Central South University

Jin Qin

Hui Liu

Zhu Duan

Shi Yin

Chao Chen

Yanfei Li

Haiping Wu

Chengming Yu

Lei Zhang

The present invention discloses a method and system for training a passenger distribution prediction model, and a method and system for guiding passengers. In an embodiment, the passenger distribution is intelligently sensed by means of the characteristics of temperature, humidity and COconcentration distribution changes in cars caused by passenger density changes, which avoids the problems of crowd flow and obscuration faced by passenger distribution detection conducted with images, and avoids the difficulty in floor intrusive transformation faced by passenger distribution detection conducted with pressure sensors; the passenger flow is guided by adjusting the brightness of lighting tubes in the cars, for example, the lighting tubes in areas with high passenger density are dimmed, and the lighting tubes in areas with low passenger density are brightened, to guide ordered flow of passengers toward areas with low passenger density. Further details are disclosed herein.

Training method and system for passenger distribution prediction model, and passenger guiding method and system

The present invention discloses a train compartment vibration monitoring method and vibration signal feature library establishment and application methods. The non-intrusive train compartment vibration monitoring method only obtains vibration signals of a main measurement point in a train compartment during actual monitoring. The method accurately and truthfully reflects the relationship between the position of a vibration source and the phase offset and amplitude attenuation, can monitor the vibration of an unknown vibration source, and can identify the abnormal vibration to provide a basis for abnormal vibration processing. The method can realize the reconstruction of vibration source signals on the basis of only measuring the vibration signals of the main measurement point, so as to realize the real-time update of multiple variable vibration signal feature library; and the multivariable vibration signal feature library can provide a data basis for vibration signal optimization decomposition, vibration signal image identification, abnormal vibration signal identification, etc.

Train compartment vibration monitoring method and vibration signal feature library establishment and application methods

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Hunan, China

Jin Qin