Soft Sensor for Flame Temperature Measurement and IoT based Monitoring in Power Plants

Investigation of temperature measurement from the flame colour in thermal and gas turbine power plants is of enormous significance in the realm of vision machine technology. The primary objective for this work relies on detection, recognition and understanding of colour image processing for flame colour analysis. In this effort, soft computing methods using Artificial Neural Network (ANN) model with Back Propagation Algorithm (BPA) and Ant Colony Optimisation (ACO) are used for this purpose. The central theme of this work uses the fact that the colour of the flame images is dependent on the temperature. The initial move is to describe a facet quantity for each flame image together with 10 facet rudiments, which are the brightness of flame, the area of the high temperature flame, the brightness of high temperature flame, the rate of area of the high temperature flame, the flame centroid about X and Y, orientation and the two discriminant vectors correspondingly. The superiority of the images used is improved using Curvelet transform. The conception of flame detection and classification is conceded to compute the temperature from its colour. The specimen incorporates 51 flame images, a portion of which is used for trail and testing the ANN and ACO model. Ultimately, the whole specimen flame images are recognized and classified based on the temperatures corresponding to the core of the fire ball. The results are being validated by comparing with the conventional Euclidean classifier. Demonstrations establish an effective and indigenous system for flame temperature measurement. The elucidation states that the Internet of Things (IoT) with the proposed intelligent temperature sensor is connected to the embedded computing system to monitor the fluctuation in flame temperature with respect to colour changes in order to ensure complete combustion. This scheme utilizes wearable electronics technology which constantly monitors and controls the improvement of productivity in power plants. Therefore a flame tracker is deliberated in the projected model and assessed using an archetype, consisting of Arduino UNO board, intelligent temperature sensor and MATLAB with Arduino hardware support package. The realization is used for measurement of the flame temperature with respect to combustion conditions to prevent anomalous operating circumstances thereby providing a feed forward intelligent temperature controller for maximization of flame temperature to make the environment smart. (C) 2017 Elsevier Ltd. All rights reserved.