Developing an Opacity Sensor :: Opacity Sensors Technology Essays

Developing an Opacity SensorThere is a huge range of different sensors in this world, designed todetect changes in temperature, size, duration and many other importantfactors.Their ability to do this makes them valuable for use in industry, inparticular, production processes.I have chosen to develop a sensor which measures the concentration ofsolution, suitable for the factory production of pre-diluted fruitsquashes. The sensor can control the machinery via a servo-mechanism,indicating whether more squash needs to be added.The circumstance in which my sensor is to be used is an importantconsideration as it determines a suitable sensitivity and resolution.Factors to consider when designing a sensor sensitivenessThe ratio of change of output to change of input. A very sensitivesensor will give a big change of output for a small change of input. Asensor which detects very small changes of input will need to be verysensitive so these changes can be observed.ResolutionThe smallest chang e the sensor can detect in the quantity it ismeasuring. If you had a quantity which was paradeed as 0.0076, thissensor would have quite a advanced resolution (depending on what it wasmeasuring). If the last digit were fluctuating this would be themaximum resolution of the sensor as it can only just resolve a changeof that magnitude 10,000th.A cooks oven may only need a resolution of 5C whereas a babymonitoring system requires a resolution of 0.5 1C.Response timeThe time a sensor takes to respond to a change in input. If changesoccur more rapidly than this thence they will usually be averaged out.The response time should be suitable to detect important changes asthey occur. SystematicMost sensors are affected by changes in temperature, even those thatarent designed to detect them. Some sensors may also be affected byother environmental changes depending on their methods of detection,for exemplification a LDR might produce different readings on a sunny day ifthe whole system isnt enclosed. Such influences will produce readingsthat display the correct trend but each reading is erroneous by thesame amount. For this reason systematic errors are difficult to detectand an only by making another more accurate measurement. Today smartsystems process information to compensate for disturbing influences.Noise, random error, fluctuationsThe input signal may quaver or the sensor itself may generatenoise. Unsystematic variations are present in all experimental dataand their size determines the reliability of the data and limits the clearcutness with which a measurement can be made. Taking an average overrepeated measurements can improve the final result