SENSOR SYSTEM DESIGN FOR PROPELLER TEST BENCH

The sensor system is a system that functions to detect signals that come from changes in energy such as electrical energy, physical energy, chemical energy, biological energy, mechanical energy, and so on. The propeller test bench is an propeller performance testing platform prior to propeller installation on an aircraft to ensure engine suitability. The purpose of this design is to test the performance capability of the engine with the right sensor system measurement tool so that it can generate the value of thrust, rpm speed, and the temperature of an engine which will be designed to be used in the learning process to support propulsion practicum activities. The method used in this research is an experimental method of sensor system design. The design of the sensor system consists of a tachometer as a rpm measurement sensor, a thermostat as a sensor to measure the temperature of the propeller spool and temperature of the engine fin, and also a load cell as a sensor to measure the thrust value.The sensor system test results were then validated using the measurement results by the sensor manufacturer. The test was carried out on a wood-type propeller measuring 22 x 8 chords 4,5 cm and 5 cm. Based on the test results, it is known that the chord wood type propeller is 4,5 cm, at the maximum rpm is 7021.7, the resulting thrust value is 6.75. In testing the 5cm chord wood type propeller shows the maximum speed of 6977.5 produces a thrust of 6.95. Validation was carried out on the measurement results of rpm and thrust, the average error factor obtained for 4,5 cm chord wood type propeller was 0.783%, while for 5 cm chord wood type propeller the average error factor obtained was 1.0582%. From the resulting average error, it can be concluded that the measuring instrument for this sensor system has good accuracy

Barriers for Industrial Sensor Integration Design—An Exploratory Interview Study

The transition to Industry 4.0 poses new challenges for sensor integration design. The foundation of any intelligent system is the data, and the data quality depends largely on the integration of the sensor generating it. In this study, the barriers for robust sensor system design are explored through an interview study among practitioners from different industrial contexts. The aim is to explore potential challenges within different contexts and suggest possible directions for research within the field of sensor integration design. Beyond the question of new sensing technologies, the study highlights an increasing challenge of physical integration tasks and illustrates the varying requirements for development support in different industry sectors.

Analysis of Basic Principles for Sensor System Design Process Mobile Robots

This work considers general classification of SS, which is grouped according to their functional tasks and consists of three groups of devices, as result, an analysis is carried out and features that must be taken into account when designing such sensor systems are determined. The paper proposes a general principle for design of sensor systems of mobile robots, which differs in that an initial model is proposed, which will be one of key components for further design concept. General principles of sensory systems organization are proposed: sensitivity, modality, adaptation and speed.

Laser Absorption Sensing Systems: Challenges, Modeling, and Design Optimization

Laser absorption spectroscopy (LAS) is a promising diagnostic method capable of providing high-bandwidth, species-specific sensing, and highly quantitative measurements. This review aims at providing general guidelines from the perspective of LAS sensor system design for realizing quantitative species diagnostics in combustion-related environments. A brief overview of representative detection limits and bandwidths achieved in different measurement scenarios is first provided to understand measurement needs and identify design targets. Different measurement schemes including direct absorption spectroscopy (DAS), wavelength modulation spectroscopy (WMS), and their variations are discussed and compared in terms of advantages and limitations. Based on the analysis of the major sources of noise including electronic, optical, and environmental noises, strategies of noise reduction and design optimization are categorized and compared. This addresses various means of laser control parameter optimization and data processing algorithms such as baseline extraction, in situ laser characterization, and wavelet analysis. There is still a large gap between the current sensor capabilities and the demands of combustion and engine diagnostic research. This calls for a profound understanding of the underlying fundamentals of a LAS sensing system in terms of optics, spectroscopy, and signal processing.