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Development of a prototype for oil analysis in real time, to predict failures in transport & cargo mining equipment.

Smoa.Cl aims at prototyping a system for real-time in-motion analysis of hydraulic oils and engines in mining transport and machinery.The system will act in real working conditions collecting relevant data that will be centralised and processed through mathematical models for early failure diagnosis

In mining industry production processes, such as mineral extraction, are very intensive, requiring a systematic maintenance schedule to ensure the maximum availability of the machinery. This situation becomes more complex when the prices of the product go down and it is necessary to decrease more and more the times of detention, without risking unexpected failures. In this context, predictive failure prevention mechanisms are essential and thus, improving the maintenance process and getting accurate and on-time vital information of the mining transport and machinery. Unlike other technologies, the proposed solution will be able to measure the direct impact that working conditions have on the wear of the critical elements of these machines, in terms of internal and external contaminants. The monitoring process will be performed in real time, in motion and with the possibility of generating prognosis models that allow to estimate reliability and risk in the short, medium and long term. The system will be designed to be tolerant/resistant to extreme external conditions (such as external vibrations, load and temperature changes, etc...) so that its effectiveness will remain unaffected by operating conditions as demanding as those of the mining sector. The system that the SMOA.cl Project aims to develop includes three main components: 1. An advanced optical sensor for the measurement of lubricants, which is installed in the transport and load machinery to be monitored and connected to the fluid system. The module must be able to work while the transport is in motion, collect data from contaminated and dark fluids and process and transmit it to the monitoring centre. This sensor also has the ability to deliver visible and audible alarms locally, in case of detecting critical levels of contamination in the lubricants, in order to avoid catastrophic failures or greater hazards for people. 2. Advanced NIR sensors aimed at measuring and monitoring external contaminants that may reduce the efficiency of the engines and shorten their lifetime, as well as to analysing the efficiency of the engine by measuring the generation of soot in the engine combustion process. This functionality will allow decision-making mechanism to improve the efficiency of the machines and control the contamination. 3. Predictive Monitoring and Analysis Centre: The central technological platform that will be implemented to gather and process the collected data. Advanced mathematical and machine learning algorithms will be designed and developed inside the platform in order to determine the machinery status and perform an accurate predictive maintenance. Historical data will be used by machine-learning techniques to improve the failure detection and prediction mechanisms. The global system aims to detect typical elements of the wear in critical components of diesel engines as gears and power generation elements (combustion process), as well as to monitor the lube oil degradation. Classifying this variables according to their type, source and concentration in the time, and crossing them with the machine operational conditions as loads, temperatures, speed, accelerations, will provide a very advanced prognosis to estimate the risk of failure and as consequence the operational risk.
Acronym: 
SMOA.CL
Project ID: 
11 241
Start date: 
02-05-2017
Project Duration: 
18months
Project costs: 
340 000.00€
Technological Area: 
Electrical Engineering and Technology / Electrical Equipment
Market Area: 
Industrial measurement and sensing equipment

Raising the productivity and competitiveness of European businesses through technology. Boosting national economies on the international market, and strengthening the basis for sustainable prosperity and employment.