توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱The Effect of Nano Silica on the Thermal Properties of Acrylic Resins
نویسنده(ها): ، ،
اطلاعات انتشار: سومین کنگره بین المللی رنگ و پوشش، سال
تعداد صفحات: ۱۲
study the effect of nano silica on the thermal properties of acrylic resins, two different series of water–based acrylic resin has been prepared. The first one is the acrylic latex synthesized by emulsion copolymerization and the second is acrylate\ silica nanocomposite synthesizied via miniemulsion copolymerization. The nanocomposite resins with the well dispersion of nano silica in the polymeric particles show higher abrasion and heat resistance. According to the TGA results, decomposition temperature of the nanocomposites increased with respect to the pure acrylic resins. For the washed nanocomposite latex prepared via miniemulsion polymerization, the residual weight after 600° C in the TGA was more than 7% while for the pure acrylic resin it was less than 1%. On the other hand, the glass transition temperature of the nanocomposite (Tg= 26°C) is higher than that of the pure acrylic latex (Tg = 13°C). Higher abrasion resistance and hardness resulted from the presence of the nano silica in the structure of acrylic resins.<\div>

۲Fuzzy–Rule–Based Faults Classification of Gearbox of MF 285 Tractor
نویسنده(ها): ، ، ،
اطلاعات انتشار: چهارمین کنفرانس تخصصی پایش وضعیت و عیب یابی، سال
تعداد صفحات: ۱۲
This paper presents a fault Classification method based on a fuzzy inference system.The vibration signal from a piezoelectric transducer is captured for the following conditions of MF285 gearbox: ‘Healthy Gearbox’ (Healthy), ‘Gear with tooth face worn’ (Worn) and ‘Gear with tooth face broken’ (Broken), at two working speed (800 and 1500 rpm). The features of signal were extracted using descriptive statistic parameters. The output of the J48 algorithm is a decision tree that was employed to produce the crisp if–then rule and membership function sets. Results showed that the total classification accuracy for 800 and 1500 rpm conditions were about 87% and 100%.<\div>

۳Data mining based on statistical parameters to improve fault diagnosis accuracy
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس ملی نگهداری و تعمیرات، سال
تعداد صفحات: ۱۴
Vibration signals contain rich information about the health of machinery. There for vibration condition monitoring is used in industries. In present study vibration signals from gearbox of Massey Ferguson 285 tractor is gained in three health condition of a gear: Healthy, Worn tooth face and Broken tooth. Vibration signals are turned to frequency domain by applying a Fast Fourier Transform (FFT) to them. Then some statistical parameter is used for data mining from the signals. Processed signals are used as input vectors for Feed Forward Back–propagation neural networks with variable hidden layer neurons count between 1 and 10 in 2 main structures, two and three layers network. Maximum 100% classification accuracy gained from two–layer network with 4 hidden layer neurons and three–layer network with 3x3 and 8x7 hidden layer neurons.<\div>

۴A PracticalWork for Fault Classification of Electromotor of SAR–2 Hydraulic Pump by an Intelligent Combined Method Based on Data Mining and Fuzzy Logic
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس ملی نگهداری و تعمیرات، سال
تعداد صفحات: ۱۵
Vibration technique in a machine condition–monitoring program provides useful reliable information, bringing significant cost benefits to industry. The main purpose of this research is to explore the intelligent way to classify three common faults versus healthy state of electromotor. Vibration signal by FFT technique went to frequency domain. Then the features are extracted by using statistical feature parameters that reduced the data. The improved distance evaluation (IDE) technique was used to select the significant features from the whole feature set. The J48 algorithm as a decision tree generated fuzzy rules. The structure of the FIS classifier was then defined based on the crisp sets. Results showed that the total classification accuracy were about 88%. This work demonstrates that the combined J48–FIS model has the possible capacity for fault diagnosis of electromotor.<\div>

۵Fault Diagnosis of Electromotor of SAR–7 Hydraulic Pump by an Intelligent Combined Method Based on k–Nearest Neighbor and Improved Distance Evaluation
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس ملی نگهداری و تعمیرات، سال
تعداد صفحات: ۱۰
In present paper, an electro–motor of a Search and Rescue (SAR–7) is studied by its frequency domain signals. Vibration Signals gained from electro–motor while its daily work. Some statistical parameters are used for data mining from raw signals and the Improved Distance Evaluation (IDE) technique is used for feature extraction. Variant thresholds for IDE are used to study the effect of this feature selection algorithm on overall performance of classification by k–Nearest neighbor (kNN) algorithm. Variable k value is used in order to make effect of IDE independent from classifier settings. Behavior of kNN performance depending variable k value between 1 and 10 is like descending linear function. As results, IDE made calculations faster and increased overall performance for fault classification with kNN.<\div>

۶Predicting the amount of Particle Quantifier in Oil by ANFIS
نویسنده(ها): ، ،
اطلاعات انتشار: ششمین کنفرانس ملی نگهداری و تعمیرات، سال
تعداد صفحات: ۱۶
Lubricant analysis programs evaluate the condition of the circulating fluid to determine if the oil is suitable for further use or not. Several methods are used to analyze oil condition and contamination. These include spectrometry, viscosity analysis, dilution analysis, water detection, Acid Number assessment, Base Number assessment, particle counting, and microscopy. In this paper, the amount of particle quantifier of engine oil of Universal 665 tractor was predicted by using calculating the amount of Fe, Cu, Sn and Cr in oil analysis. At First, Multiple linear regression was implemented that show which material in oil analysis have the correlation with the amount of PQ.A Linear model base on regression was presented Then a Sugeno–type fuzzy inference system based on fuzzy c–means clustering was generated. In Matlab, Neural Network was used to optimize the parameter of fuzzy set. Results show that ANFIS have the best coefficient of determination about 0.9.<\div>

۷Calculation of Maximum and Minimum Plastic Zone Radius Around Circular Tunnels; New Emprical Relation
نویسنده(ها): ، ،
اطلاعات انتشار: هفتمین کنگره ملی مهندسی عمران، سال
تعداد صفحات: ۴
This paper discusses the calculation of plastic zone radius around the circular tunnel which were based on the Hoek–Brown failure criterion. The importance of plastic zone radius calculation for different stress ratio can be illustrated by knowing that for each stress ratio, the shape of failure zone will get changed. The calculation of plastic zone radius was done for five stress ratio with numerical modeling by defining the factor of d. The maximum and minimum of plastic zone radius were determined for each stress ratio and after that by fitting the curve to the data, the emprical relations were obtained. New emprical relations are the results of this paper which can be used for calculation of maximum and minimum plastic zone radius in different condition.<\div>
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