Analysis of steel wire rope diagnostic data applying multi-criteria methods

Abstract

Steel ropes are complex flexible structures used in many technical applications, such as elevators, cable cars, and funicular cabs. Due to the specific design and critical safety requirements, diagnostics of ropes remains an important issue. Broken wire number in the steel ropes is limited by safety standards when they are used in the human lifting and carrying installations. There are some practical issues on loose wires—firstly, it shows end of lifetime of the entire rope, independently of wear, lubrication or wrong winding on the drums or through pulleys; and, secondly, it can stick in the tight pulley—support gaps and cause deterioration of rope structure up to birdcage formations. Normal rope operation should not generate broken wires, so increasing of their number shows a need for rope installation maintenance. This paper presents a methodology of steel rope diagnostics and the results of analysis using multi-criteria analysis methods. The experimental part of the research was performed using an original test bench to detect broken wires on the rope surface by its vibrations. Diagnostics was performed in the range of frequencies from 60 to 560 Hz with a pitch of 50 Hz. The obtained amplitudes of the broken rope wire vibrations, different from the entire rope surface vibration parameters, was the significant outcome. Later analysis of the obtained experimental results revealed the most significant values of the diagnostic parameters. The evaluation of the power of the diagnostics was implemented by using multi-criteria decision-making (MCDM) methods. Various decision-making methods are necessary due to unknown efficiencies with respect to the physical phenomena of the evaluated processes. The significance of the methods was evaluated using objective methods from the structure of the presented data. Some of these methods were proposed by authors of this paper. Implementation of MCDM in diagnostic data analysis and definition of the diagnostic parameters significance offers meaningful results.