Determination method and program, and information processing system

Abstract

To enable detection of foreign objects getting stuck or accumulating in the turbines used for power generation. [Solution] This determination method includes the steps of (A) acquiring acoustic data of acoustic signals acquired around a hydroelectric turbine, and (B) determining whether or not foreign objects are stuck in or accumulated on the hydroelectric turbine by at least one of the following: an index value obtained from the acoustic data that represents the degree of acoustic fluctuation, and whether or not the relationship between the modulation peak frequency obtained from the acoustic data and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions.

Description

Technical Field

[0001] The present invention relates to a technique for estimating abnormalities in a water turbine for hydroelectric power generation.

Background Art

[0002] Foreign substances such as driftwood, dust, and stones may flow into a reaction turbine for hydroelectric power generation (for example, Francis turbine, Kaplan turbine, valve turbine, etc.), which is a prime mover of a synchronous generator, from an upstream river. When a foreign object is caught between the blades of the turbine or accumulates around the blades, a water flow obstruction occurs, resulting in a decrease in the turbine output. For restoration, the turbine equipment must be stopped, the water drained, and the foreign object removed. There is a problem that the longer the period from the occurrence of the water flow obstruction to the completion of restoration, the more the power generation opportunity is lost, and the equipment operation rate decreases. Therefore, it is required to detect early the jamming or accumulation of foreign objects in the turbine.

[0003] On the other hand, for example, in Non-Patent Document 1, in order to detect various abnormal phenomena occurring in a turbine generator, a method focusing on the magnitude of the peak of the vibration amplitude and a method of identifying a frequency component having an amplitude amount larger than a reference as an abnormal vibration frequency, and diagnosing which abnormal phenomenon (including phenomena such as foreign object biting into the guide vane and foreign object mixing into the runner) is occurring according to what frequency the abnormal vibration frequency matches have been proposed.

[0004] Also, for example, in Patent Document 1, in order to detect an abnormality in a bearing included in a rotating mechanism, a first sound quality index including loudness, sharpness, roughness, and fluctuation intensity is calculated for each sampling period using the sound pressure of environmental sound including the sound emitted by the rotating mechanism, and a technique for detecting an abnormality from the time change of the first sound quality index is disclosed.

[0005] Furthermore, for example, Patent Document 2 discloses a technique for diagnosing abnormalities in a continuous casting machine as a low-speed rotating machine. This technique involves converting the vibration of the low-speed rotating machine into an electrical vibration detection signal, performing a bandpass filter on the vibration detection signal to extract a specific band component representing the abnormal state of the machine to be diagnosed, calculating the crest ratio of the extracted specific band component, calculating the crest ratio of the calculated crest ratio, and comparing the crest ratio of the calculated crest ratio with a preset threshold. If a peak exceeding the threshold occurs, an abnormality is diagnosed.

[0006] It is unclear whether the technologies disclosed in the two patent documents can be applied to detecting foreign matter lodged or accumulated in water turbines. Furthermore, while Non-Patent Document 1 describes the detection of foreign matter jamming in guide vanes and foreign matter contamination in runners, it uses the same abnormal vibration frequency for other abnormal phenomena as well, and it is unclear whether this is the optimal indicator for the problem of detecting foreign matter lodged or accumulated in power generation water turbines. [Prior art documents] [Patent Documents]

[0007] [Patent Document 1] Japanese Patent Publication No. 2013-221741 [Patent Document 2] Japanese Patent Application Publication No. 6-323899 [Non-patent literature]

[0008] [Non-Patent Document 1] Yasushi Sugo, Hideaki Koike, and Keiichiro Shibano, "Development of a Simple Anomaly Diagnosis Device for Hydroelectric Generators," Koei Forum No. 9 / 2001.1, pp. 57-62. [Overview of the project] [Problems that the invention aims to solve]

[0009] In one aspect, the object of the present invention is to provide a novel technique for detecting foreign objects getting stuck in or accumulating in a water turbine for power generation. [Means for solving the problem]

[0010] The determination method according to the present invention includes the steps of (A) acquiring acoustic data of acoustic signals acquired around a hydroelectric turbine, and (B) determining whether or not foreign matter is stuck in or accumulated in a hydroelectric turbine by at least one of the following: an index value obtained from the acoustic data that represents the degree of acoustic fluctuation, and whether or not the relationship between the modulation peak frequency obtained from the acoustic data and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions. [Effects of the Invention]

[0011] One aspect of this approach is that it will become possible to properly detect foreign objects getting stuck or accumulating in the turbines used for power generation. [Brief explanation of the drawing]

[0012] [Figure 1] Figure 1 is a diagram showing the configuration of a system according to an embodiment of the present invention. [Figure 2] Figure 2 is a diagram showing the processing flow of the system. [Figure 3] Figure 3 shows the processing flow of the abnormality detection process. [Figure 4] Figure 4 is a diagram illustrating modulation intensity. [Modes for carrying out the invention]

[0013] This embodiment focuses on evaluating acoustic changes caused by foreign matter getting stuck or accumulating in a hydroelectric reaction turbine, specifically the pulsed noise generated during abnormal conditions, and aims to enable appropriate detection of abnormalities based on the characteristic quantities described below.

[0014] Figure 1 shows an overview of the system according to this embodiment. The system according to this embodiment includes a first information processing device 100 located at a hydroelectric power plant, and a second information processing device 300 connected to the first information processing device 100 via a network 1000 and located, for example, at a maintenance base located away from the hydroelectric power plant. A microphone 200 is connected to the first information processing device 100, and the microphone 200 is located, for example, around the draft tube of a water turbine to collect sound. However, it is not limited to the draft tube, and may be located in any location where a similar acoustic signal can be acquired. In addition, the second information processing device 300 may be located in the cloud and accessed from, for example, a personal computer located at a maintenance base located away from the hydroelectric power plant.

[0015] The first information processing device 100 includes an A / D conversion unit 110 that converts an analog acoustic signal obtained from the microphone 200 into digital acoustic data, an acoustic data storage unit 120 that stores the acoustic data which is the output of the A / D conversion unit 110, and a transmission unit 130 that transmits the acoustic data stored in the acoustic data storage unit 120 to the second information processing device 300 via the network 1000 at predetermined intervals.

[0016] The second information processing device 300 includes a receiving unit 310, an acoustic data storage unit 320, an analysis unit 330, an analysis result storage unit 340, and an output unit 350. The receiving unit 310 stores acoustic data sent from the first information processing device 100 in the acoustic data storage unit 320. The analysis unit 330 performs the analysis processing described below on the acoustic data stored in the acoustic data storage unit 320, determines whether or not there are any abnormalities, and stores the analysis results in the analysis result storage unit 340. The output unit 350 outputs the data stored in the analysis result storage unit 340 to an output device such as a display device, or to another computer connected via a LAN (Local Area Network) or network 1000.

[0017] Next, the processing content of the system shown in FIG. 1 will be described using FIGS. 2 to 4. It is assumed that the water turbine for hydroelectric power generation is already operating in a steady state.

[0018] First, the A / D conversion unit 110 of the first information processing device 100 performs AD (Analog-to-Digital) conversion on the acoustic signal acquired by the microphone 200 to generate acoustic data, and stores the acoustic data in the acoustic data storage unit 120 (FIG. 2: step S1). The transmission unit 130 transmits the acoustic data stored in the acoustic data storage unit 120 to the second information processing device 300 (step S3). This transmission is performed, for example, periodically, but may also be performed at an arbitrary timing in response to a request from the second information processing device 300 side.

[0019] When the reception unit 310 of the second information processing device 300 receives acoustic data from the first information processing device 100, it stores the acoustic data in the acoustic data storage unit 320 (step S5). Then, the analysis unit 330 generates display data of the acoustic waveform from the newly stored acoustic data in the acoustic data storage unit 320 for confirmation by, for example, a manager at a maintenance base far from the hydroelectric power plant, and stores the display data in the analysis result storage unit 340 (step S7). In addition, the analysis unit 330 performs frequency analysis on the newly stored acoustic data in the acoustic data storage unit 320 to generate a spectrogram, and stores the data of the spectrogram in the analysis result storage unit 340 (step S9). The spectrogram is also generated for confirmation by, for example, a manager at a maintenance base.

[0020] Then, the analysis unit 330 performs an abnormality determination process on the newly stored acoustic data in the acoustic data storage unit 320 (step S11). This process will be described using FIGS. 3 and 4.

[0021] The analysis unit 330 calculates an index value representing the degree of acoustic variation for the acoustic data newly stored in the acoustic data storage unit 320 (step S21). This index value is, for example, the crest factor for a specific frequency band. The crest factor, also called the wave crest ratio, is calculated as peak value / RMS value. In this water turbine example, although there is little difference in low-frequency sounds, they have a large impact on sound pressure. Therefore, to bring out more characteristics, the acoustic data in the frequency band between 2000Hz and 24000Hz, which was experimentally determined, is filtered with a bandpass filter before the crest factor is calculated.

[0022] Furthermore, the evaluation value in step S21 may also be the modulation intensity. Modulation intensity represents the degree of variation in a wave whose loudness fluctuates (i.e., an amplitude-modulated wave that repeatedly fluctuates between loud and quiet). Figure 4 shows an example of an acoustic waveform whose amplitude is modulated with a certain modulation period (=1 / modulation peak frequency). If the maximum amplitude is a and the minimum amplitude is b, the modulation intensity m is expressed as follows. m = (ab) / (a ​​+ b) The modulation intensity is m=0 when b=a, i.e., no modulation, and m=1 when b=0, i.e., 100% modulation. The modulation intensity is a value that does not depend on the modulation frequency.

[0023] Furthermore, the evaluation value in step S21 may also be fluctuation strength. Fluctuation strength is a type of modulation strength that emphasizes the modulation component around 4 Hz based on known auditory characteristics. An example of how to calculate this modulation strength is shown in, for example, Alejandro Osses Vecchi et al., "Modelling the sensation of fluctuation strength", PROCEEDINGS of the 22nd International Congress on Acoustics, Sept 2016, so the details will be omitted here.

[0024] In step S21, one or more index values ​​representing the degree of such acoustic fluctuations are calculated. In this water turbine example, it has been confirmed that when foreign objects are stuck in or accumulated on the water turbine, larger values ​​are produced for the band crest factor, modulation intensity, and fluctuation intensity. Appropriate thresholds are set in advance to experimentally distinguish between normal and abnormal conditions for each of these values.

[0025] The analysis unit 330 determines whether the calculated evaluation value exceeds the threshold (step S23). If the evaluation value exceeds the threshold, the analysis unit 330 sets the judgment result to "abnormal" and stores it in the analysis result storage unit 340 (step S31). Then the process returns to the calling process. If multiple evaluation values ​​are calculated, the process proceeds to step S31 if any of the evaluation values ​​exceed the threshold. However, it is also possible to proceed to step S31 only if all evaluation values ​​exceed the threshold.

[0026] On the other hand, if the evaluation value does not exceed the threshold, the analysis unit 330 calculates the modulation peak frequency from the acoustic data newly stored in the acoustic data storage unit 320 (step S25). The analysis unit 330 then determines whether the relationship between the calculated modulation peak frequency and the frequency derived from the rotational speed of the water turbine satisfies predetermined conditions (step S27). In this water turbine example, it has been confirmed that if there is foreign matter stuck in or accumulated on the water turbine, the modulation peak frequency will be equal to or close to the frequency derived from the rotational speed of the water turbine. The frequency derived from the rotational speed of the water turbine is, for example, 8.3 Hz or an integer multiple thereof when the water turbine is rotating at 500 rpm, 12.5 Hz or an integer multiple thereof when the water turbine is rotating at 750 rpm, and 6.25 Hz or an integer multiple thereof when the water turbine is rotating at 375 rpm. The predetermined conditions in step S27 are conditions to indicate that the two are equal to or close to each other, and in some cases a predetermined degree of agreement may be calculated. The degree of agreement can sometimes be expressed as a ratio or difference between the two. Specifically, it determines whether the ratio or difference falls within a certain range.

[0027] If the relationship between the modulation peak frequency and the frequency derived from the turbine's rotation speed satisfies predetermined conditions, the process proceeds to step S31. That is, the determination result is set to "abnormal". On the other hand, if the relationship between the modulation peak frequency and the frequency derived from the turbine's rotation speed does not satisfy predetermined conditions, the analysis unit 330 sets the determination result to "normal" and stores it in the analysis result storage unit 340 (step S29). Then the process returns to the calling process.

[0028] Returning to the explanation of the process in Figure 2, the output unit 350 reads the acoustic waveform display data and spectrogram, as well as the judgment result, from the analysis result storage unit 340 and outputs them to an output device or the like (step S13). For example, a manager at a maintenance base can check the pulse-like noise that occurs during an abnormality using the acoustic waveform and spectrogram, and then, based on the judgment result, determine whether or not maintenance of the water turbine is necessary.

[0029] In this way, based on an evaluation value representing the degree of acoustic fluctuation and the modulation peak frequency, it becomes possible to automatically and appropriately determine whether or not foreign objects are stuck or accumulated in the turbine. If necessary, maintenance can be carried out early, thereby quickly resolving the loss of power generation opportunities.

[0030] Although embodiments of the present invention have been described above, the present invention is not limited thereto. The functional block configuration in Figure 1 is an example and may not match the program module configuration. The processing flows shown in Figures 2 and 3 may also include steps that can be executed in parallel or in a different order, provided that the processing results are the same. Furthermore, while examples of determining abnormalities using a combination of an evaluation value representing the degree of acoustic fluctuation and a modulation peak frequency have been shown, the determination may be made using only one of them. Moreover, an abnormality may be indicated only when all of them, rather than just one, indicate an abnormality.

[0031] Furthermore, the division of functions between the first information processing device 100 and the second information processing device 300 is not limited to what is shown in Figure 1; for example, the first information processing device 100 may include an analysis unit 330. Also, the second information processing device 300 may be implemented as a single device or as multiple devices. Thus, the second information processing device 300 may be constructed as an information processing system realized by one or more devices, and the case of a single device may also be referred to as an information processing system. Moreover, if the first information processing device 100 includes an analysis unit 330, the first information processing device 100 may also be realized by one or more devices, and in such cases, the case of a single device may also be referred to as an information processing system.

[0032] The information processing device 100 or 300 described above is a computer device in which memory, a CPU (Central Processing Unit), a hard disk drive (HDD; sometimes an SSD (Solid State Drive)), a display control unit connected to a display device, a drive unit for removable disks, an input device, and a communication control unit for connecting to a network are connected by a bus. The operating system (OS) and the application program for performing the processing in this embodiment are stored on the HDD and are read from the HDD to memory when executed by the CPU. The CPU controls the display control unit, communication control unit, and drive unit according to the processing content of the application program to perform predetermined operations. Data in the process of processing is mainly stored in memory, but may also be stored on the HDD. In the embodiment of the present invention, the application program for performing the processing described above is stored on a computer-readable removable disk and distributed, and installed on the HDD from the drive unit. It may also be installed on the HDD via a network such as the Internet and the communication control unit. Such computer devices achieve the various functions described above through the organic cooperation of hardware such as the CPU and memory mentioned above, and programs such as the OS and application programs.

[0033] To summarize the embodiment described above, it is as follows:

[0034] The determination method according to this embodiment includes the steps of (A) acquiring acoustic data of acoustic signals acquired around a hydroelectric turbine, and (B) determining whether or not foreign matter is lodged or accumulated in the hydroelectric turbine by at least one of the following: an index value obtained from the acoustic data that represents the degree of acoustic fluctuation, and whether or not the relationship between the modulation peak frequency obtained from the acoustic data and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions. This makes it possible to appropriately detect foreign matter lodged or accumulated in the hydroelectric turbine using such evaluation values ​​and modulation peak frequencies.

[0035] The index values ​​mentioned above may include at least one of the following for a specific frequency band: crest factor, modulation intensity, and fluctuation intensity. These evaluation values ​​can be significantly affected by pulsed noise caused by foreign matter lodged or accumulated in the turbine. The crest factor can be judged more appropriately by limiting it to the frequency band where the characteristics of foreign matter lodged or accumulated in the turbine are emphasized. Note that foreign matter lodged or accumulated in the turbine may also be referred to as the presence of foreign matter near the turbine blades, for example. Of the hydroelectric turbines, reaction turbines for hydroelectric power generation are particularly preferred.

[0036] Furthermore, whether the relationship between the modulation peak frequency obtained from the acoustic data described above and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions may be determined by whether the modulation peak frequency obtained from the acoustic data matches or approximates the frequency derived from the rotational speed of the hydroelectric turbine. For example, if the difference between the two is 0 or within a predetermined range, or if the ratio between the two is 1 or within a predetermined range, the conditions are deemed to be met. The frequency derived from the rotational speed of the turbine is the frequency converted from the rotational speed multiplied by n (where n is an integer of 1 or more).

[0037] Furthermore, a program can be created to perform the above processing, and this program can be stored on a computer-readable storage medium or device such as a flexible disk, optical disk (CD-ROM, DVD-ROM, etc.), magneto-optical disk, semiconductor memory, or hard disk. Intermediate processing results are temporarily stored in a storage device such as main memory. [Explanation of symbols]

[0038] 100 First information processing device 110 A / D conversion unit 120 Audio data storage unit 130 Transmission unit 300 Second information processing device 310 Receiving unit 320 Acoustic data storage unit 330 Analysis unit 340 Analysis result storage unit 350 Output unit

Claims

1. The steps include acquiring acoustic data of acoustic signals obtained around a hydroelectric turbine, A step of determining whether or not foreign matter is lodged or accumulated in the hydroelectric turbine, based on at least one of the following: an index value obtained from the acoustic data that represents the degree of acoustic fluctuation, and whether or not the relationship between the modulation peak frequency obtained from the acoustic data and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions; A determination method that includes this.

2. The aforementioned index value is at least one of the following for a specific frequency band: crest factor, modulation intensity, and fluctuation intensity. The determination method according to claim 1.

3. Whether the relationship between the modulation peak frequency obtained from the aforementioned acoustic data and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions is determined by: The question is whether the modulation peak frequency obtained from the aforementioned acoustic data matches or approximates the frequency derived from the rotational speed of the hydroelectric turbine. The determination method according to claim 1.

4. A program for causing a computer to execute the determination method described in any one of claims 1 to 3.

5. A means for determining whether or not foreign objects are lodged or accumulated in a hydroelectric turbine, based on at least one of the following: an index value obtained from acoustic data of acoustic signals acquired around the hydroelectric turbine and representing the degree of acoustic fluctuation; and whether or not the relationship between the modulation peak frequency obtained from the acoustic data and the frequency derived from the rotational speed of the hydroelectric turbine satisfies predetermined conditions. An information processing system having

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