Fault Diagnosis of Centrifugal Pump and Vibration Control Using Shape Memory Alloy Based ATDVA

2015 ◽  
Vol 787 ◽  
pp. 927-931
Author(s):  
Mouleeswaran Senthilkumar ◽  
M. Yuvaraja ◽  
M. Kok
Keyword(s):  
Fault Diagnosis ◽  
Shape Memory Alloy ◽  
Shape Memory ◽  
Centrifugal Pump ◽  
Vibration Spectrum ◽  
Excitation Frequency ◽  
Centrifugal Pumps ◽  
Pump System ◽  
Vibration Data ◽  
Bearing Defects

Centrifugal pumps are widely used in industry and also domestically. It is commonly used for its robust design and its efficiency. Every machine has to be monitored periodically in order to maintain its efficiency and also to avoid unexpected failure which lead to loss of efficiency. So fault diagnosis is necessary to monitor the pump periodically for finding out the defects in pump and to replace it if necessary. Dismantling and assembling of pumps during fault diagnosis is a tedious process, vibration analysis can be helpful to monitor the performance of the pump system without dismantling. For the experimentation purpose mono-block centrifugal pumps have been used in this work. By using the Lab VIEW program and DAQ card as an interface, amplitude and frequency of vibration is obtained at different axes of the pump with the help of an accelerometer. Then the vibration spectrum is analyzed and defects are pointed out by identifying the frequency at which the amplitude of vibration is above the danger limit. The defects such as unbalance of impeller, bent shaft in pump, misalignment of shaft, hydraulic pulsation, cavitation and bearing defects are diagnosed using vibration data. The frequency at which different defects are occurring has been founded out by means of experimentation in the centrifugal pumps. Thus by diagnosing centrifugal pump using vibration data reduces cost and time for periodical maintenance. Shape memory alloy based ATDVA is used to control the amplitude of vibration due to hydraulic pulsation. Around 60% reduction in amplitude of vibration is evident for the varying excitation frequency between 336 Hz and 340 Hz due to hydraulic pulsation.

Experimental characterization and control of a magnetic shape memory alloy actuator using the modified generalized rate-dependent Prandtl–Ishlinskii hysteresis model

2018 ◽  
Vol 232 (5) ◽  
pp. 506-518 ◽  
Author(s):  
Saeid Shakiba ◽  
Mohammad Reza Zakerzadeh ◽  
Moosa Ayati
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Excitation Frequency ◽  
Hysteresis Loops ◽  
Experimental Results ◽  
Hysteretic Behavior ◽  
Magnetic Shape Memory ◽  
Shape Memory Alloy Actuator ◽  
Rate Dependent ◽  
Magnetic Shape Memory Alloy

In this article, two models are used, namely rate-independent and rate-dependent generalized Prandtl–Ishlinskii, to characterize a magnetic shape memory alloy actuator. The results show that the rate-independent model cannot consider the effect of input excitation frequency, while the rate-dependent model omits this drawback by defining a time-dependent operator. For the first time, the effects of excitation frequency on the hysteretic behavior of magnetic shape memory alloy actuator are investigated. In this study, five excitation voltages with different frequencies in the range of 0.05–0.4 Hz are utilized as inputs to the magnetic shape memory alloy actuator and the displacement outputs are measured. Experimental results indicate that, with increasing the excitation frequency, the size of the hysteresis loops changes. Since the generalized rate-dependent Prandtl–Ishlinskii model cannot consider the asymmetric hysteresis loops, in the developed model, a tangent hyperbolic function is applied as an envelope function in order to improve the capability of the model in characterizing the asymmetric behavior of magnetic shape memory alloy actuator. The parameters of both rate-dependent and rate-independent models are identified by genetic algorithm optimization. The results reveal that the rate-independent form is not capable of accurately describing the hysteretic behavior of magnetic shape memory alloy actuator for different input frequencies. Simulation and experimental results also demonstrate the proficiency of the developed model for precise characterization of the saturated rate-dependent hysteresis loops of magnetic shape memory alloy actuator. In addition, the proposed model is utilized for determining a proper range for controller coefficients during controller design.

Modeling and characterization of the shape memory alloy–based morphing wing behavior using proposed rate-dependent Prandtl-Ishlinskii models

2019 ◽  
Vol 234 (4) ◽  
pp. 550-565 ◽  
Author(s):  
Saeid Shakiba ◽  
Aghil Yousefi-Koma ◽  
Mehdi Jokar ◽  
Mohammad Reza Zakerzadeh ◽  
Hamid Basaeri
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Dead Zone ◽  
Excitation Frequency ◽  
Experimental Results ◽  
Frequency Effect ◽  
Rate Dependency ◽  
Unknown Parameters ◽  
Hysteresis Behavior ◽  
Rate Dependent

Unique features of shape memory alloys make them a proper actuation choice in various control systems. However, their nonlinear hysteresis behavior negatively affects wide utilization of such materials in structure actuation. In this study, the frequency effect on the hysteresis behavior of a shape memory alloy–actuated structure is experimentally investigated, and also two proposed versions of rate-dependent Prandtl-Ishlinskii (modified rate-dependent Prandtl-Ishlinskii and revised modified rate-dependent Prandtl-Ishlinskii) are presented, which are capable of characterizing this phenomenon. Experimental results show that increasing excitation frequency leads to bigger hysteresis loops. It is also proven that rate-dependency cannot be predicted by generalized Prandtl-Ishlinskii model. In addition, a comparison between the dead zone function-based rate-dependent Prandtl-Ishlinskii model as an only benchmark model and the proposed models have been done that proves the proposed models’ superiority. In addition, genetic algorithm is exploited to identify unknown parameters of all models. Trained models performance is also experimentally evaluated at different input frequencies. Comparison between simulation and experimental results indicates that the proposed models can reliably predict saturated, asymmetric, rate-dependent hysteresis behavior, and minor loops in shape memory alloy–embedded actuators.

Steerable Unidirectional Wave Emission From a Single Piezoelectric Transducer Using a Shape Memory Alloy Composite Metasurface

2020 ◽  
Author(s):  
Yihao Song ◽  
Yanfeng Shen
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Excitation Frequency ◽  
Element Model ◽  
Martensite Phase ◽  
Guided Wave ◽  
Ultrasonic Waves ◽  
Unit Cell ◽  
Wave Radiation ◽  
Wave Emission

Abstract Structural Health Monitoring (SHM) and Nondestructive Evaluation (NDE) systems generally adopt piezoelectric transducers which emit omnidirectional wave fields. The achievement of directionality of guided wave generation will benefit the structural sensing purpose, which allows better detection and localization of the damage sites. In this study, a type of metamaterial ultrasonic radar is proposed for the steerable unidirectional wave manipulation. It contains a circular array of unit cells stuck in an aluminum plate which are delicately arranged in a circular fashion. Each unit cell is composed of a shape memory alloy substrate and a lead stub. The controllable bandgap of such metamaterial system can be achieved due to the stiffness change of nitinol between its martensite phase and austenite phase under a thermal load. This research starts with a Finite Element Model (FEM) of the unit cell to compute its frequency-wavenumber domain dispersion characteristics, demonstrating the adjustable bandgap feature. Then, numerical modeling of the metamaterial radar is performed by shifting the bandgap of one sector of the metasurface away from the excitation frequency. The modeling results demonstrate that the martensite phase metasurface area forms a bandgap region where guided wave energy cannot penetrate, while the bandgap of the austenite sector shifts away from the excitation frequency, opening up a transmission path for the ultrasonic waves. By rotating the austenite sector, the metamaterial structure can work like a wave emission radar, realizing of the steerable unidirectional wave radiation with a single transducer. Such an active metasurface possesses great application potential in future SHM and NDE systems.

Development of a frequency-dependent constitutive model for hysteresis of shape memory alloys

2020 ◽  
Vol 234 (12) ◽  
pp. 1535-1549
Author(s):  
Saeid Shakiba ◽  
Aghil Yousefi-Koma ◽  
Moosa Ayati
Keyword(s):  
Shape Memory Alloy ◽  
Constitutive Model ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
High Strain ◽  
Excitation Frequency ◽  
Constitutive Models ◽  
Original Model ◽  
Frequency Effect ◽  
Proposed Model

In this study, a constitutive model based on Liang-Rogers’s relations is developed to characterize the effect of the excitation frequency in the hysteresis of shape memory alloys. Shape memory alloys are good candidates as smart actuators because of their high strain and power density, although the complex hysteresis behavior barricades their usage. Although constitutive models are one of the most potent methods to predict the shape memory alloys behavior, they cannot consider the effect of excitation frequency in active applications. In this paper, the Liang-Rogers model is modified to consider this effect using a linear relation between the excitation frequency and martensite transformation temperatures. A shape memory alloy-driven actuator as a morphing wing is employed to characterize the frequency effect on shape memory alloy hysteresis. Experimental results show that the hysteresis is widened when the excitation frequency increases. The modeling results show that the original model significantly fails to predict the correct behavior when the frequency increases, whereas the proposed model can adequately handle the frequency effect on the behavior of the shape memory alloy-driven actuator.

Development of Hybrid Prandtl–Ishlinskii and Constitutive Models for Hysteresis of Shape-Memory-Alloy-Driven Actuators

Robotica ◽  
2021 ◽  
pp. 1-15
Author(s):  
Saeid Shakiba ◽  
Moosa Ayati ◽  
Aghil Yousefi-Koma
Keyword(s):  
Shape Memory Alloy ◽  
Constitutive Model ◽  
Shape Memory ◽  
Hybrid Model ◽  
Volume Fraction ◽  
Excitation Frequency ◽  
Constitutive Models ◽  
Driven Systems ◽  
Hysteresis Behavior ◽  
First Case

SUMMARY Prandtl–Ishlinskii (PI) model has an excellent compromise to characterize an asymmetric saturated hysteresis behavior of shape-memory-alloy (SMA)-driven systems, but it cannot consider thermomechanical relations between components of SMA-driven systems. On the other hand, constitutive models are composed of these relations, but their precision needs to be improved. In this paper, PI model is proposed to boost constitutive models in two cases. In the first case, PI model is used to characterize martensite volume fraction (MVF) called hybrid model. In the second case, the model is applied as a regulator in the output of a constitutive model called PI-based output (PIO) regulator. Due to simplicity and ability of Liang–Rogers (LR) model in transformation phases, it is considered as an MVF in the original constitutive model. The performance of both proposed models is compared with the original LR-based constitutive model. Unknown parameters of all three models are identified using genetic algorithm in MATLAB Toolbox. The performance of the three models is investigated at three different frequencies of \[\frac{{2\pi }}{8}\] , \[\frac{{2\pi }}{{15}}\] , and \[\frac{{2\pi }}{{30}}\] Hz because the excitation frequency changes the hysteresis behavior. Results show that the proposed hybrid model keeps the precision of the original constitutive model at different frequencies. In addition, the proposed PIO model shows the best performance to predict hysteresis behavior at different frequencies.

scholarly journals Vibration Suppression by Modulation of Elastic Modulus Using Shape Memory Alloy

1993 ◽  
Author(s):  
Daniel J. Segalman ◽  
Gordon G. Parker ◽  
Daniel J. Inman
Keyword(s):  
Elastic Modulus ◽  
Shape Memory Alloy ◽  
Resonant Frequency ◽  
Shape Memory ◽  
Vibration Suppression ◽  
Excitation Frequency ◽  
Rotating Machinery ◽  
Operating Speed

Abstract A method is proposed for suppressing the resonances that occur as an item of rotating machinery is spun-up from rest to its operating speed. This proposed method invokes “stiffness scheduling” so that the resonant frequency of the system is shifted during spin-up so as to be distant from the excitation frequency. A strategy for modulating the stiffness through the use of shape memory alloy is also presented.

scholarly journals TF Entropy and RFE Based Diagnosis for Centrifugal Pumps Subject to the Limitation of Failure Samples

2020 ◽  
Vol 10 (8) ◽  
pp. 2932
Author(s):  
Xuanyuan Su ◽  
Hongmei Liu ◽  
Laifa Tao
Keyword(s):  
Feature Extraction ◽  
Fault Diagnosis ◽  
Entropy Method ◽  
Recursive Feature Elimination ◽  
Decomposition Algorithms ◽  
Centrifugal Pumps ◽  
Time Frequency ◽  
Vibration Data ◽  
Failure Data ◽  
Non Stationary Signal

In practical engineering, the vibration-based fault diagnosis with few failure samples is gaining more and more attention from researchers, since it is generally hard to collect sufficient failure records of centrifugal pumps. In such circumstances, effective feature extraction becomes quite vital, since there may not be enough failure data to train an end-to-end classifier, like the deep neural network (DNN). Among the feature extraction, the entropy combined with signal decomposition algorithms is a powerful choice for fault diagnosis of rotating machinery, where the latter decomposes the non-stationary signal into multiple sequences and the former further measures their nonlinear characteristics. However, the existing entropy generally aims at processing the 1D sequence, which means that it cannot simultaneously extract the fault-related information from both the time and frequency domains. Once the sequence is not strictly stationary (hard to achieve in practices), the useful information will be inevitably lost due to the ignored domain, thus limiting its performance. To solve the above issue, a novel entropy method called time-frequency entropy (TfEn) is proposed to jointly measure the complexity and dynamic changes, by taking into account nonlinear behaviors of sequences from both dimensions of time and frequency, which can still fully extract the intrinsic fault features even if the sequence is not strictly stationary. Successively, in order to eliminate the redundant components and further improve the diagnostic accuracy, recursive feature elimination (RFE) is applied to select the optimal features, which has better interpretability and performance, with the help of the supervised embedding mechanism. To sum up, we propose a novel two-stage method to construct the fault representation for centrifugal pumps, which develops from the TfEn-based feature extraction and RFE-based feature selection. The experimental results using the real vibration data of centrifugal pumps show that, with extremely few failure samples, the proposed method respectively improves the average classification accuracy by 12.95% and 33.27%, compared with the mainstream entropy-based methods and the DNN-based ones, which reveals the advantage of our methodology.

Research on stator current characteristics of centrifugal pumps under different mechanical seal failures

2021 ◽  
pp. 095440622110610
Author(s):  
Jiamin Zou ◽  
Yin Luo ◽  
Yuejiang Han ◽  
Yakun Fan
Keyword(s):  
Centrifugal Pump ◽  
Negative Impact ◽  
Maximum Amplitude ◽  
Mechanical Seal ◽  
Centrifugal Pumps ◽  
Pump System ◽  
Seal Failure ◽  
Stator Current ◽  
Marginal Spectrum ◽  
Current Characteristics

Mechanical seal failure has a great negative impact on the operation of a centrifugal pump system. A method to analyze the stator current characteristics of the motor in a centrifugal pump system is proposed to monitor the internal flow of the centrifugal pump and to identify the failure status of the mechanical seal. Experiments were conducted under different mechanical seal states. Based on sensorless technology, the stator current signal of the motor is collected, processed by windowing function, anti-aliasing filter, singular value decomposition, Hilbert–Huang transform, and the marginal spectrum of correlation quantity is drawn. The results show that according to the external characteristic curve of the centrifugal pump, after the failure of the mechanical seal, the head and efficiency of the centrifugal pump decrease, and the head is greatly affected by the degree of failure, while the degree of mechanical seal failure has little effect on the shaft power of the centrifugal pump; the centrifugal pump has good operation stability under design conditions or near slightly large flow; the stability of centrifugal pump operation decreases with the aggravation of mechanical seal failure; the corresponding maximum amplitude in the marginal spectrum can be used as an index to diagnose the damage degree of the mechanical seal.

Application of a Balancing Filter for Model-Based Fault Diagnosis on a Centrifugal Pump in Active Magnetic Bearings

2009 ◽  
Author(s):  
Philipp Beckerle ◽  
Norman Butzek ◽  
Rainer Nordmann ◽  
Stephan Rinderknecht
Keyword(s):  
Fault Diagnosis ◽  
Fault Detection ◽  
Centrifugal Pump ◽  
Magnetic Bearings ◽  
Active Magnetic Bearings ◽  
Model Matching ◽  
Centrifugal Pumps ◽  
Test Rig ◽  
Model Based ◽  
Flexible Mode

This paper discusses the suitability of a special discrete filter, called balancing filter, to improve the performance of model-based fault detection and fault diagnosis on a centrifugal pump in active magnetic bearings. The focus in this subject lies on the extraction of better symptoms for the fault diagnosis. The application of the balancing filter sets up on a multi-model approach which uses a model of the system for the reference state and every fault that is to be detected. These models are stimulated with the same test signals as the ones applied to the process while it is running. To compare the simulation results of the models with the process response the output error is calculated. After this the remaining residuals are used as symptoms for the fault detection. The balancing filter is used to remove the large differences within the amplitude responses of the models caused by the lowpass characteristics of the mechanical part of the system. Hence the influence of the smaller differences caused by the examined faults is weighted equally at all interesting frequencies. This leads to new residuals which are separated more clearly. This approach is used to detect common faults appearing on centrifugal pumps as dry run, incorrect installation and worn out balance pistons. The test rig used to examine the suitability of the proposed filter is a one-level centrifugal pump in magnetic bearings. The rotor of the pump is driven by an asynchronous motor at rotation speeds up to 3000 rpm. The first flexible mode of the rotor is located at 280 Hz. In the seal gap fluid-structure-interaction is appearing. The forces on the rotor are calculated based on the current applied to the bearings, while its displacement is measured by eddy current sensors integrated into the bearings. The first two natural frequencies of the system are located at about 200Hz and 500 Hz. These frequencies are shifted when a fault is occuring. In the models for the fault states this behaviour is represented. Hence the model matching the current state of the pump leads to the lowest residual. The advantage of the balancing filter is that the detection of faults becomes more reliable. Below the examined faults, the model-based concept and the design of the balancing filter are described in detail. Results from experiments on the test rig are given to show the advantages of the balancing filter.

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