ADAPTIVE COAL CLASSIFICATION USING DEEP LEARNING

AUTHOR(S)

D.Mohanapriya, N.Nafreen Banu, K.Vannamathi, L.Sharnitha shri

DOI: https://doi.org/10.46647/ijetms.2023.v07i02.058

ABSTRACT
Coal classification is an essential process in the mining industry, which involves identifying the quality and type of coal extracted from the earth. Traditional methods of coal classification rely on manual inspection and analysis, which can be time-consuming and prone to errors. With the advent of machine learning techniques, it is now possible to automate this process and achieve higher accuracy and speed in coal classification. The first effort in learning about coal is observing coal features. This project developed a coal search system that allows users to do a search even when they do not know the coal name simply by observing coal characteristics. At present, coal classification uses machine vision to extract and analyze color, size, shape, and surface texture. Still, the new extraction margin method can be carried out roughly yet there is still a difference between the margin of extracted polygon, shape and the margin of the shape of original image. The project aims in finding the gangue in the coal. Total gangue percent in the coal data is then calculated and displayed which is based on pixels count of gangue colors. This assists in evaluating the coal quality. If future researchers were to expand to other features, coal gangue, etc., even those that are hard to quantify, can also be quantified. Artificial Neural Network is used for classifying the coal dataset. The project is designed using Python as frontend environment. The coding language used is the Python 3.7.

Page No: 502 - 510

References:

1. Guo Y, WangX, Wang S, Hu K, Wang W. (2021).“Identificationmethodof coal and coal ganguebased on dielectriccharacteristics,”IEEE Access.,vol. 9, pp. 9845-9854,Jan. 202
2. ZhaohuiZheng,Ping Wang,Wei Liu, Jinze Li, RongguangYe,DongweiRen. “Distance-IoULoss: Fasterand BetterLearning for Bounding Box Regression,” Presentedat AAAIConference on Artificial Intelligence 2020. Available:https://ojs.aaai.org//index.php/AAAI/article/view/6999.
3. Gao, Mingyu, et al. “Adaptive anchor box mechanism to improve the accuracy in the object detection system,” Multimedia Tools and Applications., vol. 78, no. 19, pp. 27383-27402, Oct. 2019.
4. Jain, Anil K. . “Data clustering:50 years beyondK-means.” PatternRecognitionLetters., vol. 31, no. 8, pp. 651-666,June. 2010.
5. S. Ren, K. He, R. Girshickand J. Sun, “Faster R-CNN:Towards Real-Time Object Detection with Region Proposal Networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence.,vol. 39,no. 6, pp. 1137-1149,June. 2017.
6. Hou, Wei. Identification of Coal and Gangue by Feed-forward Neural Network Based on Data Analysis [J]. International Journal of Coal Preparation and Utilization., vol. 39, no. 1, pp. 33-43, Jan. 2019.
7. Dou, Dongyang; Zhou, Deyang; Yang, Jianguo, et al. Coal and gangue recognition under four operating conditions by using image analysis and Relief-SVM [J]. International Journal of Coal Preparation and Utilization., vol. 40, no. 7, pp.473-482, Jul. 2020.
8. Li, Man; Duan, Yong; He, Xianli, et al. Image positioning and identification method and system for coal and gangue sorting robot [J]. International Journal of Coal Preparation and Utilization., May. 2020. DOI.10.1080/19392699.2020.1760855.

9. Jian Song. “Research on Identification Algorithm of Coal and Gangue Based on Image Feature,” M.S. thesis, Dept. Computer science and technology., Hebei University of Engineering., Hebei, China, 2016.
10. Xianmin Ma, Xiaoru ng. “Coal Gangues Automation Selection System Based on ARM Core and CAN Bus, ”Chinese Journal of Scientific Instrument.,vol. 26, no. 8, pp. 305-307, 318, August.2005.
11. Hailing Zhang, Jialin Wang, Jiansheng Wu, Rong Shi. “Application of Rough Sets Theory to Image Enhancement Processing,” Journal of Tongji University (Natural Science)., vol. 36, no. 2, pp. 254-257, Feb. 2008.
12. Wanzhi Wang, Zengcai Wang. “Characteristic Analysis and Recognition of Coal and Rock Based on Visual Technology,” Coal Technology., vol. 33, no. 10, pp. 272-274,Oct. 2014.
13. Yunxia Wu, Yimin Tian. “Methodof coal-rock image feature extraction and recognition based on dictionary learning,” Journal of China Coal Society., vol. 41, no. 12, pp. 3190-3196, Dec. 2016.
14. J. Redmon, S. Divvala,R. Girshickand A. Farhadi, “You only look once: Unified real-time object detection,” in Proc. CVPR, Las Vegas, NV, United States, 2016, pp. 779-788.
15. Ping Huo, Hanlin Zeng, KeyanHuo. “Research on density identification system of coal and refuse based on image processing technology, ”Goal Preparation Technology., no. 2, pp. 69-73, Apr.2015.
16. Guo Y, Wang, X, Wang S, Hu K, Wang W. (2021).“Identification method of coal and coal gangue based on dielectric characteristics,” IEEE Access., vol. 9, pp. 9845-9854,Jan. 2021.
17. Xijie Dou, Shibo Wang, Yang Xie, Tong Xuan. “Coal and gangue identification based on IMF energy moment and SVM, ” Journal of Vibration and Shock, vol. 39, no. 24, pp. 39-45, Dec. 2020.
18. Wei Hou. “Identification of Coal and Gangue by Feed-forward Neural Network Based on Data Analysis,” International Journal of Coal Preparation and Utilization, vol. 39, no. 1, pp.33-43, Jan. 2019.
19. Shwetasaibal Samanta Sahoo; Mousime Xalxo; B G Mukunda. "A Study on Tourist Behaviour Towards Sustainable Tourism in Karnataka". International Research Journal on Advanced Science Hub, 2, 5, 2020, 27-33. doi: 10.47392/irjash.2020.28
20. Muniyandy Elangovan; Mohamed Yousuf; Mohamed Nauman; Mohammed Nayeem. "Design and Development of Delivery Robot for Commercial Purpose". International Research Journal on Advanced Science Hub, 4, 07, 2022, 192-197. doi: 10.47392/irjash.2022.047
21. Manikandan N; Swaminathan G; Dinesh J; Manish Kumar S; Kishore T; Vignesh R. "Significant Attention in Industry and Academia for Wire Arc Additive Manufacturing (WAAM) - A Review". International Research Journal on Advanced Science Hub, 4, 07, 2022, 198-204. doi: 10.47392/irjash.2022.048
22. Shoeb Ahmed Syed; Steve Ales; Rajesh Kumar Behera; Kamalakanta Muduli. "Challenges, Opportunities and Analysis of the Machining Characteristics in hybrid Aluminium Composites (Al6061-SiC-Al2O3 ) Produced by Stir Casting Method". International Research Journal on Advanced Science Hub, 4, 08, 2022, 205-216. doi: 10.47392/irjash.2022.051
23. Ashima Saxena; Preeti Chawla. "A Study on the Role of Demographic Variables on Online Payment in Delhi NCR". International Research Journal on Advanced Science Hub, 4, 08, 2022, 217-221. doi: 10.47392/irjash.2022.052
24. Vishnupriya S; Nirsandh Ganesan; Ms. Piriyanga; Kiruthiga Devi. "Introducing Fuzzy Logic for Software Reliability Admeasurement". International Research Journal on Advanced Science Hub, 4, 09, 2022, 222-226. doi: 10.47392/irjash.2022.056
25. GANESAN M; Mahesh G; Baskar N. "An user friendly Scheme of Numerical Representation for Music Chords". International Research Journal on Advanced Science Hub, 4, 09, 2022, 227-236. doi: 10.47392/irjash.2022.057
26. Nirsandh Ganesan; Nithya Sri Chandrasekar; Ms. Gokila; Ms. Varsha. "Decision Model Based Reliability Prediction Framework". International Research Journal on Advanced Science Hub, 4, 10, 2022, 236-242. doi: 10.47392/irjash.2022.061
27. Vishnupriya S; Nithya Sri Chandrasekar; Nirsandh Ganesan; Ms. Mithilaa; Ms. Jeyashree. "Comprehensive Analysis of Power and Handloom Market Failures and Potential Regrowth Options". International Research Journal on Advanced Science Hub, 4, 10, 2022, 243-250. doi: 10.47392/irjash.2022.062
28. Minh Duc Ly; Que Nguyen Kieu Viet. "Improvement Productivity and Quality by Using Lean Six Sigma: A Case Study in Mechanical Manufacturing". International Research Journal on Advanced Science Hub, 4, 11, 2022, 251-266. doi: 10.47392/irjash.2022.066
29. Ragunath A; Poonam Syal. "Net Zero Energy Buildings Initiatives - A Review". International Research Journal on Advanced Science Hub, 4, 11, 2022, 267-271. doi: 10.47392/irjash.2022.067
30. Suresh P; Justin Jayaraj K; Aravintha Prasad VC; Abishek Velavan; Mr Gokulnath. "Deep Learning for Covid-19 Identification: A Comparative Analysis". International Research Journal on Advanced Science Hub, 4, 11, 2022, 272-280. doi: 10.47392/irjash.2022.068
31. Chirag H B; Darshan M; Rakesh M D; Priyanka D S; Manjunath Aradya. "Prediction of Concrete Compressive Strength Using Artificial Neural Network". International Research Journal on Advanced Science Hub, 4, 11, 2022, 281-287. doi: 10.47392/irjash.2022.069
32. Minh Ly Duc; Que Nguyen Kieu Viet. "Analysis Affect Factors of Smart Meter A PLS-SEM Neural Network". International Research Journal on Advanced Science Hub, 4, 12, 2022, 288-301. doi: 10.47392/irjash.2022.071
33. Lely Novia; Muhammad Basri Wello. "Analysis of Interpersonal Skill Learning Outcomes in Business English Students Class". International Research Journal on Advanced Science Hub, 4, 12, 2022, 302-305. doi: 10.47392/irjash.2022.072
34. Ms. Nikita; Sandeep Kumar; Prabhakar Agarwal; Manisha Bharti. "Comparison of multi-class motor imagery classification methods for EEG signals". International Research Journal on Advanced Science Hub, 4, 12, 2022, 306-311. doi: 10.47392/irjash.2022.073
35. Aniket Manash; Ratan Kumar; Rakesh Kumar; Pandey S C; Saurabh Kumar. "Elastic properties of ferrite nanomaterials: A compilation and a review". International Research Journal on Advanced Science Hub, 4, 12, 2022, 312-317. doi: 10.47392/irjash.2022.074
36. Prabin Kumar; Rahul Kumar; Ragul Kumar; Vivek Rai; Aniket Manash. "A Review on coating of steel with nanocomposite for industrial applications". International Research Journal on Advanced Science Hub, 4, 12, 2022, 318-323. doi: 10.47392/irjash.2022.075
37. Twinkle Beniwal; Vidhu K. Mathur. "Cloud Kitchens and its impact on the restaurant industry". International Research Journal on Advanced Science Hub, 4, 12, 2022, 324-335. doi: 10.47392/irjash.2022.076
38. T. Pravin, C. Somu, R. Rajavel, M. Subramanian, P. Prince Reynold, Integrated Taguchi cum grey relational experimental analysis technique (GREAT) for optimization and material characterization of FSP surface composites on AA6061 aluminium alloys, Materials Today: Proceedings,Volume 33, Part 8, 2020, Pages 5156-5161, ISSN 2214-7853. doi.org/10.1016/j.matpr.2020.02.863.
39. R. Ranjith, C. Somu, G. Tharanitharan, Venkatajalapathi.T, Naveenkumar M, Integrated Taguchi cum Grey Relational Experimental Analysis (GREAT) for Optimization and Machining Characterization of Cryogenic Cooled AA6063 Aluminium Alloys, Materials Today: Proceedings, Volume 18, Part 7, 2019,Pages 3597- 605, https://doi.org/10.1016/j.matpr.2019.07. 291.
40. R. Devi Priya, R. Sivaraj, Ajith Abraham, T. Pravin, P. Sivasankar and N. Anitha. "Multi-Objective Particle Swarm Optimization Based Preprocessing of Multi-Class Extremely Imbalanced Datasets". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems Vol. 30, No. 05, pp. 735-755 (2022). Doi: 10.1142/S0218488522500209
41. M. S. N. K. Nijamudeen, G. Muthuarasu, G. Gokulkumar, A. Nagarjunan, and T. Pravin, “Investigation on mechanical properties of aluminium with copper and silicon carbide using powder metallurgy technique,” Advances in Natural and Applied Sciences, vol. 11, no. 4, pp. 277–280, 2017.
42. Pravin T, M. Subramanian, R. Ranjith,Clarifying the phenomenon of Ultrasonic Assisted Electric discharge machining, “Journal of the Indian Chemical Society”, Volume 99, Issue 10, 2022, 100705, ISSN 0019-4522, Doi: 10.1016/j.jics.2022.100705
43. V.S. Rajashekhar; T. Pravin; K. Thiruppathi , “Control of a snake robot with 3R joint mechanism”, International Journal of Mechanisms and Robotic Systems (IJMRS), Vol. 4, No. 3, 2018. Doi: 10.1504/IJMRS.2018.10017186
44. T. Pravin, M. Sadhasivam, and S. Raghuraman, “Optimization of process parameters of Al-10% Cu compacts through powder metallurgy,” Applied Mechanics and Materials, vol. 813-814, pp. 603–607, 2010.
45. Rajashekhar, V., Pravin, T., Thiruppathi, K.: A review on droplet deposition manufacturing-a rapid prototyping technique. Int. J. Manuf. Technol. Manage. 33(5), 362–383 (2019) https://doi.org/10.1504/IJMTM.2019.103277
46. Rajashekhar V S, Pravin T, Thirupathi K, Raghuraman S.Modeling and Simulation of Gravity based Zig-zag Material Handling System for Transferring Materials in Multi Floor Industries. Indian Journal of Science and Technology.2015 Sep, 8(22), pp.1-6.

How to Cite This Article:
D.Mohanapriya, N.Nafreen Banu, K.Vannamathi, L.Sharnitha shri . ADAPTIVE COAL CLASSIFICATION USING DEEP LEARNING . ijetms;7(2):502-510. DOI: 10.46647/ijetms.2023.v07i02.058