Self-propelled Mining Machine Monitoring System - Data Validation, Processing and Analysis RADOSLAW ZIMROZ 1 , 2* ,JACEK WODECKI 2 , ROBERT KRÓL 1,2 MAREK ANDRZEJEWSKI 3 , PAWEL SLIWINSKI 3 and PAWEL STEFANIAK 1 Self-propelled Mining Machines constitute large group of basic machines in underground copper ore mining in Poland. Depends on their purpose and design there are several key parameters that (according to mining companies suggestions) should be monitored and processed in order to assess machine efficiency, its condition, proper operation (according to manufacturer recommendation), human factors influence and so on. Several studies have been done regarding selection of parameters, developing algorithms of data processing, data storage and management and finally reporting and visualization of knowledge extracted from measured data. Although serious efforts have been done in this field, there is still some work to do. In this paper, a new look on the problem will be presented including data acquisition process validation, importance of data quality for automatic processing and analysis. Finally new approach for signal analysis will be proposed and compared with already existing parameters. Also kind of target re-definition attempt will be discussed. All discussed issues will be illustrated using real data acquired during machine operation. Keywords: Self-Propelled Mining Machine, Monitoring System, Data Processing, Data Analysis Introduction Self-propelled mining machines are commonly used in the biggest mining company – KGHM Polish Copper. Their design and operation depends on machine type, basically one can classify them into three categories: i) machines and equipment for mining and preparation of mining faces (drilling and bolting rigs, vehicles for ripping), ii) self-propelled machines for short distance haulage (loaders and haul trucks) and iii) machines for auxiliary works. Machines from two first groups are the most important due to their number, role of their operation in production line and place of their work. The production process in the underground mine is complex process, which consists of preparing for mining operation (excavation), drilling-blasting, hauling, bolting etc. To effectively manage mining work, it is the necessary to introduce IT support for maintenance and operation management. It means that managing the process of mining production requires the acquisition of basic information about the processes. Monitoring the processes requires the installation in an underground mine a wide variety of sensors that control each sub-process components such as mobile machinery performance, efficiency of work they do, monitoring the technical condition of selected elements of machinery, etc. There are some recent international initiatives in Europe (SMIFU, I2Mine [1,2]) that face up these challenges. This paper might be treated as introduction to the practical aspects of the problem. A key issue is to understand what kind of information is expected and what departments are interested in acquisition of such information. This step has been fully investigated by interdisciplinary team working for KGHM several years ago [3,4]. They proposed definitions of variety of indicators estimated based on online monitoring system. Now, investigation on practical implementation of these ideas, their validation and further extension are carried out in parallel by two collaborating teams, namely KGHM Cuprum R&D working in frame of Work Package 1 of I2Mine project and engineers in KGHM. It should be said, that there are several good examples of successful work on similar issues, 1 Machinery Systems Division, Wroclaw University of Technology, Na Grobli 15, 50-421 Wroclaw, 2 KGHM CUPRUM Ltd CBR Sikorskiego 2-8 , 53-659 Wroclaw Corresponding author: R.Zimroz 3 KGHM Polska Miedź SA, Lubin