Intelligent early warning method and system for pressure pulsation of a hydraulic turbine

Abstract

The present application relates to a kind of water turbine pressure pulsation intelligent early warning method and system, the method includes pressure pulsation data acquisition and monitoring, abnormal pressure pulsation intelligent discrimination strategy, abnormal pressure pulsation cumulative duration calculation, pressure pulsation threshold calculation, pressure pulsation abnormal intelligent early warning strategy.The present application is used for intelligently capturing pressure pulsation anomaly, and timely early warning output is carried out.Meanwhile, the method of the present application has the characteristics of simple operation, strong universality, and is easy to popularize and apply.

Description

Technical Field

[0001] This invention belongs to the technical field of stable operation of hydro-generators, specifically relating to an intelligent early warning method and system for pressure pulsation in hydro-generators. Background Technology

[0002] To ensure the long-term safe operation of hydro-generators, stability tests are typically conducted on the unit under all operating conditions. Based on the test data, criteria for determining prohibited operating zones, restricted operating zones, and stable operating zones are established. Units generally operate within the stable operating zone for extended periods. However, under extreme operating conditions, or when flow-through components such as the runner are damaged, abnormal fluctuations in tailwater pressure are often observed. During operational monitoring, most attention is focused on external characteristics such as vibration, sway, and temperature; monitoring and early warning systems for pressure pulsations are currently lacking.

[0003] The industry standard practice is to set fixed warning limits for tailrace pressure pulsations, issuing a warning when the measured value exceeds the limit. However, in actual engineering applications, occasional fluctuations are quite common, often resulting in false alarms; furthermore, the pressure pulsation limits vary under different operating conditions. Summary of the Invention

[0004] To address the aforementioned problems, this invention proposes an intelligent early warning method and system for pressure pulsation in hydraulic turbines. Primarily targeting long-term operation under extreme conditions or abnormal situations such as runner damage, it intelligently identifies pressure pulsations and issues timely warnings. The two limit values ​​of this invention are dynamic, changing in real-time according to operating conditions, thus overcoming the shortcomings of traditional limit-based early warning systems. It can effectively identify abnormal pressure pulsations caused by prolonged operation under extreme conditions or damage to flow components such as the runner, and issue warnings after intelligent judgment. This method is simple to operate, highly versatile, and easy to promote and apply.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for intelligent early warning of pressure pulsation in a hydraulic turbine includes the following steps:

[0007] Step (1) Collect real-time data of pressure pulsation peak value P, working head H, and guide vane opening D of the tailrace cone of the mixed-flow turbine;

[0008] Step (2) Calculate the pressure pulsation head limit of the tailrace cone, denoted as P. H ;

[0009] Step (3) Based on historical data, select data under stable operating conditions, calculate the upper limit threshold of tailwater pressure fluctuation under each operating condition, and denot it as P. T n, n=1, 2, 3, 4, 5....;

[0010] Step (4) Calculate the pressure pulsation super P in the tailrace cone based on real-time data.H Cumulative runtime T1;

[0011] Step (5) Calculate the pressure pulsation super P in the tailrace cone based on real-time data. T n. Cumulative runtime T2;

[0012] Step (6) When the intelligent early warning conditions are met, output an early warning signal. The intelligent early warning conditions are as follows:

[0013] If T1 is greater than or equal to the first time setpoint or T2 is greater than or equal to the second time setpoint, an early warning of abnormal pressure pulsation will be issued.

[0014] T1 ≥ First time setpoint output: The unit times out under adverse operating conditions;

[0015] T2 ≥ Second time setpoint output: Unit pressure pulsation deteriorates;

[0016] The first and second time setpoints are set by the user according to the characteristics of the turbine.

[0017] Furthermore, in step (1), the tailrace cone pressure pulsation, working head, and guide vane opening data are stored simultaneously with consistent time coordinates and a data acquisition cycle of less than 5 minutes.

[0018] Furthermore, in step (2), the specific calculation method is as follows:

[0019] P H =H*1.1;

[0020] Where: H is the real-time working head, in meters.

[0021] Furthermore, the specific calculation method for step (3) is as follows:

[0022] Filter historical data and select data from the stable operating range;

[0023] Divide the head into x segments and the guide vane opening into y segments. Each combination of head and guide vane opening constitutes a working condition, resulting in a total of x*y = n working conditions. Calculate the median tailwater pressure fluctuation under each working condition, denoted as P. median 1, P median 2, P median 3.....P median n;

[0024] P T n = P median n*1.5;

[0025] Where: P T n is the upper limit threshold of tailwater pressure pulsation under each operating condition, where n represents each operating condition.

[0026] Furthermore, in step (4): T1 is reset to zero at regular intervals, when the real-time value P ≥ P H Start accumulating the runtime to obtain T1.

[0027] Furthermore, the characteristic feature is that, in step (5), the specific method is as follows:

[0028] Data from the stable operating range was selected for calculation;

[0029] T2 timer resets to zero when the real-time pressure pulsation measurement value P ≥ P T n, where P T n represents the upper limit threshold of pressure pulsation corresponding to the current operating condition. Start accumulating the running time to obtain T2.

[0030] The present invention also relates to a computer system, including a collector, a memory, a processor, and a computer program on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above method.

[0031] The present invention also relates to an electronic device, including a memory, a processor, and a computer program on the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above method.

[0032] The present invention also relates to a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0034] 1. Currently, the tailwater pressure pulsation is set with a fixed limit. During start-up and shutdown, the unit often experiences false alarms when passing through a low-load zone or when the load is adjusted too quickly, which affects the monitoring and judgment of operation and maintenance personnel. This invention determines the cumulative running time after exceeding the limit, thus avoiding false alarms.

[0035] 2. Under different heads and guide vane openings, the tailrace pressure pulsations of a hydro-generator vary, resulting in different stresses on the runner. Dynamic limits should be set based on the head and guide vane opening. The two limits calculated in this invention are both dynamic limits, automatically generated according to the current operating conditions, and are more consistent with the actual situation of the unit.

[0036] 3. This invention takes into account both the pressure pulsation limit calculated based on water head as stipulated in industry standards and the pressure pulsation limit calculated based on the historical data of the unit. Exceeding either limit may trigger an early warning, thus realizing intelligent early warning of tailwater pressure pulsation, which is the first of its kind in the industry.

[0037] 4. This invention can be implemented using various data analysis tools and programming tools, which is conducive to mobilizing professional and technical personnel to carry out research work based on it. With slight modifications, it can also be applied to other types of water turbines. Attached Figure Description

[0038] Figure 1 This is a system block diagram according to an embodiment of the present invention. Detailed Implementation

[0039] The technical solutions in this embodiment will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some examples of the present invention, and not all examples. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0040] Those skilled in the art will understand that the following embodiments are for illustrative purposes only and should not be construed as limiting the scope of the invention. Where specific techniques or conditions are not specified in the embodiments, they are performed in accordance with the techniques or conditions described in the literature in the field or according to the product instructions. Materials or equipment whose manufacturers are not specified are all conventional products that can be obtained by purchase.

[0041] Example 1

[0042] The intelligent early warning method for pressure pulsation in mixed-flow turbines in this embodiment includes the following steps:

[0043] Step (1) Collect and store real-time data of pressure pulsation P (unit: kPa), working head H (unit: m), and guide vane opening D (unit: %) of the tailrace cone of the mixed-flow turbine.

[0044] Data on tailrace cone pressure pulsation, working head, and guide vane opening are stored simultaneously with consistent time coordinates and a data acquisition cycle of less than 5 minutes.

[0045] Step (2) Calculate the pressure pulsation head limit of the tailrace cone, denoted as P. H The specific method is as follows:

[0046] P H =H*1.1.

[0047] Where: H is the real-time working head, in meters.

[0048] Step (3) Based on historical data, select data under stable operating conditions, calculate the upper limit threshold of tailwater pressure fluctuation under each operating condition, and denot it as P. T n (n = 1, 2, 3, 4, 5....), the specific method is as follows:

[0049] 3.1 Select data from the stable operating area for calculation.

[0050] 3.2 Divide the head into x segments and the guide vane opening into y segments. Each combination of head and guide vane opening constitutes one operating condition, resulting in a total of x*y=n operating conditions. Calculate the median tailwater pressure fluctuation under each operating condition, denoted as P. median 1, P median 2, P median 3.....P median n.

[0051] P T n = P median n*1.5;

[0052] Among them, P T n is the upper limit threshold of tailwater pressure pulsation under each operating condition, where n represents each operating condition.

[0053] Step (4) Calculate the pressure pulsation super P in the tailrace cone based on real-time data. H Cumulative runtime T1.

[0054] The specific method is as follows:

[0055] T1 can be set to be reset to zero at 00:00 every day, when the real-time value P≥P H Start accumulating the runtime to obtain T1.

[0056] Step (5) Calculate the pressure pulsation super P in the tailrace cone based on real-time data. T n. Cumulative runtime T2.

[0057] The specific method is as follows:

[0058] T2 can be set to be reset at 00:00 every day, when the real-time pressure pulsation measurement value P≥P T n(P T n represents the upper limit threshold of pressure pulsation corresponding to the current operating condition), and the running time is accumulated to obtain T2.

[0059] Step (6) When the intelligent early warning conditions are met, an early warning signal is output. The specific method is as follows:

[0060] When T1 ≥ the first time setpoint (20 minutes) or T2 ≥ the second time setpoint (2 minutes), an abnormal pressure pulsation warning will be issued. If T1 ≥ the first time setpoint, the output will be: The unit has timed out under adverse operating conditions.

[0061] T2 ≥ Second time setpoint, output: Unit pressure pulsation deteriorates.

[0062] As a specific application:

[0063] A power plant's Unit 2 turbine operated under adverse conditions for an extended period. In April, an intelligent early warning system for tailrace pressure pulsation was issued, indicating that "Unit 2 has exceeded the time limit for operation under adverse conditions." However, no improvements were made to the unit's operating conditions, and it continued operating until May. At that point, a core component was damaged, and the pressure pulsation worsened, triggering the "Unit 2 has exceeded the time limit for operation under adverse conditions" warning. The process includes the following steps:

[0064] Step (1) Collect and store real-time data on the pressure pulsation P (unit: kPa), working head H (unit: m), and guide vane opening D (unit: %) of the tailrace cone of the mixed-flow turbine, as shown in Table 1 below:

[0065] Table 1

[0066]

[0067] Step (2): Calculate the pressure pulsation head limit of the tailrace cone, denoted as P. H As shown in Table 2 below:

[0068] Table 2

[0069]

[0070]

[0071] Step (3): Based on historical data, calculate the upper limit threshold of tailwater pressure pulsation under each operating condition, denoted as P. T n (n=1, 2, 3, 4, 5....).

[0072] This embodiment uses data from the previous year for calculation, but this can be chosen by the user, as long as it covers the full range of water head, as shown in Table 3:

[0073] Table 3

[0074]

[0075] Step (4): Calculate the pressure pulsation super P in the tailrace cone based on real-time data. H Cumulative runtime T1

[0076] T1 can be set to be reset to zero at 00:00 every day, when the real-time value P≥P H Start accumulating the runtime to obtain T1. As shown in Table 4:

[0077] Table 4

[0078]

[0079]

[0080] When T1 is greater than or equal to the time setpoint 1 (1200 seconds), an abnormal pressure pulsation warning is issued. The alarm system outputs "Unit 2 has timed out under adverse operating conditions" at 20:36:53 on April 27, 2023.

[0081] Step (5): Calculate the pressure pulsation super P in the tailrace cone based on real-time data. T n. Cumulative runtime T2.

[0082] T2 can be set to be reset to zero at 00:00 every day, when the real-time value P≥P T Let n be the runtime, and start accumulating the runtime to obtain T2. ​​See Table 5 for details.

[0083] Table 5

[0084]

[0085]

[0086] When T2 is greater than or equal to the time setpoint 2 (120 seconds), an abnormal pressure pulsation warning is issued. The alarm system outputs "Pressure pulsation of Unit 2 has deteriorated" at 20:18:53 on March 28, 2023.

[0087] Example 2

[0088] As shown in Figure 1, in order to implement the method of Embodiment 1, this embodiment provides a mixed-flow turbine pressure pulsation intelligent early warning system, including a collector, a memory, a processor, a display, and a computer program on the memory and executable on the processor. The collector collects relevant information about the mixed-flow turbine, and the processor executes the computer program to implement the steps of the method of Embodiment 1 described above.

[0089] The processors mentioned above can be general-purpose processors, including central processing units, network processors, etc.; they can also be digital signal processors, application-specific integrated circuits, field-programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0090] Optionally, embodiments of this application also provide a storage medium storing instructions that, when run on a computer, cause the computer to perform the methods described in the above embodiments.

[0091] Optionally, embodiments of this application also provide a chip for executing instructions, the chip being used to execute the methods of the embodiments shown above.

[0092] This application also provides a program product, which includes a computer program stored in a storage medium. At least one processor can read the computer program from the storage medium, and when the at least one processor executes the computer program, it can implement the method of the above embodiments.

[0093] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent early warning of pressure pulsation of a hydraulic turbine, characterized in that, The method comprises the following steps: Step (1) collecting the peak-to-peak value P of the pressure fluctuation of the draft tube of the mixed-flow water turbine, the working water head H, and the guide vane opening D in real time; Step (2) calculates the tail water cone pipe pressure pulsation water head limit value, which is P H The specific calculation method is: P H =H*1.1; Wherein: H is the real-time working water head, unit: meter; Step (3) According to historical data, select stable working condition data, calculate the upper limit threshold of the tail water pressure fluctuation under each working condition, and count as P T n, n = 1, 2, 3, 4, 5…; The specific calculation method is: Screening historical data and selecting data in the stable operation zone; The water head is divided into x sections, the guide vane opening is divided into y sections, the combination of each section of water head and guide vane opening is a working condition, a total of x*y=n working conditions, the median of the tail water pressure fluctuation under each working condition is calculated, and is P median 1, P median 2, P median 3.....P median n; P T n=P median n*1.5; Where: P T n is the upper limit threshold of the tail water pressure fluctuation under each working condition, and n represents various working conditions. Step (4) According to real-time data, calculate the tail water cone pipe pressure pulsation super P H Cumulative running time T1; T1 timing zero, when the real-time value P≥P H , start to accumulate running time, get T1; Step (5) According to real-time data, calculate the tail water cone pipe pressure pulsation super P T n Cumulative running time T2; The specific method is: Selecting data in the stable operation zone for calculation; T2 timing clear, when the real-time pressure pulsation measurement value P≥P T n, wherein P T n represents the upper limit threshold of pressure pulsation corresponding to the current working condition, and the running duration is accumulated to obtain T2; Step (6) when the intelligent early warning condition is met, output the early warning signal, and the intelligent early warning condition is as follows: T1≥the first time constant value or T2≥the second time constant value, and the pressure fluctuation abnormality early warning is performed; T1≥the first time constant value is output: the unit is operated in the adverse condition for too long; T2≥the second time constant value is output: the pressure fluctuation of the unit deteriorates; Wherein, the first time constant value and the second time constant value are set by the user according to the characteristics of the water turbine.

2. The method of claim 1, wherein, In step (1), the pressure fluctuation of the draft tube, the working water head, and the guide vane opening data are stored simultaneously, the time coordinates are consistent, and the data acquisition period is less than 5 minutes.

3. A computer system, characterized by: The device comprises a collector, a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method of any one of claims 1-2 when executing the computer program.

4. An electronic device, comprising: The device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method of any one of claims 1-2 when executing the computer program.

5. A non-transitory computer-readable storage medium, characterized in that: The device has a computer program stored thereon, and the computer program is executed by the processor to implement the steps of the method of any one of claims 1-2.

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