Pre-alarm model of diesel vapour detection and alarm based on grey forecasting

The signal forecasting and processing is an important research direction in the sensors and instrumentation fields. In order to solve the false alarm problem in the diesel vapour detection and alarm system in engine room of ship, this paper builds an pre-alarm model based on grey forecasting theory. An experiment is designed to test the model. The results show that the model can forecasts the concentration of diesel vapour according to the sensor output with a high accuracy of large than 90%. The best recording duration time is determined to 10 min with a higher accuracy of large than 99%.

► A mathematic model is built based on grey forecasting.
► The model is used for to pre-alarm in diesel vapour detection and alarm system.
► An experiment is conducted to obtain data for the model.
► The model can forecast the concentration with an accuracy of 90%.
► The best recording duration time for in the system is 10 min.