1,327 research outputs found
Recommended from our members
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
\u3ci\u3eCases on Federal Taxation\u3c/i\u3e, by Joseph Henry Beale and Roswell Magill (1926)
\u3ci\u3eCases on Partnership and Other Unincorporated Associations\u3c/i\u3e, by Scott Rowley (1927)
Volcanic eruptions dry fogs and the european palaeoenvironmental record: Localised phenomena or Hemispheric impacts?
Recommended from our members
Enhanced Raman Detection System based on a Hollow-core Fiber Probe design
This paper focus on an enhanced Raman-based detection probe and its performance evaluated. The probe employs a hollow-core fiber design to allow liquid micro-sample to be analyzed. The hollow-core fiber is used both to transmit the light signal used to excite the sample and to collect the Raman scattering signal received from the micro-sample under analysis. In order to maximize the performance of the system, various parameters have been studied experimentally, including the diameter and the height of the liquid sample in the probe. The aim has been optimizing both as a means to enhance the Raman scattering signal received from the liquid sample. As a result, a Raman-based detection probe using a reflector approach was developed and evaluated. This design enabling a greater area for interaction with the sample to be formed and to concentrate the excitation light into it. This then increases the efficiency of the light-liquid interaction and improves the collection efficiently of the forward Raman scattering light signal. With the use of this design, the detected Raman scattering signal was increased by a factor of 103~104 over what otherwise would be achieved. A key feature is that with the use of a hollow-core fiber to collect the liquid sample, only a very small volume is needed, making this well suited to practical applications where limited amounts of material are available e.g. biofluids or high value liquids. The system designed and evaluated thus provides the basis of an effective all-fiber Raman-based detection system, capable of being incorporated into portable analysis equipment for rapid detection and in-the-field use
Recommended from our members
Studies on Temperature and Strain Sensitivities of a Few-mode Critical Wavelength Fiber Optic Sensor
This paper studied the relationship between the temperature/strain wavelength sensitivity of a fiber optic in-line Mach-Zehnder Interferometer (MZI) sensor and the wavelength separation of the measured wavelength to the critical wavelength (CWL) in a CWL-existed interference spectrum formed by interference between LP01 and LP02 modes. The in-line MZI fiber optic sensor has been constructed by splicing a section of specially designed few-mode fiber (FMF), which support LP01 and LP02 modes propagating in the fiber, between two pieces of single mode fiber. The propagation constant difference, Δβ, between the LP01 and LP02 modes, changes non-monotonously with wavelength and reaches a maximum at the CWL. As a result, in sensor operation, peaks on the different sides of the CWL then shift in opposite directions, and the associated temperature/strain sensitivities increase significantly when the measured wavelength points become close to the CWL, from both sides of the CWL. A theoretical analysis carried out has predicted that with this specified FMF sensor approach, the temperature/strain wavelength sensitivities are governed by the wavelength difference between the measured wavelength and the CWL. This conclusion was seen to agree well with the experimental results obtained. Combining the wavelength shifts of the peaks and the CWL in the transmission spectrum of the SFS structure, this study has shown that this approach forms the basis of effective designs of high sensitivity sensors for multi-parameter detection and offering a large measurement range to satisfy the requirements needed for better industrial measurements
Recommended from our members
Fabrication of a high sensitive Ag-nanoparticle substrate and its application to the detection of toxic substances
Surface Enhanced Raman Scattering (SERS) is typically observed with the substrate in a liquid medium and it has been proposed as a promising technique for detecting low levels of pollutants in liquids. A technique is presented for self-assembly to immobilize Ag nanoparticles (Ag-NPs), with diameters ranging from 100 to 800nm on a solid support. Experimental results have been obtained through experiments using Ag-NPs active substrates to detect Rhodamine 6G (R6G) and crystal violet in the deionized water. Further, the SERS spectrum and Raman spectrum of phoxim were also measured, showing the enhancement in the performance of the active substrate as a result
Recommended from our members
Research on VCSEL interference analysis and elimination method
Laser methane gas sensors have been increasingly accepted in coal mine safety monitoring. Most laser spectroscopic methane gas sensors are based in BFB lasers at around 1650nm. However, they suffer from high power consumption and high cost due to temperature control is required for laser diode operation at constant temperature. VCSEL lasers have offered low operation current and low power consumption when operating at non-TEC mode. However, it is found that the interference noise is critical for laser methane detection. This paper report typical results of the laser diode ripple characterization method and methods of noise reduction methods are discussed
- …