Prognostic and Reliability for Electrical Contacts

A prognostic model for separable electrical contacts is considered by (Ostendorf, 2014). The paper examines providing reliability to separable electrical contacts and looks at the mandatory measures for the discrete nature of the contact interface as well as the necessity of fulfilling a broad variety of product requirements. The paper also examines the formation of real and conductive contact area controls for the reliability and efficiency of an electrical contact. These processes depend on a great number of independent or interrelated factors. The variety of these factors can be divided into (a) performance factors governed by the operating conditions and (b) design-technological factors determined by fabrication characteristics of the contact unit. The paper derives a model to determine the influences of the design technological factors based on the reliability and quality of electrical contacts. The consideration of mathematical models for reliability and failure such as Weibull, Arrehenius, Hallburg- Peck and Coffin-Manson. Together with the lifetime tests and their statistical evaluation it is possible to deduce fault rates combined with the probability of failure and reliability for a newly designed contact unit. Furthermore detailed surface analytical investigations of the contact zone were performed to identify the occurrence of physical and chemical processes which are influencing the state of the contact interface and finally, the contact resistance and reliability.

A considerable body of work has been directed around the failure of electrical connectors used in integrated circuits and associated static connections subject to temperature and environmental stresses such vibration.

(Lopez et al., 2008) presents a methodology based on the physics of failure and the sequential probability ratio test, for modelling and monitoring electrical interconnects in health monitoring, and electronic prognostic applications. The resistance behaviour of an electrical contact was characterized as a function of temperature. The physics of failure of the contact technology was analysed. A contact resistance model was selected based on the a-spot radius and a function of temperature. The parameters are estimated as a power law and were fitted using the temperature characterization data using linear regression.

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The physics of failure model was evaluated with a reliability application (temperature cycle test), and was found to produce estimation errors of < 1 m Ohm during a training period. The temperature and resistance of ten sample contacts were continuously monitored during the temperature cycle test, identifying the maximum temperature and resistances for each cycle. Using the physics of failure model, maximum resistance estimates were generated for each test sample. The residual between the monitored and estimated resistance values was evaluated with the sequential probability ratio test. The method was shown to overcome the issues of traditional threshold-based monitoring approaches, providing accurate resistance estimates, and allowing the detection of abnormal resistance behaviour with low false alarm and missed alarm probabilities.

In (Lall, et al. 2012), again the leading indicators of failure has been developed to monitor the progression of fretting corrosion in electrical connectors and prognosticate remaining useful life. Connectors subjected to harsh environments may experience vibration resulting in fretting corrosion and degradation in contact resistance over time. Tin coated, rectangular-pin and socket electrical connectors have been studied. In this paper, a random vibration test profile has been used to stimulate the contact resistance degradation due to connector fretting corrosion. The contact resistance has been measured in situ using the resistance spectroscopy method in conjunction with phase sensitive detection. It has been shown that precise resistance spectroscopy and phase measurements can provide a leading indicator of failure significantly prior to the traditional definition of failure.

The prognostic approach here accepts the inputs to the system are not measureable and using the resistance measurement creates a feature vector model based on the resistance spectroscopy. The resistance change of 0.3 Ω has been used as a leading indicator of failure for the electrical connector prior to the traditional deformation of failure caused by fretting degradation. A Kalman filter was used as a recursive algorithm to estimate the true state of the electrical connector.

A technique has been developed for monitoring the structural damage accrued in ball grid array interconnects during operation in vibration environments (Lall, 2012). The technique uses resistance spectroscopy based state space vectors, rate of change of the state variable, and acceleration of the state variable in conjunction with Extended

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Kalman filter, and is intended for the pre-failure time-history of the component. Condition monitoring using the presented technique can provide knowledge of impending failure in high reliability applications where the risks associated with loss- of-functionality are too high to bear.

The future state of the system has been estimated based on a second order extended Kalman filter model and a Bayesian Framework. The measured state variable has been related to the underlying interconnect damage using plastic strain. The performance of the prognostication health management algorithm during the vibration test has been quantified using performance evaluation metrics. Model predictions have been correlated with experimental data. The presented approach is applicable to functional systems where corner interconnects in area-array packages may be often redundant.

From the literature search it can be seen quite a large body of work has been developed on ascertaining the reliability of relays via various methods, however, little work has been carried out so far in producing a prognostic solution to switching contact failure. This research proposes to remedy this, by suggesting a model based prognostic solution of the most common failure mechanism within the relay, namely, the electrical contacts.