Seismic multiple events – a study on signals’ separation

In this paper we investigate an issue of multiple seismic events. Such events might occur in the case of both natural and mine-induced seismicity. In this paper we investigate an issue whether the distances between two overlapping impulses can be derived from a noisy seismic vibration measurement if the impulses are not equally spaced in time. Such distances might be therefore used for localization of the events or even for detection if more than one event occurred. The methodology is based on minimum entropy deconvolution (MED) and automatic peak finding. Simulated data analysis are performed in order to examine MED with different distances between events. Moreover, comprehensive simulated data analysis provide recommendations regarding MED filter size

Time-varying group delay as a basis for clustering and segmentation of seismic signals

In this paper the applications of group delay in seismic vibration signals analysis are discussed. A method which bases on the autoregressive model with sliding-window is used to track volatility of signal’s properties in time. The analysis of time-frequency maps of group delay can be used in a process of distinguishing signals of different characteristics. Moreover, the method is robust for the different parameters of the sliding-window AR model. In the article applications of the time-frequency maps of group delay in a signal segmentation and clustering are also discussed. In seismic analysis an ability to distinguish signals with different seismic nature is very important, especially in case of safety in copper-ore underground mines. Creation of tools for revealing the origin of vibration will have positive impact on evaluation of hazard level

Seismic signals discrimination based on instantaneous frequency

In this paper a problem of seismic vibration signals discrimination and clustering is investigated. We propose two criteria based on instantaneous frequency (IF) of the seismic signal. IF of a raw multicomponent signal is meaningless and a decomposition must be performed in order to obtain a monocomponent signal. One of the possible solutions incorporates the Hilbert-Huang transform. It is based on Empirical Mode Decomposition (EMD) algorithm. It is a data-driven procedure which calculates so called Intrinsic Mode Functions (IMFs) and a Residuum, which added all together give the raw signal. One of the proposed criteria quantifies distribution of the IF through the signal and provide limited information about volatility of IF throughout the entire signal (for a given monocomponent). The second criterion gives information about the most frequently occurring instantaneous frequency in the considered monocomponent. Usefulness of IF in discrimination of seismic vibration signals is validated by using considered criteria for clustering of seismic signals

Seismic signal segmentation procedure using time-frequency decomposition and statistical modelling

In the paper a novel automatic seismic signal segmentation procedure is proposed. This procedure is motivated by analysis of real seismic vibration signals acquired in an underground mine. During regular mining activities in the underground mine one can expect some seismic events which appear just after the mining activity, e.g. blasting procedures, provoked relaxation of rock and some events that are unexpected, like natural rock burst. It often happens that, during one signal realization, several shocks (events) appear. Apart from two main sources of events (i.e. rock burst and blasting), other activities in the mine might also initiate seismic signal recording procedure (for example machine moving nearby the sensor). Obviously, significance of each type of recorded signal is very different, its shape in time domain, energy and frequency structure (i.e. spectrum of the signal) are different. In order to recognize these events automatically, recorded observation should be pre-processed in order to isolate a single event. The problem of signal segmentation is investigated in literature, several application domains might be found. Although, there are just a few works on seismic signal segmentation. In this paper we propose to use a time-frequency decomposition of the signal and model each sub-signal at every frequency bin using statistical methods. Narrowband components are much easier to search for so called structural breakpoint, i.e. time instance when properties of signal significantly change. It is obvious that simple energy-based methods applied to raw signal fail when one event begins before the previous one relaxed. In order to find beginning and end of a single event we propose to use measures based on empirical quantiles estimated for each sub-signal and, finally, aggregate 2D array into 1D probability vector which indicates location where statistical features has switched from one regime to another one. The proposed procedure can be applied in order to improve time domain isolation of single event for the case, when duration of signal acquisition is longer than duration of the event or to isolate single event from sequence of events (recorded for example during blasting)

Features based on instantaneous frequency for seismic signals clustering

Seismic signals discrimination is a multidimensional problem since recorded events may vary in terms of type, location, energy, etc. Recently, two discrimination features based on instantaneous frequency (IF) were proposed by the Authors. The first of these features is determined by distribution of the signals’ first Intrinsic Mode Function’s (IMF) IF. The second one is a particular simplification of the previous one as it gives information about the most frequently occurring instantaneous frequency in the considered first IMF. In order to exhibit features’ potential in distinguishing of seismic vibration signals, one has to use clustering algorithms. The features were already subjected to k-means algorithm. In this paper we show results of agglomerative hierarchical clustering (AHCA) and compare it with outcomes of k-means. In order to test optimal number of clusters, method based on average silhouette was accomplished. The results are illustrated by analysis of real seismic vibration signals from an underground copper ore mine

Improvements in methods for monitoring anchor casings in mining excavations of KGHM Polska Miedź S.A. mines

This article presents the results of works carried out by KGHM CUPRUM Sp z o.o. CBR (Research and Development Centre), on behalf of KGHM Polska Miedź SA. It is aimed at improving previously used monitoring methods of mine excavation anchor casings used in underground copper ore mines of KGHM Polska Miedź S.A. It presents a method allowing for continuous measurement and recording of load changes in instrumented anchors. This method was developed by request of KGHM Polska Miedź S.A. Particular attention was paid to issues related to the impact of dynamic changes of rock formation pressure on the excavation in anchor casing

Górnictwo rud metali nieżelaznych w dolinie Bystrzycy a zamek Grodno

The article discusses the issues of mining works from the Middle Ages and early modern period (until 1618), carried out in the region of the Bystrzyca river valley, in the vicinity of Grodno Castle (the area located on the border of three meso-regions: the Sowie Mountains and the Wałbrzyskie Mountains and Foothills). The chronology of local mining probably dates back to the Middle Ages; however, the best documented reports refer to mining works carried out in the 16th century. They were undertaken both in the territory of the Grodno Castle fiefdom – mainly in Dziećmorowice – and in the neighboring villages: Schlesierthal, Modliszów, Lubachów and Bystrzyca Górna. The remains of former mining works have been the subject of mining archeology research for years. A significant part of them was entered in the register of sites included in the Archaeological Picture of Poland program. The authors of the article presented the most important historical mining excavations in the given area and documentation related to the individual sites.W artykule omówiono zagadnienia dotyczące prac górniczych z okresu średniowiecza i wczesnego okresu nowożytnego (do 1618), prowadzonych w rejonie doliny rzeki Bystrzycy, w sąsiedztwie zamku Grodno (obszar położony na granicy trzech mezoregionów: Gór Sowich oraz Gór i Pogórza Wałbrzyskiego). Chronologia tutejszego górnictwa sięga zapewne okresu średniowiecza, najlepiej udokumentowane są jednak przekazy odnoszące się do prac górniczych prowadzonych w XVI w. Podejmowano je zarówno na obszarze lenna zamku Grodno – głównie w Dziećmorowicach – jak i w sąsiednich miejscowościach: wsi Schlesierthal, w Modliszowie, Lubachowie oraz Bystrzycy Górnej. Pozostałości dawnych robót górniczych są od lat przedmiotem badań archeologii górniczej. Znaczna ich część włączona została do ewidencji stanowisk ujętych w programie Archeologicznego Zdjęcia Polski. Autorzy artykułu przedstawili najważniejsze z historycznych wyrobisk górniczych na omawianym obszarze oraz dokumentację związaną z poszczególnymi stanowiskami

Stochastic Modelling as a Tool for Seismic Signals Segmentation

In order to model nonstationary real-world processes one can find appropriate theoretical model with properties following the analyzed data. However in this case many trajectories of the analyzed process are required. Alternatively, one can extract parts of the signal that have homogenous structure via segmentation. The proper segmentation can lead to extraction of important features of analyzed phenomena that cannot be described without the segmentation. There is no one universal method that can be applied for all of the phenomena; thus novel methods should be invented for specific cases. They might address specific character of the signal in different domains (time, frequency, time-frequency, etc.). In this paper we propose two novel segmentation methods that take under consideration the stochastic properties of the analyzed signals in time domain. Our research is motivated by the analysis of vibration signals acquired in an underground mine. In such signals we observe seismic events which appear after the mining activity, like blasting, provoked relaxation of rock, and some unexpected events, like natural rock burst. The proposed segmentation procedures allow for extraction of such parts of the analyzed signals which are related to mentioned events