Frequency domain approaches to locate forced oscillation source to control device

Luan, Moude; Li, Shangyuan; Gan, Deqiang; Wu, Di

doi:10.1016/j.ijepes.2019.105704

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…Then, a combination of EMD and Delay Vector Variance (DVV) was developed for oscillation detection in chemical industries [8]. There is also a method based on the frequency domain property of time series data analysis using the Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) that measures the frequency in data signal at Point of Common Coupling (PCC) to detect oscillation in control loops [9], [10].…”

Section: Introductionmentioning

confidence: 99%

Multi-oscillations Detection for Process Variables Based on K-Nearest Neighbor

Amrullah,

Wardana,

Arif

2023

ELKHA

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In the process industry, a control system is important to ensure the process runs smoothly and keeps the product under predetermined specifications. Oscillations in process variables can affect the decreasing profitability of the plant. It is important to detect the oscillation before it becomes a problem for profitability. Various methods have been developed; however, the methods still need to improve when implemented online for multi-oscillation. Therefore, this research uses a machine learning-based method with the K-Nearest Neighbour (KNN) algorithm to detect multi-oscillation in the control loop, and the detection methods are made to carry out online detection from real plants. The developed method simulated the Tennessee Eastman Process (TEP), and it used Python programming to create a KNN model and extract time series data into the frequency domain. The Message Queuing Telemetry Transport (MQTT) communication protocol has been used to implement as an online system. The result of the implementation showed that two KNN models were made with different window size variations to get the best performance model. The best model for multi-oscillation detection was obtained with an F1 score of 76% for detection.

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Section: Introductionmentioning

confidence: 99%

Multi-oscillations Detection for Process Variables Based on K-Nearest Neighbor

Amrullah,

Wardana,

Arif

2023

ELKHA

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“…The FBG technology is a typical fiber grating method for impact detection of the large-scale structure [24][25][26]. For example, Kwon et al [27] performed localization of a lowvelocity impact using strain amplitude information from FBG sensors.…”

Section: Introductionmentioning

confidence: 99%

Multi FBG sensor-based impact localization with a hybrid correlation interpolation method

Liangya¹,

Jiang²,

Luo³

et al. 2022

Meas. Sci. Technol.

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To locate the impact source of a composite material structure with a series of Fiber Bragg grating (FBG) sensors, a hybrid correlation interpolation (HCI) method is proposed, in this paper, based on a weighted correlation analysis and a unidirectional cubic spline interpolation. First, the signals collected by FBG sensors are preprocessed on the frequency domain to reduce noise interference. Second, the impact similarity map is built by using the weighted cross-correlation value to estimate the location of the impact roughly. Third, the similarity map is further subdivided by the unidirectional cubic spline interpolation to increase the impact localization. Fourth, the FBG sensor network is experimental analyzed to optimize the layout and the structure of the FBG sensor network. The validity of the multi FBG sensor-based impact localization method is verified on a carbon fiber composite plates with a size of 650 × 500 (mm). The experimental result shows that the Mean Absolute Error (MAE) is 9.74mm for our suggested method and 15.51mm for the bicubic polynomial interpolation (BPI) algorithm, which is reduced by 5.77mm. The maximum errors are 36.40mm for the BPI algorithm while are reduced to 21.55mm for our suggested method. Furthermore, the effect of FBG sensor combination layout and number on impact location accuracy is analyzed and compared. It shows that the sensor network layout of rectangular structure using four FBG sensors is a better choice after the comprehensive consideration of economic benefits, localization accuracy, and Error Rate (ER).

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“…The method in [14] can only locate the FO source in the mechanical part of synchronous generators. In [15], the frequency domain approach was applied to locate the I FO source in control devices. The approach in [15] can locate sources of the FO in mechanical or electromechanical parts of synchronous generators.…”

Section: Introductionmentioning

confidence: 99%

“…In [15], the frequency domain approach was applied to locate the I FO source in control devices. The approach in [15] can locate sources of the FO in mechanical or electromechanical parts of synchronous generators. Simultaneous estimation of the EMs and FOs was proposed in [16].…”

Section: Introductionmentioning

confidence: 99%

Forced Oscillation Detection Amid Communication Uncertainties

Surinkaew

Shah

Mithulananthan

et al. 2021

IEEE Systems Journal

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This paper proposes a novel technique for detection of forced oscillation (FO) in a power system when the measured signals received through the communication channels are uncertain. Impacts of communication uncertainties on measured signals are theoretically investigated based on mathematical models developed in this paper. The proposed data recovery method is applied to reconstruct the signal under the effects of communication losses. The proposed FO detection considering communication uncertainties is evaluated in the modified 14-Machine Southeast Australian (SE-A) power system. Rigorous comparative analysis is made to examine the effectiveness of the proposed data recovery and FO detection methods.

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Frequency domain approaches to locate forced oscillation source to control device

Cited by 7 publications

References 26 publications

Multi-oscillations Detection for Process Variables Based on K-Nearest Neighbor

Multi-oscillations Detection for Process Variables Based on K-Nearest Neighbor

Multi FBG sensor-based impact localization with a hybrid correlation interpolation method

Forced Oscillation Detection Amid Communication Uncertainties

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