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Papers by Gyanendra Singh

Research paper thumbnail of Abnormal Health Monitoring and Assessment of a Three-Phase Induction Motor Using a Supervised CNN-RNN-Based Machine Learning Algorithm

Mathematical Problems in Engineering, Jan 30, 2023

Tis paper shows the health monitoring and assessment of a three-phase induction motor in abnormal... more Tis paper shows the health monitoring and assessment of a three-phase induction motor in abnormal conditions using a machine learning algorithm. Te convolutional neural network (CNN) and recurrent neural network (RNN) algorithms are the prominent methods used in machine learning algorithms, and the combined method is known as the CRNN method. Te abnormal conditions of a three phase-induction motor are represented by three-phase faults, line-to-ground faults, etc. Te pattern of fault current is traced, and key features are extracted by the CRNN algorithm. Te performance parameters like THD (%), accuracy, and reliability of abnormal conditions are measured with the CRNN algorithm. Te assessment of abnormal conditions is being realized at the terminals of a three-phase induction motor. A fuzzy logic controller (FLC) is also used to assess such abnormalities. It is observed that performance parameters are found to be better with the CRNN method in comparison to CNN, RNN, ANN, and other methods. Such a realization makes the system more compatible with abnormality recognition.

Research paper thumbnail of An Invasive Weed Optimization for Sensor Less Control of Grid Integrated Wind Driven Doubly Fed Induction Generator

IEEE Access

The article presents the design and development of invasive weed optimization (IWO) for the senso... more The article presents the design and development of invasive weed optimization (IWO) for the sensor less speed control of doubly fed induction generator (DFIG) under balanced and unbalanced conditions. A healthy condition represents the balanced condition while unbalancing condition is characterized by unhealthy conditions like three-phase fault, single line to ground fault, the line-to-line fault, and double line to ground fault. The DFIG is driven by wind and integrated with the grid. The advantages associated with IWO technique are a simple mathematical approach and less data computation. Normally, DFIG consists of two back-to-back converters namely grid side converter (GSC) and rotor side converter (RSC). The GSC is an uncontrolled converter while the RSC is a controlled converter. The existing methods have poor performance parameters like settling time, peak overshoot for balanced conditions, and poor power quality parameters like total harmonic distortion (THD) for unbalanced conditions. An IWO technique has been applied to overcome such limitations. The effectiveness of the sensor less speed control is also analyzed with other techniques like Adaptive Neuro-Fuzzy Interference System (AN-FIS) & artificial neural network (ANN). The design of ANN is based on the feed-forward method using back propagation delay and the design of ANFIS is based on adaptive control and state space control strategy. It is observed that performance parameters like peak overshoot and settling time for the sensor less speed of DFIG are found to be more profound with IWO in comparison to ANFIS, ANN, and other existing techniques for balanced conditions. Similarly in the unbalanced condition, faulty current approaches are quite closer to their healthy state with the IWO method in comparison to other methods. In addition to this, minimum distortion (%THD) for the grid current under unbalanced conditions is also attained with IWO in comparison to ANFIS, ANN, and other existing techniques. Such application of IWO makes the system highly efficient and robust.

Research paper thumbnail of Nanomaterials for Postharvest Management of Insect Pests: Current State and Future Perspectives

Frontiers in Nanotechnology, 2022

Globally, between one quarter and one-third of total grains produced each year are lost during st... more Globally, between one quarter and one-third of total grains produced each year are lost during storage mainly through infestation of insect pests. Among the available control options such as chemical and physical techniques, fumigation with aluminum phosphide (AlP) is so far considered the best control strategy against storage insect pests. However, these insect pests are now developing resistance against AIP due to its indiscriminate use due to non-availability of any effective alternative control option. Resistance to AIP among storage insect pests is increasing, and its inhalation has shown adverse effects on animals and human beings. Nanotechnology has opened up a wide range of opportunities in various fields such as agriculture (pesticides, fertilizers, etc.), pharmaceuticals, and electronics. One of the applications of nanotechnology is the usage of nanomaterial-based insecticide formulations for mitigating field and storage insect pests. Several formulations, namely, nanoemul...

Research paper thumbnail of Perspective of enhancing wheat production and productivity in Uttar Pradesh by improving varietal replacement rate

Journal of Cereal Research, 2020

Research paper thumbnail of Enhancing the livelihoods of Uttarakhand farmers by introducing pigeonpea cultivation in hilly areas

Pilot production demonstrations conducted in Uttarakhand state of India indicated that pigeonpea ... more Pilot production demonstrations conducted in Uttarakhand state of India indicated that pigeonpea [Cajanus cajan (L.) Millsp.] variety 'VL Arhar-1' (ICPL 88039) can be grown successfully up to the elevations of 2,000 metres. This extrashort duration pigeonpea variety is well-adapted to the agroecological conditions of Uttarakhand, and suitable for grain production (up to 1,800 kg/ha) and for soil conservation. The cultivation of pigeonpea, therefore, can be extended into areas predominantly characterized by low soil fertility and inhabited by resource poor farmers. The introduction of pigeonpea in the hills of the Himalayas will help in promoting sustainable and eco-friendly agricultural practices that are cost effective and easy to adopt by the poor farming community. Pigeonpea, being a good source of home-grown high protein food, would directly benefit the nutrition, health and livelihoods of small holder farmers of Uttarakhand. Hence, it is recommended that sincere efforts should be made to promote the cultivation of pigeonpea on a large scale in the slopes and waste lands of this state, and possibly on the hilly areas in India.

Research paper thumbnail of FSAS: An IoT-Based Security System for Crop Field Storage

International Journal of Distributed Sensor Networks

Internet of Things abstracts the ability to remotely associate and observe things or objects over... more Internet of Things abstracts the ability to remotely associate and observe things or objects over the Internet. When it comes to agriculture, this idea has been incorporated to make agriculture-related tasks smart, secure, and automated. Agriculture is vital for economic growth and also for the survival of humans. Farmers living in rural areas of India face a common problem of the theft of equipment like induction motors from small storage houses meant for storing commodities in crop fields. In this study, we present a remote security management framework for monitoring the crop field storage house, known as the farm security alert system (FSAS). FSAS is a small, energy efficient, low cost, and accurate security management system that uses microcontroller-based passive infrared (PIR) sensor and global system for mobile communication (GSM) module to generate an alert to the farm owner if there is an intrusion event at the crop field store. The microcontroller board utilized in the pr...

Research paper thumbnail of Research Article FSAS: An IoT-Based Security System for Crop Field Storage

International Journal of Distributed Sensor Networks, 2023

Internet of Things abstracts the ability to remotely associate and observe things or objects over... more Internet of Things abstracts the ability to remotely associate and observe things or objects over the Internet. When it comes to agriculture, this idea has been incorporated to make agriculture-related tasks smart, secure, and automated. Agriculture is vital for economic growth and also for the survival of humans. Farmers living in rural areas of India face a common problem of the theft of equipment like induction motors from small storage houses meant for storing commodities in crop fields. In this study, we present a remote security management framework for monitoring the crop field storage house, known as the farm security alert system (FSAS). FSAS is a small, energy efficient, low cost, and accurate security management system that uses microcontroller-based passive infrared (PIR) sensor and global system for mobile communication (GSM) module to generate an alert to the farm owner if there is an intrusion event at the crop field store. The microcontroller board utilized in the proposed model is the Arduino Uno, and PIR motion sensor is used to recognize the intruder. In addition, FSAS also can be used for monitoring of induction motor by utilizing a similar arrangement of sensors. The sensor signal is transmitted to the cloud whenever the intruder is within the sensing range of the sensor node. Naive Bayes' prediction model is used to identify the level of encroachment as no (green), mild (yellow), or high (red) threat. The status and the alarms can be received by the farm owners, either on their smartphones as application alerts or as a short message/phone call, at any distance, and independent of whether their cell phones are connected to the Internet.

Research paper thumbnail of Abnormal Health Monitoring and Assessment of a Three-Phase Induction Motor Using a Supervised CNN-RNN-Based Machine Learning Algorithm

Mathematical Problems in Engineering, Jan 30, 2023

Tis paper shows the health monitoring and assessment of a three-phase induction motor in abnormal... more Tis paper shows the health monitoring and assessment of a three-phase induction motor in abnormal conditions using a machine learning algorithm. Te convolutional neural network (CNN) and recurrent neural network (RNN) algorithms are the prominent methods used in machine learning algorithms, and the combined method is known as the CRNN method. Te abnormal conditions of a three phase-induction motor are represented by three-phase faults, line-to-ground faults, etc. Te pattern of fault current is traced, and key features are extracted by the CRNN algorithm. Te performance parameters like THD (%), accuracy, and reliability of abnormal conditions are measured with the CRNN algorithm. Te assessment of abnormal conditions is being realized at the terminals of a three-phase induction motor. A fuzzy logic controller (FLC) is also used to assess such abnormalities. It is observed that performance parameters are found to be better with the CRNN method in comparison to CNN, RNN, ANN, and other methods. Such a realization makes the system more compatible with abnormality recognition.

Research paper thumbnail of An Invasive Weed Optimization for Sensor Less Control of Grid Integrated Wind Driven Doubly Fed Induction Generator

IEEE Access

The article presents the design and development of invasive weed optimization (IWO) for the senso... more The article presents the design and development of invasive weed optimization (IWO) for the sensor less speed control of doubly fed induction generator (DFIG) under balanced and unbalanced conditions. A healthy condition represents the balanced condition while unbalancing condition is characterized by unhealthy conditions like three-phase fault, single line to ground fault, the line-to-line fault, and double line to ground fault. The DFIG is driven by wind and integrated with the grid. The advantages associated with IWO technique are a simple mathematical approach and less data computation. Normally, DFIG consists of two back-to-back converters namely grid side converter (GSC) and rotor side converter (RSC). The GSC is an uncontrolled converter while the RSC is a controlled converter. The existing methods have poor performance parameters like settling time, peak overshoot for balanced conditions, and poor power quality parameters like total harmonic distortion (THD) for unbalanced conditions. An IWO technique has been applied to overcome such limitations. The effectiveness of the sensor less speed control is also analyzed with other techniques like Adaptive Neuro-Fuzzy Interference System (AN-FIS) & artificial neural network (ANN). The design of ANN is based on the feed-forward method using back propagation delay and the design of ANFIS is based on adaptive control and state space control strategy. It is observed that performance parameters like peak overshoot and settling time for the sensor less speed of DFIG are found to be more profound with IWO in comparison to ANFIS, ANN, and other existing techniques for balanced conditions. Similarly in the unbalanced condition, faulty current approaches are quite closer to their healthy state with the IWO method in comparison to other methods. In addition to this, minimum distortion (%THD) for the grid current under unbalanced conditions is also attained with IWO in comparison to ANFIS, ANN, and other existing techniques. Such application of IWO makes the system highly efficient and robust.

Research paper thumbnail of Nanomaterials for Postharvest Management of Insect Pests: Current State and Future Perspectives

Frontiers in Nanotechnology, 2022

Globally, between one quarter and one-third of total grains produced each year are lost during st... more Globally, between one quarter and one-third of total grains produced each year are lost during storage mainly through infestation of insect pests. Among the available control options such as chemical and physical techniques, fumigation with aluminum phosphide (AlP) is so far considered the best control strategy against storage insect pests. However, these insect pests are now developing resistance against AIP due to its indiscriminate use due to non-availability of any effective alternative control option. Resistance to AIP among storage insect pests is increasing, and its inhalation has shown adverse effects on animals and human beings. Nanotechnology has opened up a wide range of opportunities in various fields such as agriculture (pesticides, fertilizers, etc.), pharmaceuticals, and electronics. One of the applications of nanotechnology is the usage of nanomaterial-based insecticide formulations for mitigating field and storage insect pests. Several formulations, namely, nanoemul...

Research paper thumbnail of Perspective of enhancing wheat production and productivity in Uttar Pradesh by improving varietal replacement rate

Journal of Cereal Research, 2020

Research paper thumbnail of Enhancing the livelihoods of Uttarakhand farmers by introducing pigeonpea cultivation in hilly areas

Pilot production demonstrations conducted in Uttarakhand state of India indicated that pigeonpea ... more Pilot production demonstrations conducted in Uttarakhand state of India indicated that pigeonpea [Cajanus cajan (L.) Millsp.] variety 'VL Arhar-1' (ICPL 88039) can be grown successfully up to the elevations of 2,000 metres. This extrashort duration pigeonpea variety is well-adapted to the agroecological conditions of Uttarakhand, and suitable for grain production (up to 1,800 kg/ha) and for soil conservation. The cultivation of pigeonpea, therefore, can be extended into areas predominantly characterized by low soil fertility and inhabited by resource poor farmers. The introduction of pigeonpea in the hills of the Himalayas will help in promoting sustainable and eco-friendly agricultural practices that are cost effective and easy to adopt by the poor farming community. Pigeonpea, being a good source of home-grown high protein food, would directly benefit the nutrition, health and livelihoods of small holder farmers of Uttarakhand. Hence, it is recommended that sincere efforts should be made to promote the cultivation of pigeonpea on a large scale in the slopes and waste lands of this state, and possibly on the hilly areas in India.

Research paper thumbnail of FSAS: An IoT-Based Security System for Crop Field Storage

International Journal of Distributed Sensor Networks

Internet of Things abstracts the ability to remotely associate and observe things or objects over... more Internet of Things abstracts the ability to remotely associate and observe things or objects over the Internet. When it comes to agriculture, this idea has been incorporated to make agriculture-related tasks smart, secure, and automated. Agriculture is vital for economic growth and also for the survival of humans. Farmers living in rural areas of India face a common problem of the theft of equipment like induction motors from small storage houses meant for storing commodities in crop fields. In this study, we present a remote security management framework for monitoring the crop field storage house, known as the farm security alert system (FSAS). FSAS is a small, energy efficient, low cost, and accurate security management system that uses microcontroller-based passive infrared (PIR) sensor and global system for mobile communication (GSM) module to generate an alert to the farm owner if there is an intrusion event at the crop field store. The microcontroller board utilized in the pr...

Research paper thumbnail of Research Article FSAS: An IoT-Based Security System for Crop Field Storage

International Journal of Distributed Sensor Networks, 2023

Internet of Things abstracts the ability to remotely associate and observe things or objects over... more Internet of Things abstracts the ability to remotely associate and observe things or objects over the Internet. When it comes to agriculture, this idea has been incorporated to make agriculture-related tasks smart, secure, and automated. Agriculture is vital for economic growth and also for the survival of humans. Farmers living in rural areas of India face a common problem of the theft of equipment like induction motors from small storage houses meant for storing commodities in crop fields. In this study, we present a remote security management framework for monitoring the crop field storage house, known as the farm security alert system (FSAS). FSAS is a small, energy efficient, low cost, and accurate security management system that uses microcontroller-based passive infrared (PIR) sensor and global system for mobile communication (GSM) module to generate an alert to the farm owner if there is an intrusion event at the crop field store. The microcontroller board utilized in the proposed model is the Arduino Uno, and PIR motion sensor is used to recognize the intruder. In addition, FSAS also can be used for monitoring of induction motor by utilizing a similar arrangement of sensors. The sensor signal is transmitted to the cloud whenever the intruder is within the sensing range of the sensor node. Naive Bayes' prediction model is used to identify the level of encroachment as no (green), mild (yellow), or high (red) threat. The status and the alarms can be received by the farm owners, either on their smartphones as application alerts or as a short message/phone call, at any distance, and independent of whether their cell phones are connected to the Internet.