Characteristics of Bottom Ash Produced from Fixed Bed Gasification of Polyurethane

( Tanvir Alam ),( Jang-soo Lee ),( Won-seok Yang ),( Se-won Park ),( Jae-jun Kang ),( Yong-chil Seo ) 한국폐기물자원순환학회(구 한국폐기물학회) 2015 한국폐기물자원순환학회 심포지움 Vol.2015 No.2

With the booming of economy, consumption of electronic products have increased rapidly and so do the generation rate of electronic waste. A common type of electronic waste in the final stage at recycling facilities is polyurethane. Polyurethane could be utilized as valuable fuel, since it has higher heating value and low hazardous contents. Gasification experiment was conducted on pellet type SRF made of polyurethane at 1000℃ using a fixed bed reactor. One of the final product in gasification experiment is bottom ash, which usually discarded on landfill. In this study, we tried to figure out the characteristics of bottom ash, which will enable us to know about the recycling possibilities of this residue.

Reliability improvement in the presence of weak fault features using non-Gaussian IMF selection and AdaBoost technique

Tanvir Alam Shifat,허장욱 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.8

In machinery fault detection and identification (FDI), decomposing vibration signals into corresponding intrinsic mode functions (IMFs) reduces the intricacy in extracting weak fault features at the early failure state. However, selecting a suitable IMF for fault information extraction is a challenging task. Analyzing the non-Gaussian IMFs allows extracting effective fault-related information rather than the entire signal or other IMFs because the vibration signals are random in nature. In this study, we present an IMF selection method based on the maximum kurtosis value of each IMF. A kurtosis computation method named autogram is used. It considers the autocovariance function to characterize the 2nd order cyclostationary. We deploy the AdaBoost algorithm with a decision tree classifier to gain a better performance compared with other tree-based classifiers. The proposed FDI framework can effectively detect and classify multiple fault features at the incipient failure stage.

Effect of Low Cost Natural Minerals on Solid Refuse Fuel Gasification

( Tanvir Alam ),( Jang-soo Lee ),( Won-seok Yang ),( Se-won Park ),( Sang-yeop Lee ),( Gun-ho Han ),( Youn-ouk Jeong ),( Yong-chil Seo ) 한국폐기물자원순환학회(구 한국폐기물학회) 2017 한국폐기물자원순환학회 심포지움 Vol.2017 No.1

Waste gasification is a promising pathway to convert carbonaceous materials into valuable end products through different synthesis routes, besides the efficient production of power and useable heat. Solid refuse fuel (SRF), which is an alternative fuel produced from the combustibles in municipal solid waste (MSW) and composed of waste plastic, paper, textiles, wood, etc., is one of the main topics in waste gasification nowadays. In this study, an effort was made to do SRF gasification using low cost natural minerals as a bed material to analyze the effect of low cost minerals on gas quality and yield. It is believed that low cost minerals like dolomite and lime usually shows some catalytic effect in promoting hydrocarbon destruction; by cracking reaction, steam reforming reaction and CO₂ reforming reactions. From our previous study, we found that optimum conditions for SRF gasification is ER 0.2, at 950 ℃ temperature in a fixed bed reactor. Thus, experiments were conducted at these conditions by measuring the characteristics of producer gas, concentration of gaseous pollutants and tar. Also, the lower heating value (LHV) of product gas, cold gas efficiency (CGE), carbon conversion (Cc), and residue yield (Ry) were analyzed. Results showed that uses of low cost natural minerals increased the syngas yield. It also increased LHV, CGE and Cc of producer gas. Uses of minerals also successfully decreased the residue yield and tar concentration. However, it increased the concentration of gaseous pollutants a bit, but still the concentration was much less than the allowable limit. In terms of overall performance, dolomite showed comparatively better performance than lime.

EEMD assisted supervised learning for the fault diagnosis of BLDC motor using vibration signal

Tanvir Alam Shifat,허장욱 대한기계학회 2020 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.34 No.10

Predictive maintenance (PdM) has become a major issue in system health monitoring, as machines are operating under more complex and diverse conditions nowadays. Besides minimizing the risk of a catastrophic failure, a proper maintenance scheme can amplify system yield as well as largely reduce production and maintenance costs. This paper presents a comprehensive study of a permanent magnet brushless DC (BLDC) motor’s fault diagnosis using vibration signals. Based on the degree of deviation from the normal operating condition, three health states are chosen from the entire lifecycle of motor. Acquired signals are decomposed using ensemble empirical mode decomposition (EEMD) and the appropriate intrinsic mode function (IMF) is selected based on the similarity index. Later, selected IMF is analyzed in time-frequency domain by using continuous wavelet transform (CWT) for better localization of fault frequencies. Several statistical features that indicate the health state of the motor are also extracted to diagnose different fault states. Later, feature dimensions were reduced using principal component analysis (PCA) technique and classified using a supervised machine learning technique named k-nearest neighbor (KNN). Extracted IMF from EEMD provides significant fault related information to detect and diagnose different fault states. Proposed method is effectively used to diagnose fault at the incipient stage as well as classify different fault states at incipient stage and severe stage.

A Practical Condition Monitoring Approach Using Normalized Modal Current and Support Vector Machine

Tanvir Alam Shifat,Jang Wook Hur 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.2

Current signature analysis is a proven method to diagnose motor-related faults at the incipient stage as well as to model a prognostics framework. Due to three-phase operational complexity, selecting a suitable phase current is a challenging task. Working with all three phases will increase computational expense and decision making will become time-consuming. Therefore, a method is required that guarantees accurate condition monitoring in a shorter period is necessary. In this paper, we present an improved fault diagnosis and prognostics framework of electric motors using a single-phase normalized modal current computation that preserves the characteristics of all three-phases. The normalized modal current ensures the presence of three-phase currents as it is calculated using a linear phase relationship and normalized current amplitudes. The effectiveness of this method is verified using a brushless DC (BLDC) motor at different health states. Using the modal current analysis, anomalies were detected through the third harmonic analysis in different health states of the motor. Also, for future predictions, a support vector machine (SVM) classifier is trained and validated for the features computed from the motor current.

Morphology, Morphometry, Growth Performance and Carcass Characteristics of Pekin, Nageswari and Their F₁ Crossbred Ducks under Intensive Management

Md. Tanvir Ahmad,Drishti Nandita,Tanvir Mohammad Maruf,Mohammad Hasanuzzaman Pabitra,Sabrina Islam Mony,Md. Shawkat Ali,Md. Sarwar Ahmed,Mohammad Shamsul Alam Bhuiyan 한국가금학회 2021 韓國家禽學會誌 Vol.48 No.2

This study investigated the morphological features, growth, and meat yield performance of Pekin (P), Nageswari (N), and their reciprocal F1 crossbreds (P♂×N♀ and N♂×P♀). A total of 301-day-old ducklings were reared in four different pens up to 20 weeks of age under intensive management conditions. Feeding and management practices were similar for all individuals throughout the experimental period. The morphology and plumage pattern of F1 crossbreds were similar to those of indigenous Nageswari ducks because of the dominant inheritance of the extended Black allele (E locus). Genotype had significant differences (P<0.05) among the four genotypes in morphometric measurements, except wing and shank length. Growth performance was highly significant among the four genotypes (P<0.001) from one-day to 12 weeks of age. The average live weights of P, N, P♂×N♀ and N♂×P♀ crossbred genotypes at 12 weeks of age were 2038.35±29.74, 1542.44±33.61, 1851.85±28.59 and 1691.08±27.80 g, respectively. Meat yield parameters varied significantly (P<0.05) among the different genotypes for all studied traits, except for liver and gizzard weight. Moreover, no significant differences (P>0.05) were observed between P and P♂×N♀ crossbred for important meat yield traits such as hot carcass weight, dressing%, back half weight, drumstick with thigh weight and breast meat weight. Remarkably, the P♂×N♀ crossbreed possesses 50% native inheritance, which contributes to better adaptation in a hot-humid environment. Our results revealed that the P♂×N♀ genotype could be suitable for higher meat production with better adaptability in the agro-climatic conditions of Bangladesh.

Experimental Evaluation of Deteriorated CMPs Retrofitted by Different Non-invasive Approaches

Shaurav Alam,Tanvir Manzur,John Matthews,Chris Bartlett,Erez N. Allouche 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.11

Corrugated metal pipes (CMPs) deployed across North America are in various states of deteriorations with diminishing structural health that can cause road failure and pose serious threat to public safety. This paper presents an extensive experimental study conducted on deteriorated and retrofitted CMPs, and compares the results with available analytic approach - Modified Iowa equation. Simulated deterioration was performed on the new CMPs using mechanical approach and later, those CMP specimens were retrofitted using four different non-invasive methods. The specimens were tested under five different overburden pressures. Responses of the soil-pipe systems for deteriorated and rehabilitated specimens in terms of surrounding soil pressure and deformations at crown, spring-line, and invert were recorded and compared. It was found that the soil envelops and the CMPs experienced considerable change in pressure and deflections, respectively due to deterioration. However, rehabilitation using all the invasive approaches helped to regain soil pressures and deflections close to the original state, indicating their viability. The measured deflections from experimental studies were also compared with the predicted values obtained from the Modified Iowa equation. Such comparison is of immense importance to establish design guidelines for rehabilitated liner-CMP culvert systems.

빅데이터와 머신러닝 기반의 인버터 고장 분류

김민섭(Min-Seop Kim),Tanvir Alam Shifat,허장욱(Jang-Wook Hur) 한국기계가공학회 2021 한국기계가공학회지 Vol.20 No.3

With the advent of industry 4.0, big data and machine learning techniques are being widely adopted in the maintenance domain. Inverters are widely used in many engineering applications. However, overloading and complex operation conditions may lead to various failures in inverters. In this study, failure mode effect analysis was performed on inverters and voltages collected to investigate the over-voltage effect on capacitors. Several features were extracted from the collected sensor data, which indicated the health state of the inverter. Based on this correlation, the best features were selected for classification. Moreover, random forest classifiers were used to classify the healthy and faulty states of inverters. Different performance metrics were computed, and the classifiers’ performance was evaluated in terms of various health features.

SRF(Solid Refuse Fuel) 잔재물을 이용한 고정층 반응기에서의 가스화 연구

이상엽,서용칠,이장수,양원석,Alam MD Tanvir 한국폐기물자원순환학회 2016 한국폐기물자원순환학회 학술대회 Vol.2016 No.11

지속적인 화석 연료의 사용으로 인해 발생하는 환경오염 때문에 대체에너지를 찾는데 많은 연구가 진행되고 있다. 국내에서 발생되는 폐기물은 가연분 함량이 높아 폐기물 고형연료로 생산할 경우 화석원료의 대체제로 사용 가능성이 크다. 이러한 SRF는 최근 주목 받기 시작한 기술로 폐기물을 선별・파쇄 및 건조를 거쳐 생산되며, 국내 SRF의 발열량 기준은 약 3,500kcal/kg 으로 화석연료 및 바이오매스와 비교했을 때 연료로 사용하는데 문제가 없을 정도의 품질기준을 만족시키고 있다. 하지만 SRF의 생산 효율이 60%이하로 낮은 실정에 있어, 연료로 사용가능한 폐기물들이 버려지고 있다. 따라서 본 연구에서는 이를 극복하기 위한 방안으로 SRF를 생산하고 남은 잔재물(저품위 폐기물)을 다시 고형연료로 생산하여 열처리 시설에서 에너지 회수 시설에 적용하기 위한 실험의 하나로 저품위 폐기물의 기초특성분과 본 폐기물의 연소특성에 대해서 평가하였다. 실험결과 비록 MBT(Mechanical Biological Treatment) 처리를 거친 저품위 폐기물을 사용했지만 기존 SRF 연소특성과 비교했을 때 좋은 연소특성을 보였으며, 대기배출허용기준 또한 만족하였다. 본 연구에서는 SRF를 이용하여 에너지화 기술 중 하나인 가스화기술을 적용해 실험을 진행하였다. 실험조건으로는 고정층 반응기에서 공기 산화제를 사용하였으며 반응온도와 시료투입량을 900℃와 1g/min으로 고정하였다. 최적 ER(Equivalent ratio)을 찾기 위하여 0.2,0.4,0.6으로 변화를 주었다. 또한, 가스특성을 평가하기 위하여 Micro-GC를 통해 합성가스의 조성을 파악하였으며, 건조가스수율, 냉가스 효율, 탄소 전환율을 가스화특성 평가 인자로 사용하였다.

Fluff SRF의 연소특성 및 오염물질의 발생 특성 연구

강재준,이장수,양원석,박세원,( Alam Md Tanvir ),이상엽,서용칠 한국폐기물자원순환학회 2016 젊은 연구자 학술연구발표회 Vol.14 No.0