Performance Monitoring Of Block Cave Mines Using Signal Processing And Waveform Analysis Of Gps Data

Discrete (digital) signal processing techniques are proving to be very valuable tools for miners using the block cave method. Waveform analysis of different measured signals associated with active mining provides valuable information on production dynamics and safe operation of the mine. For example, correlation of the 3D surface displacement velocity waveform and the production output waveform reveals a remarkably predictable time-varying physical process. Studying the geometrical and temporal relationship between these two signals opens a broad window through which new management techniques become apparent. In this paper we discuss the signal processing techniques used to study these relationships, as well as the related implications for mining. This research was carried out in association with the Chevron Mining underground molybdenum mine in Questa, New Mexico. Some of these new techniques will be integrated into the decision management process at the mine and will provide insight on ore production, draw control, and safe reclamation. The science of signal processing involves the analysis and interpretation of physical processes that vary with time. Two general categories of signals1 are recognized. A continuous signal is a waveform of varying amplitude that is continuous in time (such as a sine wave). A discrete signal is a sequence of quantized values. The independent time variable and amplitude are sampled periodically such that we only know the value and shape of the waveform at the sampling frequency. Displacements measured by a Global Positioning System (GPS) receiver are an example of this. Discrete signals may be studied in the time, frequency, autocorrelation, or wavelet domains. In this paper the amount of ore extracted from the mine and the measured surface displacements are analyzed in the time domain.