نشریه مهندسی مکانیک ایران
سال بیست و پنجم شماره 3 (پیاپی 72، پاییز 1402)

The monitoring system for induction motors (IMs) plays an important role in the majority of industrial plants. Bearing faults and shaft misalignment are common mechanical defects in induction motors. The aim of this paper is to detect simultaneously two common faults in induction motor including bearing defect and shaft misalignment. For this purpose, a test setup consisting of an induction motor coupled to a rotor shaft is designed and tested under different loading conditions and at different speeds. The diagnosis parameters of vibration signal are calculated by conventional signal processing methods as well as bispectrum analysis. Feature extraction and KNN classification techniques are applied to the calculated parameters to provide condition monitoring of the induction motor. The results show that the application of bispectrum analysis along with the conventional signal processing methods improves detecting bearing fault in induction motor and shaft misalignment in the case of single fault as well as multiple simultaneous faults.

In this paper, effect of pitch variation on vibrations of a propeller variable pitch is studied numerically and experimentally. The free vibrations equations of a propeller blade were extracted using the Galerkin method. A three-dimensional scanner was utilized to obtain blade profile and static trust with the aim of determining propeller loading status. To obtain modal analysis, the simulation analysis was done using Abaqus software in rotating condition, and results were validated with experimental modal test in static status. Both of experimental and analytical methods results represent that with increasing pitch, the variations of natural frequency are reduced and increased at odd and even frequency modes, respectively. Considering the campbell diagram, no resonance problem was observed in the case of the propeller blade, at working period.

In the present work, a special type of concentric two-pipe heat exchangers has been analyzed, in which the inner tube of the heat exchanger is considered as helical grooved. The turbulent flow of water-aluminum oxide nanofluid is used on both sides of the heat exchanger and a constant intensity magnetic field is used to enhance the effect of using the nanofluid. The effect of using this system as well as the use of nanofluid and magnetic field on the total heat transfer coefficient and the total pressure drop of the heat exchanger have been investigated. The results of studies in this field show that the use of nanofluids increases the heat transfer that occurs in the heat exchanger and also decreases the total pressure. While the most suitable volume percentage of nanofluid for the best ratio of heat transfer to pressure drop is also reported to be 15%. The numerical results of this article have also shown that the best optimal conditions in terms of heat transfer enhancement and pressure drop (according to the PEC performance evaluation criteria) are at 15% volume of nanofluid. Applying a magnetic field to the nanofluid current in the transducer also helps to increase the heat transfer in the heat exchanger while also increasing the total pressure drop. The amount of flow velocity has an obvious effect on the displacement heat transfer coefficient of the heat exchanger as well as the amount of total pressure drop. The simulation of the heat exchanger in different values ​​of the turbulent flow Reynolds number shows that the increase in the Reynolds number has a direct effect on the displacement heat transfer and the total pressure drop. The results show that in the intensity of the magnetic field with Hartmann number 40, the best ratio of heat transfer to the pressure drop of the heat exchanger occurs. The best PEC number in Hartmann number 40 is 1.05. However, with further increase of Hartmann number to 60 and 80, the value of PEC number decreases and in Hartmann number 80 decreases to 0.99, which practically makes the use of nanofluid in the presence of magnetic field affectless. The rate of flow velocity has a significant effect on the heat transfer coefficient of the heat exchanger and also the rate of total pressure drop. The value of the PEC number increases from 1.01 to 1.09 in increasing the Reynolds number from 6000 to 10000. However, it seems that with a relatively small increase in the PEC number and increasing costs in increasing the Reynolds number, using a lower Reynolds number scaler is a better choice.

Demand for cost-effective, reliable operation and safety of machinery, especially reciprocating compressors, which are among the most expensive machines in maintenance, requires accurate troubleshooting and fault classification. Due to their advantages, data-driven methods are often preferred to physical modeling methods for fault detection. This research simulates the mathematical model of a two-stage reciprocating compressor and conventional faults for use as a monitored system. The artificial neural network used is the probabilistic neural network whose main task is classification. Classification classes include one healthy compressor class and seven defective compressor classes for eight classes. Classification with the probabilistic neural network was performed using time domain and envelope spectrum characteristics. Then, the selected features are optimized using a genetic algorithm before feeding into the probabilistic neural network. Classification with the probabilistic neural network using time-domain characteristics shows a poor classification percentage with 44% Correct accuracy. But classification with a probabilistic neural network and envelope spectrum features has a 95% correct classification accuracy. Also, optimizing the selection of statistical features of the time-domain and frequency envelope spectrum with a genetic algorithm brings 48 and 99% correct accuracy in classification, respectively.

In this paper, mathematical model of different pumping plants including two or three centrifugal pumps in parallel connection is developed and simulated by MATLAB/Simulink. The effect of utilizing of variable speed (VS) and constant speed (CS) control on efficiency and energy is studied against different water consumption patterns. In according to results, in plants with double pumps, efficiency is a function of operating points as it varies by different consumption patterns, but in plants with three pumps it varies with a steady algorithm. It is recommended to implement (CS + VS + VS) strategy of control in pumping plant with three centrifugal pumps rather than (VS + VS + CS) as it costs lower in primary expenses of plant construction besides higher reliability, lower maintenance cost and shorter payback time. 10 to 15 percent efficiency increase by all VS control and 5 to 10 percent increase in efficiency is proposed by VS and CS compositional control strategies.

The present study examined the pool boiling process in a specific geometry by designing, constructing a laboratory complex and Providing Empirical Relations. Investigation of pool boiling process, electrical resistance, critical heat flux, heat transfer coefficient, bubble growth and departure, bubble growth frequency, and nucleation site density by applying heat flux to critical heat flux was carried out on wire mesh element in deionized water at different temperatures. According to the results, increasing the size of mesh and fluid temperature decreased the critical heat flux. In the case of a wire mesh with a constant size of mesh, a fluid with a constant temperature, and the use of heat flux values less than the critical heat flux, the wire temperature increased, but it decreased in the case of increasing the size of mesh, a fluid with a constant temperature and applying critical heat flux values. In the case of a constant size of mesh, the heat transfer coefficient was constant by increasing fluid temperature at values of heat flux less than the critical heat flux, but the heat transfer coefficient was increased with increasing values of heat flux less than the critical heat flux and decreased at critical heat flux values. By increasing 4 times the mesh size in the fluid at 30, 70 and 100°C in the critical heat flux, the heat transfer coefficient decreases by 0.7%. The maximum bubble growth frequency is related to the 0.5 mm wire mesh in 100°C fluid with 0.0763 bubbles per millisecond.