The invention relates to a visual intelligent
monitoring system and method for the ash deposition
corrosion wear state of medium-low temperature
smoke heat exchange equipment, which are characterizedin that actual
smoke is adopted, the actual operation working condition is fitted, the
smoke inlet temperature and air speed can be adjusted, the working conditions of different smoke temperatures andflow speeds of the whole smoke
system are simulated, and online
monitoring data are provided; a resistance probe and an
eddy current sensor are used for monitoring the conditions of heat exchange,
corrosion resistance,
wear resistance, ash deposition, coking and the like of the heat exchange tube; based on the
convolutional neural network and an intelligent identification and analysis model of amonitoring probe state image, an image
data set is made by using a large number of on-site pictures of the monitoring probe and the calculated
heat transfer coefficient, ash deposition
thermal resistance,
corrosion rate and wear rate, and accurate matching of the image and the heat exchange tube state is realized; the intelligent identification and analysis model adopts a
convolutional neural network algorithm model to carry out pixel-level
processing on the image, state image features are accurately identified, and the accuracy of an analysis result is high; and the
heat transfer coefficient,the ash deposition
thermal resistance, the corrosion rate and the wear rate of the heat exchange tube are analyzed by images.