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How to detect the service life of the connector

the service life of the connector is the primary index to measure the reliability of the performance of the connector. With the increasing requirements for the fault-free performance of electronic products, improving the service life of the connector design has become a design orientation.

 

 

In addition, the increasing competition in the market also requires designers to find suitable materials in non-expensive alloys to reduce the cost of connectors.In many cases, the combined result of these trends is that the copper alloy of the connector operates closer to its performance limit.

 

 

Initial contact force is an important factor in connector design and material properties. Since the elastic deformation will be transformed into plastic deformation in the contact, the stress release will lead to the reduction of the contact force. If the contact force falls below a critical level, the contact will fail.

 

 

Therefore, predicting stress release as a function of time and temperature is naturally a key factor in ensuring connector reliability. LHE will discuss stress release testing to predict connector life

 

 

Stress release data are an effective tool for designers to predict the service life of electronic connectors and enable them to make decisions about the choice of contact materials based on the available data. These data are now widely used in the computer, communications and automotive electronics industries.

 

At present, data about the life cycle of products is very scarce, especially in the field of computers. Not only that, but it is a much more useful piece of data for shortening product development cycles and lifecycles.

 

 

Stress release data is used by most connector designers primarily to narrow the choice of contact materials according to application requirements. However, many designers are also seeking appropriate testing methods to more accurately predict connector life characteristics. This can greatly reduce the number of samples required for testing and the associated costs of testing many samples.

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