Ayaz Ahmed Soomro ¹, Imtiaz Hussain Kalwar ², Kamran Kazi ², Sarang Karim Khoso ², Shahzeb Ansari ³

Affiliations
1 Quaid-e-Awam University College of Engineering, Science and Technology, Nawabshah, PK
2 Mehran University of Engineering and Technology, Jamshoro, PK
3 D1Quaid-e-Awam University College of Engineering, Science and Technology, Nawabshah, PK

Abstract

The paper aims to engineer an efficient technique for the condition monitoring of induction motor that not only provides the detection and identification of the faults but also assesses the operational condition of the motor. Induction motors possess one of the most important roles industrially and commercially. The developing faults in the motors can become catastrophic, if remain unanalyzed. The paper presents an effective novel solution to diagnose the major mechanical faults at the early possible stage by utilizing two efficient condition monitoring techniques to effectively deploy the strategies for the predictive maintenance. Primarily it employs the MCSA (Motor Current Signature Analysis), in which the faults are located by the spectral analysis of the particular harmonic components in the line current at specific characteristic frequencies generated by specific faults as the unique rotating flux. Fuzzy logic system has also been utilized, which assesses severity of the fault and operating condition of machine. The induction machine’s modular Simulink implementation has been presented that unlike other approaches provides the access to almost all parameters of the machine for analysis and control purposes. The mechanical faults specially bearing and eccentricity faults are simulated and successfully detected and localized in the results along with the severity assessment of the operational condition due to simulated faults.

Keywords

Bearing faults, Condition Monitoring, Eccentricity, Fault Diagnosis, Fuzzy Logic, MCSA.

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Shahzeb Ansari ¹, Ayaz Ahmed Soomro ¹, Imtiaz Hussain Kalwar ², Umair Saeed Solangi ¹, Abdul Sattar Noonari ¹

Affiliations
1 Quaid-e-Awam University College of Engineering, Science and Technology, Nawabshah, PK
2 Mehran University of Engineering and Technology, Jamshoro, PK

Abstract

This paper demonstrates the design and implementation of a binary distillation and collection of Ethanol-Water solution. The PLC based distillation and collection of the liquids is one of the innovative industrial automation projects. The conventional design contains a PLC based automated model of liquid distillation and collection systems, where PLC (SIMATIC S7-300) is used as the controlling brain of the system and distillation and collection are the two main units of the designed system. The distillation control system separates the homogeneous mixture of water and alcohol (ethanol) by comparing the current temperature of the solution of the continuous solution feeding to the column with the boiling points of individual compounds and collection system collects the separated solvents into the bottles placed on the conveyor belt. The monitoring and controlling of the whole systems are evaluated on the basis of temperature and level of the specific units under consideration of atmospheric pressure. Thus the accurate working of process control can lead to smooth operation of the system, preventing unwanted failures, shutdowns and providing notable cost saving and reliability.

Keywords

Collection, Distillation, Ethanol-Water Mixture, PLC SIMATIC S7 300.

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Umema Tasleem Shaikh ¹, Imtiaz Hussain Kalwar ², Tayab Din Memon ¹, Faiza Shaikh ¹

Affiliations
1 Mehran University of Engineering and Technology, Indus Hwy, Jamshoro 76062, PK
2 DHA Suffa University

Abstract

In this paper, Particle Swarm Optimization (PSO) algorithm based Adaptive Infinite Impulse Response (IIR) filter is designed. PSO algorithm is inspired by bird or fish swarm movement. PSO as global optimization technique provides advantages of simple implementation, quickly convergence providing better results and robustness for avoiding local minima problem. The designed PSO based Adaptive filter is then implemented to work as a noise canceller. Simulation results shows that the designed filter is effective with good noise suppression. The PSO based filter is also synthesized in FPGA and run fittings in small commercial devices Stratix-II and cyclone-II

Keywords

Adaptive Infinite Impulse Response (IIR) Filter, FPGA implementation, Particle Swarm Optimization, VHDL

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