3results about How to "Early detection" patented technology

The invention discloses an electric drive system NVH dynamic test system and method based on XIL. The system comprises a driver-in-the-loop module, a real object-in-the-loop module and an NVH data acquisition system. The driver in-the-loop module is used for collecting a driver real-time operation signal and providing a virtual driving environment; the real object in-the-loop module receives a signal through a real-time simulation machine, and a co-simulation model is used for resolving vehicle dynamic operation parameters; and the rack system drives the dynamometer to apply a dynamic load to the tested electric driving system by adopting a composite control framework based on rotating speed closed-loop control and combined with dynamic compensation according to the parameters. By constructing a human-vehicle-road closed-loop coupling mechanism, the problem that transient load change in a complex driving scene cannot be reproduced in a traditional rack test is solved, working conditions such as urgent acceleration and braking can be simulated in a high-fidelity manner, vibration and noise response of an electric driving system in real dynamic operation can be accurately captured, and the reliability of the electric driving system is improved. And the authenticity and the effectiveness of the NVH test are obviously improved.

This invention discloses an online monitoring method for external leakage in aircraft hydraulic systems based on a mechanistic model, belonging to the field of hydraulic system technology. It aims to solve the technical bottlenecks of existing aircraft hydraulic system external leakage monitoring, such as poor real-time performance, high false alarm rate, and inability to detect the leakage amount and rate. The method includes the following steps: First, a mechanistic model is constructed based on the law of conservation of mass. Combined with temperature and pressure data monitored by airborne sensors, the oil volume inside each hydraulic component outside the tank is calculated according to volumetric deformation characteristics, deriving the theoretical value of the oil volume inside the self-pressurized tank. Second, the mechanistic model is corrected by comparing the theoretical value with the actual monitored value using flight parameter data under leak-free conditions, eliminating inherent errors. Finally, real-time flight parameter data is input to recalculate the theoretical value, and compared with the real-time monitoring value from the level sensor to determine if the system is leaking. If leakage occurs, the leakage amount and rate are calculated, and an early warning result is output. This invention relies on existing airborne sensors, requiring no additional equipment or sensors. It can effectively distinguish between normal oil fluctuations and actual leakage, improving monitoring accuracy and real-time performance. It provides data support for the handling and maintenance of aircraft hydraulic system leakage faults and has certain engineering application value.

The application relates to the technical field of intelligent crop pesticide application, and relates to a precision pesticide application method and system of an agricultural robot based on adaptive control, which comprises the following steps: crop pest state score identification is performed on a crop information set to obtain a pest state matrix and acquire a pest matrix change sequence; a risk area set in the pest matrix change sequence is identified according to a pest threshold value, and the total pest intensity of the risk area set is acquired; when the total pest intensity is greater than a pesticide application threshold value, the spraying suitability of an environment information set is identified; when the spraying suitability is greater than an implementation condition threshold value, drug type identification is performed on the crop information set to obtain first pesticide configuration information and second pesticide configuration information; a pest development trend identification operation is performed on the pest matrix change sequence to obtain a pest trend range; and the first pesticide is proportioned according to the first pesticide configuration information and the risk area set, and the second pesticide is proportioned according to the second pesticide configuration information and the pest trend range. The application can improve the accuracy of crop pesticide application.