An Analysis of Noise Characteristics of Drill Bits

2011 ◽  
Vol 134 (1) ◽  
Author(s):  
Christian Gradl ◽  
Alfred W. Eustes ◽  
Gerhard Thonhauser
Keyword(s):  
Natural Diamond ◽  
Strong Relationship ◽  
High Amplitude ◽  
Frequency Characteristics ◽  
Frequency Spectra ◽  
Rock Interaction ◽  
Vibration Sensors ◽  
Drag Bits ◽  
Noise Characteristics ◽  
Vibrational Characteristics

There have been papers that analyze the relationship between bit design and a bit’s vibrational characteristics. These papers typically are based on the analysis of three-axis near-bit down-hole vibration sensors. In this paper, the authors take a simpler approach. Using a standard microphone literally pointed at the bit, they record the noise of the bit/rock interaction while drilling and analyze the resulting noise for these bit vibrational characteristics. The data were gathered at the Colorado School of Mines in Golden, CO. The noise of a PDC core, roller cone, and diamond core bits were recorded under various weight and rotary speeds using a microphone and a vertically mounted uniaxial geophone (used for confirming the data recorded on the microphones). Using a Fast Fourier Transform, the frequency spectra were extracted from the recorded data and analyzed. The data were normalized for rotational speed. The results of the frequency analysis of the roller cone, the PDC, and the natural diamond bits are presented in this paper. The major differences in the three bit frequency characteristics could be detected and furthermore, for drag bits, the frequency characteristics could be related to the bit’s design. The frequency spectra of the roller cone bit can best be described with a general high amplitude level that is relatively evenly distributed over the whole frequency spectrum. The drag bit data showed a strong relationship between the number and arrangement of cutting elements and frequency peaks on a plot of amplitude versus cycles per revolution. Frequency peaks were observed at multiples of the number of cutting elements. In general this relationship was strongly visible on the PDC bit data but not as strongly visible on the diamond bit data. The conclusion is that bit characteristics can be determined using only the noise of a bit. Potential applications of this research include detecting and diagnosing bit problems (e.g., broken teeth and bit balling) in real time using simple microphone based acoustic data.

An Analysis of Noise Characteristics of Drill Bits

2008 ◽  
Author(s):  
Christian Gradl ◽  
Alfred W. Eustes ◽  
Gerhard Thonhauser
Keyword(s):  
Natural Diamond ◽  
Strong Relationship ◽  
High Amplitude ◽  
Frequency Characteristics ◽  
Frequency Spectra ◽  
Rock Interaction ◽  
Vibration Sensors ◽  
Drag Bits ◽  
Noise Characteristics ◽  
Vibrational Characteristics

There have been papers that analyze the relationship between bit design and a bit’s vibrational characteristics. These papers typically are based on the analysis of three-axis near-bit down-hole vibration sensors. In this paper, the authors take a simpler approach. Using a standard microphone literally pointed at the bit, they record the noise of the bit/rock interaction while drilling and analyze the resulting noise for these but vibrational characteristics. The data were gathered at the Colorado School of Mines in Golden, Colorado. The noise of a PDC core, roller cone, and diamond core bits were recorded under various weight and rotary speeds using a microphone and a vertically mounted uniaxial geophone (used for confirming the data recorded on the microphones). Using a Fast Fourier Transform, the frequency spectra were extracted from the recorded data and analyzed. The data was normalized for rotational speed. The results of the frequency analysis of the roller cone, the PDC, and the natural diamond bits are presented in this paper. The major differences in the three bit frequency characteristics could be detected and furthermore, for drag bits, the frequency characteristics could be related to the bit’s design. The frequency spectra of the roller cone bit can best be described with a general high amplitude level that is relatively evenly distributed over the whole frequency spectrum. The drag bit data showed a strong relationship between the number and arrangement of cutting elements and frequency peaks on a plot of amplitude vs. cycles per revolution. Frequency peaks were observed at multiples of the number of cutting elements. In general this relationship was strongly visible on the PDC bit data but not as strongly visible on the diamond bit data. The conclusion is that bit characteristics can be determined using only the noise of a bit. Potential applications of this research include detecting and diagnosing bit problems (e.g. broken teeth, bit balling) in real time using simple microphone based acoustic data.

scholarly journals Models of Frequency Characteristics of Ecological Systems and their Conversion to Sound Form

2020 ◽  
Vol 161 ◽  
pp. 01061
Author(s):  
Alexander Bogomolov ◽  
Victor Nevezhin ◽  
Elena Piskun ◽  
Vladimir Khokhlov
Keyword(s):  
Frequency Spectrum ◽  
Ecological Systems ◽  
Frequency Characteristics ◽  
The State ◽  
Ecological System ◽  
New Information ◽  
Vibrational Characteristics ◽  
The Fourier Transform ◽  
The Moment ◽  
Creative Understanding

Real-time monitoring of the state of ecological systems can contribute to early warning of their deviation from an equilibrium state (homeostasis) or a change that leads to a threat to human health or existence. In addition to the existing means of monitoring the state of ecological systems and models for predicting the assessment of their state in the future, it is proposed to use models of the frequency characteristics of these systems, monitoring of which can detect signals about the appearance of unwanted deviations from homeostasis in the form of a change in the frequency spectrum. A change in the frequency spectrum can be converted into the sound waveform, which will allow timely detection of this undesirable change in the state of the ecological system. As a new information channel and analysis of the dynamics of the state of ecological systems, in the article it is proposed to use the wavelet transform of time series with the subsequent translation of the totality of their harmonic vibrations into sound form. In contrast to the Fourier transform, in which the spectrum of stationary and non-stationary processes is practically indistinguishable and it is impossible to determine the moment of the appearance of a new harmonic, the wavelet transformation gives this opportunity. In addition to the purely utilitarian application of the conversion of the vibrational characteristics of an ecological system into sound form, it becomes be possible to convert them into the “music” of ecological systems, which may give a new direction for creative understanding of the state of nature.

scholarly journals Synthesis of Human Voice Fragments Based on Frequency Spectra Reconstruction

2021 ◽  
Vol 24 (2) ◽  
pp. 14-20
Author(s):  
G. Lan ◽  
◽  
A. S. Fadeev ◽  
A. N. Morgunov ◽  
◽  
...  
Keyword(s):  
Speech Signal ◽  
Analytical Description ◽  
Frequency Characteristics ◽  
Frequency Spectra ◽  
Human Voice ◽  
Synthesized Speech

This article details the development of methods for the synthesis of phonemes of the human voice based on the analytical description of individual formants. A technique for analyzing the spectrum and spectrograms of original phonemes to obtain the main amplitude-frequency characteristics of the signal components is presented. An algorithm to reconstruct a speech signal based on the obtained sets of parameters is proposed. A technique to assess the quality of synthesized speech elements is described

scholarly journals Evaluation of Cracks in Metallic Material Using a Self-Organized Data-Driven Model of Acoustic Echo-Signal

2018 ◽  
Vol 9 (1) ◽  
pp. 95 ◽  
Author(s):  
Xudong Teng ◽  
Xin Zhang ◽  
Yuantao Fan ◽  
Dong Zhang
Keyword(s):  
Crack Growth ◽  
Statistical Significance ◽  
Distance Matrix ◽  
Strong Relationship ◽  
Data Driven ◽  
P Value ◽  
Probability Models ◽  
Statistical Parameters ◽  
Frequency Spectra ◽  
Statistical Probability

Non-linear acoustic technique is an attractive approach in evaluating early fatigue as well as cracks in material. However, its accuracy is greatly restricted by external non-linearities of ultra-sonic measurement systems. In this work, an acoustical data-driven deviation detection method, called the consensus self-organizing models (COSMO) based on statistical probability models, was introduced to study the evolution of localized crack growth. By using pitch-catch technique, frequency spectra of acoustic echoes collected from different locations of a specimen were compared, resulting in a Hellinger distance matrix to construct statistical parameters such as z-score, p-value and T-value. It is shown that statistical significance p-value of COSMO method has a strong relationship with the crack growth. Particularly, T-values, logarithm transformed p-value, increases proportionally with the growth of cracks, which thus can be applied to locate the position of cracks and monitor the deterioration of materials.

Low-frequency characteristics extension for vibration sensors

2004 ◽  
Vol 3 (1) ◽  
pp. 139-146 ◽  
Author(s):  
Yang Xueshan ◽  
Gao Feng ◽  
Hou Xingmin
Keyword(s):  
Low Frequency ◽  
Frequency Characteristics ◽  
Vibration Sensors

scholarly journals Pathological and physiological high-frequency oscillations in focal human epilepsy

2013 ◽  
Vol 110 (8) ◽  
pp. 1958-1964 ◽  
Author(s):  
Andrew Matsumoto ◽  
Benjamin H. Brinkmann ◽  
S. Matthew Stead ◽  
Joseph Matsumoto ◽  
Michal T. Kucewicz ◽  
...  
Keyword(s):  
High Frequency ◽  
Motor Task ◽  
High Amplitude ◽  
Spectral Amplitude ◽  
Support Vector ◽  
Frequency Spectra ◽  
Time Frequency ◽  
Human Epilepsy ◽  
High Frequency Oscillations ◽  
Measuring Frequency

High-frequency oscillations (HFO; gamma: 40–100 Hz, ripples: 100–200 Hz, and fast ripples: 250–500 Hz) have been widely studied in health and disease. These phenomena may serve as biomarkers for epileptic brain; however, a means of differentiating between pathological and normal physiological HFO is essential. We categorized task-induced physiological HFO during periods of HFO induced by a visual or motor task by measuring frequency, duration, and spectral amplitude of each event in single trial time-frequency spectra and compared them to pathological HFO similarly measured. Pathological HFO had higher mean spectral amplitude, longer mean duration, and lower mean frequency than physiological-induced HFO. In individual patients, support vector machine analysis correctly classified pathological HFO with sensitivities ranging from 70–98% and specificities >90% in all but one patient. In this patient, infrequent high-amplitude HFO were observed in the motor cortex just before movement onset in the motor task. This finding raises the possibility that in epileptic brain physiological-induced gamma can assume higher spectral amplitudes similar to those seen in pathologic HFO. This method if automated and validated could provide a step towards differentiating physiological HFO from pathological HFO and improving localization of epileptogenic brain.

Attenuation of Continuous Vibration Transmission in the Hand and Arm Using Composite-Based Tool Designs

2007 ◽  
Author(s):  
Daniel Brisach ◽  
Matthew Griffith ◽  
Janelle Konchar ◽  
Stephen Petfield ◽  
Peter Popper ◽  
...  
Keyword(s):  
Hearing Loss ◽  
Sound Pressure ◽  
Mechanical Shock ◽  
Noise Levels ◽  
Noise Emission ◽  
Frequency Spectra ◽  
High Noise ◽  
Vibration Transmission ◽  
Noise Characteristics ◽  
Metal Impact

Exposure to high noise levels may be the most common occupational hazard. Recent estimates suggest that as many as 30 million Americans are exposed to noise levels greater than the current safe limits for workplaces. At current durations of exposure, it is expected that 25% of these workers will develop permanent, noise-induced hearing loss. In many of these industrial environments, high levels of vibration also exist that can lead to several injuries and ailments. To address the adverse effects associated with the use of high noise emission impact tools, a study was initiated to develop and evaluate alternate tool designs that reduce the potential for hearing loss and vibration-related injuries. Recent work has focused on integrating advanced engineering polymers (composites) into tool designs for the purpose of eliminating direct metal-to-metal impact. This approach has several significant performance advantages including reduced operator discomfort due to hand-arm mechanical shock, reduced noise, and less danger from flying metal fragments. To quantify sound emission characteristics of these new designs, continuous sound pressure, maximum sound pressure, and maximum sound pressure level were measured using an array of five precision microphones each located 1 meter from the tool. Data was sampled at 40 kHz while test subjects operate both pneumatic tools and hand-struck tools. Frequency spectra of the sound pressure signals were examined for all tool treatments, and indicate that the addition of a polymer insert between metal impact components significantly reduces noise emission, especially at higher frequencies. Sound pressure levels were reduced by as much as 4 dBA compared to conventional tool designs. Similar reductions were observed in vibration transmission in the hand and arm. As a result, tools that integrate polymer-based components may be operated for longer daily exposure times without inducing hearing loss or vibration-related injuries. Data from this study may also help auditory and ergonomic specialists in understanding impulse noise characteristics and exposure.

scholarly journals Frequency Occurrence Plot-Based Convolutional Neural Network for Motor Fault Diagnosis

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1711
Author(s):  
Eduardo Jr Piedad ◽  
Yu-Tung Chen ◽  
Hong-Chan Chang ◽  
Cheng-Chien Kuo
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Fault Diagnosis ◽  
Convolutional Neural Network ◽  
Axis Deviation ◽  
Frequency Spectra ◽  
Load Variations ◽  
Vibration Sensors ◽  
New Feature ◽  
Frequency Occurrence

A novel motor fault diagnosis using only motor current signature is developed using a frequency occurrence plot-based convolutional neural network (FOP-CNN). In this study, a healthy motor and four identical motors with synthetically applied fault conditions—bearing axis deviation, stator coil inter-turn short circuiting, a broken rotor strip, and outer bearing ring damage—are tested. A set of 150 three-second sampling stator current signals from each motor fault condition are taken under five artificial coupling loads (0, 25%, 50%, 75% and 100%). The sampling signals are collected and processed into frequency occurrence plots (FOPs) which later serve as CNN inputs. This is done first by transforming the time series signals into its frequency spectra then convert these into two-dimensional FOPs. Fivefold stratified sampling cross-validation is performed. When motor load variations are considered as input labels, FOP-CNN predicts motor fault conditions with a 92.37% classification accuracy. It precisely classifies and recalls bearing axis deviation fault and healthy conditions with 99.92% and 96.13% f-scores, respectively. When motor loading variations are not used as input data labels, FOP-CNN still satisfactorily predicts motor condition with an 80.25% overall accuracy. FOP-CNN serves as a new feature extraction technique for time series input signals such as vibration sensors, thermocouples, and acoustics.

scholarly journals UPPER CATCHMENT OF BRIBIN UNDERGROUND RIVER HYDROGEOCHEMISTRY (GUNUNG SEWU KARST, GUNUNG KIDUL, JAVA, INDONESIA)

2017 ◽  
Author(s):  
Tjahyo Nugroho Adji
Keyword(s):  
Rainy Season ◽  
Strong Relationship ◽  
Dry Season ◽  
Hydrogeochemical Processes ◽  
Karst Area ◽  
Rock Interaction ◽  
Hydrogeochemical Process ◽  
Low Correlation ◽  
Underground River ◽  
Water Rock Interaction

This research was conducted within Bribin underground river, the primary river in the Gunung Sewu karst area, Gunung Kidul, Java, Indonesia. The main purpose of this study is to describe hydrogeochemical processes that occur at the upstream of Bribin River. In addition, this study also differentiates hydrogeochemical dominant processes, which come about in rainy season and dry season. Study area boundary is the upper rainfall catchment of Bribin River that is focused on three locations: Pentung River (surface), Luweng Jomblangan, and Gilap Cave. Discharge measurements for one yearperiod are conducted to define discharge hydrograph. Furthermore, baseflow separation analysis is conducted to determine the percentage of base flow (PAD) throughout the year. Water sampling for hydrogeochemical analysis is taken everymonth to represent dry season and rainy season condition. To describe the hydrogeochemical processes, scatter plot analysis with small sample size is conducted. The result shows that within dry season, dominant hydrogeochemical process is water rock interaction that indicates by: achieving maximum level of Ca2+-HCO3- ; strong relationship between discharge increment and PAD reduction; strong relationship between increasing of Ca2+-HCO3- and increasing of PAD. In addition,strong relationship between the increase in Ca2+-HCO3- and reduction of carbondioxide in water as well as minimum level of carbondioxide gas in water at the peak of dry season, is also present. In rainy season, hydrogeochemical process shifted from water-rock interaction to dilution by precipitation as a result of rain water supply through conduit system channel,which is characterized by: declining in Ca2+-HCO3- when discharge increase; increasing Ca2+-HCO3- when discharge decrease; low correlation of spesific conductivity vs Ca2+-HCO3 -; low correlation of PAD vs Ca2+-HCO3 - when discharge increase, strong correlation between declining in PAD by increasing of CO2 in the water, and rising of CO2 when discharge increase.

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