Motor Intelligence Versus Vibration Analysis for Early-Stage Diagnosis of Electric Submersible Pumps

2021 ◽  
Author(s):  
Amir Badkoubeh ◽  
Francisco E. Trevisan
Keyword(s):  
Condition Monitoring ◽  
Vibration Analysis ◽  
Early Stage ◽  
Analysis Method ◽  
Flow Loop ◽  
Variable Frequency Drive ◽  
Interesting Insight ◽  
Application Condition ◽  
Electric Machinery ◽  
Scale Down

Abstract The main objective of this paper is to investigate the condition monitoring based on electric signature analysis for electric submersible pumps (ESPs) as introduced in our previous paper, SPE-201169-MS. While an ESP core physical concept is similar to other rotary electric machinery, they have unique features which make their selection, installation and operation different than typical rotating equipment applications. For the purpose of this study, a scale-down ESP system and flow loop was utilized to replicate an actual ESP application. Condition monitoring of the ESP was completed with mechanically and electrically induced vibrations and compare the results vis-à-vis those obtained by a common vibration analysis method. Furthermore, by running the ESP at various operation points, we show how the mechanical and electrical efficiency of the pump, induction motor and variable frequency drive are intertwined. This observation may suggest an interesting insight for further discussion on ESP optimization.

Research on transformer vibration monitoring and diagnosis based on Internet of things

2021 ◽  
Vol 30 (1) ◽  
pp. 677-688
Author(s):  
Zhenzhuo Wang ◽  
Amit Sharma
Keyword(s):  
Internet Of Things ◽  
Power Distribution ◽  
Vibration Analysis ◽  
Vibration Monitoring ◽  
Power Transformers ◽  
Normal Operation ◽  
Analysis Method ◽  
Power Distribution Network ◽  
Monitoring And Diagnosis ◽  
Distribution Transformers

Abstract A recent advent has been seen in the usage of Internet of things (IoT) for autonomous devices for exchange of data. A large number of transformers are required to distribute the power over a wide area. To ensure the normal operation of transformer, live detection and fault diagnosis methods of power transformers are studied. This article presents an IoT-based approach for condition monitoring and controlling a large number of distribution transformers utilized in a power distribution network. In this article, the vibration analysis method is used to carry out the research. The results show that the accuracy of the improved diagnosis algorithm is 99.01, 100, and 100% for normal, aging, and fault transformers. The system designed in this article can effectively monitor the healthy operation of power transformers in remote and real-time. The safety, stability, and reliability of transformer operation are improved.

On the use of jerk and snap in condition monitoring of machinery – review and case studies

2021 ◽  
Vol 63 (8) ◽  
pp. 457-464
Author(s):  
S Lahdelma
Keyword(s):  
Condition Monitoring ◽  
Large Scale ◽  
Early Stage ◽  
Time Derivative ◽  
Additional Insight ◽  
Rolling Bearings ◽  
Monitoring Applications ◽  
Derivatives Of ◽  
Insight Into ◽  
Peak Value

The time derivatives of acceleration offer a great advantage in detecting impact-causing faults at an early stage in condition monitoring applications. Defective rolling bearings and gears are common faults that cause impacts. This article is based on extensive real-world measurements, through which large-scale machines have been studied. Numerous laboratory experiments provide additional insight into the matter. A practical solution for detecting faults with as few features as possible is to measure the root mean square (RMS) velocity according to the standards in the frequency range from 10 Hz to 1000 Hz and the peak value of the second time derivative of acceleration, ie snap. Measuring snap produces good results even when the upper cut-off frequency is as low as 2 kHz or slightly higher. This is valuable information when planning the mounting of accelerometers.

Oscillation analysis of numerical solution of Nonlinear Operator Equation

2021 ◽  
Vol 7 (5) ◽  
pp. 2111-2126
Author(s):  
Yang Zhou ◽  
Cuimei Li
Keyword(s):  
Numerical Solution ◽  
Operator Equation ◽  
Vibration Analysis ◽  
Nonlinear Operator ◽  
Vibration Spectrum ◽  
Nonlinear Operator Equation ◽  
Analysis Method ◽  
Analysis Model ◽  
Oscillation Analysis ◽  
Analysis Equation

There is a problem of low accuracy in the analysis of the vibration of the numerical solution of the nonlinear operator equation. In this work, the vibration analysis equation is constructed by the step-by-step search method, and the vibration quadrant of the equation is divided by the dichotomy method. The vibration spectrum is determined by the iteration method, and the vibration analysis model of the numerical solution of the nonlinear operator equation is constructed. The vibration analysis of the numerical solution of the nonlinear operator equation is completed based on the solution of the model and the numerical calculation and display of the step-by-step Fourier. The experimental results show that the proposed method has higher accuracy than the traditional vibration analysis method, which meets the requirements of the vibration analysis of the numerical solution of nonlinear operator equation.

An analysis method to determine how changes in dynamic complexity impact on rotor-bearing systems

2020 ◽  
pp. 095440622095488
Author(s):  
Mian Jiang ◽  
Shuangqi Liu ◽  
Yuhua Wang
Keyword(s):  
Condition Monitoring ◽  
Lubricating Oil ◽  
Analysis Method ◽  
Dynamic Complexity ◽  
Rotor Systems ◽  
Methodological Choices ◽  
Rotor Bearing ◽  
Nonlinearity Measures ◽  
Monitoring Performance ◽  
Bearing System

Condition monitoring performance and diagnosis of rotor-bearing systems depend not only on the methods used, but also on the dynamic complexity of the system itself. Thus, it is important to analyze how changes in parameters under various working conditions impact on dynamic complexity. Most of previous research efforts on this topic have been focused on the analysis of nonlinear dynamics of rotor-bearing systems with different parameters. In this paper, a nonlinearity quantification based analysis method is presented to determine how parameter dynamics impact the complexity of rotor-bearing systems. The dynamic complexity of rotor system is estimated using defined nonlinearity measures. To validate this method, a sliding rotor-bearing system with a loose pedestal is used. The estimates (nonlinearity degrees) and the states of motion are matched with increasing rotational speeds. It is then investigated, how the eccentricities, lubricating oil viscosities, and bearing clearances impacted the dynamic complexity at several critical rotational speeds. These results can guide methodological choices for condition monitoring and diagnosis of rotor systems.

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