The fault or mechanical flaw causes several feeble fluctuations to the position signal. The identification of these oscillations by the encoders may help to determine the performance of the machine and the health conditions. In operations, the trend is usually several orders higher than the interested magnitude fluctuations, making it hard to identify feeble swings without signal deformity. Besides, the swings can be intricate, and the amplitude can be changed under a non-stationary operating condition. In order to overcome this problem, the singular spectrum analysis (SSA) is suggested to detect the feeble position oscillations of the rotary encoder signal in this article. It allows the complex signal of the encoder to be reduced to a variety of explainable noise-containing components, a collection of periodic oscillations and a trend. The numerical emulation reveals the achievement of the technique; it demonstrates that the SSA is superior to the empirical mode decomposition (EMD) in terms of accuracy and ability. In addition, rotary encoder signals from the robot arm are evaluated to identify the causes of oscillation at junctions during industrial robot movements. The proposed route for the robotic arm is proven, feasible and reliable.
