Demands for various products, higher qualities, reduction of costs and competitiveness, have resulted in the use of intelligent fault detection systems. Bearing fault diagnosis as a major component of the electric motors has had an essential role in the operation of production units' reliability. In addition, vibration analysis is one of the most powerful tools in diagnostics. Advances in signal processing technology and electrical equipment have developed a machinery condition monitoring for defect detection. This study has used the extracted features of vibration signals and the adaptive neuro-fuzzy interface system (ANFIS) network proposing a structure for fault detection and diagnosis of rolling bearings. Time-domain and frequency-domain statistical characteristics have been extracted fault information from vibration signals. Besides, the test data sets are presented to the ANFIS network. Simulation results indicated that the performance of the ANFIS network is acceptable. The results reveal that this method has more accuracy and better classification performance in comparison with other methods proposed in the literature.

a b s t r ac tIn this study, the application of synthesized Fe 3 O 4 magnetic nanoparticles and 1-butyl-3-methylimidazolium tetrachloroferrate (bmim [FeCl 4 ]), as a magnetic ionic liquid, for removal of Acid Red 88 (AR88) from aqueous solution was investigated. At first, Fe 3 O 4 magnetic nanoparticles (MNPs) were synthesized via a chemical co-precipitation method with drop-wise addition of sodium hydroxide to an ideal mole ratio mixture of Fe 2+ and Fe 3+ solutions (Fe 2+ /Fe 3+ ), about 0.5, as well as under argon gas protection. X-ray diffraction and transmission electron microscopy were used to characterize the synthesized nanoparticles. The effect of important experimental parameters on the removal of Acid Red 88 such as pH of solution, contact time, temperature, ionic liquid and sorbent dosages was investigated. Also, Langmuir and Freundlich isotherm models were used for evaluation of the equilibrium adsorption. Acid dye adsorption equilibrium data were fitted well to the Langmuir isotherm and the maximum monolayer capacity q max was calculated from it as 909.1 mg g -1 . Thermodynamic studies indicated that the adsorption process was exothermic and spontaneous, and the adsorption mechanism was physisorption. On the other hand, a rapid sorption dynamics and quantitative removal of dye (≈95%) were observed under optimal conditions: 50 mL of 50 ppm dye solution at pH 3, 5 mg of ionic liquid, 10 mg of magnetic nanoparticles (MNPs), 2 min contact time at 10°C. Finally, this method was used for the removal of AR88 from real water samples of Chalus River. The obtained results indicated that Fe 3 O 4 MNP and magnetic ionic liquid (bmim [FeCl 4 ]) could be used as an efficient sorbent material for very simple and fast removal of acid dyes from aqueous solutions.