Optimal Sensor Placement for Reliable Virtual Sensing Using Modal Expansion and Information Theory

A framework for optimal sensor placement (OSP) for virtual sensing using the modal expansion technique and taking into account uncertainties is presented based on information and utility theory. The framework is developed to handle virtual sensing under output-only vibration measurements. The OSP maximizes a utility function that quantifies the expected information gained from the data for reducing the uncertainty of quantities of interest (QoI) predicted at the virtual sensing locations. The utility function is extended to make the OSP design robust to uncertainties in structural model and modeling error parameters, resulting in a multidimensional integral of the expected information gain over all possible values of the uncertain parameters and weighted by their assigned probability distributions. Approximate methods are used to compute the multidimensional integral and solve the optimization problem that arises. The Gaussian nature of the response QoI is exploited to derive useful and informative analytical expressions for the utility function. A thorough study of the effect of model, prediction and measurement errors and their uncertainties, as well as the prior uncertainties in the modal coordinates on the selection of the optimal sensor configuration is presented, highlighting the importance of accounting for robustness to errors and other uncertainties.

Download Full-text

Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost

Mechanical Systems and Signal Processing ◽

10.1016/j.ymssp.2021.108787 ◽

2022 ◽

Vol 169 ◽

pp. 108787

Author(s):

Azin Mehrjoo ◽

Mingming Song ◽

Babak Moaveni ◽

Costas Papadimitriou ◽

Eric Hines

Keyword(s):

Parameter Estimation ◽

Wind Turbine ◽

Sensor Placement ◽

Offshore Wind ◽

Offshore Wind Turbine ◽

Optimal Sensor Placement ◽

Virtual Sensing ◽

Installation Cost

Download Full-text

Enhancing the performance of structural model identification by optimal sensor placement

10.1063/1.3452241 ◽

2010 ◽

Author(s):

H. F. Lam ◽

H. M. Chow ◽

T. Yin ◽

Jane W. Z. Lu ◽

Andrew Y. T. Leung ◽

...

Keyword(s):

Structural Model ◽

Sensor Placement ◽

Model Identification ◽

Optimal Sensor Placement

Download Full-text

A Probabilistic Approach for Optimal Sensor Placement of Bridge Structures for the Purpose of Structural Model Updating

Design, Construction, and Maintenance of Bridges ◽

10.1061/9780784478516.003 ◽

2014 ◽

Author(s):

Tao Yin

Keyword(s):

Structural Model ◽

Model Updating ◽

Probabilistic Approach ◽

Sensor Placement ◽

Optimal Sensor Placement ◽

Bridge Structures

Download Full-text

INFORMATION-DRIVEN AUTONOMOUS EXPLORATION FOR A VISION-BASED MAV

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w3-59-2017 ◽

2017 ◽

Vol IV-2/W3 ◽

pp. 59-66 ◽

Cited By ~ 6

Author(s):

E. Palazzolo ◽

C. Stachniss

Keyword(s):

Utility Function ◽

Real Time ◽

Information Gain ◽

Autonomous Exploration ◽

Elapsed Time ◽

Aerial Vehicles ◽

3D Environment ◽

Starting Point ◽

Expected Information ◽

Expected Information Gain

Most micro aerial vehicles (MAV) are flown manually by a pilot. When it comes to autonomous exploration for MAVs equipped with cameras, we need a good exploration strategy for covering an unknown 3D environment in order to build an accurate map of the scene. In particular, the robot must select appropriate viewpoints to acquire informative measurements. In this paper, we present an approach that computes in real-time a smooth flight path with the exploration of a 3D environment using a vision-based MAV. We assume to know a bounding box of the object or building to explore and our approach iteratively computes the next best viewpoints using a utility function that considers the expected information gain of new measurements, the distance between viewpoints, and the smoothness of the flight trajectories. In addition, the algorithm takes into account the elapsed time of the exploration run to safely land the MAV at its starting point after a user specified time. We implemented our algorithm and our experiments suggest that it allows for a precise reconstruction of the 3D environment while guiding the robot smoothly through the scene.

Download Full-text

Optimal Sensor Placement for the Tower Structure Based on Key Components

The Open Electrical & Electronic Engineering Journal ◽

10.2174/1874129001408010348 ◽

2014 ◽

Vol 8 (1) ◽

pp. 348-354

Author(s):

Yang Chao-Shan ◽

Cheng Hua ◽

Wang Zhong-Gang

Keyword(s):

Large Scale ◽

Sensor Placement ◽

Optimal Sensor Placement ◽

Modal Expansion ◽

Structure System ◽

Damage Degree ◽

Tower Structure ◽

Structure State ◽

Structure Sensor ◽

Weight Coefficients

In order to improve the large-scale complex spatial structure sensor placement, this paper puts forward an optimal sensor placement method for the tower structure based on key components. According to this method, different probabilities of the structure system’s reliability degree caused by the same damage degree of components are firstly calculated; then component weight coefficients are introduced to measure the relative importance of various components in the whole structure system; the key components of the structure system are defined according to the value of weight coefficients; then modal parameters are adopted to analyze the damage sensitivity of the key components and to find out the vibration modes and measuring points sensitive to the damage of key components, thus to finish the sensor placement. Fully considering the structure characteristics, this method can solve the optimization issues, including the quantity of measurement points and the position, and avoid the complex iterative algorithm and modal expansion error, so it contributes to better controlling the structure state. Finally, through the calculation example of a communication tower, the feasibility and the validity of the method are proved.

Download Full-text

Optimal Sensor Placement Algorithm for Structural Damage Identification

Recent Patents on Engineering ◽

10.2174/1872212113666190110124551 ◽

2020 ◽

Vol 14 (1) ◽

pp. 69-81

Author(s):

C.H. Li ◽

Q.W. Yang

Keyword(s):

Structural Damage ◽

Damage Identification ◽

Sensor Placement ◽

Optimization Procedure ◽

Frame Structure ◽

Truss Structures ◽

Optimal Sensor Placement ◽

Structural Damage Identification ◽

Placement Algorithm ◽

Sensor Locations

Background: Structural damage identification is a very important subject in the field of civil, mechanical and aerospace engineering according to recent patents. Optimal sensor placement is one of the key problems to be solved in structural damage identification. Methods: This paper presents a simple and convenient algorithm for optimizing sensor locations for structural damage identification. Unlike other algorithms found in the published papers, the optimization procedure of sensor placement is divided into two stages. The first stage is to determine the key parts in the whole structure by their contribution to the global flexibility perturbation. The second stage is to place sensors on the nodes associated with those key parts for monitoring possible damage more efficiently. With the sensor locations determined by the proposed optimization process, structural damage can be readily identified by using the incomplete modes yielded from these optimized sensor measurements. In addition, an Improved Ridge Estimate (IRE) technique is proposed in this study to effectively resist the data errors due to modal truncation and measurement noise. Two truss structures and a frame structure are used as examples to demonstrate the feasibility and efficiency of the presented algorithm. Results: From the numerical results, structural damages can be successfully detected by the proposed method using the partial modes yielded by the optimal measurement with 5% noise level. Conclusion: It has been shown that the proposed method is simple to implement and effective for structural damage identification.

Download Full-text