International Journal of Engineering and Technology Innovation

Edge Detection Method Driven by Knowledge-Based Neighborhood Rules

2022-12-16T19:41:15+08:00

Edge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the rules is based on the observed continuity properties and the neighborhood characteristics of the edge pixels, which are expressed as simple arithmetical operations to improve computational complexity. The results show that the method has an advantage over the gradient-based methods in terms of performance and computational load. It is appropriately four times faster than Canny method and shows superior performance compared to the gradient-based methods in general. Furthermore, the proposed method provides robustness to effectively identify edges at the corners. Due to its light computational requirement and inherent parallelization properties, the method would be also suitable for hardware implementation on field-programmable gate arrays (FPGA).

A Robust Technique for Detection, Diagnosis, and Localization of Switching Faults in Electric Drives Using Discrete Wavelet Transform

2022-12-16T19:41:15+08:00

Detection, diagnosis, and localization of switching faults in electric drives are extremely important for operating a large number of induction motors in parallel. This study aims to present the design and development of switching fault detection, diagnosis, and localization strategy for the induction motor drive system (IMDS) by using a novel diagnostic variable that is derived from discrete wavelet transform (DWT) coefficients. The distinctiveness of the proposed algorithm is that it can identify single/multiple switch open and short faults and locate the defective switches using a single mathematical computation. The proposed algorithm is tested by simulation in MATLAB/Simulink and experimentally validated using the LabVIEW hardware-in-the-loop platform. The results demonstrate the robustness and effectiveness of the proposed technique in identifying and locating faults.

Analysis of Outer Race Bearing Damage by Calculation of Sound Signal Frequency Based on the FFT Method

2023-02-02T08:53:46+08:00

This study aims to identify the outer race bearing needed to protect an induction motor from severe damage. Faults are diagnosed using a non-invasive technique through the sound signal from an induction motor. The diagnosis aims to assess the damage to the bearings on the fan or main shaft. Moreover, this study discusses the type of damage, loading variations, and the diagnostic accuracy with the damage to the outer race bearing placed on the fan or main shaft rotor. The disturbance detection approach is used to analyze the sound spectrum to identify the harmonic components near the disturbance frequency. The damage frequency characteristics are also calculated to determine the sound spectrum peak value. The results show that the detection is slightly affected by the damage severity and the incorrect placement of the bearings on the rotor shaft. The lowest detection accuracy in testing the outer race bearing damage on the fan shaft is 91.66%. However, the accuracy percentage is 100% with the outer race bearing damage on the main shaft.

A Review of Control Techniques for Wind Energy Conversion System

2022-12-16T19:41:15+08:00

Wind energy is the most efficient and advanced form of renewable energy (RE) in recent decades, and an effective controller is required to regulate the power generated by wind energy. This study provides an overview of state-of-the-art control strategies for wind energy conversion systems (WECS). Studies on the pitch angle controller, the maximum power point tracking (MPPT) controller, the machine side controller (MSC), and the grid side controller (GSC) are reviewed and discussed. Related works are analyzed, including evolution, software used, input and output parameters, specifications, merits, and limitations of different control techniques. The analysis shows that better performance can be obtained by the adaptive and soft-computing based pitch angle controller and MPPT controller, the field-oriented control for MSC, and the voltage-oriented control for GSC. This study provides an appropriate benchmark for further wind energy research.

Using Feedback Control to Control Rotor Flux and Torque of the DFIG-Based Wind Power System

2022-12-16T19:41:14+08:00

Direct torque control (DТС) is a method of controlling electrical machines that are widely used, and this is due to its simplicity and ease of use. However, this method has several issues, such as torque, rotor flux, and current fluctuations. To overcome these shortcomings and improve the characteristics and robustness of the DTC strategy of the doubly-fed induction generator (DFIG), a new DTC scheme based on the feedback control method (FCM) and space vector modulation (SVM) is proposed. In the proposed DTC technique, a proportional-integral controller based on feedback control theory is used to control and regulate the torque and rotor flux of the DFIG. On the other hand, the SVM technique is used to control the rotor side converter (RSC) to obtain a high-quality current. The simulation result shows that the proposed DTC technique has the advantages of faster dynamics and reduced harmonic distortion of current compared to the ‎conventional technique.‎

On the Performance Analysis and Environmental Impact of Concrete with Coal Fly Ash and Bottom Ash

2022-12-16T19:41:15+08:00

Coal is a commonly used fuel by coal power plants that produce coal fly ash and coal bottom ash (coal FABA) as byproducts. The latest regulation in Indonesia changes coal FABA classification to non-toxic waste, which opens up its utilization possibility. This paper analyses the coal FABA potential from Suralaya Coal Power Plant as concrete material and its environmental impact. To determine coal FABA potential, the methods used in this paper are slump test, compressive strength test, flexural strength test, and carbon footprint calculation. This paper shows that concrete mixture with coal FABA content has a lower slump value, lower compressive strength, and generally lower flexural strength. Furthermore, the carbon footprint calculation result shows that concrete mixture with coal FABA content has lower CO₂ emissions than conventional concrete. Finally, the result shows that concrete with coal FABA could be used as non-structural concrete.