Gaussian Process Regression Analysis of Passive Intermodulation Level and DCR for Spring Contacts

In modern consumer electronic devices, for the purpose of having easier access for assembly and repair in a compact designed product, metallic connection components such as springs are universally used for metallic connections between modules or chassis. However, the non-ideal metallic connections tend to have a certain level of non-linearity. Therefore, significant attention has been aroused recently because the passiveintermodulation (PIM) can degrade the radio-frequency (RF) antennas’ receiving quality especially when the unsatisfying spring connections are placed near the RF antenna. Typically, advanced and expensive instruments and components are required to estimate the non-linearity levels of the springs. However, those instruments are usually not available for the manufacturing factories for massive tests. This paper is focused on investigating the feasibility of estimating the nonlinearity level of spring contacts using DC resistance (DCR), which has easier access to be tested with much lower cost. Study showed that the DCR, when under certain conditions, can serve as the alternative figure of merit for PIM prediction. Then, the Gaussian process regression (GPR) analysis based on measured data can provide a statistical estimation to the generated PIM from the DCR values.