scholarly journals Comparison of arrival time estimation methods for partial discharge pulses in power cables

2008 ◽  
Author(s):  
Paul Wagenaars ◽  
Peter A.A.F. Wouters ◽  
Peter C.J.M. van der Wielen ◽  
E. Fred Steennis
Keyword(s):  
Arrival Time ◽  
Partial Discharge ◽  
Time Estimation ◽  
Estimation Methods ◽  
Power Cables

scholarly journals Extraction of Partial Discharge Pulses from the Complex Noisy Signals of Power Cables Based on CEEMDAN and Wavelet Packet

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3242 ◽  
Author(s):  
Sun ◽  
Zhang ◽  
Shi ◽  
Gou
Keyword(s):  
White Noise ◽  
Arrival Time ◽  
Wavelet Packet ◽  
Partial Discharge ◽  
Gaussian White Noise ◽  
Power Cable ◽  
Sampling Point ◽  
Power Cables ◽  
Threshold Method ◽  
Narrowband Noise

While both periodic narrowband noise and white noise are significant sources of interference in the detection and localization of partial discharge (PD) signals in power cables, existing research has focused nearly exclusively on white noise suppression. This paper addresses this issue by proposing a new signal extraction method for effectively detecting random PD signals in power cables subject to complex noise environments involving both white noise and periodic narrowband noise. Firstly, the power cable signal was decomposed using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and the periodic narrowband noise and frequency aliasing in the obtained signal components were suppressed using singular value decomposition. Then, signal components contributing significantly to the PD signal were determined according to the cross-correlation coefficient between each component and the original PD signal, and the PD signal was reconstructed solely from the obtained significant components. Finally, the wavelet packet threshold method was used to filter out residual white noise in the reconstructed PD signal. The performance of the proposed algorithm was demonstrated by its application to synthesized PD signals with complex noise environments composed of both Gaussian white noise and periodic narrowband noise. In addition, the time-varying kurtosis method was demonstrated to accurately determine the PD signal arrival time when applied to PD signals extracted by the proposed method from synthesized signals in complex noise environments with signal-to-noise ratio (SNR) values as low as −6 dB. When the SNR was reduced to −23 dB, the arrival time error of the PD signal was only one sampling point.

scholarly journals Short-Term Scheduling Model of Cluster Tool in Wafer Fabrication

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1029
Author(s):  
Ying-Mei Tu
Keyword(s):  
Arrival Time ◽  
Time Estimation ◽  
Advanced Technology ◽  
Shop Floor ◽  
Process Time ◽  
Short Term ◽  
Work In Process ◽  
Scheduling Model ◽  
Cluster Tools ◽  
Cluster Tool

Since last decade, the cluster tool has been mainstream in modern semiconductor manufacturing factories. In general, the cluster tool occupies 60% to 70% of production machines for advanced technology factories. The most characteristic feature of this kind of equipment is to integrate the relevant processes into one single machine to reduce wafer transportation time and prevent wafer contaminations as well. Nevertheless, cluster tools also increase the difficulty of production planning significantly, particularly for shop floor control due to complicated machine configurations. The main objective of this study is to propose a short-term scheduling model. The noteworthy goal of scheduling is to maximize the throughput within time constraints. There are two modules included in this scheduling model—arrival time estimation and short-term scheduling. The concept of the dynamic cycle time of the product’s step is applied to estimate the arrival time of the work in process (WIP) in front of machine. Furthermore, in order to avoid violating the time constraint of the WIP, an algorithm to calculate the latest time of the WIP to process on the machine is developed. Based on the latest process time of the WIP and the combination efficiency table, the production schedule of the cluster tools can be re-arranged to fulfill the production goal. The scheduling process will be renewed every three hours to make sure of the effectiveness and good performance of the schedule.

scholarly journals A Fusion Algorithm for Estimating Time-Independent/-Dependent Parameters and States

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4068
Author(s):  
Zheshuo Zhang ◽  
Jie Zhang ◽  
Jiawen Dai ◽  
Bangji Zhang ◽  
Hengmin Qi
Keyword(s):  
Unscented Kalman Filter ◽  
Time Estimation ◽  
Estimation Algorithm ◽  
Estimation Methods ◽  
Fusion Algorithm ◽  
State Variable ◽  
Current Estimation ◽  
Real Time Estimation ◽  
And Control ◽  
Independent Parameters

Vehicle parameters are essential for dynamic analysis and control systems. One problem of the current estimation algorithm for vehicles’ parameters is that: real-time estimation methods only identify parts of vehicle parameters, whereas other parameters such as suspension damping coefficients and suspension and tire stiffnesses are assumed to be known in advance by means of an inertial parameter measurement device (IPMD). In this study, a fusion algorithm is proposed for identifying comprehensive vehicle parameters without the help of an IPMD, and vehicle parameters are divided into time-independent parameters (TIPs) and time-dependent parameters (TDPs) based on whether they change over time. TIPs are identified by a hybrid-mass state-variable (HMSV). A dual unscented Kalman filter (DUKF) is applied to update both TDPs and online states. The experiment is conducted on a real two-axle vehicle and the test data are used to estimate both TIPs and TDPs to validate the accuracy of the proposed algorithm. Numerical simulations are performed to further investigate the algorithm’s performance in terms of sprung mass variation, model error because of linearization and various road conditions. The results from both the experiment and simulation show that the proposed algorithm can estimate TIPs as well as update TDPs and online states with high accuracy and quick convergence, and no requirement of road information.

scholarly journals Advances in Time Estimation Methods for Molecular Data

2016 ◽  
Vol 33 (4) ◽  
pp. 863-869 ◽  
Author(s):  
Sudhir Kumar ◽  
S. Blair Hedges
Keyword(s):  
Time Estimation ◽  
Molecular Data ◽  
Estimation Methods

Development of a Portable XLPE Cable Insulation Detection Device

2014 ◽  
Vol 960-961 ◽  
pp. 881-884
Author(s):  
Xiao Guang Xi ◽  
Yu Yan Man ◽  
Chi Zhang ◽  
Ming Lei Wu ◽  
Yan Wei Dong ◽  
...  
Keyword(s):  
Acoustic Emission ◽  
Electromagnetic Wave ◽  
Electromagnetic Coupling ◽  
Partial Discharge ◽  
Power Cables ◽  
Cable Insulation ◽  
Xlpe Cable ◽  
Insulation Status

In this article, a portable XLPE cable insulation detection device is introduced. Such a device utilizes electromagnetic coupling, UHF electromagnetic wave and acoustic emission to detect partial discharge signals in power cables. By analyzing the partial discharge signals and cable temperatures, the insulation status of XLPE power cables is judged.

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