面对物联网的快速发展,需要低延时、高性能的处理器来实现关键数据的传输和保护,同时要提高处理器的硬件安全,减少非法用户对处理器的攻击。结合当前开源第五代精简指令集(Reduced Instruction Set Computing-Five,RISC-V)处理器架构优...面对物联网的快速发展,需要低延时、高性能的处理器来实现关键数据的传输和保护,同时要提高处理器的硬件安全,减少非法用户对处理器的攻击。结合当前开源第五代精简指令集(Reduced Instruction Set Computing-Five,RISC-V)处理器架构优点,与现场可编程门阵列(Field Programmable Gate Array,FPGA)相结合,设计了异构处理器,提出了基于密码的安全启动模型。首先,细化RISC-V异构处理器的体系结构,设计轻量级密码启动安全模型TrustZone,实现处理器性能与安全的平衡,并结合FPGA的优点,实现定制化的专用协议与业务通信。其次,提出当前RISC-V异构处理器可实现的便捷途径,并基于此进行模型搭建和测试验证。验证结果表明,虽然采用TrustZone安全度量后处理器启动时间有所增加,但针对轻量级的处理器应用场景,在增强处理器安全的前提下,该启动时间开销是可以接受的。展开更多
Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineeri...Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.展开更多
文摘Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.
