Degradation estimation using feature increment stepwise linear regression for PWM Inverter of Electro-Mechanical Actuator

Yu, Peng; Zhang, Y. J.; Liu, Datong; Liu, L. S.

doi:10.1016/j.microrel.2018.06.025

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…Equation 3also reveals that the output ( ) is approximately proportional to the ( ), therefore, if the input signal w(t) is a time varying then the frequency of input signal ( ) must be large enough to obtain the almost constant value of output ( ) [20].…”

Section: + -mentioning

confidence: 99%

“…Among them, PWM is widely used because it has many advantages such as robust against disturbances and easily implemented. It could be found application of PWM in motor controls [12], pneumatic and hydraulic actuators [13][14], shape memory alloy actuator [15,16], 3-RPR parallel robot [17], pneumatic valves [18,19], Electro-Mechanical Actuator [20], and in piezo air jet actuators [21]. This paper introduce a contactless suspension system by using modulation techniques.…”

Section: Introductionmentioning

confidence: 99%

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Control of Electrostatic Suspension System Using Pulse Width Modulation

Le¹

2020

Adv. sci. technol. eng. syst. j.

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Electrostatic suspension systems have great potential applications in contactless transportation objects since they allow many different materials to be suspended. The electrostatic suspension will be widely applied in practice if the system cost is inexpensive. This paper presents an electrostatic suspension system controlled by using pulse width modulation (PWM). The use of PWM in electrostatic suspension system will reduce the system cost since inexpensive switching power amplifiers could be applied instead of linear analogue power amplifiers, which are bulky and costly. The simulation and experimental results are performed and showed that PWM can be used effectively to control the position of the levitated object in the electrostatic suspension.

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Section: + -mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Control of Electrostatic Suspension System Using Pulse Width Modulation

Le¹

2020

Adv. sci. technol. eng. syst. j.

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“…Stepwise regression (SR) is a method of selecting the independent variables that can explain the dependent variable with step by step iterative construction very efficiently [11], [12]. The construction is through adding and removing of the independent variables from or into the model [12]. The two main procedures in SR are the forward selection method and backward elimination [12]- [17].…”

Section: Introductionmentioning

confidence: 99%

“…The construction is through adding and removing of the independent variables from or into the model [12]. The two main procedures in SR are the forward selection method and backward elimination [12]- [17]. For the forward selection, the method starts with no independent variables in the model except the intercept.…”

Section: Introductionmentioning

confidence: 99%

A novel application of artificial neural network for classifying agarwood essential oil quality

Mahabob

Yusoff

Amidon

et al. 2022

IJECE

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<p><span lang="EN-US">This work studies the agarwood oil classification into high and low quality by using two different techniques. Initially, the Forest Research Institute Malaysia (FRIM) and Universiti Malaysia Pahang (UMP) are where the sample preparation and compound extraction of agarwood oil is collected. The data collections were done from the previous researcher consists of 96 samples from seven significant agarwood oil compounds. The artificial neural network (ANN) and the proposed stepwise regression technique were used in this study. The stepwise regression was done the feature selection and successfully reduced agarwood oil compounds from seven to four. Then, the ANN technique was used to classify agarwood oil into high and low using input from seven and four compounds separately. The performance of ANN with different inputs is compared (ANN with seven inputs compared with ANN with four inputs). All the experimental work was performed using the MATLAB R2017b using the “patternet” implemented Levenberg Marquardt algorithm and ten hidden neurons. It was found that the ANN technique using seven compounds obtained the best performance according to high accuracy and lower mean square error (MSE) value. Finally, 1 hidden neuron in ANN with seven inputs selected as the best neuron for grading the agarwood oil compounds.</span></p>

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“…With EMA increasingly utilized in safety-critical applications, the development of reliable and accurate EMA prognostic health management (PHM) systems becomes more and more important [8,10,11,12]. Development of EMA PHM can also contribute to increasing the overall availability and safety of EMA, in which performance degradation, faults and catastrophic failures can be prevented [13,14,15]. Furthermore, EMA PHM also makes EMA more suitable for aerospace applications due to the ability of minimizing failures [16,17,18].…”

Section: Introductionmentioning

confidence: 99%

An Electro-Mechanical Actuator Motor Voltage Estimation Method with a Feature-Aided Kalman Filter

Zhang

Liu

et al. 2018

Sensors

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Electro-Mechanical Actuators (EMA) have attracted growing attention with their increasing incorporation in More Electric Aircraft. The performance degradation assessment of EMA needs to be studied, in which EMA motor voltage is an essential parameter, to ensure its reliability and safety of EMA. However, deviation exists between motor voltage monitoring data and real motor voltage due to electromagnetic interference. To reduce the deviation, EMA motor voltage estimation generally requires an accurate voltage state equation which is difficult to obtain due to the complexity of EMA. To address this problem, a Feature-aided Kalman Filter (FAKF) method is proposed, in which the state equation is substituted by a physical model of current and voltage. Consequently, voltage state data can be obtained through current monitoring data and a current–voltage model. Furthermore, voltage estimation can be implemented by utilizing voltage state data and voltage monitoring data. To validate the effectiveness of the FAKF-based estimation method, experiments have been conducted based on the published data set from NASA’s Flyable Electro-Mechanical Actuator (FLEA) test stand. The experiment results demonstrate that the proposed method has good performance in EMA motor voltage estimation.

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Degradation estimation using feature increment stepwise linear regression for PWM Inverter of Electro-Mechanical Actuator

Cited by 12 publications

References 9 publications

Control of Electrostatic Suspension System Using Pulse Width Modulation

Control of Electrostatic Suspension System Using Pulse Width Modulation

A novel application of artificial neural network for classifying agarwood essential oil quality

An Electro-Mechanical Actuator Motor Voltage Estimation Method with a Feature-Aided Kalman Filter

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