Device for detecting cavitation performance of pump turbine model test based on acousto-optic analysis

Abstract

The utility model discloses a device for detecting cavitation performance of a pump turbine model test based on acousto-optic analysis, which comprises a pump turbine model test bed (1), and the pump turbine model test bed (1) is respectively connected with an optical image acquisition module (2) and a multi-channel integrated acoustic emission acquisition module (3). The system further comprises a signal processing module (4), the input end of the signal processing module (4) is connected with the pump turbine model test bed (1), the optical image acquisition module (2) and the multi-channel integrated acoustic emission acquisition module (3), and the output end of the signal processing module (4) is provided with a display terminal (5). The utility model has the characteristic that the cavitation bubble image and the bubble breaking sound of the water turbine can be effectively and accurately acquired.

Description

Technical Field

[0001] The utility model relates to the field of water pump turbine model test in the direction of pumped storage power generation, in particular to a detection device for cavitation performance of water pump turbine model test based on acoustic and optical analysis. Background Art

[0002] With the continuous development of pumped storage, the requirements for unit equipment are increasing day by day, and the overall performance of the unit has become crucial. The high-precision and high-quality pump-turbine runner is the core of the unit. Therefore, the real machine can only be put into production after the pump-turbine model test has passed the inspection. After years of development, the pump-turbine model test bench has become mature, but there are not many methods for detecting cavitation performance. It still remains in the traditional observation or recording through ordinary cameras. There are situations that cannot be recorded, and there is no timely feedback and the observation error is very large. When it cannot be observed or photographed, it can only be judged by listening to the sound. The noise caused by the rotation of the model unit makes it impossible to distinguish the sound of bubble bursting. Therefore, it is urgent to develop a pump-turbine model test cavitation performance detection device that can effectively and accurately collect turbine cavitation bubble images and bubble burst sounds to meet the use needs. Utility Model Content

[0003] The purpose of the utility model is to provide a detection device for cavitation performance of a pump turbine model test based on acoustic and optical analysis. The utility model has the characteristics of being able to effectively and accurately collect the cavitation bubble image and bubble burst sound of the turbine.

[0004] The technical solution of the utility model is as follows: a detection device for cavitation performance of a pump-turbine model test based on acoustic-optical analysis, comprising a pump-turbine model test bench, the pump-turbine model test bench being respectively connected with an optical image acquisition module and a multi-channel integrated acoustic emission acquisition module; and also comprising a signal processing module, the input end of the signal processing module being respectively connected with the pump-turbine model test bench, the optical image acquisition module and the multi-channel integrated acoustic emission acquisition module, and the output end of the signal processing module being provided with a display terminal.

[0005] In the aforementioned detection device for cavitation performance of pump-turbine model test based on acoustic-optical analysis, the optical image acquisition module includes a group of phased array CCD image sensors distributed in a ring on the outer edge of the pump-turbine model test bench, the phased array CCD image sensor is connected to a high-definition picosecond image rapid imaging unit, and the high-definition picosecond image rapid imaging unit is connected to the signal processing module.

[0006] In the aforementioned detection device for cavitation performance of pump-turbine model test based on acoustic and optical analysis, the multi-channel integrated acoustic emission acquisition module includes a low-frequency probe located on the side of the pump-turbine model test bench, the low-frequency probe is connected to a signal amplifier, the signal amplifier is connected to a signal acquisition processing unit, the signal acquisition processing unit is connected to a filtering analysis unit, and the filtering analysis unit is connected to the signal processing module.

[0007] Compared with the prior art, the utility model uses an optical image acquisition module to capture the image of the bubble generation process on the runner blades of the pump turbine model, and uses a multi-channel integrated acoustic emission acquisition module to collect the sound wave changes caused by the bubble bursting on the blades, and collects the operating conditions of the model test bench at this time, so that the turbine bubble image can be effectively and accurately collected and the bubble bursting sound can be identified and collected, thereby avoiding the problems of the traditional method that the situation cannot be recorded, the feedback cannot be given in time, the observation error is very large, and the noise caused by the rotation of the model unit makes it impossible to distinguish the sound of the bubble bursting. Through the mutual cooperation between the above-mentioned structures, the present application can capture the bubble generation with high accuracy and fast speed, capture the bubble burst analysis accurately, and the test results are highly reliable and referential, and can be widely used in the cavitation performance detection of pump turbine model tests.

[0008] In summary, the utility model has the characteristics of being able to effectively and accurately collect the cavitation bubble images and bubble burst sounds of the turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a flow chart of the detection method of the utility model;

[0010] Figure 2 This is a schematic diagram of the flow field model of the water pump turbine model test bench of the utility model;

[0011] Figure 3 It is a structural view of the detection device of the utility model;

[0012] Figure 4 This is a schematic diagram of the optical image acquisition module of the utility model;

[0013] Figure 5 It is a schematic diagram of a multi-channel integrated acoustic emission device in an embodiment of the utility model.

[0014] The markings in the accompanying drawings are: 1-pump turbine model test bench, 2-optical image acquisition module, 3-multi-channel integrated acoustic emission acquisition module, 4-signal processing module, 5-display terminal, 101-phased array CCD image sensor, 102-high-definition picosecond image fast imaging unit, 301-low-frequency probe, 302-signal amplifier, 303-signal acquisition and processing unit, 304-filtering and analysis unit. DETAILED DESCRIPTION

[0015] The present invention is further described below in conjunction with the accompanying drawings and embodiments, but they are not intended to limit the present invention.

[0016] Embodiment 1. A detection device for cavitation performance of a pump-turbine model test based on acoustic-optical analysis, comprising: Figure 3 As shown, it includes a pump-turbine model test bench 1, which is respectively connected to an optical image acquisition module 2 and a multi-channel integrated acoustic emission acquisition module 3; it also includes a signal processing module 4, the input end of the signal processing module 4 is respectively connected to the pump-turbine model test bench 1, the optical image acquisition module 2 and the multi-channel integrated acoustic emission acquisition module 3, and the output end of the signal processing module 4 is provided with a display terminal 5.

[0017] like Figure 4 As shown, the optical image acquisition module 2 includes a group of phased array CCD image sensors 101 distributed in an annular manner on the outer edge of the pump-turbine model test bench 1, and the phased array CCD image sensor 101 is connected to a high-definition picosecond image rapid imaging unit 102, and the high-definition picosecond image rapid imaging unit 102 is connected to the signal processing module 4.

[0018] like Figure 5 As shown, the multi-channel integrated acoustic emission acquisition module 3 includes a low-frequency probe 301 located on the side of the pump-turbine model test bench 1, the low-frequency probe 301 is connected to a signal amplifier 302, the signal amplifier 302 is connected to a signal acquisition processing unit 303, the signal acquisition processing unit 303 is connected to a filtering and analysis unit 304, and the filtering and analysis unit 304 is connected to the signal processing module 4.

[0019] The pump-turbine model test bench can be a general hydraulic machinery test bench.

[0020] The optical image acquisition module is mainly embodied in: the phased array CCD (Charge-coupled Device) image sensor is mainly used to quickly capture the bubble birth process at the first time, and the high-definition picosecond image rapid imaging system outputs the image signal through the HDMI (High Definition Multimedia Interface) transmitter and transmits the signal to the signal processing module using the HDMI (High Definition Multimedia Interface) receiver.

[0021] The multi-channel integrated acoustic emission module mainly includes: through the low-frequency probe (60kHz-excellent for receiving single bubble rupture signals) through the signal amplifier to the signal acquisition and processing unit, filtering out the unit rotation and external noise interference bands, and transmitting to the signal processing module through the band spectrum analysis of the filtering and analysis unit.

[0022] The signal processing module is used to receive and process the bubble image transmitted by the optical image acquisition module and the bubble burst sound transmitted by the multi-channel integrated acoustic emission acquisition module, and display them through the display terminal.

[0023] The pump-turbine model under test is operated in different frequency domain ranges and working conditions. In the operating area with less than the optimal flow rate, the primary cavitation coefficient is defined as the cavitation coefficient corresponding to the appearance of visible bubbles on the surface of two or more runner blades. In the operating area with more than the optimal flow rate, the operating conditions are constantly changed, and the light image acquisition module is used to capture the bubble generation process on the runner blades of the pump-turbine model. At the same time, the multi-channel integrated acoustic emission acquisition module is used to collect the sound wave changes caused by the bubble bursting on its blades; the light image acquisition device uses a phased array CCD (Charge-coupled Device) image sensor to quickly capture the bubble birth process in the first time, and the high-definition picosecond image rapid imaging unit outputs the image signal through the HDMI (High Definition Multimedia Interface) transmitter, and the HDMI (High Definition Multimedia Interface) receiver transmits the signal to the signal processing module.

[0024] The multi-channel integrated acoustic emission acquisition module generates a high-amplitude acoustic emission signal through bubble crushing, which is then transmitted through a low-frequency probe (60kHz - excellent for receiving single bubble burst signals) through a signal amplifier to a signal acquisition processing unit, filtering out the unit rotation and external noise interference bands, and then transmitted to the signal processing module through a filter analysis unit.

[0025] The primary cavitation coefficient is determined by combining sound and light, and the operating conditions of the model test bench are collected at this time. It is determined that cavitation occurs under this condition, thereby judging the cavitation performance of the pump-turbine model.

[0026] Example 2. Pump turbine model test cavitation performance detection method, the process is as follows Figure 1 , including the following steps:

[0027] The test speed is constant at 1000r / min, and the cavitation reference surface is the guide vane centerline. Critical cavitation coefficient σ c The value is σ 0.5 , σ 0.5Refers to the cavitation coefficient when the efficiency is reduced by 0.5% compared with the efficiency under non-cavitation conditions. The cavitation test was started after the test water was pumped for 30 minutes. In the operating area less than the optimal flow rate, the primary cavitation coefficient is defined as the cavitation coefficient corresponding to the appearance of visible bubbles on the surface of 2 or more runner blades. In the operating area greater than the optimal flow rate, the primary cavitation coefficient is determined by combining the acoustic and optical methods. The light image acquisition module is used to capture the bubble generation process on the runner blades of the pump-turbine model. At the same time, the spectrum analysis of the multi-channel integrated acoustic emission acquisition module is used to determine that the bursting of bubbles on the blades causes changes in the sound waves. The primary cavitation coefficient is determined by combining acoustics and light, and the operating conditions of the model test bench at this time are collected. It is determined that cavitation occurs under this condition, and the cavitation performance of the pump-turbine model is judged.

[0028] The cavitation coefficient is calculated as follows: (Z1 and Z2 are Figure 2 (shown)

[0029] Head (lift) H:

[0030]

[0031] Simplify the above formula Get the water head H(m)

[0032] Where: ΔP is the static pressure difference of the pressure measuring section on the inlet and outlet sides, measured by the differential pressure sensor (Pa);

[0033] V1 is the average flow velocity of the inlet pressure measurement section (m / s), V1 = Q / A1 (Q is the test flow rate m 3 / s)

[0034] V2 is the average flow velocity of the outlet pressure measurement section (m / s), V2 = Q / A2 (Q is the test flow rate m 3 / s)

[0035] A1 is the pressure measuring cross-sectional area on the high pressure side (m 2 );

[0036] A2 is the pressure measurement section area of ​​the turbine outlet under working condition (m 2 );

[0037] E is specific water energy (J / kg);

[0038] g is the acceleration due to gravity (m / s 2 ).

[0039] Cavitation coefficient σ:

[0040]

[0041] Simplify the above two equations: NPSE is the net positive suction specific energy; Pm is the tail water measurement pressure (Pa); P amb is the atmospheric pressure of the test bench (Pa); P va is the vaporization pressure under actual water temperature (Pa); Zc is the elevation of cavitation reference surface (guide vane centerline) (m), where Zc=Zr; Zm is the installation elevation of tail water pressure sensor (m); H is the test net water head / lift (m); V2 is the average flow velocity of the outlet pressure measuring section (m / s).

[0042] When the model test bench operates under conditions higher or lower than the optimal flow rate, the phased array CCD (Charge-coupled Device) image sensor is used to quickly capture the bubble birth process in the first time. When the system captures two or more bubbles appearing on the runner blades, the operating conditions at this time are recorded. The critical range areas at both ends are the optimal operating areas, and the areas outside the range are the cavitation areas. The cavitation performance is determined by this flow range.

[0043] When the model test bench operates under conditions higher than or lower than the optimal flow rate, a high-amplitude acoustic emission signal is generated by capturing the bubble collapse on the runner blades. When the system captures two or more bubbles breaking on the runner blades, the operating conditions at this time are recorded. The critical range areas at both ends are the optimal operating areas, and the areas outside the range are the cavitation areas. The cavitation performance is determined by this flow range.

Claims

1. A device for detecting cavitation performance of a pump-turbine model test based on acoustic and optical analysis, characterized in that: The invention comprises a water pump turbine model test bench (1), wherein the water pump turbine model test bench (1) is respectively connected to an optical image acquisition module (2) and a multi-channel integrated acoustic emission acquisition module (3); and further comprises a signal processing module (4), wherein the input end of the signal processing module (4) is respectively connected to the water pump turbine model test bench (1), the optical image acquisition module (2) and the multi-channel integrated acoustic emission acquisition module (3), and the output end of the signal processing module (4) is provided with a display terminal (5).

2. The detection device for cavitation performance of a pump-turbine model test based on acoustic-optical analysis according to claim 1 is characterized in that: The optical image acquisition module (2) comprises a group of phased array CCD image sensors (101) distributed in an annular manner on the outer edge of the pump-turbine model test bench (1), the phased array CCD image sensor (101) being connected to a high-definition picosecond image rapid imaging unit (102), and the high-definition picosecond image rapid imaging unit (102) being connected to a signal processing module (4).

3. The detection device for cavitation performance of a pump-turbine model test based on acoustic-optical analysis according to claim 1 is characterized in that: The multi-channel integrated acoustic emission acquisition module (3) comprises a low-frequency probe (301) located on the side of the pump-turbine model test bench (1); the low-frequency probe (301) is connected to a signal amplifier (302); the signal amplifier (302) is connected to a signal acquisition processing unit (303); the signal acquisition processing unit (303) is connected to a filtering and analyzing unit (304); and the filtering and analyzing unit (304) is connected to the signal processing module (4).

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