An improved pulse width modulation (PWM) neural network VLSI circuit for fault diagnosis is presented, which differs from the software-based fault diagnosis approach and exploits the merits of neural network VLSI circ...An improved pulse width modulation (PWM) neural network VLSI circuit for fault diagnosis is presented, which differs from the software-based fault diagnosis approach and exploits the merits of neural network VLSI circuit. A simple synapse multiplier is introduced, which has high precision, large linear range and less switching noise effects. A voltage-mode sigmoid circuit with adjustable gain is introduced for realization of different neuron activation functions. A voltage-pulse conversion circuit required for PWM is also introduced, which has high conversion precision and linearity. These 3 circuits are used to design a PWM VLSI neural network circuit to solve noise fault diagnosis for a main bearing. It can classify the fault samples directly. After signal processing, feature extraction and neural network computation for the analog noise signals including fault information,each output capacitor voltage value of VLSI circuit can be obtained, which represents Euclid distance between the corresponding fault signal template and the diagnosing signal, The real-time online recognition of noise fault signal can also be realized.展开更多
A current-mode MOS neuron circuit with 4-bit programmable weights is presented by using CMOS technology. The weights of the neurcn have high resolution and also can easily be digitally stored. The resolution can be ex...A current-mode MOS neuron circuit with 4-bit programmable weights is presented by using CMOS technology. The weights of the neurcn have high resolution and also can easily be digitally stored. The resolution can be extended into high levels such as 8-bit, etc. by the design methodology presented in this paper. The operational principle of the neuron is discussed. Circuit simulation has been made by use of SPICE II. The results give a good agreement for the design requirements.展开更多
基金Supported by National Natural Science Foundation (60274015) the "863" Program of P, R. China (2002AA412420)
文摘An improved pulse width modulation (PWM) neural network VLSI circuit for fault diagnosis is presented, which differs from the software-based fault diagnosis approach and exploits the merits of neural network VLSI circuit. A simple synapse multiplier is introduced, which has high precision, large linear range and less switching noise effects. A voltage-mode sigmoid circuit with adjustable gain is introduced for realization of different neuron activation functions. A voltage-pulse conversion circuit required for PWM is also introduced, which has high conversion precision and linearity. These 3 circuits are used to design a PWM VLSI neural network circuit to solve noise fault diagnosis for a main bearing. It can classify the fault samples directly. After signal processing, feature extraction and neural network computation for the analog noise signals including fault information,each output capacitor voltage value of VLSI circuit can be obtained, which represents Euclid distance between the corresponding fault signal template and the diagnosing signal, The real-time online recognition of noise fault signal can also be realized.
文摘A current-mode MOS neuron circuit with 4-bit programmable weights is presented by using CMOS technology. The weights of the neurcn have high resolution and also can easily be digitally stored. The resolution can be extended into high levels such as 8-bit, etc. by the design methodology presented in this paper. The operational principle of the neuron is discussed. Circuit simulation has been made by use of SPICE II. The results give a good agreement for the design requirements.
