scholarly journals Performance Assessment and Prediction for Superheterodyne Receivers Based on Mahalanobis Distance and Time Sequence Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Jinwen Sun ◽  
Chen Lu ◽  
Manxi Wang ◽  
Hang Yuan ◽  
Le Qi
Keyword(s):  
Neural Network ◽  
Sequence Analysis ◽  
Performance Assessment ◽  
Mahalanobis Distance ◽  
Time Sequence ◽  
Residual Error ◽  
Elman Neural Network ◽  
Receiver System ◽  
Superheterodyne Receiver ◽  
Time Sequence Analysis

The superheterodyne receiver is a typical device widely used in electronics and information systems. Thus effective performance assessment and prediction for superheterodyne receiver are necessary for its preventative maintenance. A scheme of performance assessment and prediction based on Mahalanobis distance and time sequence analysis is proposed in this paper. First, a state observer based on radial basis function (RBF) neural network is designed to monitor the superheterodyne receiver and generate the estimated output. The residual error can be calculated by the actual and estimated output. Second, time-domain features of the residual error are then extracted; after that, the Mahalanobis distance measurement is utilized to obtain the health confidence value which represents the performance assessment result of the most recent state. Furthermore, an Elman neural network based time sequence analysis approach is adopted to forecast the future performance of the superheterodyne receiver system. The results of simulation experiments demonstrate the robustness and effectiveness of the proposed performance assessment and prediction method.

Performance Assessment of Hydraulic Servo System Based on Radial Basis Function Neural Network and Mahalanobis Distance

2015 ◽  
Vol 764-765 ◽  
pp. 613-618
Author(s):  
Zhen Ya Wang ◽  
Chen Lu ◽  
Hong Mei Liu ◽  
Zi Han Chen
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Performance Assessment ◽  
Basis Function ◽  
Mahalanobis Distance ◽  
Rbf Neural Network ◽  
Residual Error ◽  
Servo Systems ◽  
Radial Basis ◽  
Hydraulic Servo

The performance assessment of hydraulic servo systems has attracted an increasing amount of attention in recent years. However, only a few studies have focused on practical approaches in this field. A performance assessment method based on radial basis function (RBF) neural network and Mahalanobis distance (MD) is proposed in this study; the method is quantized by the performance confidence value (CV). An observer model based on RBF neural network is designed to calculate the residual error between the actual and estimated outputs. The root mean square (RMS), peak value, and average absolute value are then extracted as the features of residual error, which serve as the coordinates of the feature points. Lastly, the MD between the most recent feature point and the constructed Mahalanobis space is calculated. The condition of the system is assessed by normalizing MD into a CV. The proposed method is proven to be effective by a simulation model in which leakage faults are injected. Experimental results show that the proposed method can assess the performance of hydraulic servo systems effectively.

Application Study of Load Forecasting of Central Air-Conditioning System Based on Time Sequence Analysis Method

2012 ◽  
Vol 220-223 ◽  
pp. 622-625
Author(s):  
Xue Li Zhu ◽  
Bo Dong ◽  
Yong Jun Zhu
Keyword(s):  
Sequence Analysis ◽  
Air Conditioning ◽  
Time Lag ◽  
Load Forecasting ◽  
Time Sequence ◽  
Analysis Method ◽  
Air Conditioning System ◽  
Central Air Conditioning ◽  
Heating Load ◽  
Time Sequence Analysis

With the characteristics of non-stationarity, non-linearity, time-lag of refrigeration/ heating supplying in minds, load forecasting of central air-conditioning system is carried using time sequence analysis method. Firstly, acquisition sample data of central air-conditioning system is pretreated, and random time sequence AR model of system is formulated. Then, forecasting of AR refrigeration/heating load based on Yule-walker method is conducted. In order to enhance forecasting accuracy, crossover forecasting is introduced into the load forecasting, that is, to use vertical forecasting to follow household demands for load and horizontal forecasting to track changes of weather. Then, weight cross is made to vertical and horizontal forecasting results. Finally, refrigeration/heating load forecasting software of central air-conditioning system is developed, which is used in energy-saving monitoring and control of central air-conditioning system.

NONLINEAR TIME SEQUENCE ANALYSIS

1991 ◽  
Vol 01 (03) ◽  
pp. 521-547 ◽  
Author(s):  
PETER GRASSBERGER ◽  
THOMAS SCHREIBER ◽  
CARSTEN SCHAFFRATH
Keyword(s):  
Dynamical Systems ◽  
Sequence Analysis ◽  
Lyapunov Exponents ◽  
Spectral Methods ◽  
Nonlinear Dynamical Systems ◽  
Short Review ◽  
Time Sequence ◽  
Nonlinear Dynamical ◽  
Time Sequences ◽  
Time Sequence Analysis

We review several aspects of the analysis of time sequences, and concentrate on recent methods using concepts from the theory of nonlinear dynamical systems. In particular, we discuss problems in estimating attractor dimensions, entropies, and Lyapunov exponents, in reducing noise and in forecasting. For completeness and since we want to stress connections to more traditional (mostly spectrum-based) methods, we also give a short review of spectral methods.

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