Systems and methods for rope evaluation

A method of analyzing a rope to estimate its residual break strength (RBS), the method comprising:

• training a multi-layered neural network to recognize rope damage and estimate an RBS for the rope under study, wherein training the multi-layered neural network to recognize rope damage and correlate it to an RBS comprises:
• collecting high-resolution visual data of a plurality of sample ropes, each sample rope having a known rated RBS and each having experienced an amount of a predetermined type of damage activity;
• extracting visual features of damaged areas of each rope;
• resolving each visual feature into a damage type and clustering damage type exemplars;
• breaking each sample rope to determine an actual RBS for each rope;
• and
• classifying the visual data via determined RBS, specific to product type and damage mode;
• receiving job and product data related to the rope under study;
• paying out a studied length of the rope under study;
• spooling back the paid out length of the rope under study while capturing high-resolution visual data and sensor data of the rope as it spools;
• and
• providing the captured data to the trained multi-layered neural network to generate an estimate of RBS for the rope under study.