INTELLIGENT TECHNIQUE OF CANCELING MATERNAL ECG IN FECG EXTRACTION

ABSTRACT. In this paper, we propose a technique of artificial intelligence called adaptive neuro fuzzy inference system (ANFIS) for canceling maternal electrocardiogram (MECG) in fetal electrocardiogram extraction (FECG).This technique is used to estimate the MECG present in the abdominal signal of a pregnant woman. The FECG is then extracted by subtracting the estimated MECG from the abdominal signal. Performance of the proposed method in terms of mean square error, signal to noise ratio is compared with neural network. Our results show that this method is a simple and powerful means for the extraction of FECG

Fault simulation and fuzzy controller for high pressure heater in thermal power plant (writers from India)

This paper presents fault simulation and design of fuzzy logic controller for a high pressure heater in a thermal power plant. An analytical model for the system has been presented in the nonlinear state space form based on fundamental physical laws. The mathematical model is validated with the real time plant data. A fuzzy controller is developed, which performs like a classical proportional plus integral controller, giving the level reference variation based on error in condensate level inside a heater and its change. The state variables are estimated for the normal and faulty condition using the model which is simulated using the plant data. The performances of both controllers are evaluated and the faults are simulated using Matlab simulink

Fault diagnosis in deaerator using fuzzy logic

In this paper a fuzzy logic based fault diagnosis system for a deaerator in a power plant unit is presented. The system parameters are obtained using the linearised state space deaerator model. The fuzzy inference system is created and rule base are evaluated relating the parameters to the type and severity of the faults. These rules are fired for specific changes in system parameters and the faults are diagnosed

OPTIMIZED FUZZY MODELLING OF A BOILER SUPERHEATER

Modelling of systems is very much useful to study the response of a system for different input variations and for the design of control schemes in both real time application and in the off-line simulation. The development of optimized fuzzy model for a boiler superheater of a 210 MW coal fired thermal boiler power plant is reported in this paper. The fuzzy model has been developed first taking into the input output data sequences of the transfer function model. The complexity of the fuzzy model is removed by means of various optimization techniques. The resulting optimized model is complete, compact, and consistent (C 3). Simulation study has been carried out on the fuzzy model both prior and after optimization to get the response of the superheater for various inputs. These results are validated with the results of the transfer function model and are found to be analogous. 1