Actuator fault detection using extended Kalman filter for a wastewater treatment process

Miron, Mihaela; Frangu, Laurenţiu; Caraman, Sergiu

doi:10.1109/icstcc.2017.8107098

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…In eqn (9), if the value of D n deviates away from zero, null hypothesis is rejected as it indicates that samples of F n (y) does not belong to F(y). The empirical CDF (ECDF) of F n (y) will be very close to the ECDF of F(y) when D n is equal to zero.…”

Section: Kolmogorov Smirnov (Ks) Indicatormentioning

confidence: 99%

“…For instance, in ref. 9, a fault detection method based on adaptive filtering is proposed for biological wastewater treatment processes is presented. The study focuses on detecting actuator, sensor, and toxicity faults within these systems.…”

Section: Introductionmentioning

confidence: 99%

“…Similarly, in ref. 9, a model-based method for detecting faults in the actuators of biological wastewater treatment processes is proposed based on an extended Kalman filter. This approach involves comparing the estimated states affected by actuator faults with the process model, and the paper generates residuals for fault detection.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhanced data-driven monitoring of wastewater treatment plants using the Kolmogorov–Smirnov test

Kini,

Harrou,

Madakyaru

et al. 2024

Environ. Sci.: Water Res. Technol.

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Section: Kolmogorov Smirnov (Ks) Indicatormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Enhanced data-driven monitoring of wastewater treatment plants using the Kolmogorov–Smirnov test

Kini,

Harrou,

Madakyaru

et al. 2024

Environ. Sci.: Water Res. Technol.

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“…The Extended Kalman Filter (EKF) and its various enhancement have been applied in control engineering. Therefore the process of sensor fault detection has been realized using EKF by Van Eykeren et al (2012) also actuator fault detected by Miron et al (2017) and Skach & Puncochar (2017).…”

Section: Introductionmentioning

confidence: 99%

Fault detection in a three-tank hydraulic system using unknown input observer and extended Kalman filter

HASSAN

Mohammed

Demirkol

2021

JER is an international, peer-reviewed journal that publishes f

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This paper presents the problem of fault diagnosis in a three-tank hydraulic system. A mathematical model of the system is developed in order to apply two different observing algorithms. Unknown Input Observer (UIO) and Extended Kalman Filter (EKF) have been used to detect and isolate actuator and sensor faults. For Unknown Input Observer (UIO), residuals are calculated from the measured and estimated output according to the eigenvalues of the system after processed by Linear Matrix Inequality (LMI). Extended Kalman filter uses process and measurement noise variances for state estimation. Unknown Input Observer and Extended Kalman Filter's performance in fault estimation and isolation is evaluated under different scenarios. Using Extended Kalman Filter (EKF), faults can be diagnosed effectively in the presence of noise, while Unknown Input Observer (UIO) is working better in the absence of noise, and simulation results illustrate that clearly.

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“…This being a data-driven method involves input and output data collected from the system and estimates Markov parameters. A method for the detection of actuator faults in a wastewater treatment plant using a model-based method is summarised in [9]. Here, change in the plant state because of change in actuator faults was studied, and based on the estimated and actual value, residuals were calculated.…”

Section: Introductionmentioning

confidence: 99%

Is Fault Detection and Diagnosis in Pneumatic Actuator A Topic of Concern?

Navada

Santhosh

2020

ARFMTS

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The present civilization highly depends on industrial products and hence there is an increased demand for the same. Therefore, each industry is trying to increase its production output without hindering the quality. Maintenance of plant health is essential to improve the production rate without any loss. Industrial processes require monitoring of every element as their consistent behavior is a fundamental concern. Any deviation in the working of these components may alter the quality of the end product, causing a huge loss for the industry. Therefore, monitoring and finding the root cause for irregular behavior of industrial processes is a requisite for avoiding any future loss. In this paper, an attempt is made to present types of faults, types of pneumatic actuator faults, and different techniques used for the detection and isolation of faults. Simulation work is carried out to generate stiction behavior in the control valve using the Choudhury stiction model. Valve stiction behavior for different values of stick band and jump values are discussed in this paper. A comparison of several techniques used for the detection of faults based on two performance indices namely true detection rate and false alarm rate has been given at the end of this paper. From these techniques, it is observed that these indices are interdependent, such that an increase in the detection rate increases the false detection rate and increases detection time.

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Actuator fault detection using extended Kalman filter for a wastewater treatment process

Cited by 6 publications

References 9 publications

Enhanced data-driven monitoring of wastewater treatment plants using the Kolmogorov–Smirnov test

Enhanced data-driven monitoring of wastewater treatment plants using the Kolmogorov–Smirnov test

Fault detection in a three-tank hydraulic system using unknown input observer and extended Kalman filter

Is Fault Detection and Diagnosis in Pneumatic Actuator A Topic of Concern?

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