Recognition of Microseismic and Blasting Signals in Mines Based on Convolutional Neural Network and Stockwell Transform

The microseismic monitoring signals which need to be determined in mines include those caused by both rock bursts and by blasting. The blasting signals must be separated from the microseismic signals in order to extract the information needed for the correct location of the source and for determining the blast mechanism. The use of a convolutional neural network (CNN) is a viable approach to extract these blast characteristic parameters automatically and to achieve the accuracy needed in the signal recognition. The Stockwell Transform (or S-Transform) has excellent two-dimensional time-frequency characteristics and thus to obtain the microseismic signal and blasting vibration signal separately, the microseismic signal has been converted in this work into a two-dimensional image format by use of the S-Transform, following which it is recognized by using the CNN. The sample data given in this paper are used for model training, where the training sample is an image containing three RGB color channels. The training time can be decreased by means of reducing the picture size and thus reducing the number of training steps used. The optimal combination of parameters can then be obtained after continuously updating the training parameters. When the image size is 180 × 140 pixels, it has been shown that the test accuracy can reach 96.15% and that it is feasible to classify separately the blasting signal and the microseismic signal based on using the S-Transform and the CNN model architecture, where the training parameters were designed by synthesizing LeNet-5 and AlexNet

Time-frequency analyses of blasting vibration signals in single-hole blasting model experiments

With common horseshoe cavern in underground engineering as the prototype, three single-hole blasting model experiments have been carried out. And coupled SPH-FEM approach is adopted for analyzing the limit effect of pre-excavated horseshoe cavern on blasting crater. During the experiment, the blasting vibration signals on the top surface of cemented sand model have been recorded. Then Hilbert-Huang transform has been applied to analyzing the time-frequency characteristics of recorded blasting vibration signals. Both experiment results and numerical cases indicate that the range of blasting crater is controlled effectively by pre-excavating horseshoe cavern, and the limit effect of pre-excavating on blasting crater has a close connection with its length. Moreover, the 50 mm pre-excavated horseshoe cavern presents an amplification effect in blasting vibration effect both along the blasthole direction and perpendicular to the blasthole direction, and it also demonstrates a weaken effect in the main blasting vibration frequency of vertical blasting vibration signal. HHT analyses of vertical blasting vibration signals show that single-hole blasting vibration signals present a centralized distribution in time domain and an uneven distribution in frequency domain. The dominant energy of blasting vibration signal is distributed in several IMF components, where main blasting vibration frequency locates. When cutting the charge, the blasting vibration effect will be reduced, while the main blasting vibration frequency of blasting vibration signal will be increased

Analysis of vibration and acoustic signals for noncontact measurement of engine rotation speed

The non-contact measurement of engine speed can be realized by analyzing engine vibration frequency. However, the vibration signal is distorted by harmonics and noise in the measurement. This paper presents a novel method for the measurement of engine rotation speed by using the cross-correlation of vibration and acoustic signals. This method can enhance the same frequency components in engine vibration and acoustic signal. After cross-correlation processing, the energy centrobaric correction method is applied to estimate the accurate frequency of the engine's vibration. This method can be implemented with a low-cost embedded system estimating the cross-correlation. Test results showed that this method outperformed the traditional vibration-based measurement method.Web of Science203art. no. 68

SYNTHESIS OF SINGLE-HOLE VIBRATION WAVEFORMS FROM A MINING BLAST

In mining engineering, blast-induced ground vibration has become one of the major concerns when production blasts are conducted, especially when the mining areas and the blast sites are near inhabited areas or infrastructure of interest. To comply with regulations, a vibration monitoring program should be developed for each mining operation. The vibration level, which is usually indicated by the peak particle velocity (PPV) of the vibration waveform, should fall below the maximum allowable values. Ideally, when blasting is near structures of interest (power towers, dams, houses, etc.), the vibration level (PPV) should be predicted prior to the actual production blasts. There are different techniques to predict the PPV, one in particular is the signature hole technique. This technique is based on signals and systems theory and uses a mathematical operation called convolution to assess the waveform of the production blast. This technique uses both the vibration waveform of an isolated hole and the timing function given by the timing used in the blast. The signature hole technique requires an isolated single-hole waveform to create a prediction. Sometimes this information is difficult to acquire, as it requires the synthesis of a single-hole vibration waveform from a production blast vibration signal. The topic of ground vibrations from mining blasts, and more specifically the synthesis of a single-hole vibration waveform, has been studied by researchers in past decades, but without any concrete success. This lack of success may be partially due to the complexity and difficulty of modelling and calculation. However, this inverse methodology can be very meaningful if successfully applied in blasting engineering. It provides a convenient and economical way to obtain the single-hole vibration waveform and make the prediction of a production blast waveform easier. This dissertation research involves the theories of deconvolution, linear superposition, and Fourier phases to recover single-hole vibration waveforms from a production waveform. Preliminary studies of deconvolution included spectral division deconvolution and Wiener filtering deconvolution. In addition to the adaptation of such methodologies to the blast vibrations problems, the effectiveness of the two deconvolution methods by the influence of delay interval and number of holes is also discussed. Additionally, a new statistical waveform synthesis method based on the theories of linear superposition, properties of Fourier phase, and group delays was developed. The validation of the proposed methodology was also conducted through several field blasting tests. Instead of synthesizing one normalized single-hole vibration waveform by deconvolution, the proposed statistical waveform synthesis methodology generates a different single-hole vibration waveform for each blast hole. This method is more effective and adaptable when synthesizing single-hole vibration waveforms. Recommendations for future work is also provided to improve the methodology and to study other inverse problems of blast vibrations

Measurement and Analysis of Civil Engineering Vibrations

Man-made vibrations caused by construction activities, blasting, rail and vehicular traffic, and machinery can have an adverse impact on buildings and facilities, human occupants of buildings, and sensitive equipment housed within these facilities. Comparisons between vibrations are often difficult because of different methods used to measure, analyze, and interpret vibration data. To facilitate these comparisons, standard methods of selecting and mounting transducers, processing vibration data, and interpreting test results are reviewed. Specific measurement and analysis techniques and maximum allowable vibration criteria used for evaluating the influence of vibrations on humans, the potential for cosmetic damage to structures, and the impact on vibration-sensitive equipment are also summarized

Analysis of the blast-induced vibration structure in open-cast mines

Blasting in opencast mines is characterized by the use of large masses of explosives for a single blast. Blasting is done in a series of several to tens or even hundreds of charges placed in long holes and fired with a millisecond delay. Works are often carried out in the vicinity of buildings; therefore, reducing vibration impact is essential for opencast mines. This paper presents the applicability of the method of time-frequency Matching Pursuit (MP) for analysis of vibration structure. The use of MP analysis enables the development of much deeper and more reliable impact assessments of blasting on the environment

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 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)

Dynamic performance of transmission pole structures under blasting induced ground vibration

Structural integrity of electric transmission poles is crucial for the reliability of power delivery. In some areas where blasting is used for mining or construction, these structures are endangered if they are located close to blasting sites. Through field study, numerical simulation and theoretical analysis, this research investigates blast induced ground vibration and its effects on structural performance of the transmission poles. It mainly involves: (1) Blast induced ground motion characterization; (2) Determination of modal behavior of transmission poles; (3) Investigation of dynamic responses of transmission poles under blast induced ground excitations; (4) Establishment of a reasonable blast limit for pole structures; and (5) Development of heath monitoring strategies for the electric transmission structures. The main technical contributions of this research include: (1) developed site specific spectra of blast induced ground vibration based on field measurement data; (2) studied modal behavior of pole structures systematically; (3) proposed simplified but relatively accurate finite element (FE) models that consider the structure-cable coupling; (4) obtained dynamic responses of transmission pole structures under blast caused ground vibration both by spectrum and time-history analysis; (5) established 2 in/s PPV blast limit for transmission pole structures; (6) developed two NDT techniques for quality control of direct embedment foundations; and (7) described an idea of vibration-based health monitoring strategy for electric transmission structures schematically