WINS CLIENT SPACE
RVI underground storage tank (UST) inspection (VIDEO)
President Tom Hay presents at Acoustic Emission Working Group (AEWG-54) meeting in Baltimore, MD, May 2012
President Tom Hay delivers talk on NDT Applied to Bridge Inspection at Association for Bridge Construction & Design (ABCD) in Batavia, NY, April 2012
New remote visual inspection (RVI) capability - Video
DOT special permit approval for Acoustic Emission Retesting of 107A tubes
New pipeline inspection technology for Splashtron coated pipes
2013 NDT Training Course Calendar
Portable Rail Head Inspection
WINS' long range ultrasonic technology (LRUT) for rail inspection is designed to be retrofitted onto Hy-Rail vehicles. The EMATs are housed inside and aluminum enclosure to protect the electronics from the environment. Inspect your track for internal flaws in conjunction with your weekly visual inspections. The sensor cables are installed along the Hy-Rail vehicle chassis into the cab of the vehicle and connected to the ultrasonic instrumentation. In-vehicle computer, keyboard and monitor are used to alert the rail inspector to rail flaws.
The LRUT technology is designed to detect the most costly rail flaws ~ head defects. Long range ultrasound travels axially in the rail at distances ranging from a few feet to a few hundred feet depending on the application. Powerful ultrasonic waves are reflected from transverse defects and rail breaks when the longitudinally traveling wave strikes the discontinuity.
Long range ultrasound is generated efficiently in rail using non-contact electromagnetic acoustic transducers (EMATs). The EMATs travel along the rail head and introduce pulses of ultrasound into the rail head. The pulses flood the rail head with ultrasonic energy that reflect powerfully from transverse oriented rail flaws and discontinuities. The ultrasound penetrates underneath surface shelling and engine burns to detect hidden transverse flaws that are commonly missed by tradition rail flaw inspection techniques. The analysis software is embedded with artificial intelligence capabilities. Pattern recognition classifiers are used to classify defects in real-time. Each defect is tagged with GPS coordinates for follow-up inspection and reporting purposes.