In this study, contribution evaluation method applying Independent Component Analysis (ICA) was proposed. The necessity of applying ICA to the contribution evaluation was investigated through numerical simulation. The simulation modeled a scenario where the vibration/noise sources were physically overlapped in a small space, and their frequency characteristics were similar. For comparison between the conventional contribution evaluation method and the proposed method, the contribution evaluation was performed using the ordinary and partial contribution evaluation methods. Through this analysis, it was confirmed that the proposed method can identify contributions by restoring the signal when the frequency characteristics of the vibration/noise sources were similar, and their positions overlapped. These results confirm that the contribution evaluation method based on independent component analysis is effective in appropriately analyzing vibration/noise sources when their frequency characteristics are similar, and their positions overlap.

In this study, the pre-stress characteristics of magnetic rheological rubber, an intelligent material widely applied to mechanical systems, are measured. Intelligent materials are substances that change their properties in response to external inputs and are extensively used in mechanical systems. Magnetic rheological rubber is a representative intelligent material that can exhibit variable characteristics depending on the conditions. When measuring the physical properties of magnetic rheological rubber, it is placed in a magnetic field application device, where a magnetic field is applied, and the material is subjected to pre-stress. Similarly, when manufacturing intelligent mechanical systems using magnetic rheological rubber, pre-stress is induced by components used to apply the magnetic field. Generally, when a material is subjected to pre-stress, its properties change. Consequently, the performance of magnetic rheological rubber under pre-stress also varies. If the characteristics of the material under pre-stress change, the expected performance during design may deviate, leading to differences in the mechanical system's performance from the intended design. This variability makes it challenging to design mechanical systems based on intelligent materials, highlighting the importance of experimentally investigating their characteristics. Therefore, this study measures and identifies the pre-stress characteristics of magnetic rheological rubber under pre-stress. These findings can be applied to improve the measurement methods and design approaches for magnetic rheological rubber in pre-stressed conditions.