Abstract: A new generation of network resource management architecture for coverage is provided, which constructs a structure of “signal coverage+capacity coverage” by incorporating satellite, space-based, and ground access points to achieve large-scale regional signal coverage and local area capacity coverage. In the core network, a global resource orchestrator is added, and in the access network, local resource orchestrator and virtual network management and maintenance unit are added for multiple functional units of resource management and control. In terms of coverage structure, it is divided into three-dimensional dense capacity coverage and three-dimensional global signal coverage. The former consists of ground dense network and aerial ad-hoc network, respectively realizing high traffic density coverage and large connection three-dimensional coverage.

Abstract: A generalized autocorrelation method for bearing fault feature extraction under a variable rotational speed condition includes: resampling an original vibration signal in an order domain based on instantaneous phase information by using an order tracking processing method, to greatly weaken a frequency modulation phenomenon; further weakening background noise in consideration of a correlation between a plurality of adjacent fragments by using a generalized autocorrelation method; and controlling an accumulation of periodic disturbances by considering only a correlation between several adjacent signal fragments based on that conventional noise resistant correlation (NRC) methods consider a correlation between all signal fragments and cannot eliminate influence of accumulated periodic disturbances. Compared with the conventional methods, this method overcomes the difficulties caused by mutually restricting signal features, and achieves a better effect.

Abstract: A strong-robustness method for extracting early degradation features of signals and monitoring an operational status of a device is provided. Acquired vibration signal data of a rotating mechanical device is grouped at equal time intervals in a chronological order. Compression conversion is performed on the data, a newly defined function is solved, thereby a performance degradation index of the device is obtained. Data of the device in a normal status is obtained by determining an overall trend of an Exponentially Weighted Moving Average (EWMA) statistic, and a control limit for the EWMA statistic is constructed by using the data in the normal status. The calculated performance degradation index of the device is converted into an EWMA statistic, and the EWMA statistic is compared with the control limit. If the EWMA statistic does not fluctuate about a center line or exceeds the control limit, a monitored state is out of control.

Abstract: A generalized autocorrelation method for bearing fault feature extraction under a variable rotational speed condition includes: resampling an original vibration signal in an order domain based on instantaneous phase information by using an order tracking processing method, to greatly weaken a frequency modulation phenomenon; further weakening background noise in consideration of a correlation between a plurality of adjacent fragments by using a generalized autocorrelation method; and controlling an accumulation of periodic disturbances by considering only a correlation between several adjacent signal fragments based on that conventional noise resistant correlation (NRC) methods consider a correlation between all signal fragments and cannot eliminate influence of accumulated periodic disturbances. Compared with the conventional methods, this method overcomes the difficulties caused by mutually restricting signal features, and achieves a better effect.

Abstract: This application discloses a vehicle drivable area detection method, an autonomous driving assistance system, and an autonomous driving vehicle. The method includes: processing, by using a neural network, image data obtained by a camera apparatus, to obtain a first probability distribution of an obstacle; obtaining a second probability distribution of the obstacle based on a time of flight and an echo width of a radar echo signal; and obtaining, based on the first probability distribution of the obstacle and the second probability distribution of the obstacle, a drivable area of a vehicle represented by a probability, where the probability is a probability that the vehicle cannot drive through the area. The autonomous driving assistance system includes a camera apparatus, at least one radar, and a processor. The system is configured with the technical solutions that can implement the method. The autonomous driving vehicle includes the foregoing autonomous driving assistance system.

Abstract: An automated parking interaction method and apparatus are provided. The method includes: receiving a parking instruction and presenting a parking interaction interface on a display screen in response to the parking instruction; detecting a touch operation performed on the parking interaction interface, so that a vehicle icon moves in the parking interaction interface; obtaining a position of the vehicle icon after the vehicle icon moves in the parking interaction interface; attaching the vehicle icon to a target virtual parking space based on the position of the moved vehicle icon, so that the vehicle icon matches the target virtual parking space; and generating a parking response instruction, so that an automated parking system controls a to-be-parked vehicle to drive into an actually available parking space indicated by the target virtual parking space.