Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

Abstract This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter’s related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

[1]  Desire L. Massart,et al.  Noise suppression and signal compression using the wavelet packet transform , 1997 .

[2]  Khalid Sayood,et al.  Introduction to Data Compression , 1996 .

[3]  Shahin Hedayati Kia,et al.  Windings monitoring of wound rotor induction machines under fluctuating load conditions , 2011, IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society.

[4]  Enguo Zhu,et al.  Network Security Protection Solutions of Electric Power Enterprise Based on VPN Technology , 2009, 2009 International Conference on Computational Intelligence and Security.

[5]  C.D. Whelan,et al.  Trends in advanced motor protection and monitoring , 2004, IEEE Transactions on Industry Applications.

[6]  Eduardo Cabal-Yepez,et al.  FPGA-Based Online Induction Motor Multiple-Fault Detection with Fused FFT and Wavelet Analysis , 2009, 2009 International Conference on Reconfigurable Computing and FPGAs.

[7]  Peter W. Tse,et al.  A Novel, Fast, Reliable Data Transmission Algorithm for Wireless Machine Health Monitoring , 2009, IEEE Transactions on Reliability.

[8]  Arturo Garcia-Perez,et al.  FPGA-Based Online Detection of Multiple Combined Faults in Induction Motors Through Information Entropy and Fuzzy Inference , 2011, IEEE Transactions on Industrial Electronics.

[9]  Dong Sam Ha,et al.  Selective Application of Burrows-Wheeler Transformation for Enhancement of JPEG Entropy Coding , 1999 .

[10]  Khalid Sayood,et al.  Introduction to data compression (2nd ed.) , 2000 .

[11]  Carlo Concari,et al.  Differential Diagnosis Based on Multivariable Monitoring to Assess Induction Machine Rotor Conditions , 2008, IEEE Transactions on Industrial Electronics.

[12]  M. Jhaveri,et al.  Intelligent microprocessor based devices provides advanced motor protection, flexible control, and communication in paper mills , 1996, Conference Record of 1996 Annual Pulp and Paper Industry Technical Conference.

[13]  Alireza Rezvanian,et al.  Evaluation of Persian text based on Huffman data compression , 2009, 2009 XXII International Symposium on Information, Communication and Automation Technologies.

[14]  Wenxian Yang,et al.  Research on a novel online condition monitoring technique for induction machinery , 2012 .

[15]  T.G. Habetler Current-based motor condition monitoring: Complete protection of induction and PM machines , 2007, 2007 International Aegean Conference on Electrical Machines and Power Electronics.

[16]  Bhim Singh,et al.  Incipient Turn Fault Detection and Condition Monitoring of Induction Machine Using Analytical Wavelet Transform , 2014 .

[17]  Ida Pu Fundamental Data Compression , 2005 .

[18]  Robert E. Tarjan,et al.  A Locally Adaptive Data , 1986 .

[19]  Kil To Chong,et al.  Induction Machine Condition Monitoring Using Neural Network Modeling , 2007, IEEE Transactions on Industrial Electronics.