Motor Current Signature Analysis (MCSA) is a popular method for the detection of faults in electric motor drives, particularly in Induction Machines (IMs). For Bearing Defects (BDs), which are very much related to the rotational frequency, it is important to maintain the speed at a target reference value in order to distinguish and locate the different BDs. This can be achieved by using a powerful control such as the Direct Torque Control (DTC), but this control causes the variation of the supply frequency and the current signal to become non-stationary, so the integration of advanced signal processing methods becomes necessary by using a suitable filter to handle the frequency content depending on the BDs, such as the Hilbert filter. This paper aims to adopt the Hilbert Transform (HT) for extracting the signature of the faults from the stator current envelope to detect the different BDs in the IMs when they are controlled by an intelligent DTC control driven by Artificial Neural Networks (ANN-DTC). This ANN-DTC control is a shaping factor rather than a disturbing one, which contributes with the Hilbert filter to the diagnosis of BDs. This technique is tested for the four locations of BDs: the inner ring, the outer ring, the ball, and the bearing cage in different operating situations without control and with conventional DTC and ANN-DTC controls. Thus, detecting the location of the defect exactly at an early stage contributes to achieving maintenance in a fairly short time. The performance of the chosen approach lies in minimizing the electromagnetic torque ripples as a result of the control and increase of the amplitudes of the spectra related to BDs compared to other harmonics. This performance is verified in the MATLAB/SIMULINK environment.
This experiment is performed according to literature method [1-3]. N,N-Dibutylamine 1 (20 mL, 0.024 mol) in ethanol solution and triethylamine (6.65 g, 0.048 mol) were cooled to 5°C under stirring. Then carbon disulfide (3.65 g. 0.48 mol) was added to the solution. After 1 hour of stirring, solid iodine (2,8 g, 0.022 mol) was added in portions and stirred until the colour disappeared completely. Then a methanolic solution of iodine was added dropwise until a faint colour persists. Excess of iodine was neutralised with Na 2 S 2 O 3 solution. The product was extracted with diethyl ether, washed thrice with water, dried over Na 2 SO 4 , filtered, and diethylether was evaporated at room temperature to give liquid compound 2. Yield: 83%.
This experiment is performed according to literature method [1][2][3][4]. 3,5-Dimethyl pyrazole 1 (2,3 g; 0.024 mole) in ethanol solution and triethylamine (6.65 g, 0.048 mole) were cooled to 5°C under stirring, then carbon disulfide (3.65 g, 0.048 mole) was added to the solution. After 1 hour of stirring, solid iodine (2,8 g, 0.022 mol) was added in portions and stirred until the colour disappeared completely. Then a methanolic solution of iodine was added dropwise until a faint colour persists. Excess of iodine was neutralised with Na 2 S 2 O 3 solution. The product was extracted with diethyl ether, washed thrice with water, dried over Na 2 SO 4 , filtered, and diethyl ether was evaporated at room temperature to give compound 2 as a white solid. Yield: 93%.Mp.: 87-89°C (diethyl ether/hexane: 8/2).1 H-NMR (CDCl 3 ) d (ppm): 2,43 (s, 12H, CH 3 ); 6,00 (s, 2H, H pyrazole ). 13 C-NMR(CDCl 3 ) d :193 ppm (-C=S), 150 (C 3 ), 148 (C 5 ), 110 (C 4 ), 12 (CH 3 ). IR (KBr , cm -1 ) : 3000 (-S-S-); 1290 (C=S). MS (m/z): 342 [M] + . U.V.: l max = 285 nm (-C=S).
This experiment is performed according to literature method [1][2][3][4]. To a solution of bis[(3methoxycarbonyl-5-methyl pyrazol)-1-yl thiocarbonyl] disulfide 1 (7.3x10 -2 mol) in dry diethyl ether was added a solution of LiAlH 4 (2.78 g, 7.3x10 -2 mol) in 10 mL of dry ether. The mixture was stirred for 6h at 30 °C and the product was extracted with CHCl 3 dried over Na 2 SO 4 and filtred. The solvent was removed under reduced pressure and the product was dried under high vacuum.
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