Developing an Opacity Sensor :: Opacity Sensors Technology Essays

Developing an Opacity SensorThere is a huge range of different sensors in this world, designed todetect transfers in temperature, size, distance and many other importantfactors.Their ability to do this makes them precious for use in industry, inparticular, toil paradees.I have chosen to develop a sensor which measures the concentration ofsolution, suitable for the factory production of pre-diluted fruit rackes. The sensor can control the machinery via a servo-mechanism,indicating whether more squash subscribes to be added.The context in which my sensor is to be utilize is an important make outation as it determines a suitable sensitivity and resolution.Factors to consider when designing a sensorSensitivityThe ratio of change of take to change of input. A very sensitivesensor will wee a big change of output for a small change of input. Asensor which detects very small changes of input will study to be verysensitive so these changes can be observed. closedownThe smallest chan ge the sensor can detect in the quantity it ismeasuring. If you had a quantity which was displayed as 0.0076, thissensor would have quite a broad(prenominal) resolution (depending on what it wasmeasuring). If the last digit were fluctuating this would be theupper limit resolution of the sensor as it can only just propose a changeof that magnitude 10,000th.A cooks oven may only need a resolution of 5C whereas a babymonitor system requires a resolution of 0.5 1C.Response periodThe time a sensor takes to respond to a change in input. If changes blow over more rapidly than this then they will usually be averaged out.The solvent time should be suitable to detect important changes asthey occur. authoritativeMost sensors ar impact 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 example a LDR efficiency produce different readings on a sunny day ifth e on the whole system isnt enclosed. Such influences will produce readingsthat display the manufacture trend but each reading is erroneous by the equivalent 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 fluctuate or the sensor itself may generatenoise. Unsystematic variations are present in all experimental dataand their size determines the reliableness of the data and limits theprecision with which a measurement can be made. fetching an average overrepeated measurements can improve the final impart