A study on Fast Predicting the Washability Curve of Coal

AbstractA pure new MATLAB-based image recognition system was developed to compute the coal particle picture of same grain class through the digital image processing method, 13 image feature parameters was selected to be most representative image characteristic parameters. Take the above parameters as the input of RBF neural network, the density level of coal particles could be estimated, combined with the real ash content of each density level, the washability curve could be drawed. Experement show,the absolute error of the total ash is 2.375%,which is Slightly big in the China standards of coal preparation (GB/T477 -1998); the related coefficients of each indicator in both actual and predicted float-and-sink material are all close to 1, while the curves of λ, β, θ and δ are very similar and the deviation of ξ curve is relatively large

Gas turbine performence based creep life estimation using soft computing technique

Accurate and simple prediction system has become an urgent need in most disciplines. Having the accurate prediction system for gas turbine components will allow the user to produce reliable creep life prediction. Focusing on the turbine blades and its life, the current method to calculate its creep life is complex and consumes a lot of time. For this reason, the aim of this research is to use an alternative performance–based creep life estimation that is able to provide a quick solution and obtain accurate creep life prediction. By the use of an artificial neural network to predict creep life, a neural network architecture called Sensor Life Based (SLB) architecture that produces a direct mapping from gas path sensor to predict the blade creep life was created by using the gas turbine simulation performance software. The performance of gas turbine and the effects of multiple operations on the blade are studied. The result of the study is used to establish the input and output to train the Sensor Life Based network. The result shows that the Sensor Life-Based architecture is able to produce accurate creep life predictions yet performing rapid calculations. The result also shows that the accuracy of prediction depends on the way, how the gas path sensor is grouped together

Monitoring the Land Cover Change in the Historic Range of Cambarus veteranus in West Virginia Using a 1973-2013 Landsat Time Series

The crayfish Cambarus veteranus is near extinction in its historic range of the Upper Guyandotte River watershed. The biggest threats to C. veteranus are mining and road construction. Mining has been a continuous activity in the southern coalfields where the crayfish has historically been found, yet little is known about how much land cover change the practice has done to the region. Crayfish act as important organisms within aquatic ecosystems and without them, those systems are often degraded. Quantifying the change in land cover is important to understanding threats to C. veteranus for future protection of the crayfish and its habitat. Using twelve Landsat satellite images from 1973-2013, I performed a supervised land cover classification to track land cover change within the Upper Guyandotte River watershed. There was an overall 5.5% change in land cover with a significant decreasing trend in forested area over time. In addition to overall land cover changing, three, out of seven, subwatersheds where C. veteranus was historically found saw significant decreasing trends in forested area as well. The last known location of C. veteranus is within one of those three watersheds. This increased disturbance from mining likely explains the near extinction of Cambarus veteranus. Without further protection and monitoring the land cover, the crayfish is likely to go extinct within its native West Virginia range

Texture and Colour in Image Analysis

Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews

Characterisation of Minerals and Other Properties of Mukah Coal

An increase in human population correlates with an increase in demand for energy. Coal has been a vital energy source for human populations for millennia, where it has played a major role in various industries, especially in the thermal-based industries. Coal is found in all three geographical provinces of Malaysia: Peninsular Malaysia, Sarawak, and Sabah. However, at most, the widespread and abundant occurrences of coal are found in Sarawak, especially in Mukah. The age of the coal deposits found in Mukah has instigated research that focuses mainly on the characterization of minerals and other properties in the coal, where those findings could be used to propose coal usage in other types of industries. To achieve those objectives, this research starts with a theoretical approach by discussing the coalification process, followed by understanding the types of coal produced from this process. Basic coal analysis, visual inspection, proximate analysis, XRD, SEM-EDX, and FTIR analysis were done to achieve all the objectives. At the end of the research, it was found that the Mukah coal sample is denser and has a higher gold content compared to the commercial coal sample. It was seen that the commercial coal possessed a high caloric value compared to the Mukah coal. This may be due to the high moisture and silicone content in the coal sample as it is mined directly from the earth. Overall, the Mukah coal sample could be used for other industries, like the fertilizer industry, rather than just being used to generate electricity by burning

Site Characterization Using Integrated Imaging Analysis Methods on Satellite Data of the Islamabad, Pakistan, Region

We develop an integrated digital imaging analysis approach to produce a first-approximation site characterization map for Islamabad, Pakistan, based on remote-sensing data. We apply both pixel-based and object-oriented digital imaging analysis methods to characterize detailed (1:50,000) geomorphology and geology from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. We use stereo-correlated relative digital elevation models (rDEMs) derived from ASTER data, as well as spectra in the visible near-infrared (VNIR) to thermal infrared (TIR) domains. The resulting geomorphic units in the study area are classified as mountain (including the Margala Hills and the Khairi Murat Ridge), piedmont, and basin terrain units. The local geologic units are classified as limestone in the Margala Hills and the Khairi Murat Ridge and sandstone rock types for the piedmonts and basins. Shear-wave velocities for these units are assigned in ranges based on established correlations in California. These ranges include Vs30-values to be greater than 500 m/sec for mountain units, 200–600 m/sec for piedmont units, and less than 300 m/sec for basin units. While the resulting map provides the basis for incorporating site response in an assessment of seismic hazard for Islamabad, it also demonstrates the potential use of remote-sensing data for site characterization in regions where only limited conventional mapping has been done

Annotated Bibliography of Techniques for Image Enhancement and Interpretation in Remote Sensing

The purpose of this annotated bibliography is to provide the user of the Remote Sensing Information Subsystem (RSIS) with brief descriptions of recent research techniques of image enhancement and their applications to specific image interpretation problems. Table 2 of the May 1979 ASVT/RSIS Technical Report entitled "Functional Design Narrative Descriptions" listed digital image processing requirements of the RSIS. The references in this bibliography were chosen because they describe these processing requirements. The format of that table was modified slightly and used as the outline for Section One of this bibliography. The bibliography is not intended to be an exhaustive compilation of all pertinent articles. Such a collection would be outdated as soon as it was printed. It does, however, contain a broad sampling of the recent remote sensing literature. We tried not to include multiple references to the same technique, but some repetition was necessary in order to fully describe some procedures of image enhancement and interpretation.Bureau of Economic Geolog

A CLASSIFICATION OF LOWER PALEOZOIC CARBONATE-BEARING ROCKS FOR GEOTECHNICAL APPLICATIONS

An empirically-based classification of lower Paleozoic carbonate-bearing rocks was created for field-based geotechnical applications. Geotechnical parameters were subsequently correlated to that classification. Seven hundred seventy-seven samples were used as the basis for the classification. Thirteen categories based on visual and tactile properties and a hydrochloric acid test were created. Samples were from central, north-central, and south-central Kentucky and represented the majority of Ordovician exposures in the state, and some Mississippian exposures. Few Silurian and Devonian units were included in the sample set. Geotechnical parameters, including density as well as elastic constants (shear and compression wave velocities, Poisson’s ratio, Young’s modulus, and shear modulus), were calculated for 113 representative samples from the classification. Compression strength testing was completed on 29 samples and the slake durability index was calculated for 18 samples. Testing values were correlated to the classification system in an attempt to use the classification as a predictive and comparative tool for geotechnical applications. Despite samples being heterogeneous and isotropic, each of the 13 categories behaved differently and predictably, with the sharpest contrast in siliciclastic and carbonate rocks