Unsteady characteristics analysis of centrifugal pump operation based on motor stator current

Sun, Hao; Yuan, Shouqi; Luo, Yin; Guo, Yihang; Yin, Jiangnan

doi:10.1177/0957650917710554

Cited by 8 publications

(4 citation statements)

References 13 publications

(18 reference statements)

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“…2 However, at present, it is quite common to find centrifugal pumps fail to operate under their optimal operation conditions in the industry, 3 which would bring unpredictable waste of resources and hidden safety troubles. 4 Thus, an effective operation condition detection method for centrifugal pump seems extremely necessary for operational reliability, and such method could also enable the timely remedial measures to be taken to improve the efficiency for energy savings. 5…”

Section: Introductionmentioning

confidence: 99%

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Research on the operation condition indicator for centrifugal pump based on sensorless monitoring technology

Luo

Han

Zhang

2020

Proceedings of the Institution of Mechanical Engineers, Part E:

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A centrifugal pump operates under off-design operation conditions would lead to flow instability, additional energy loss or mechanical damage. Early detection is of great importance to its operation efficiency and safety. Sensorless monitoring technology based on motor current signature analysis (MCSA) is a cost-effective and non-intrusive technology to monitor motor-driven devices. However, existing researches on MCSA for centrifugal pump usually realize their monitoring function through complicated time-frequency or energy analysis, they stop short of an indicator that has less calculation cost and definite physical significance compatible with the pump’s operation condition. In response to the limitations, this paper aimed at establishing such indicator for centrifugal pump based on MCSA. Theoretical analysis, CFD simulation and experiments were conducted to study the characteristics of pump torque and motor stator current, whose results suggest that the torque fluctuation frequency characteristics would be transmitted to motor stator current by electromagnetic coupling effect, and distribute as sidebands in current spectrum through power frequency modulation. As a result, torque disturbance caused by off-design operation would be reflected as stronger harmonic and noise distortion of motor stator current, and the distortion intensity could be quantified and employed as the operation condition indicator (OCI) for centrifugal pump. Experimental results show that the OCI has its lowest value under the design operation condition, and gradually increases as the pump’s operation condition getting worse. Such change law agrees well with the efficiency characteristics of centrifugal pump, which provides a new thought for the operation monitoring of centrifugal pump based on MCSA. The proposed indicator could be directly obtained from the current signal and easily calculated, which is more appropriate for application and probably more preferred for industry compared to the former operation monitoring methods.

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Section: Introductionmentioning

confidence: 99%

“…In 2017, Hui Sun et al. 4 employed the Hilbert-Huang Transform method and the Singular Value Decomposition method to the analysis of motor stator current for centrifugal pump. The results show that the Hilbert marginal spectrum of motor stator current energy could depict the operation stability of centrifugal pump to some extent.…”

Section: Introductionmentioning

confidence: 99%

Research on the operation condition indicator for centrifugal pump based on sensorless monitoring technology

Luo

Han

Zhang

2020

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…Faults of electrical rotating motors (stator faults, rotor faults, broken rotor bar, ring cracking, bearing failures, rotor shaft failure, air-gap irregularities, broken teeth on sprocket) can be diagnosed by vibration [1][2][3][4][5][6][7][8][9][10][11][12] and acoustic signals [13][14][15][16][17][18][19][20][21][22]. Electric current analysis [23][24][25][26][27][28][29][30][31] and thermal analysis [32][33][34] are mostly used for limited faults, such as stator faults, rotor faults, and bearing failures. Acoustic signals are difficult to process, because they are very noisy (for example, several operating motors generate many acoustic signals).…”

Section: Introductionmentioning

confidence: 99%

Acoustic-Based Fault Diagnosis of Commutator Motor

Głowacz

2018

Electronics

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In the paper, the author presents acoustic-based fault diagnosis of a commutator motor (CM). Five states of the commutator motor were considered: healthy commutator motor, commutator motor with broken rotor coil, commutator motor with shorted stator coils, commutator motor with broken tooth on sprocket, commutator motor with damaged gear train. A method of feature extraction MSAF-15-MULTIEXPANDED-8-GROUPS (Method of Selection of Amplitudes of Frequency Multiexpanded 8 Groups) was described and implemented. Classification methods, such as nearest neighbour (NN), nearest mean (NM), self-organizing map (SOM), backpropagation neural network (BNN) were used for acoustic analysis of the commutator motor. The paper provides results of acoustic analysis of the commutator motor. The results had a good recognition rate. The results of acoustic analysis were in the range of 88.4–94.6%. The NM classifier and the MSAF-15-MULTIEXPANDED-8-GROUPS provided TERCM = 94.6%.

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“…12,13 Motor current signature analysis (MCSA) technology was utilized in operation detection and impeller crack diagnosis of centrifugal pumps, which could provide reference for cavitation prediction. 14,15 Intensive vibration signals induced by cavitation could inversely reflect the characteristics of the fault. 16,17…”

Section: Introductionmentioning

confidence: 99%

Characterization of cavitation and seal damage during pump operation by vibration and motor current signal spectra

Sun

Yuan

Luo

2018

Proceedings of the Institution of Mechanical Engineers, Part A:

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Cyclic spectral analysis is conducted to extract the frequency characteristic components from nonstationary current signals under cavitation and seal damage conditions as indicators of fault characterization. Specifically, vibration and current signals are both acquired and pre-processed by envelope extraction and singular value decomposition methods, respectively. Since there are more noise waves in vibration power spectral density spectra in comparison with current signals, the cyclic spectral analysis is conducted for the current signal analysis. Cyclic autocorrelation functions of signals are firstly calculated then corresponding slices are extracted from the cyclic autocorrelation functions and processed by fast Fourier transform method. Consequently from the spectra, indicators for characterization are extracted to demonstrate the occurrence and severity of faults. Results show that the rotating frequency component shows obvious tendency as the flow rate deviates from the designed point without any faults. The indicators for seal damage characterization are 250 Hz and 350 Hz frequency components related with rotating frequency and blade passing frequency in the current signals. Meanwhile, the occurrence and development status of cavitation are indicated by the frequency component of 100 Hz in the slice spectra of cyclic autocorrelation functions. Additionally, the effect of instability caused by off-design, seal damage, as well as cavitation operation conditions is distinguished by cyclic spectral analysis. Characteristic components are innovatively extracted at specific frequencies to avoid the effect from modulated and noise components in the current signals. And the results about the recognition of different types of faults could provide important evidences for fault detection during pump operation.

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Unsteady characteristics analysis of centrifugal pump operation based on motor stator current

Cited by 8 publications

References 13 publications

Research on the operation condition indicator for centrifugal pump based on sensorless monitoring technology

Research on the operation condition indicator for centrifugal pump based on sensorless monitoring technology

Acoustic-Based Fault Diagnosis of Commutator Motor

Characterization of cavitation and seal damage during pump operation by vibration and motor current signal spectra

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