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This paper presents an instrumentation system to measure the degradation in lubricating oil using a bare, tapered and bent multi-mode optical fiber (BTBMOF) sensor probe and a temperature probe. The sensor system consists of (i) a bare, tapered and bent multi-mode optical fiber (BTBMOF) as optical sensor along with a laser source and a LDR (Light Dependent Resistor) as detector (ii) a temperature sensor (iii) a ATmega microcontroller based data acquisition system and (iv) a trained ANN for processing and calibration. The BTBMOF sensor and the temperature sensor are used to provide the measure of refractive index (RI) and the temperature of a lubricating oil sample. A microcontroller based instrumentation system with trained ANN algorithm has been developed to determine the degradation of the lubricating oil sample by sampling the readings of the optical fiber sensor, and the temperature sensor.

Now days, computer technology mostly focusing on storage space and speed With the rapid growing of important data and increased number of applications, devising new approach for efficient compression and encryption methods are playing a vital role in performance. In this work, burrows wheeler transformation is introduced for pre processing of the input data and made several performance analysis experiments over different compression techniques for various types of text files and improved compression ratio has been found by applying burrows wheeler transform as pre-processing step.

This paper describes an optical fiber sensor and temperature sensor-based instrumentation system to measure the moisture content in transformer oil. The sensor system consists of (i) Diode Laser Source, (ii) a bare and bent multimode fiber as sensor probe, (iii) an LDR as detector, (iv) LM35-based temperature sensor, and (v) microcontroller system having a trained ANN for processing and calibration. The bare and bent optical fiber sensor and the temperature sensor LM35 are used to provide the measures of refractive index (RI) and temperature of a transformer oil sample. An ATmega32-microcontroller-based system with trained ANN algorithm has been developed to determine the moisture content of the transformer oil sample by sampling the readings of the bare bent optical fiber sensor and the temperature sensor.