As we stepped into the new millennium, the inspection of cable connectors and assessing their cleanliness required the use of microscopes. Technicians had to rely on their eyesight to examine cable connectors. Exposing themselves to personal injury risks each time they accessed a cable connector’s end face.
Fast forward to mid-2005, and the eye care community received a welcome advancement: the introduction of fiber inspection probes designed specifically for cable connectors. These probes could display an image of the cable connector’s end face on an LCD screen instead of directly on a technician’s retina.
However, interpreting this image remained a challenge when it came to assessing cable connector cleanliness. Determining what qualified as a defect or contaminant still depended on the technician’s knowledge and gut instinct, especially when it came to cable connectors. Depending on factors like focus quality, image centering, and other parameters, there was always room for misinterpretation.
By 2010, the landscape changed again with the development of intelligent analysis software for cable connector inspection and cleanliness, aligned with the IEC standard. This software had the capability to automatically detect and analyze defects in cable connectors, highlight them on the display screen, and provide an overall pass-fail status. This advancement aimed to eliminate the burden of interpretation and human error from the equation when dealing with cable connectors. Or did it?
Regardless of the sophistication of onboard intelligence, issues like poor focus and subpar image capture could still lead to errors when assessing cable connectors. Frequently, an out-of-focus speck, scratch, or trace might not even appear on the screen when inspecting cable connectors. In such cases, the intelligent software might erroneously give the cable connector a passing grade when it shouldn’t have—a phenomenon known as a ‘false positive’ when dealing with cable connectors. This situation can be summed up by the age-old adage: garbage in, garbage out.
Figure 1 (shown below) offers a visual comparison between manual centering and focusing on cable connectors and their automated counterparts. The traditional approach involved inspecting the cable connector, cleaning it, and re-inspecting it (using the manual focus probe) until it passed. Subsequently, the same cable connector underwent inspection with an automated unit designed specifically for cable connectors.
[Figure 1: Image comparison between manual and automated centering and focusing on cable connectors]
Conclusion
The adoption of automated solutions has undoubtedly improved the efficiency of cable connector inspection and cleanliness assessment. Reducing the risk to technicians and providing more consistent results, especially in the context of cable connectors. However, it’s essential to recognize that even with these advancements, certain challenges persist when dealing with cable connectors. Understanding the limitations of automated systems and ensuring proper calibration and maintenance remain crucial for achieving accurate and reliable results in the world of cable connectors.