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Небесная энциклопедия

Космические корабли и станции, автоматические КА и методы их проектирования, бортовые комплексы управления, системы и средства жизнеобеспечения, особенности технологии производства ракетно-космических систем

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Мониторинг СМИ

Мониторинг СМИ и социальных сетей. Сканирование интернета, новостных сайтов, специализированных контентных площадок на базе мессенджеров. Гибкие настройки фильтров и первоначальных источников.

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Поддерживает ввод нескольких поисковых фраз (по одной на строку). При поиске обеспечивает поддержку морфологии русского и английского языка
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Применить Всего найдено 3. Отображено 3.
23-06-2023 дата публикации

Hydraulic oil gas tank sound identification method based on subdivision abstract features

Номер: CN116312625A
Автор: ZHANG HAO, ZHAO ZENGTAO, PENG YUMIN, CHEN MAN, ZHONG XUEHUI, ZHOU YUPENG, YANG XIPENG, HE RUFEI, HUANG FANQI, FENG ZHIYAN, LU XINXIN, YAO JIANCHAO, JIN HONG-HO, SHEN YAN, ZHANG HUI, SUN JIANCHAO, LI ZHUANG, DOU BOWEN, ZHONG JIANXU, WANG WEI, TAN YIKAI, WANG XIAOYI, ZHONG BAOQIANG, FU JIANMEI, LIU SHIGANG, LIN WEIJIE, ZHENG CHUN
Принадлежит:

The invention discloses a compressed oil gas tank sound identification method based on subdivision abstract features. The method comprises the following steps of: acquiring sound data and performing subdivision and re-processing by utilizing a high sampling rate of a sound sensor; equipment sound abstract feature extraction is carried out by using a matrix auto-encoder; building a convolution-circulation parallel neural network, and carrying out training through subdividing abstract coding features; and obtaining a sound recognition result of the compressed oil gas tank according to the trained convolution-circulation parallel neural network. The method effectively solves the problems of low identification speed, low reliability and the like of the current power plant auxiliary equipment state detection technology, reduces data redundancy through extracting and subdividing abstract features, effectively avoids the possibility that gas leakage features are hidden, and improves the detection ...

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Номер записи: 1
09-05-2023 дата публикации

Electrical equipment sound identification method based on characteristic frequency band selection

Номер: CN116092524A
Автор: ZHANG HAO, ZHAO ZENGTAO, PENG YUMIN, CHEN MAN, ZHONG XUEHUI, ZHOU YUPENG, YANG XIPENG, HE RUFEI, HUANG FANQI, FENG ZHIYAN, LU XINXIN, YAO JIANCHAO, JIN HONG-HO, SHEN YAN, ZHANG HUI, SUN JIANCHAO, LI ZHUANG, DOU BOWEN, ZHONG JIANXU, WANG WEI, TAN YIKAI, WANG XIAOYI, ZHONG BAOQIANG, FU JIANMEI, LIU SHIGANG, LIN WEIJIE, ZHENG CHUN
Принадлежит:

The invention discloses an electrical equipment sound identification method based on characteristic frequency band selection. The method comprises the following steps of: acquiring and preprocessing sound time domain data, and converting the sound time domain data into a frequency domain by using Fourier transform; the method comprises the following steps of: randomly sampling a set number of samples by adopting a Metropolis-Hastings sampling method to establish a partial least square regression model; filtering the frequency band with the minimum weight of the absolute value of the regression coefficient by using a logarithmic attenuation function; selecting a frequency band with a set retention ratio by using weighted sampling, and selecting a corresponding frequency band with a relatively small root-mean-square error of interactive verification as a characteristic frequency band; and establishing a neural network, and identifying the sound state. According to the method, the space dimension ...

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Номер записи: 2
09-05-2023 дата публикации

Electrical equipment state voice recognition method considering time-frequency domain feature fusion

Номер: CN116092525A
Автор: ZHANG HAO, ZHAO ZENGTAO, PENG YUMIN, CHEN MAN, ZHONG XUEHUI, ZHOU YUPENG, YANG XIPENG, HE RUFEI, HUANG FANQI, FENG ZHIYAN, LU XINXIN, YAO JIANCHAO, JIN HONG-HO, SHEN YAN, ZHANG HUI, SUN JIANCHAO, LI ZHUANG, DOU BOWEN, ZHONG JIANXU, WANG WEI, TAN YIKAI, WANG XIAOYI, ZHONG BAOQIANG, FU JIANMEI, LIU SHIGANG, LIN WEIJIE, ZHENG CHUN
Принадлежит:

The invention discloses an electrical equipment state voice recognition method considering time-frequency domain feature fusion. The method comprises the following steps: acquiring and preprocessing sound time domain data; fourier transform is utilized to convert a time domain signal into a frequency domain signal, frequency domain feature selection and algorithm training are simultaneously carried out based on an embedding method, and an optimal feature subset is selected; performing time domain signal feature extraction on the original sound signal by using a packaging method; the time domain features and the frequency domain features are filtered and fused through a mutual information method; and establishing a neural network, and identifying the sound state based on the time-frequency domain fusion signal. On the basis of effective fusion of the time domain information and the frequency domain information, on one hand, important feature information of the time domain and the frequency ...

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Номер записи: 3