scholarly journals Application of powerline noise cancellation method in correlation identification of controlled source electromagnetic method

2021 ◽  
Vol 18 (3) ◽  
pp. 339-354
Author(s):  
Zhi Yang ◽  
Jingtian Tang ◽  
Xiao Xiao ◽  
Qiyun Jiang ◽  
Xiangyu Huang ◽  
...  
Keyword(s):  
System Identification ◽  
Estimation Method ◽  
Wiener Filter ◽  
Noise Estimation ◽  
Identification Accuracy ◽  
Electromagnetic Method ◽  
Filter Method ◽  
Noise Elimination ◽  
Controlled Source ◽  
Transmitted Signal

Abstract Powerline interference in the controlled source electromagnetic method has traditionally been one of the biggest conundrums plaguing geophysicists, and its conventional denoising methods primarily include filtering and noise estimation. The filter method leaches noise at specific frequency points, which might also filter useful signals; the noise estimation method significantly eliminates interference, whereas the premise is that the noise is stable after a short time and a recorder is necessary in the field. In the present study, using the periodicity and symmetry of powerline noise, we propose a subtraction and an addition method for cancellation of the powerline noise. First, the transmitted signal is optimized so that the equivalent transmitted signal is an m sequence; then the response signal is processed by using the cancellation method; subsequently, the correlation identification is applied and finally, we solve the earth impulse response by means of the Wiener filter deconvolution method. Simulation experiments and field data tests demonstrate that the powerline noise can be well suppressed by the cancellation method proposed in the present study, so that the system identification accuracy is greatly improved. The method is simple in principle and effective in removing powerline noise, which presents a novel perspective on noise elimination for system identification.

Adaptive Modeling of Laser Powder Deposition Process for Control and Monitoring Application

2005 ◽  
Author(s):  
Mohammad Durali ◽  
Alireza Fathi ◽  
Amir Khajepour ◽  
Ehsan Toyserkani
Keyword(s):  
Kalman Filter ◽  
System Identification ◽  
Least Square Method ◽  
Deposition Process ◽  
Least Square ◽  
Filter Method ◽  
Recursive Least Square ◽  
Noise Elimination ◽  
Laser Powder Deposition ◽  
Powder Deposition

Laser Powder Deposition technique is an advanced production method with many applications. Despite this fact, reliable and accurate control schemes have not yet fully developed for this method. This article presents method for in time identification of the process for modeling and adaptation of proper control strategy. ARMAX structure is chosen for system model. Recursive least square method and Kalman Filter methods are adopted for system identification, and their performance are compared. Experimental data was used for system identification, and proper filtering schemes are devised here for noise elimination and increased estimation results. It was concluded that although both methods yield efficient performance and accurate results, Kalman Filter method gives better results in parameter estimations. The comparison of the results shows that this method can be used very efficiently in control and monitoring of Laser Powder Deposition process.

scholarly journals An Initial Value Estimation Method for the Kalman and Extended Kalman Filters in Underground Metal Detection

2019 ◽  
Vol 9 (19) ◽  
pp. 4113 ◽  
Author(s):  
Yadong Wan ◽  
Zhen Wang ◽  
Peng Wang ◽  
Zhiyang Liu ◽  
Na Li ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Estimation Method ◽  
Detection Methods ◽  
Polarizability Tensor ◽  
Filter Method ◽  
Excellent Performance ◽  
Initial Value ◽  
Initial State ◽  
Metal Detection ◽  
Value Estimation

As an underground metal detection technology, the electromagnetic induction (EMI) method is widely used in many cases. Therefore, the EMI detection algorithms with excellent performance are worth studying. One of the EMI detection methods in the underground metal detection is the filter method, which first obtains the secondary magnetic field data and then uses the Kalman filter (KF) and the extended Kalman filter (EKF) to estimate the parameters of metal targets. However, the traditional KF methods used in the underground metal detection have an unsatisfactory performance of the convergence as the algorithms are given a random or a fixed initial value. Here, an initial state estimation algorithm for the underground metal detection is proposed. The initial state of the target’s horizontal position is estimated by the first order central moments of the secondary field strength map. In addition, the initial state of the target’s depth is estimated by the full width at half maximum (FWHM) method. In addition, the initial state of the magnetic polarizability tensor is estimated by the least squares method. Then, these initial states are used as the initial values for KF and EKF. Finally, the position, posture and polarizability of the target are recursively calculated. A simulation platform for the underground metal detection is built in this paper. The simulation results show that the initial value estimation method proposed for the filtering algorithm has an excellent performance in the underground metal detection.

Development of Control System by Nonlinear Compensation Using Digital Acceleration Control

2010 ◽  
Author(s):  
Takanori Emaru ◽  
Kazuo Imagawa ◽  
Yohei Hoshino ◽  
Yukinori Kobayashi
Keyword(s):  
Control System ◽  
System Identification ◽  
Mechanical System ◽  
Pid Control ◽  
Estimation Method ◽  
Proportional Integral Derivative ◽  
Inertia Term ◽  
Modeling Errors ◽  
Nonlinear Compensation ◽  
Simulation Results

Proportional-Integral-Derivative (PID) control has been most commonly used to operate mechanical systems. In PID control, however, there are limits to the accuracy of the resulting movement because of the influence of gravity, friction, and interaction of joints. We have proposed a digital acceleration control (DAC) that is robust over these modeling errors. One of the most practicable advantages of DAC is robustness against modeling errors. However, it does not always work effectively. If there are modeling errors in the inertia term of the model, the DAC controller cannot control a mechanical system properly. Generally an inertia term is easily modeled in advance, but it has a possibility to change. Therefore, we propose an online estimation method of an inertia term by using a system identification method. By using the proposed method, the robustness of DAC is considerably improved. This paper shows the simulation results of the proposed method using 2-link manipulator.

Prediction of double stacking hydrocarbon using Marine Controlled Source Electromagnetic method

2014 ◽  
Author(s):  
Muhammad Rauf ◽  
Noorhana Yahya ◽  
Tadiwa Elisha Nyamasvisva ◽  
Adeel Ansari ◽  
Afza Shafie ◽  
...  
Keyword(s):  
Electromagnetic Method ◽  
Controlled Source

scholarly journals Noise masking method based on an effective ratio mask estimation in Gammatone channels

2018 ◽  
Vol 7 ◽  
Author(s):  
Feng Bao ◽  
Waleed H. Abdulla
Keyword(s):  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Wiener Filter ◽  
Power Spectra ◽  
Auditory Scene Analysis ◽  
Accurate Estimation ◽  
Noise Power ◽  
Noise Masking ◽  
Time Frequency ◽  
Mask Estimation

In computational auditory scene analysis, the accurate estimation of binary mask or ratio mask plays a key role in noise masking. An inaccurate estimation often leads to some artifacts and temporal discontinuity in the synthesized speech. To overcome this problem, we propose a new ratio mask estimation method in terms of Wiener filtering in each Gammatone channel. In the reconstruction of Wiener filter, we utilize the relationship of the speech and noise power spectra in each Gammatone channel to build the objective function for the convex optimization of speech power. To improve the accuracy of estimation, the estimated ratio mask is further modified based on its adjacent time–frequency units, and then smoothed by interpolating with the estimated binary masks. The objective tests including the signal-to-noise ratio improvement, spectral distortion and intelligibility, and subjective listening test demonstrate the superiority of the proposed method compared with the reference methods.

Complex Resistivity Method and its Application in Mineral Resource Exploration

2011 ◽  
Vol 396-398 ◽  
pp. 115-118
Author(s):  
Xin Gong Tang ◽  
Xing Bing Xie ◽  
Liang Jun Yan
Keyword(s):  
Oil And Gas ◽  
Supply And Demand ◽  
Mineral Resources ◽  
Underground Water ◽  
Electromagnetic Method ◽  
Complex Resistivity ◽  
West China ◽  
Controlled Source ◽  
Resistivity Method ◽  
Resource Exploration

Complex resistivity (CR) is one of an electromagnetic method which plays an important role in the exploration of oil and gas, underground water as well as solid mineral resources in recent years. Nowadays China is under fast developing and there is still a big gap between the supply and demand of mineral resources. As an effective controlled source electromagnetic method, CR method can be easily used to judge the content of resources, determine the target reservoir and select a favorable drilling area. In this paper, an introduction to CR method and its application in copper mine exploration in west China is present. The result shows that CR is an effective electromagnetic method in the exploration of deep mineral resources.

Sign in / Sign up

Export Citation Format

Share Document