In recent years, many industrialfacilities have been required to install sensing system to monitor the health status of the equipment. Although the PC-based diagnosis system is a good alternative, it undoubtedly increases the hardware cost greatly, and also causes restrictions on system assembly. In some critical environments, installation of the PC-based system is not suitable because of high temperature, dust, and humidity. On the contrary, a high mobility portable smart sensor will be relatively adequate for onsite inspections. To solve this problem, we developed a low-cost embedded handheld smart sensor. Instead of using sophisticated algorithms, certain frequently used statistic indicators are considered. Nevertheless, due to the resource limitations of the embedded systems, it causes difficulty for real-time realization and therefore, the recursive architecture of the statistic indicators is derived. These statistical factors are then fed into a Gaussian classifier for online defect detection, which gives a great contribution to field operators for onsite inspections. The highly integrated hardware/software co-design of the developed device provides user-friendly and high mobility for field inspections. Finally, a practical industrial application regarding the online diagnosis of a solenoid valve actuator defect is presented to demonstrate the effectiveness of the developed embedded smart sensor.

中文翻译：

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用于工业设备现场缺陷检测的低成本嵌入式实时手持式振动智能传感器

近年来，许多工业设施都需要安装传感系统来监控设备的健康状态。虽然基于PC的诊断系统是一个不错的选择，但无疑大大增加了硬件成本，同时也对系统组装造成了限制。在一些关键环境中，由于高温、灰尘和潮湿，不适合安装基于PC的系统。相反，高移动性的便携式智能传感器将相对足够用于现场检查。为了解决这个问题，我们开发了一种低成本的嵌入式手持智能传感器。不使用复杂的算法，而是考虑某些经常使用的统计指标。然而，由于嵌入式系统的资源限制，实时实现存在困难，因此，导出统计指标的递归架构。然后将这些统计因素输入到高斯分类器中进行在线缺陷检测，为现场操作人员的现场检查做出了巨大贡献。所开发设备的高度集成的硬件/软件协同设计为现场检查提供了用户友好和高移动性。最后，提出了关于电磁阀执行器缺陷在线诊断的实际工业应用，以证明所开发的嵌入式智能传感器的有效性。所开发设备的高度集成的硬件/软件协同设计为现场检查提供了用户友好和高移动性。最后，提出了关于电磁阀执行器缺陷在线诊断的实际工业应用，以证明所开发的嵌入式智能传感器的有效性。所开发设备的高度集成的硬件/软件协同设计为现场检查提供了用户友好和高移动性。最后，提出了关于电磁阀执行器缺陷在线诊断的实际工业应用，以证明所开发的嵌入式智能传感器的有效性。