Kenichi Hirotsu

Study on detection for the defects of XLPE cable lines

This paper reports the results of a basic study of testing methods to replace the DC after laying test that is presently most frequently used as an after laying test for XLPE power cable lines. Chosen as the alternative waveforms for DC voltage were damped oscillating wave (OSW) and very-low-frequency wave (VLF) voltages. Experiments were conducted on the ability to detect various types of line defects under these voltages. It was found that these alternative waveforms are promising as after laying test voltage waveforms to replace DC and that greater defect detection ability can be achieved by combining them when conducting tests.

A CMOS feedforward neural-network chip with on-chip parallel learning for oscillation cancellation

The paper presents a mixed signal CMOS feedforward neural-network chip with on-chip error-reduction hardware for real-time adaptation. The chip has compact on-chip weighs capable of high-speed parallel learning; the implemented learning algorithm is a genetic random search algorithm: the random weight change (RWC) algorithm. The algorithm does not require a known desired neural network output for error calculation and is suitable for direct feedback control. With hardware experiments, we demonstrate that the RWC chip, as a direct feedback controller, successfully suppresses unstable oscillations modeling combustion engine instability in real time.