Method for realizing state monitoring and fault diagnosis of water turbine based on chaos theory
A chaos theory and turbine technology, applied in the fields of hydropower generation, mechanical equipment, engine components, etc., can solve the problem of difficulty in diagnosing cavitation faults of hydraulic turbines, and achieve the effect of improving safety, service life and system stability.
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specific Embodiment approach 1
[0070] Specific implementation mode 1: Combination figure 1 , figure 2 To explain this embodiment, the method for realizing the state monitoring of a hydraulic turbine based on chaos theory in this embodiment uses a turbine state monitoring device including a pressure sensor 1, a signal amplifier 2, a data collector 3, and an upper computer 4; the pressure sensor 1 is set in In the draft tube area of the hydraulic turbine, the signal output end of the pressure sensor 1 is connected to the signal input end of the signal amplifier 2, the signal output end of the signal amplifier 2 is connected to the signal input end of the data collector 3, and the signal output of the data collector 3 The terminal is connected with the signal input terminal of the host computer 4;
[0071] The specific steps of the method of realizing the state monitoring of the turbine based on the chaos theory are:
[0072] Step 1: Pressure sensor 1 monitors the turbine draft tube data;
[0073] Step 2: Obtain ...
specific Embodiment approach 2
[0084] Specific implementation manner two: combination image 3 This embodiment is described. The difference between this embodiment and the specific embodiment 1 is that the pressure sensor 1 is arranged outside the draft tube elbow in step 1.
[0085] Such as image 3 As shown, in this embodiment, the pressure sensor 1 is set at the third draft 3 of the monitoring point. When the water flows out from the runner outlet, it will have a greater impact on the outer wall surface of the elbow. On the outside of the draft tube elbow, the lowest frequency pressure pulsation The amplitude of is the largest, and the characteristic phenomenon of cavitation is obvious.
specific Embodiment approach 3
[0086] Specific embodiment three: This embodiment is different from specific embodiments one or two in that the sampling frequency of the pressure pulsation signal in step two is 4000 Hz.
[0087] The pressure pulsation signal sampling frequency is set to 4000Hz to collect all the pressure pulsation data of the turbine, and it can avoid the interference of the cavitation phenomenon on the pressure sensor sampling results.
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