谷歌翻译 接口有错误的分段问题

对于同一段文字，谷歌翻译结果会分成3段，而谷歌镜像结果则正常

随着工业 4.0 概念和人工智能（AI）、结构健康监测（SHM）技术的不断发展，基于数字孪生（DT）的运营维护在桥梁的生命周期中得到了越来越多的应用。建立精确可靠的桥梁数字孪生模型，可以帮助实现桥梁工程灾害的精准防控和重大灾害事故的风险识别预警。与传统方法相比，基于DT的桥梁诊断通过准确的虚拟副本提供实时洞察，能够发现人工或设备无法接触到的隐藏缺陷，实现对桥梁性能全面、准确的预测。

谷歌翻译结果

With the continuous development of the Industry 4.0 concept and artificial intelligence (AI) and structural health monitoring (SHM) technologies, operation and maintenance based on digital twins (DT) have been increasingly used in the life cycle of bridges. 
Establishing an accurate and reliable bridge digital twin model can help achieve precise prevention and control of bridge engineering disasters and risk identification and early warning of major disasters and accidents. 
Compared with traditional methods, DT-based bridge diagnosis provides real-time insights through accurate virtual copies, can discover hidden defects that are inaccessible to humans or equipment [1], and achieve comprehensive and accurate predictions of bridge performance.

谷歌镜像结果

With the continuous development of the Industry 4.0 concept and artificial intelligence (AI) and structural health monitoring (SHM) technologies, operation and maintenance based on digital twins (DT) have been increasingly used in the life cycle of bridges. Establishing an accurate and reliable bridge digital twin model can help achieve precise prevention and control of bridge engineering disasters and risk identification and early warning of major disasters and accidents. Compared with traditional methods, DT-based bridge diagnosis provides real-time insights through accurate virtual copies, can discover hidden defects that are inaccessible to humans or equipment [1], and achieve comprehensive and accurate predictions of bridge performance.