Bin Chen¹, Ziyang Li¹, Shipeng Li¹, Qingzhou Zhao¹, Xingdou Liu^2,*

Energy Engineering, Vol.121, No.5, pp. 1291-1307, 2024, DOI:10.32604/ee.2024.046374

Abstract To reduce carbon emissions, clean energy is being integrated into the power system. Wind power is connected to the grid in a distributed form, but its high variability poses a challenge to grid stability. This article combines wind turbine monitoring data with numerical weather prediction (NWP) data to create a suitable wind power prediction framework for distributed grids. First, high-precision NWP of the turbine range is achieved using weather research and forecasting models (WRF), and Kriging interpolation locates predicted meteorological data at the turbine site. Then, a preliminary predicted power series is obtained based on the fan’s wind speed-power conversion… More >

Xiangqun Li^1,*, Jiawen Liang², Jinyu Zhu², Shengping Shi², Fangyu Ding², Jianpeng Sun², Bo Liu²

Energy Engineering, Vol.121, No.1, pp. 203-219, 2024, DOI:10.32604/ee.2023.029295

Abstract To solve the problems of a few optical fibre line fault samples and the inefficiency of manual communication optical fibre fault diagnosis, this paper proposes a communication optical fibre fault diagnosis model based on variational modal decomposition (VMD), fuzzy entropy (FE) and fuzzy clustering (FC). Firstly, based on the OTDR curve data collected in the field, VMD is used to extract the different modal components (IMF) of the original signal and calculate the fuzzy entropy (FE) values of different components to characterize the subtle differences between them. The fuzzy entropy of each curve is used as the feature vector, which… More >

Yinghua Song^1,2, Hairong Lyu^1,2, Wei Zhang^1,2,*

Journal on Big Data, Vol.5, pp. 19-40, 2023, DOI:10.32604/jbd.2023.038249

Abstract A precise and timely forecast of short-term rail transit passenger flow provides data support for traffic management and operation, assisting rail operators in efficiently allocating resources and timely relieving pressure on passenger safety and operation. First, the passenger flow sequence models in the study are broken down using VMD for noise reduction. The objective environment features are then added to the characteristic factors that affect the passenger flow. The target station serves as an additional spatial feature and is mined concurrently using the KNN algorithm. It is shown that the hybrid model VMD-CLSMT has a higher prediction accuracy, by setting… More >

Shoutao Li^1,2,*, Ruyi Qu¹, Yu Zhang¹, Dingli Yu³

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2809-2823, 2023, DOI:10.32604/iasc.2023.036999

Abstract Freezing of Gait (FOG) is the most common and disabling gait disorder in patients with Parkinson’s Disease (PD), which seriously affects the life quality and social function of patients. This paper proposes a FOG recognition method based on the Variational Mode Decomposition (VMD). Firstly, VMD instead of the traditional time-frequency analysis method to complete adaptive decomposition to the FOG signal. Secondly, to improve the accuracy and speed of the recognition algorithm, use the CART model as the base classifier and perform the feature dimension reduction. Then use the RUSBoost ensemble algorithm to solve the problem of unbalanced sample size and… More >

Qiansheng Fang, Haojie Wang, Chenlei Xie^*, Jie Chen

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1237-1250, 2023, DOI:10.32604/cmes.2022.021131

Abstract At present, the leakage rate of the water distribution network in China is still high, and the waste of water resources caused by water distribution network leakage is quite serious every year. Therefore, the location of pipeline leakage is of great significance for saving water resources and reducing economic losses. Acoustic emission technology is the most widely used pipeline leak location technology. The traditional non-stationary random signal de-noising method mainly relies on the estimation of noise parameters, ignoring periodic noise and components unrelated to pipeline leakage. Aiming at the above problems, this paper proposes a leak location method for water… More >

Yingnan Zhao^1,*, Peiyuan Ji¹, Fei Chen¹, Guanlan Ji¹, Sunil Kumar Jha²

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1001-1016, 2022, DOI:10.32604/iasc.2022.027710

Abstract This paper proposes a spatio-temporal model (VCGA) based on variational mode decomposition (VMD) and attention mechanism. The proposed prediction model combines a squeeze-and-excitation network to extract spatial features and a gated recurrent unit to capture temporal dependencies. Primarily, the VMD can reduce the instability of the original wind speed data and the attention mechanism functions to strengthen the impact of important information. In addition, the VMD and attention mechanism act to avoid a decline in prediction accuracy. Finally, the VCGA trains the decomposition result and derives the final results after merging the prediction result of each component. Contrasting experiments for… More >

Yingnan Zhao^1,*, Guanlan Ji¹, Fei Chen¹, Peiyuan Ji¹, Yi Cao²

Computer Systems Science and Engineering, Vol.43, No.2, pp. 719-735, 2022, DOI:10.32604/csse.2022.027288

Abstract Improving short-term wind speed prediction accuracy and stability remains a challenge for wind forecasting researchers. This paper proposes a new variational mode decomposition (VMD)-attention-based spatio-temporal network (VASTN) method that takes advantage of both temporal and spatial correlations of wind speed. First, VASTN is a hybrid wind speed prediction model that combines VMD, squeeze-and-excitation network (SENet), and attention mechanism (AM)-based bidirectional long short-term memory (BiLSTM). VASTN initially employs VMD to decompose the wind speed matrix into a series of intrinsic mode functions (IMF). Then, to extract the spatial features at the bottom of the model, each IMF employs an improved convolutional… More >

Bei Liu¹, Xian Zhang^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1547-1563, 2022, DOI:10.32604/cmes.2022.018130

Abstract During high-intensity focused ultrasound (HIFU) treatment, the accurate identification of denatured biological tissue is an important practical problem. In this paper, a novel method based on the improved variational mode decomposition (IVMD) and autoregressive (AR) model was proposed, which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment. Firstly, the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions (IMF). The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising. Then, the AR model… More >

R. Jegadeeshwaran¹, V. Sugumaran², K.P. Soman³

Structural Durability & Health Monitoring, Vol.10, No.1, pp. 81-97, 2014, DOI:10.3970/sdhm.2014.010.081

Abstract In automobile, brake system is an essential part responsible for control of the vehicle. Vibration signals of a rotating machine contain the dynamic information about its health condition. Many research papers have reported the suitability of vibration signals for fault diagnosis applications. Many of them are based on (Fast Fourier Transform) FFT, which have their own drawback with nonstationary signals. Hence, there is a need for development of new methodologies to infer diagnostic information from such non stationary signals. This paper uses vibration signals acquired from a hydraulic brake system under good and simulated faulty conditions for the purpose of… More >

Akhil Muralidharan^1,2, V. Sugumaran¹, K.P Soman³, M. Amarnath⁴

Structural Durability & Health Monitoring, Vol.10, No.1, pp. 55-80, 2014, DOI:10.3970/sdhm.2014.010.055

Abstract Gears are machine elements that transmit motion by means of successively engaging teeth. In purely scientific terms, gears are used to transmit motion. A faulty gear is a matter of serious concern as it affects the functionality of a machine to a great extent. Thus it is essential to diagnose the faults at an initial stage so as to reduce the losses that might be incurred. This necessitates the need for continuous monitoring of the gears. The vibrations produced by gears from good and simulated faulty conditions can be effectively used to detect the faults in these gears. The introduction… More >