Department of Industrial Engineering, University of Naples Federico II, Piazzale Tecchio 80, 80125 Naples, Italy.
Department of Management, Information and Production Engineering, University of Bergamo, 24044 Dalmine, Italy.
Sensors (Basel). 2022 Feb 24;22(5):1788. doi: 10.3390/s22051788.
Systems for accurate attitude and position monitoring of large structures, such as bridges, tunnels, and offshore platforms are changing in recent years thanks to the exploitation of sensors based on Micro-ElectroMechanical Systems (MEMS) as an Inertial Measurement Unit (IMU). Currently adopted solutions are, in fact, mainly based on fiber optic sensors (characterized by high performance in attitude estimation to the detriment of relevant costs large volumes and heavy weights) and integrated with a Global Position System (GPS) capable of providing low-frequency or single-update information about the position. To provide a cost-effective alternative and overcome the limitations in terms of dimensions and position update frequency, a suitable solution and a corresponding prototype, exhibiting performance very close to those of the traditional solutions, are presented and described hereinafter. The solution leverages a real-time Kalman filter that, along with the proper features of the MEMS inertial sensor and Real-Time Kinematic (RTK) GPS, allows achieving performance in terms of attitude and position estimates suitable for this kind of application. The results obtained in a number of tests underline the promising reliability and effectiveness of the solution in estimating the attitude and position of large structures. In particular, several tests carried out in the laboratory highlighted high system stability; standard deviations of attitude estimates as low as 0.04° were, in fact, experienced in tests conducted in static conditions. Moreover, the prototype performance was also compared with a fiber optic sensor in tests emulating actual operating conditions; differences in the order of a few hundredths of a degree were found in the attitude measurements.
近年来,得益于基于微机电系统(MEMS)的传感器作为惯性测量单元(IMU)的开发,用于大型结构(如桥梁、隧道和海上平台)的精确姿态和位置监测系统正在发生变化。目前采用的解决方案主要基于光纤传感器(其特点是在姿态估计方面性能较高,但代价是相关成本大、体积大、重量重),并与全球定位系统(GPS)集成,能够提供位置的低频或单更新信息。为了提供一种具有成本效益的替代方案,并克服尺寸和位置更新频率方面的限制,提出并描述了以下一种合适的解决方案和相应的原型,其性能非常接近传统解决方案。该解决方案利用实时卡尔曼滤波器,结合 MEMS 惯性传感器和实时动态(RTK)GPS 的适当特性,实现了适合此类应用的姿态和位置估计性能。在多项测试中获得的结果强调了该解决方案在估计大型结构的姿态和位置方面具有可靠的前景和有效性。特别是,在实验室进行的多项测试中突出了系统的高度稳定性;在静态条件下进行的测试中,姿态估计的标准偏差低至 0.04°。此外,还在模拟实际工作条件的测试中比较了原型性能与光纤传感器的性能;在姿态测量中发现了几度的差异。