Influence of characteristics of time series on short-term forecasting error parameter changes in real time

Abstract

Abstract. The impact of physical factors, such as temperature and others, leads to a change in the parameters of the technical object. Monitoring the change of parameters is necessary to prevent a dangerous situation. The control is carried out in real time. To predict the change in the parameter, a time series is used in this paper. Forecasting allows one to determine the possibility of a dangerous change in a parameter before the moment when this change occurs. The control system in this case has more time to prevent a dangerous situation. A simple time series was chosen. In this case, the algorithm is simple. The algorithm is executed in the microprocessor module in the background. The efficiency of using the time series is affected by its characteristics, which must be adjusted. In the work, the influence of these characteristics on the error of prediction of the controlled parameter was studied. This takes into account the behavior of the parameter. The values of the forecast lag are determined. The results of the research, in the case of their use, will improve the efficiency of monitoring the technical object during its operation. IntroductionThe need for the advanced condition monitoring of a technical object to prevent and control the occurrence of emergency situations in order to eliminate them with minimal impact makes the formulation and implementation of the problem of determining the predicted values of the parameters, as well as the projected assessment of the status of the individual parameters of a technical object or a set of real-time, relevant and timely [1][2][3]. Modern development of microprocessor technology allows one to realize this task using microprocessor modules in information systems engineering of complex objects such as active safety systems and vehicle inertial navigation [4]. Estimates implemented in microprocessor modules provide a high dynamic response to the situation. To perform predictive assessment of the technical parameters of the object by means of the microprocessor module, it is advisable to use simple models to get results in real time without a significant load on the microcontroller module. Of interest are the models, which are based on methods of analysis and forecasting of time series [5][6][7]. Numerous methods have been developed on the basis of time-series forecasting models [8][9][10][11][12]. However, these models are quite complex to use microcontroller in the background.This article describes the model and values of the prediction algorithm for rapidly varying physical quantity based on the use of multiple exponential, smoothing its time series [5,6]. Efficiency of the model and the algorithm is assessed based on the vehicle acceleration vector of projections of the change data values measured by the three-axial accelerometer in actual driving conditions.