An Automatic Procedure for Multidimensional Temperature Signal Analysis of a SCADA System with Application to Belt Conveyor Components

In this paper, a problem of interpretation and analysis of multidimensional temperature data acquired using an online monitoring system is presented. It is highlighted, that apart from the data acquisition system there is a strong need to use automatic decision making rules. A classical if then else approach i.e. the comparison of a current value of temperature with a priori assumed threshold is not possible due to the cyclic nature of machine operation and the influence of external factors as ventilation system or bulk material stream conveyed on the belt. Moreover, these thresholds are unknown and might themselves depend on the mentioned factors. It should be also noted, that in industrial data acquisition systems, there is a high probability of external disturbances, meaning that the signals should be validated and pre-processed first. Indeed, we noticed outliers related to the data acquisition system operation. The cyclic variability of temperatures has no diagnostic meaning and makes the interpretation of data and decision making difficult. In this paper, we propose an automatic data processing framework how to extract diagnostic information and present it in a user-friendly manner The analysed example data comes from a belt conveyor used in underground mining. (C) 2015 The Authors. Published by Elsevier B.V.