ZSCJ127S steel wire rope laser strong magnetic online detection device

The ZSCJ127S steel wire rope laser+strong magnetic (permanent magnet) online detection device accurately judges the breakage and diameter shrinkage of the steel wire rope through unique laser and magnetic sensor probes and acquisition components. The LF and LMA judgment rates can reach over 99.7%, thus accurately determining the service life of the steel wire rope. Invention patent number ZL20151009465.8.

【Product Principle】

The principle of strong magnetic (permanent magnet) detection is adopted, which means that the permanent magnet magnetizer guides the magnetic energy into the steel wire rope, generates a magnetic field at the broken wire or worn area on the steel wire rope, and the magnetic sensitive device arranged in the middle of the magnetizer captures this magnetic field information and converts it into a voltage signal, ultimately forming the detection and evaluation basis for the presence of broken wire or wear. This testing principle strictly follows international standards such as ASTM E1571-11 in the United States and EN 12927-8 in Europe, as well as the national standard GM/T 21837-2008 Electromagnetic Testing Methods for Ferromagnetic Steel Wire Ropes.

Combining the theory of strong magnetic testing and laser detection of changes in the   diameter of steel wire ropes, first, through strong magnetic testing, identify the parts with significant changes in magnetic signals, that is, the parts with a high possibility of wire breakage. At the same time, measure the diameter changes of steel wire ropes through laser detection, and comprehensively obtain the usage status of steel wire ropes.

By using advanced laser technology to simultaneously detect the diameter shrinkage of steel wire ropes, real-time data on wire breakage and diameter shrinkage can be obtained. Through corresponding software technology, data recording and analysis can be achieved, and safety assessment reports can be provided within a certain time interval. When dangerous situations are detected, warning functions can be implemented, which can predict dangerous situations early and   greatly improve the level of safety production.