the linear regression curve, and carrying out abnormality early warning under the condition that the oil level of the hydro-power generating unit system is abnormal.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method as described above when executing the computer program.
The invention also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a method as described above.
The technical scheme of the oil level abnormality early warning method, the system, the equipment and the medium for the hydraulic oil system of the hydropower station at least has the following advantages and beneficial effects: according to the invention, a characteristic database of a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank is established, the total change condition of the oil level is obtained based on the oil level parameters of the oil return tank and the pressure oil tank of the hydroelectric generating set under the working condition of shutdown and the working condition of operation, and the oil level of the hydroelectric generating set is compared with the corresponding linear regression curve based on the difference value of the oil level predicted value of the oil return tank and the oil level of the oil return tank, so that early warning when the oil level of the oil system of the hydroelectric generating set is abnormal is conveniently realized, the running risk of the oil system is reduced, and the warning efficiency is improved.
Drawings
Fig. 1 is a flow chart of a method for early warning of abnormal oil level of a hydraulic oil system of a hydropower station according to embodiment 1 of the present invention;
Fig. 2 is a general flow chart of the method for early warning of abnormal oil level in the hydraulic oil system of the hydropower station according to embodiment 1 of the present invention;
Fig. 3 is a logic diagram for determining abnormality of a hydraulic oil system according to embodiment 1 of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Example 1
Referring to fig. 1, an embodiment of the invention provides a method for early warning of abnormal oil level of a hydraulic oil system of a hydropower station, which comprises the following steps:
Input data is acquired, wherein the input data is external I/O input data, and the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level. For external I/O input data acquisition, a control system design using a PLC and a soft starter as a core may be considered, for example, the CPU216 and the expansion modules EM235 and EM222 in the s 7-200 series PLC of siemens, germany are used for an automatic control system of a hydraulic device of a hydroelectric power plant generator set, and the system uses a plurality of discrete input points and analog input points, so that input data from a sensor can be effectively processed, and not described in detail herein.
Further, legitimacy processing and filtering processing are carried out on the input data, and abnormal data are filtered; in one implementation manner of this embodiment, the abnormal data is data whose adjacent time change is greater than a first preset threshold and has a jump, the first preset threshold is determined empirically by an expert, for example, if the data change at two adjacent times, i.e., the current time t and the time t-1, is greater than 10%, it indicates that the data at the time t is abnormal, and here, the abnormal data at the time t is subjected to a rejection process, and the data at the next time is continuously acquired; if the data changes at time t, time t-1, time t-2, and time t-3 are all more than 10%, the data is not deleted.
Further, an oil return tank oil level prediction value is calculated based on the pressure tank oil level. The oil level of the oil return tank is calculated according to the oil level of the pressure oil tank, and required acquisition parameters comprise the volume of the pressure oil tank, a working medium, a connection mode and a pipeline layout between the pressure oil tank and the oil return tank, the working pressure and the flow of the system and an air supplementing mechanism of the pressure oil tank, which are not described in detail.
Further, based on the equipment parameters, the state of the hydroelectric generating set is determined, and based on the state of the hydroelectric generating set, a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state is searched from a characteristic database.
In one implementation manner of this embodiment, the generating step of the feature database is as follows:
A data acquisition step: and periodically, automatically or manually extracting the pressure oil tank oil level curve and the oil return tank oil level curve under the working conditions of shutdown and operation from the computer monitoring system.
Screening: screening the curves, removing the curves in the oil pump operation interval, the curves of the hydropower unit in which accident shutdown occurs, the curves of the oil level exceeding the threshold value of the computer monitoring system, the curves of the oil level with bad quality and the curves of the oil level change at adjacent moments which are larger than a second preset threshold value and jump, wherein the first preset threshold value is determined by expert experience, and the oil pump operation interval is inquired and obtained through a history library inquiry interface of the computer monitoring system.
And (3) finishing: performing data reorganization on curves under shutdown and operation conditions at each moment to form a characteristic state matrix; the resulting feature state matrix is shown in table 1:
TABLE 1 characteristic state matrix
In the upper table, the following is a Chinese character of%) Representing the oil level of a pressure oil tank under the working condition of stopping) Representing the oil level of a pressure oil tank under the operating condition) Indicating the oil level of an oil return tank under the working condition of stopping) Indicating the oil level of the oil return tank under the operating condition.
A curve generating step: and calculating a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank by adopting a partial least square regression algorithm based on the characteristic state matrix, and generating a characteristic database. In one implementation manner of the embodiment, the fitting property of the linear regression curve is tested based on the twenty-eight principle, 80% of the linear regression curve is obtained by calculation from the characteristic state matrix, and the characteristic model linear equation 1 corresponding to the shutdown condition is obtained, which is specifically expressed asAnd a characteristic model linear equation 2 corresponding to the operating condition, specifically expressed as，Representing a functionAt the inputIn the case of (a) the resulting value,Representation ofIs a linear equation of (a),Representing a functionAt the inputIn the case of (a) the resulting value,Representation ofIs a linear equation of (2). And then substituting the rest 20% of the characteristic state matrix into the linear equation 1 and the linear equation 2, wherein the fitting test result shows that the data fitting performance is good.
Further, in this embodiment, a confidence interval with a confidence coefficient of 0.95 is taken as a criterion for judging whether the oil level of the oil system is abnormal.
Further, according to the difference value between the oil level of the oil return tank and the oil level predicted value of the oil return tank and the linear regression curve, whether the oil level of the hydro-power generating unit system is abnormal or not is determined, and abnormal early warning is carried out under the condition that the oil level of the hydro-power generating unit system is abnormal. In one implementation manner of this embodiment, the determining whether the oil level of the hydraulic oil system of the hydro-power unit is abnormal according to the difference between the oil level of the oil return tank and the predicted value of the oil level of the oil return tank and the linear regression curve specifically includes:
a difference value obtaining step: obtaining said difference over a long period, e.g. Storing the difference value into temporary storage, and clearing all the difference values in the temporary storage when the hydroelectric generating set is in a non-stop working condition in the process of acquiring the difference value in a long period;
Judging: referring to fig. 3, when the difference between adjacent moments in the temporary storage is larger than the confidence interval of the linear regression curve, the judging condition is satisfied; when N confidence intervals with differences greater than the linear regression curve exist in the temporary storage, the judging condition is satisfied, N is determined empirically by an expert, and in one implementation manner of this embodiment, N is 15% of the differences in the temporary storage.
Referring to fig. 2, the following describes a complete flow of the method for early warning of abnormal oil level of the hydraulic oil system of the hydropower station provided by the invention:
The method comprises the steps of starting a task, reading real-time data of a computer monitoring system, judging whether a unit is in an overhaul state according to the read real-time data, returning to a waiting task to restart if the unit is in the overhaul state, otherwise, further judging whether the unit is in a shutdown working condition or an operation working condition, inquiring a linear equation 1 of a corresponding state from a characteristic database and calculating an oil return tank oil level predicted value when the unit is in the shutdown working condition, further calculating a difference value between the oil return tank oil level predicted value and the oil return tank oil level, judging whether the oil level of the oil pressing system is abnormal according to the difference value and a confidence interval, alarming and inputting the abnormal oil level into a history library on a human-computer interface if the abnormal oil level is abnormal, ending the task, and returning to wait for restarting if the abnormal oil level is not abnormal; if the unit is in the shutdown working condition, a linear equation 2 of a corresponding state is queried from the characteristic database, the predicted value of the oil level of the oil return tank is calculated, and the follow-up steps which are the same as the shutdown working condition are executed.
In summary, the technical solution of the oil level abnormality early warning method, system, equipment and medium for the hydraulic oil system of the hydropower station according to the embodiments of the present invention has at least the following advantages and beneficial effects: according to the invention, a characteristic database of a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank is established, the total change condition of the oil level is obtained based on the oil level parameters of the oil return tank and the pressure oil tank of the hydroelectric generating set under the working condition of shutdown and the working condition of operation, and the oil level of the hydroelectric generating set is compared with the corresponding linear regression curve based on the difference value of the oil level predicted value of the oil return tank and the oil level of the oil return tank, so that early warning when the oil level of the oil system of the hydroelectric generating set is abnormal is conveniently realized, the running risk of the oil system is reduced, and the warning efficiency is improved.
Example 2
The embodiment of the invention provides an oil level abnormality early warning system of a hydraulic oil system of a hydropower station, which comprises the following components: the data acquisition module is used for acquiring input data, wherein the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level; the calculation module is used for calculating an oil level predicted value of the oil return tank based on the oil level of the pressure oil tank; the searching module is used for determining the state of the hydroelectric generating set based on the equipment parameters, and searching a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state from the characteristic database based on the state of the hydroelectric generating set; and the judging module is used for determining whether the oil level of the hydro-power generating unit system is abnormal according to the difference value between the oil level of the oil return tank and the oil level predicted value of the oil return tank and the linear regression curve, and carrying out abnormality early warning under the condition that the oil level of the hydro-power generating unit system is abnormal.
Example 3
An embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the method according to embodiment 1 when executing the computer program.
Example 4
Embodiments of the present invention provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method according to embodiment 1.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The method for early warning the abnormal oil level of the hydraulic oil system of the hydropower station is characterized by comprising the following steps of:
Acquiring input data, wherein the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level;
Calculating an oil level predicted value of an oil return tank based on the pressure oil tank oil level;
based on the equipment parameters, determining the state of the hydroelectric generating set, and based on the state of the hydroelectric generating set, searching a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state from a characteristic database, wherein the characteristic database is generated by the following steps:
Periodically extracting a pressure oil tank oil level curve and an oil return tank oil level curve under the working conditions of shutdown and operation from a computer monitoring system;
Screening the curves, removing the curves in the oil pump operation interval, the curves of the hydropower unit in which accident shutdown occurs, the curves of the oil level exceeding the threshold value of the computer monitoring system, the curves of the oil level with bad quality and the curves of the oil level change larger than a second preset threshold value and jump at adjacent moments, wherein the second preset threshold value is determined by expert experience;
performing data reorganization on curves under shutdown and operation conditions at each moment to form a characteristic state matrix;
Based on the characteristic state matrix, calculating a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank by adopting a partial least square regression algorithm, and generating a characteristic database;
According to the difference value between the oil level of the oil return tank and the predicted value of the oil level of the oil return tank and the linear regression curve, determining whether the oil level of the hydro-power unit oil pressing system is abnormal, and carrying out abnormality early warning under the condition that the oil level of the hydro-power unit oil pressing system is abnormal, the determining whether the oil level of the hydro-power unit oil pressing system is abnormal specifically comprises: acquiring the difference value in a long period, storing the difference value into temporary storage, and judging the abnormal oil level of the hydroelectric generating set system based on the difference value in the temporary storage;
the judging conditions of the abnormal oil level of the hydro-power generating unit system are as follows: when the difference between adjacent moments in the temporary storage is larger than the confidence interval of the linear regression curve, the judging condition is satisfied;
when N differences larger than the confidence interval of the linear regression curve exist in the temporary storage, the judging condition is met, and N is determined by expert experience.
2. The method for warning of abnormal oil level in a hydraulic oil system of a hydropower station according to claim 1, wherein the method further comprises legality processing and filtering processing of the input data and filtering of abnormal data before calculating the predicted value of the oil level of the return oil tank.
3. The method for early warning of abnormal oil level of hydraulic oil system of hydropower station according to claim 2, wherein the abnormal data is data with adjacent moment change larger than a first preset threshold value and jump, and the first preset threshold value is determined by expert experience.
4. The method for early warning of abnormal oil level of hydraulic oil system of hydropower station according to claim 1, wherein all differences in the temporary storage are removed when the hydropower unit is in a non-stop working condition in the process of obtaining the differences in a long period.
5. An abnormal oil level early warning system for a hydraulic oil system of a hydraulic power station, which is applied to the abnormal oil level early warning method for the hydraulic oil system of the hydraulic power station according to claim 1, and is characterized by comprising the following steps:
the data acquisition module is used for acquiring input data, wherein the input data comprises equipment parameters, a pressure oil tank oil level and an oil return tank oil level;
the calculation module is used for calculating an oil level predicted value of the oil return tank based on the oil level of the pressure oil tank;
the searching module is used for determining the state of the hydroelectric generating set based on the equipment parameters, and searching a linear regression curve of the oil level of the oil return tank and the oil level of the pressure oil tank corresponding to the state from the characteristic database based on the state of the hydroelectric generating set;
And the judging module is used for determining whether the oil level of the hydro-power generating unit system is abnormal according to the difference value between the oil level of the oil return tank and the oil level predicted value of the oil return tank and the linear regression curve, and carrying out abnormality early warning under the condition that the oil level of the hydro-power generating unit system is abnormal.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 4 when the computer program is executed.
7. A computer readable storage medium, characterized in that it has stored thereon a computer program which, when executed by a processor, implements the method according to any of claims 1 to 4.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104061976A (en) * | 2014-07-14 | 2014-09-24 | 济钢集团有限公司 | Dynamic monitoring device and method for liquid level of oil tank of hydraulic system |
| CN110431499A (en) * | 2016-12-22 | 2019-11-08 | 法国电力公司 | Method for one or more failures in characterization system |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3876037A (en) * | 1973-07-30 | 1975-04-08 | Nycal Company Inc | Liquid level sensing device |
| JP2010077856A (en) * | 2008-09-25 | 2010-04-08 | Hitachi-Ge Nuclear Energy Ltd | Emergency diesel generator facility and its operation method |
| JP2012202423A (en) * | 2011-03-23 | 2012-10-22 | Chugoku Electric Power Co Inc:The | Control system for pressure oil device |
| CN204902934U (en) * | 2015-07-16 | 2015-12-23 | 国家电网公司 | Oil groove liquid level switches mechanism |
| CN110702437B (en) * | 2019-09-12 | 2021-06-29 | 国能大渡河流域水电开发有限公司龚嘴水力发电总厂 | Evaluation method for health condition of hydraulic system of hydroelectric generating set |
| CN115271123A (en) * | 2022-08-05 | 2022-11-01 | 五凌电力有限公司 | Oil mass early warning method and device for hydroelectric generating set oil system and electronic equipment |
| CN115659781A (en) * | 2022-09-27 | 2023-01-31 | 南京南瑞水利水电科技有限公司 | Coastal gate station tide level prediction method and system |
| CN116125880A (en) * | 2023-01-05 | 2023-05-16 | 湖北清江水电开发有限责任公司 | Turbine oil mass monitoring system of hydropower plant and operation mode thereof |
| CN116956173A (en) * | 2023-04-06 | 2023-10-27 | 中车资阳机车有限公司 | Trend deviation early warning method and diagnosis method for establishing association relation based on data mining |
| CN117553246A (en) * | 2023-10-13 | 2024-02-13 | 中国长江电力股份有限公司 | Oil leakage alarm method for speed regulation system of hydroelectric generating set |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104061976A (en) * | 2014-07-14 | 2014-09-24 | 济钢集团有限公司 | Dynamic monitoring device and method for liquid level of oil tank of hydraulic system |
| CN110431499A (en) * | 2016-12-22 | 2019-11-08 | 法国电力公司 | Method for one or more failures in characterization system |
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