An engine control system is responsible for controlling the combustion parameters of an internal ... more An engine control system is responsible for controlling the combustion parameters of an internal combustion engine to increase the efficiency of the engine. An optimized parameter setting of an engine control system is highly influenced by the engine load. Therefore, with a change in engine load, the parameter settings need to be updated for higher engine efficiency. Hence, to optimize parameter settings during operation, engine load information is necessary. In this paper, we propose a real-time engine load classification from sensed signals. For the classification, an artificial neural network is used and trained using processed, real, measured data. To that end, a magnetic pickup sensor extracts the rotational speed of the prime mover of a four-stroke V12 marine diesel engine. The measured signal is then converted into a crank angle degree (CAD) signal that shows the behavior of the combustion strokes of firing cylinders at a particular engine load. The CAD signals are considered...
This paper introduces algorithms for the multi-RAT load balancing function to maximize QoE in ter... more This paper introduces algorithms for the multi-RAT load balancing function to maximize QoE in terrestrial and satellite combined system developed in the 5G-ALLSTAR project. The pros and cons of the considered algorithms are described and the simulator is also described in the paper with the on-going performance evaluation processes.
2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
In this paper, we propose an engine load classification algorithm using torque data in the crank-... more In this paper, we propose an engine load classification algorithm using torque data in the crank-angle domain. Engine cylinder operation is different at different engine loads. Engine load information helps to predict the chances or understanding the behavior of a malfunction in engine operation. Hence, we developed an engine load classifier based on signal processing and using an artificial neural network. To that end, we use a magnetic pickup sensor to extract a four-stroke V-type diesel engine's operational information. The pickup sensor's signals are converted to the crank-angle domain (CAD) signal and CAD signals are used in conjunction with the proposed classifier to classify the engine load. For verification, we considered two engine loads (100% and 75%) for a V-type 12-cylinder diesel engine. The proposed algorithm classifies these engine loads with 100% efficiency.
An engine control system is responsible for controlling the combustion parameters of an internal ... more An engine control system is responsible for controlling the combustion parameters of an internal combustion engine to increase the efficiency of the engine. An optimized parameter setting of an engine control system is highly influenced by the engine load. Therefore, with a change in engine load, the parameter settings need to be updated for higher engine efficiency. Hence, to optimize parameter settings during operation, engine load information is necessary. In this paper, we propose a real-time engine load classification from sensed signals. For the classification, an artificial neural network is used and trained using processed, real, measured data. To that end, a magnetic pickup sensor extracts the rotational speed of the prime mover of a four-stroke V12 marine diesel engine. The measured signal is then converted into a crank angle degree (CAD) signal that shows the behavior of the combustion strokes of firing cylinders at a particular engine load. The CAD signals are considered...
This paper introduces algorithms for the multi-RAT load balancing function to maximize QoE in ter... more This paper introduces algorithms for the multi-RAT load balancing function to maximize QoE in terrestrial and satellite combined system developed in the 5G-ALLSTAR project. The pros and cons of the considered algorithms are described and the simulator is also described in the paper with the on-going performance evaluation processes.
2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)
In this paper, we propose an engine load classification algorithm using torque data in the crank-... more In this paper, we propose an engine load classification algorithm using torque data in the crank-angle domain. Engine cylinder operation is different at different engine loads. Engine load information helps to predict the chances or understanding the behavior of a malfunction in engine operation. Hence, we developed an engine load classifier based on signal processing and using an artificial neural network. To that end, we use a magnetic pickup sensor to extract a four-stroke V-type diesel engine's operational information. The pickup sensor's signals are converted to the crank-angle domain (CAD) signal and CAD signals are used in conjunction with the proposed classifier to classify the engine load. For verification, we considered two engine loads (100% and 75%) for a V-type 12-cylinder diesel engine. The proposed algorithm classifies these engine loads with 100% efficiency.
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Papers by Maaz Shahid