Exploring the Processing Paradigm of Input Data for End-to-End Deep Learning in Tool Condition Monitoring.

Tool condition monitoring technology is an indispensable part of intelligent manufacturing. Most current research focuses on complex signal processing techniques or advanced deep learning algorithms to improve prediction performance without fully leveraging the end-to-end advantages of deep learning. The challenge lies in transforming multi-sensor raw data into input data suitable for direct model feeding, all while minimizing data scale and preserving sufficient temporal interpretation of tool wear.

Role of Altitude in Influencing the Spray Combustion Characteristics of a Heavy-Duty Diesel Engine in a Constant Volume Combustion Chamber. Part II: Impinging Diesel Jet.

Wall impingement, particularly liquid-wall impingement, has been demonstrated to be one of the critical causes of combustion deterioration in plateau diesel engines. Obviously, the complexity of wall impingement is exacerbated by the plateau scenario. However, fundamental studies specifically dedicated to this phenomenon are still inconclusive and insufficiently detailed, obviating the feasibility of the targeted design and optimization of diesel engines operating in regions with different altitudes.