Shield-carried noncontact frequency-domain electrical real-time advanced detection system and method

    公开(公告)号:US10260345B2

    公开(公告)日:2019-04-16

    申请号:US15323284

    申请日:2016-04-21

    Abstract: A shield-carried noncontact frequency-domain electrical real-time advanced detection system and method are provided. Noncontact electrodes are installed on a cutter head of a shield tunneling machine, current is emitted and received using capacitance coupling, the electrodes are connected to a host via a multi-way swivel joint, measured data is inversed and interpreted in real time, and the prediction result is transmitted to a control system of the shield tunneling machine so as to provide a technical support for safety construction of the shield tunneling machine; the noncontact electrodes are installed on the shield cutter head. Real-time advanced detection of geology in front of a tunnel face can be realized in the tunneling process, so that the requirement for quick tunneling construction is met, and the efficiency of advanced geological detection of the shield tunneling machine is improved; and an electrode system is only installed on the cutter head.

    Multi-scale unsupervised seismic velocity inversion method based on autoencoder for observation data

    公开(公告)号:US11828894B2

    公开(公告)日:2023-11-28

    申请号:US18031289

    申请日:2021-12-14

    CPC classification number: G01V1/303 G01V2210/6222 G01V2210/66

    Abstract: A multi-scale unsupervised seismic velocity inversion method based on an autoencoder for observation data. Large-scale information is extracted by the autoencoder, which is used for guiding an inversion network to complete the recovery of different-scale features in a velocity model, thereby reducing the non-linearity degree of inversion. A trained encoder part is embedded into the network to complete the extraction of seismic observation data information at the front end, so it can better analyze the information contained in seismic data, the mapping relationship between the data and velocity model is established better, then the inversion method is unsupervised, and location codes are added to the observation data to assist the network in perceiving the layout form of an observation system, which facilitates practical engineering application. Thus a relatively accurate inversion result of the seismic velocity model when no real geological model serves as a network training label can be achieved.

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