Rafia Nishat Toma

Khulna University | KU · Department of Electronics and Communication Engineering

Rolling bearings are treated as important machinery power components, faults of rolling bearings affect machinery operation, so an intelligent fault diagnosis method is very useful of safety operation in rolling bearings. This paper proposes a novel fault diagnosis method based on improved Adaptive Deep Convolution Neural Networks algorithm to real...

Condition monitoring becomes an integral part of the industrial manufacturing system to ensure a safe working environment and reduce the cost of maintenance. Involving deep learning techniques in fault diagnosis methods not only increases the accuracy and reliability of the system but also reduces the operation time and hassle of the manual feature...

In the machine learning and data science pipelines, feature extraction is considered the most crucial component according to researchers, where generating a discriminative feature matrix is the utmost challenging task to achieve high classification accuracy. Generally, the classical feature extraction techniques are sensitive to the noisy component...

Diagnostics of mechanical problems in manufacturing systems are essential to maintaining safety and minimizing expenditures. In this study, an intelligent fault classification model that combines a signal-to-image encoding technique and a convolution neural network (CNN) with the motor-current signal is proposed to classify bearing faults. In the b...

Monitoring systems for electrical appliances have gained massive popularity nowadays. These frameworks can provide consumers with helpful information for energy consumption. Non-intrusive load monitoring (NILM) is the most common method for monitoring a household’s energy profile. This research presents an optimized approach for identifying load ne...

Condition monitoring can avoid sudden breakdown and ensure the reliable and safe operation of rotating machinery used in the industry. The early detection of fault signatures and accurately classifying them in time will ensure efficient maintenance operation and reduce the possibility of losses due to uncertain breakdown. In the fault diagnosis mec...

Bearings are nonlinear systems that can be used in several industrial applications. In this study, the combination of a strict-feedback backstepping digital twin and machine learning algorithm was developed for bearing crack type/size diagnosis. Acoustic emission sensors were used to collect normal and abnormal data for various crack sizes and moto...

Fault diagnosis and classification for machines are integral to condition monitoring in the industrial sector. However, in recent times, as sensor technology and artificial intelligence have developed, data-driven fault diagnosis and classification have been more widely investigated. The data-driven approach requires good-quality features to attain...

Bearing failure is considered as one of the major problems in induction motor, which can result a huge mechanical damage if is not monitored from the initial stage. A complete fault classification method is presented in this paper by combining wavelet-based signal processing technique and deep learning method for fault classification. Vibration sig...

Condition monitoring is used to track the unavoidable phases of rolling element bearings in an induction motor (IM) to ensure reliable operation in domestic and industrial machinery. The convolutional neural network (CNN) has been used as an effective tool to recognize and classify multiple rolling bearing faults in recent times. Due to the nonline...

Condition monitoring of induction motors plays a significant role in avoiding unexpected breakdowns and reducing excessive maintenance costs. In the majority of cases, bearing faults are found to be an issue in the failure of induction motors. The detection and valuation of irregularities at an early stage can help prevent disastrous failures. In t...

Bearing fault diagnosis at early stage is very significant to ensure seamless operation of induction motors in industrial environment. The identification and classification of faults helps to undertook maintenance operation in an efficient manner. This paper presents an ensemble machine learning-based fault classification scheme for induction motor...

Efficient fault diagnosis of electrical and mechanical anomalies in induction motors (IMs) is challenging but necessary to ensure safety and economical operation in industries. Research has shown that bearing faults are the most frequently occurring faults in IMs. The vibration signals carry rich information about bearing health conditions and are...

Among an electricity provider's non-technical losses, electricity theft has the most severe and dangerous effects. Fraudulent electricity consumption decreases the supply quality, increases generation load, causes legitimate consumers to pay excessive electricity bills, and affects the overall economy. The adaptation of smart grids can significantl...

This paper deals with the design and study of parameters of square shaped microstrip patch antenna suitable for 5G communication systems. It is designed on Rogers RT Duroid 5880, which has a dielectric constant of 2.2. In this study, a micro-strip line fed patch antenna array, operating at a resonant frequency of 10.21GHz which is preferred for 5G...

As the technology enters into deep sub-micron region, signal integrity is becoming a very crucial parameter. In order to deal with the challenges associated with signal integrity problem, such as, crosstalk noise and delay, estimation and minimizing techniques should be addressed with great importance. Along with this, the peak noise amplitude and...

As the technology enters into deep sub-micron region, signal integrity is becoming a very crucial parameter. In order to deal with the challenges associated with signal integrity problem, such as, crosstalk noise and delay, estimation and minimizing techniques should be addressed with great importance. Along with this, the peak noise amplitude and...

This paper deals with the design and study of parameters of square-shaped microstrip patch antenna suitable for 5G communication systems. It is designed on Rogers RT Duroid 5880, with a dielectric constant of 2.2. In this study, a micro-strip line-fed patch antenna array, operating at a resonant frequency of 10.21GHz which is preferred for 5G appli...

The ubiquitous computing era is characterized by wide deployment of resource constraint devices. Secure communication between such devices encounters a big challenge due to their resource limitation. The lightweight cryptographic algorithms are developed to address this challenge. In this work, implementation of LBlock, a lightweight encryption alg...

In this paper, the usefulness of parabolic index profile with single clad as well as double clad fiber structure has been investigated for the design of erbium doped fiber amplifier (EDFA) and laser (EDFL). The characteristics of parabolic profile fiber lasers in terms of couple pump power and cavity length have been simulated for 980 nm pump and 1...

The modeling of interconnections is very much important, as the performance of VLSI circuit is limited by interconnect related failure modes, such as coupled noise and delay. Inductance along with capacitance causes noise in the signals, which may adversely affect the performance of the circuit and signal integrity. An analytical expression for cro...