Explore chapters and articles related to this topic
Power transmission systems
Published in Mike Tooley, Lloyd Dingle, Engineering Science, 2020
We continue our study of power transmission by looking at gears. The gearbox is designed to transfer and modify rotational motion and torque. For example, electric motor output shafts may rotate at relatively high rates, producing relatively low torque. A reduction gearbox interposed between the motor output and load, apart from reducing the speed to that required, would also increase the torque at the gearbox output by an amount equivalent to the gearbox ratio.
Gear Unit Operation: Testing, Startup, Condition Monitoring
Published in Peter Lynwander, Gear Drive Systems, 2019
Gearbox condition can be monitored by the analysis of oil samples. One widely used technique is SOAP (Spectrographic Oil Analysis Program). An oil sample is taken periodically from the gearbox sump and sent to an analytical laboratory, where it is burned and the light waves passed through a spectrometer. The spectrum of light waves given off by the sample yields information as to the types of wear metals suspended in the oil and their quantity.
Mechanical design
Published in Chris Elliott, Planning and Installing Micro-Hydro Systems, 2014
Gearboxes are typically supported on their casting via a reinforced concrete or fabricated steel foundation, or can be supported on their shaft with a torque arm to keep the gearbox stationary. Gearboxes are usually fitted with multiple shafts with spur or helical gears (usually the latter) to achieve the speed increase, but can also be epicyclic where the input and output shaft are coaxial and the gearbox is quite compact.
A Review Analysis on Performance and Classification of Wind Turbine Gearbox Technologies
Published in IETE Journal of Research, 2022
Hall and Chen [15] studied the performance of the variable ratio gear box in the drive train of a small to medium-size wind turbine to improve aerodynamic efficiency. The planetary gearbox technologies are sub-classified as Helical gears, Power split drive train, Variable ratio gearbox, and Hybrid transmission techniques (Figure 4(a–d)).
Designing concurrently and hierarchically coupled engineered systems
Published in Engineering Optimization, 2023
Gehendra Sharma, Janet K. Allen, Farrokh Mistree
A gearbox is a mechanical transmission unit containing a series of integrated gears providing torque and speed conversion. Although mechanical gearboxes are optimized for torque and speed, there are numerous other functional requirements to be satisfied, such as efficiency (Höhn, Michaelis, and Hinterstoißer 2009), noise and vibration (Bozca 2010), and volume and size (Osyczka 1978). Höhn, Michaelis, and Hinterstoißer (2009), Bozca (2010) and Goharimanesh, Akbari, and Tootoonchi (2014) present methods for designing gearboxes with a single criterion, while Osyczka (1978), Deb and Sachin (2003) and Stefanović-Marinović, Troha, and Milovančević (2017) present methods for designing gearboxes with multiple criteria. Suitable material selection is another critical aspect of designing gearboxes. Multicriteria decision-making methods are common approaches applied in material selection. Terán, Martínez-Gómez, and Leguisamo Milla (2020) present multicriteria decision methods for selecting material by optimizing surface fatigue in gearbox while also increasing its resistance to wear. Das, Bhattacharya, and Sarkar (2016) showcase an approach for the simultaneous selection of material and geometric variables in gear design using decision-based design. Maputi and Arora (2020) present a gear concept selection procedure by incorporating tacit information in the design process. Kulkarni et al. (2015) present a different approach for simultaneous exploration of the geometry and material space in gear design by considering material as a design variable. In their formulation, they use gear material as a variable with tensile strengths varying between 800 and 1600 MPa, instead of using some set of material alternatives with predefined material properties. However, in this approach they do not consider decision coupling in gearbox design, which is the main focus in this article. Regardless of the design methods, the design process associated with a gearbox requires the solution of a number of problems in several stages (Babichev and Barmina 2020). These stages involve decisions resulting from analyses involving design calculations (static, fatigue, thermal, vibration), materials, manufacturing, economics, etc. These decisions are interrelated; that is, one decision is likely to influence other decisions. To effect better decision making, it is imperative to: identify critical decisions for designing such systemsidentify analyses from various knowledge domains governing these decisionsmodel interactions among design decisions.
An Application of Fuzzy Fault Tree Analysis for Reliability Evaluation of Wind Energy System
Published in IETE Journal of Research, 2022
The energy demand is increasing day by day hence there is a need for a reliable energy source that satisfies the present energy scenario such as the wind energy system. The rapid growth of the wind energy system makes the wind generator structure extra complex, and the rate of failure is increasing consequently. However, the destructive operating conditions and a variable load of the wind turbines are responsible for the high failure rates. But, the wind energy system is beginning to present good reliability in comparison with diesel generators. Gearbox is the key component and it is used to transmit torque and control the speed. The gearbox failures are because of the long term operation of variable speed loads, unbalance of the shaft, gear damage, broken shaft, etc. The wind generator rotor is one of the main components of the wind energy system. But the rotors of the wind turbine are likely to disturb due to the water in blades, fatigue harm to the blade and unequal icing on the surface of the blade [1]. If the rotor is unstable then the vibration at shaft frequency would be more. Finally, this vibration arrives at the generator along with the wind turbine drive system. Also, stator winding faults of the generator affect the events. Also, the economic selection of converters in the wind energy system can enhance the reliability level [2]. There are many reliability assessment methods used in renewable and non-renewable based power systems such as Fault Tree Analysis, Effect Analysis and Failure Mode, etc. The trip cut decision tree approach is used with the use of separate characteristics of the wind turbine system. This provides spontaneous risk information for workers but it does not provide the early sign of failure [3]. Whereas, to enhance the maximum power output of wind turbine, the optimization model is applied and then this model is used with a reliability test system [4]. The fault tree technique is also employed to know the faults occurrence in the substation monitoring system [5]. Besides this, the impact of environmental factors on wind turbines is also determined by the life cycle cost analysis but due to the non-availability of exact database, this technique can not be used for long term investigation [6]. The old failure rate models are collected to know the reliability of any system. This data can be used to develop an accurate reliability model [7]. Whereas, an analytical method can also be used to know the reliability of the system for feeders holding renewable energy-based units [8]. Besides this, the reliability of the system can also be determined with integration of a wind based energy system with another system to know the impact on the whole system [9]. The analytical approach is used to know the reliability of the output model of large scale wind farms [10]. The fault tree analysis approach is also used to know the top event failure occurrence. So, this needs knowledge of bathtub curves for every system component. But bathtub curves require the failure time distribution functions. These functions cannot be determined by the possible approach. These can be generated by expert opinions and fuzzy formula [11].