Mitsubishi Electric

About: Mitsubishi Electric is a company organization based out in Ratingen, Germany. It is known for research contribution in the topics: Signal & Voltage. The organization has 23024 authors who have published 27591 publications receiving 255671 citations. The organization is also known as: Mitsubishi Electric Corporation & Mitsubishi Denki K.K..

Analysis of very fast transients in transformers

Abstract: Very fast transient overvoltages generated in gas-insulated switchgear could cause a voltage oscillation inside the connected transformer. A practical method to calculate the high-frequency transients in the transformer winding is developed based on multiconductor transmission-line theory. Resonance characteristics of a transformer are assessed using the inductance matrix obtainable from its winding geometry. Applicability to transients of frequencies up to several megahertz is checked in a model transformer and an actual 500 kV transformer. The calculated interturn voltage waveforms are in particularly good agreement with experiment.

Development of railway static power conditioner used at substation for Shinkansen

Abstract: High-speed AC electric railways, such as Shinkansen, require large single-phase AC electric power. So, if the short circuit capacity of the power system is not large enough, therefore, railway operation causes large voltage unbalance at the three-phase side. In this paper, a railway static power conditioner (RPC), a new system for reducing voltage unbalance and fluctuation, is described. To reduce voltage unbalance and fluctuation, the RPC balances effective power of different phase and compensates reactive power and harmonics. It enables operation of high-speed AC electrified railways even if the short circuit capacity of the power system is rather small.

Analysis of PD-generated SF/sub 6/ decomposition gases adsorbed on carbon nanotubes

Abstract: Chemical byproducts analysis has been recognized as a powerful diagnosis method for SF6 gas-insulated switchgear (GIS). The authors have previously demonstrated that a carbon nanotube (CNT) gas sensor could detect partial discharge (PD) generated in SF6 gas. However, PD-generated decomposition gas species, which were responsible for the CNT gas sensor response, have not been identified yet. In this paper, two kinds of experiments were conducted in order to identify the responsible decomposition gas species. At first, the decomposition gas molecules adsorbed on CNTs were analyzed by Fourier transformation infrared (FTIR) spectroscopy. FTIR absorbance was observed around 735 cm-1 after CNTs were exposed to PD generated in SF6. In the second experiment, the CNT gas sensor responses to typical SF6 decomposition products (HF and SF4) were examined. The CNT gas sensor responded to these gases in the same way as to PD generated in SF6. SF4 response was larger than HF response. Based on these results, SF 4 and SOF2 emerged as candidates for the responsible decomposition gases. Electrochemical interactions between adsorbed gas molecules and CNT were discussed based on theoretical predictions of molecular orbital calculations. The calculation results suggested that both of SOF2 and SF4 could increase the CNT gas sensor conductance

Charge pump circuit

Abstract: A charge pump circuit comprises a plurality of booster stages Each booster stage has a first node, a second node, a first charge pump and a second charge pump Both charge pumps operate in a complementary manner, and raise potential of the second node relative to potential of the first node by transferring charge from the first node to the second node Each charge pump comprises a pumping capacitor, an NMOS transistor and a PMOS transistor In each charge pump, the NMOS transistor is used for charging the pumping capacitor with charge input through the first node, and the PMOS transistor is used for discharging the pumping capacitor to send charge to the second node

Speech search device and speech search method

Abstract: Disclosed is a speech search device including a recognizer 2 that refers to an acoustic model and language models having different learning data and performs voice recognition on an input speech, to acquire a recognized character string for each language model, a character string comparator 6 that compares the recognized character string for each language models with the character strings of search target words stored in a character string dictionary, and calculates a character string matching score showing the degree of matching of the recognized character string with respect to each of the character strings of the search target words, to acquire both a character string having the highest character string matching score and this character string matching score for each recognized character strings, and a search result determinator 8 that refers to the acquired score and outputs one or more search target words in descending order of the scores.