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The beam-like structures are widely employed in civil, machinery, and aerospace engineering. However, the beam-like structure often suffers from undesired vibration problems due to the environmental incentives, which may influence the overall structural safety. Therefore, a real-time deformation monitoring system is critical to guarantee the safety of the beam-like structure under the condition of operating. This paper presents a novel deflection monitoring system that can be installed easily to any large-scale beam-like structures. The proposed system contains a sensing network, which is constructed of fiber Bragg grating (FBG). Such a network can monitor the quasi-distributed dynamic strain of the structure online, which has some merits such as anti-electromagnetic interference, small size, and multiplexed. An estimation algorithm for the beam-like structure based on those strain measurements is also presented in this work. The performance of the proposed sensing network and deflection estimation algorithm was validated by a cantilever beam test rig excited by impulsive excitations in the laboratory environment. The experimental results illustrate the suggested monitoring system can monitor the bending deformation of the beam-like structure successfully.

This paper proposes a novel method to detect the liquid level. Specifically, a novel structure based on the diagram and the flexible hinge is presented, in which the Fiber Bragg Grating (FBG) is employed as the sensing element and temperature compensation is considered. The corresponding analytical model of the structure is developed, which shows that the strain of the FBG is a linear correlation with the liquid level. The presented sensor show superior range (±200mm) and superior sensitivity (23.80pm/mm) when compared with some of the similar structures shown in the literature. To validate the analytical model, a Finite Element Model (FEM) is employed and the results showed that the analytical model is accurate. This paper aims to give the structure design and performance analysis for the sensor and the corresponding experiments will be given in our subsequent paper series Part II.

The cantilever plate structure is widely used in wind tunnel nozzle segments. During the operation of the wind tunnel, the flexible steel plate will bear various complex loads such as shearing, bending and twisting, etc. The bolts of the plate are prone to loosen due to the fatigue damage. The methods based on the electromechanical impedance, sub-harmonic resonance and vision have been presented in the literature. However, the mentioned methods cannot detect the bolt looseness effectively in a harsh environment. To address this issue, we presented a novel method to detect the bolt looseness for the cascaded structures based on the operational strain estimated from Fiber Bragg Grating (FBG). In this work, an improved method of the operational modal analysis (OMA) presented in our previous work is employed. And then an enhanced Structural Damage Indicator (SDI) based on the operational strain is presented to detect and locate the loose bolts. Both the results from experiments and simulations showed that the SDI can detect and locate the loose bolts accurately.

Clamp looseness in hydraulic pipelines usually accelerates the wear process of pipelines and results in the fatigue fracture of pipelines. Conventionally, the condition monitoring of pipelines is often difficult and expensive due to the long length of pipes and large number of clamps that, in turn, requires a large capacity sensing network. In recent years, the fiber Bragg grating based sensing technique has begun to attract interests because of its cost-effective and ease of forming the large capacity sensing network. Therefore, this study investigates the feasibility of a new pipeline monitoring system instrumented with fiber Bragg grating sensors, which can measure the dynamic strain along the pipeline. The experiments were performed on a laboratory hydraulic pipeline system, where the impact hammer was used to excite the vibration of pipes. The preliminary selection of significant feature from the measured strain data is made with the use of principal component analysis. Then, the extracted feature with the reduced dimension is analyzed for the diagnosis of pipelines, which utilizes support vector machines to classify the location and severity of clamp looseness. The experimental results show the proposed sensing technique and diagnostic algorithm have a promising potential in developing an economic and reliable monitoring system for online diagnosis of hydraulic pipelines.

Distributed block clamps are widely used in hydraulic piping systems to fix the pipeline and to adjust the natural frequencies of pipes. However, the clamps may get loosen due to wear over time, and if not detected, it will lead to catastrophic failures. Piezoelectric lead Zirconate Titanate (PZT) based active sensing methods have been widely used to monitor the looseness of the bolted structures. However, this method bears some drawbacks, e.g., saturation, electromagnetic interference and high cost. Therefore, Fiber Bragg Grating (FBG) based sensing technology, which is robust to electromagnetic interference and easy for multiplexing, has been employed to design smart bolts and washers to monitor the preload of the bolted structures in existing literatures. However, the applications of those structures are limited due to specific customization, e.g. the distributed feature of the smart bolt is limited by the blind hole structure and the smart washer can only be used to the bolted connections with big-diameter bolts. To address these issues, a smart clamp is presented in present study. Moreover, the 3D printing technology is also investigated to fabricate FBG based smart clamps in a flexible and cost-effective way. A novel FBG based smart clamp is proposed in this work. The influence of different print layer heights, 0.15mm and 0.2mm on the sensitivity of clamp is also evaluated. It is shown that the 0.2mm height leads to a higher sensitivity than the 0.15mm height. Its application to incipient clamp looseness detection is further performed in an industrial piping system.