Application of discrete wavelet transform to prediction of ram stuck phenomena

The ram assembly is important equipment in fueling machine of PHWR(Pressurized Heavy Water Reactor) plant where fuel replacement is possible while the plant is in service. Troubles in the ram assembly can cause lots of difficulties in power plant operation. The ram assembly is typically composed of the B-ram, the L-Ram and the C-Ram. The B-ram is focused in this paper because it plays the most important role in the ram assembly. Among the ram fault phenomena, ram stuck phenomena are the most frequent cases in the B-ram, which has a ball screw mechanism driven by a hydraulic motor. Ram stuck phenomena are due to ball wear and damage in ball nut that increase in proportion to the number of fuel replacement. It is required to predict ram stuck phenomena before they occur. In this paper, a method is proposed for predicting ram stuck phenomena using a discrete wavelet transform. The discrete wavelet transform provides information on both the time and frequency characteristics of the input signals. The proposed method uses the frequency bandwidths of coefficients of discrete wavelet decompositions and detail coefficients of discrete wavelet transform to predict ram stuck phenomena. The signal used in this paper is a torque-related signal such as a hydraulic service outlet pressure signal in a hydraulic driving system or a current signal in a DC motor driving system. Finally, the validity of the proposed method is shown via experiment using ball nut characteristic test equipment that simulates ram stuck phenomena due to increased ball friction in ball nut.