Strategic partnership between Ava Group and Mining3
Quelle: AVA Group
Ava Group is at the forefront of a digital revolution within the mining industry. Mining companies are striving to realise the full benefits of evolving digital capabilities to sustain and enhance improvements in productivity, including looking at ways of using data more effectively to enhance asset management, improve reliability and introduce predictive capability. Ava Group’s products provide insights that can help mining companies reduce cost, streamline equipment maintenance and prevent safety incidents.
The first application of Ava Group’s fibre optic technology is conveyor condition monitoring, providing wear detection to pre-empt roller failure. Conveyor maintenance is a significant daily problem for the mining industry. Conventional methods of detecting bearing failure in conveyor rollers are unreliable, time-consuming and labour intensive. Overland conveyors of 5 km are commonplace and 20 km conveyors from a local mine truck dump pocket to the processing plant are becoming increasingly common. A typical conveyor can have up to 7000 bearings per km, which means 7000 potential points of failure. There have been several attempts to speed up and reduce the cost of monitoring all the bearings along a conveyor, and yet the original method of “walking the belt” observing and listening to the sound is still the most commonly used approach.
Ava Group’s solution, that combines Ava Group’s fibre optic interrogator hardware and Mining3’s signal processing algorithms, can detect a broken ball or a cracked cage in a ball race using a single fibre optic cable, running along the length of the belt. By observing idler bearings as they progressively wear and tracking the development of potential bearing seizure, imminent issues can be detected and maintenance crews can be alerted. The conveyor can be monitored from an operation centre anywhere, saving operating costs and increasing safety of personnel by reducing manual involvement. Taking a formalized approach to asset management also means data can be used to optimize maintenance strategies and reduces reliance on costly manual inspections by demonstrating ongoing compliance with operational standards.