We propose a new algorithm for detecting weak changes in the mean of a class piece-wise stationary CHARN models. Through a simulation experiment, we establish the efficacy and precision of the new algorithm in detecting weak changes in the mean and accurately estimating their locations. Furthermore, we illustrate the robust performance of our algorithm through its application to welding electrical signals (WES).