Health Monitoring Of Buildings Research Articles

Sensing Technologies for Monitoring Intelligent Buildings: A Review

This review presents an overview of the existing state-of-the-art practices of improved performance in buildings required for the algorithmic logic and/or hardware. The main focus is on sensor-actuator-based applications in intelligent buildings like air quality, lighting, heating/cooling, ventilation, power management, water management, cooking gas management, and building health monitoring. The following are some of the major factors that usually rule in the development of intelligent buildings, such as good accuracy of the system, energy efficiency, response time of the sensor module, cost of the overall system, radio frequency interference, adequate signal-to-noise ratio, open interface capability, and intricacy of computation. The importance of the concerned issues and factors are discussed in detail for future research directions.

Performance analysis of a wireless sensor network with cognitive radio capabilities in structural health monitoring applications: A discrete model

This article studies the performance of a wireless sensor network with cognitive radio capabilities to gather information about structural health monitoring of buildings in case of seismic activity. Since the use of the local area network is intensive in office and home environments, we propose the use of empty cellular channels (primary system). As such, the structural health monitoring does not degrade the local communications. Thus, the wireless sensor network for structural health monitoring acts as secondary network. Two discrete-time analytical approaches are proposed and developed to evaluate the system performance in terms of both the average packet delay and average energy consumption. The first one is an approximation suitable for the case when the time slot duration is small relative to the mean call inter-arrival time. The second model is accurate for any time slot duration and inter-arrival times.

Stiffness Identification of High-Rise Buildings Based on Statistical Model-Updating Approach

A system identification problem is investigated for high-rise buildings to identify the story stiffnesses of a shear-bending model (SB model). In the previously proposed stiffness identification method due to the present authors, the shear and bending stiffnesses of the SB model were identified by means of the subspace and inverse-mode methods. The lowest mode of horizontal displacements and floor rotation angles of the objective building was identified first by using measured data of both horizontal and rotational accelerations via the subspace method. Considering the resolution in the measurement of floor rotation angles in lower stories, floor rotation angles in most stories were predicted from the floor rotation angle at the top floor. However, it was difficult to obtain the bending stiffnesses reliably in the previous method. In this paper, to overcome the difficulty in the stiffness identification method using the SB model, a statistical model-updating approach is proposed where the probability distribution of floor rotation angles in the lowest mode is obtained for the identified SB model, and a conditional probability problem is applied by providing additional measured data on floor rotation angle. The proposed stiffness identification method is useful for the structural health monitoring of high-rise buildings. For investigation of the reliability and accuracy of the proposed stiffness identification method, a 10-story building frame subjected to micro-tremor is examined.

Structural Health Monitoring of Buildings Using Smartphone Sensors

This article presents the results of a shaker test of the Millikan Library in Pasadena, California, using sensors inside smartphones to demonstrate their potential usage as a way to monitor health states of buildings. This approach to structural health monitoring could allow many more commercial and residential buildings to be monitored because it removes the cost prohibitive nature of traditional seismic arrays and the complexity of deploying the instruments. Recordings from the smartphones during the shaking show high correlation with those from a reference sensor in the building, illustrating that the phones can capture the shaking even when not fully coupled to the floor. The fundamental translational frequencies for the east–west and north–south directions and the torsional frequencies of the building can be extracted from single phone recordings. As we compare the displacement derived from the phone recording by double integration to that from the reference sensor, both phase and amplitude match well. Signal‐to‐noise ratio is improved further by stacking records from multiple phones. These test results demonstrate the ability to extract the fundamental translational and torsional frequencies, and absolute displacements from upper levels of buildings shaken by small local earthquakes. This work builds on the ongoing MyShake project—a global smartphone seismic network.

Preliminary Validation of an Automatic Modal Identification Methodology for Structural Health Monitoring of Historical Buildings

Preliminary Validation of an Automatic Modal Identification Methodology for Structural Health Monitoring of Historical Buildings

Application of NDT apparatus for possible use as structural health monitoring of concrete building in the field

A condition assessment of reinforced concrete building structures can be conducted accurately when the components of the building structure data are available. Otherwise, data must be developed through testing directly in the field. Non-Destructive Test method (NDT) was considered to avoid disruptions to the existing building structures. This study aims to develop a model for interpreting the residual strength of concrete structures in the field. Nine cylinder specimens with a diameter of 150 mm and a height of 300 mm and 27 cube specimens of 200x200x200 mm were prepared. Nine reinforced concrete beam specimens of 100x150x1100 mm were also prepared to represent a component of the reinforced concrete structure. Hammer and UPV apparatuses were applied to the cylinder and cube specimens considered. Results concluded that the value of the pulse velocity is directly proportional to the load and inversely proportional to the residual strength. The concrete structure with a residual strength of more than 60% is considered healthy or a structural in “good” condition. The concrete structure is also healthy when the v measured gives a value of 3.5 and above. This value is acceptable as it lies within the range v given in the reference of 3.5 to 4.5.

Toward effective structural identification of medium-rise building structures

Structural Identification (St-Id) is the process of constructing and calibrating a physics-based model based on the measured static and/or dynamic response of the structure. Over the last two decades, although the St-Id methods have become increasingly popular amongst civil–structural engineering communities, most complete and successful applications are often found with flexible structures such as long-span bridges and towers. Very few comprehensive studies were reported on building structures, especially those with medium-rise characteristics which are often associated with complicated analytical modelling and different degrees of parameter uncertainties. To address this need, this paper presents an in-depth study on St-Id of a benchmark medium-rise building firstly demonstrating the importance of developing appropriate initial analytical models that can be used for the automated model calibration techniques. Then, a novel parametric study-based sensitivity analysis approach is introduced to identify tuning parameters as well as their appropriate ranges to maximise the correlation of the calibrated model whilst preserving the physical relevance of the calibrated model. Modal data of the first few modes measured under ambient vibration conditions are used in this study. Further application of the St-Id process developed herein for structural health monitoring (SHM) of buildings is also discussed.

The MIT Green Building benchmark problem for structural health monitoring of tall buildings

This paper presents a benchmark problem for the structural health monitoring community to study tall buildings. The benchmark building is called the Green Building located at the Massachusetts Institute of Technology campus, with 21 stories above the ground (83.7 m) and a basement (3.8 m) connecting to the Massachusetts Institute of Technology tunnel system. This building was constructed as cast-in-place reinforced concrete and instrumented with 36 accelerometers to measure the building translational, torsional and vertical responses. The benchmark problem includes the detailed description of this building, 7 field measurement data sets (4 ambient data sets, 1 data set under an unidentified event, 1 data set under the excitation of fireworks, and 1 earthquake data set), and finite element models (both full-scale and condensed models). The Green Building has an identifiable soil-structure interaction behavior and the base rocking movement brings significant components into the building response. To decouple the rocking effect, storey measurement condensation and rocking response determination are discussed in this paper. A blind source separation approach is finally applied to identify the modal characteristics and quantify the rocking components. The benchmark data and models are open to the public for algorithmic development and validation.

Evaluation of an optoelectronic mould sensor for use in building health monitoring and in post-remediation performance assessment

Mould growth, due to water ingress or excess condensation, represents a significant health hazard within the built environment. Results from different mould growth models show discrepancies in their predictive abilities, partly because of the dearth of in-situ real-time mould data. The performance of an optoelectronic sensor for quantifying hidden mould growth within building wall assemblies has been examined in two separate studies. In the first, a set of 14 sensors were installed in two wood-frame wall assemblies of a full-scale test building, along with other environmental sensors for temperature, relative humidity and material moisture content. The sensors were monitored for one year under conditions for which no mould growth was expected to occur and the mould sensor voltage outputs showed very good stability over this time period. In the second test series, four small panels of oriented strand board and of gypsum wall board were instrumented and placed within an environmental chamber and subjected to high levels of relative humidity and material moisture content introduced by a wetting system. The results from the best-controlled of these experiments showed that the mould sensors were capable of clearly distinguishing the different extents of mould growth that occurred on each test panel.

Preliminary Design of Structural Health Monitoring for High-Rise Buildings

The purpose of structural health monitoring is to evaluate structural behavior due to various external loads through installation of appropriate measurement. Accordingly, a guideline for monitoring standards is necessary to evaluate the safety and performance of a structure. This paper introduces preliminary design of SHM for high-rise buildings, which is the stage creating a guideline. As for preliminary design of SHM, first step is to calculate the displacement and member force through structural analysis. After that, limitations or qualifications are proposed for management. Secondly, based on the results from first step, issues related monitoring such as monitoring method, measurement type, or installation location are determined. This method leads building managers to reasonably define the structural safety over the whole life cycle. Furthermore, this experience contributes to development of SHM forward and it is expected to be useful for other types of structures as well such as spatial structures or irregular buildings.

Structural Interpretation of Data from Static and Dynamic Structural Health Monitoring of Monumental Buildings

Structural Health Monitoring (SHM) has a crucial role in the diagnosis and conservation of historical buildings, which are typically characterized by articulated fabrics, constructed over decades using different materials and construction techniques. All these issues lead to very complex structural behaviour whose reliable assessment cannot disregard from a sound interpretation of data from SHM systems. SHM systems can be classified into (i) static systems, monitoring the long term time evolutions of specific quantities (such as amplitude of cracks, inclination of walls, relative distances, etc.) and (ii) dynamic systems, continuously monitoring the dynamic response (velocities, accelerations) in order to gather information upon overall dynamic properties such as natural frequencies, mode shapes and damping ratios. The recorded raw data need to be processed in order to distinguish eventual evolutionary trends from the seasonal and daily variations related to thermal effects. In the present work, a simple unified approach for data interpretation acquired from both static and dynamic SHM systems installed in historical buildings is presented. The approach is aimed at: (i) introducing reference quantities for interpretation of seasonal and daily variations, (ii) providing order of magnitudes of reference quantities and (iii) identifying eventual evolutionary trends which could be related to the presence of potential structural criticalities. The approach is illustrated referring to the “Two Towers” of Bologna.

Evolutionary learning based sustainable strain sensing model for structural health monitoring of high-rise buildings

Strain sensor network-based structural health monitoring systems have been used to assess the safety of high-rise buildings. In consideration of life cycle of high-rise buildings, long-term measurement by sensors should be required. However, because of unpredictable problems such as the lack of durability of sensors and data loggers, disruption in communication, and loss of data, long-term strain measurement of major structural members is currently infeasible. For sustainable safety assessment of high-rise buildings, this paper presents a sustainable strain-sensing model that employs an artificial neural network (ANN) to estimate the strain responses of columns depending on the wind-induced behavior of high-rise buildings. The ANN model used in the paper is based on evolutionary learning consists of training in radial basis function neural network (RBFN) and evolving in genetic algorithm. In this evolutionary RBFN (ERBFN). Weights between layers are trained and variables of Gaussian function in the RBFN are evolved to estimate strain responses of the column of the high-rise building structure. A wind tunnel test was performed to produce wind data and strains in column members in a high-rise building model. In the wind tunnel test, a specimen consisting of a core, perimeter columns, and outriggers is used to simulate the conditions of typical high-rise buildings with a slenderness ratio of 5.0. The proposed model is trained and verified by using the wind data such as wind speeds and directions and the corresponding strains measured with fiber optic grating sensors. In addition to estimation of the maximum and minimum values of strains in vertical members in a high-rise building, it is found that the proposed model can build a relationship between the wind data and strain of vertical members.

An Information-Theoretic Approach for Indirect Train Traffic Monitoring Using Building Vibration

This paper introduces an indirect train traffic monitoring method to detect and infer real-time train events based on the vibration response of a nearby building. Monitoring and characterizing traffic events is important for cities to improve the efficiency of transportation systems (e.g., train passing, heavy trucks, traffic). Most prior work falls into two categories: 1) methods that require intensive labor to manually record events or 2) systems that require deployment of dedicated sensors. These approaches are difficult and costly to execute and maintain. In addition, most prior work uses dedicated sensors designed for a single purpose, resulting in deployment of multiple sensor systems. This further increases costs. Meanwhile, with the increasing demands of structural health monitoring, many vibration sensors are being deployed in commercial buildings. Traffic events create ground vibration that propagates to nearby building structures inducing noisy vibration responses. We present an information theoretic method for train event monitoring using commonly existing vibration sensors deployed for building health monitoring. The key idea is to represent the wave propagation in a building induced by train traffic as information conveyed in noisy measurement signals. Our technique first uses wavelet analysis to detect train events. Then, by analyzing information exchange patterns of building vibration signals, we infer the category of the events (i.e., southbound or northbound train). Our algorithm is evaluated with an 11-story building where trains pass by frequently. The results show that the method can robustly achieve a train event detection accuracy of up to a 93% true positive rate and a 80% true negative rate. For direction categorization, compared with the traditional signal processing method, our information-theoretic approach reduces categorization error from 32.1% to 12.1%, which is a 2.5X improvement.

Highly sensitive strain sensor based on helical structure combined with Mach-Zehnder interferometer in multicore fiber

Optical fiber sensors for strain measurement have been playing important roles in structural health monitoring for buildings, tunnels, pipelines, aircrafts, and so on. A highly sensitive strain sensor based on helical structures (HSs) assisted Mach-Zehnder interference in an all-solid heterogeneous multicore fiber (MCF) is proposed and experimentally demonstrated. Due to the HSs, a maximum strain sensitivity as high as −61.8 pm/με was experimentally achieved. This is the highest sensitivity among interferometer-based strain sensors reported so far, to the best of our knowledge. Moreover, the proposed sensor has the ability to discriminate axial strain and temperature, and offers several advantages such as repeatability of fabrication, robust structure and compact size, which further benefits its practical sensing applications.

An overview on nature-inspired optimization algorithms for Structural Health Monitoring of historical buildings

Structural Health Monitoring (SHM) of historical building is an emerging field of research aimed at the development of strategies for on-line assessment of structural condition and identification of damage in the earliest stage. Built heritage is weak against operational and environmental condition and preservation must guarantee minimum repair and non-intrusiveness. SHM provides a cost-effective management and maintenance allowing prevention and prioritization of the interventions. Recently, in computer science, mimicking nature to address complex problems is becoming more frequent. Nature-inspired approaches turn out to be extremely efficient in facing optimization, commonly used to analyze engineering processes in SHM, providing interesting advantages when compared with classic methods. This paper begins with an introduction to Natural Computing. Then, focusing on its applications to SHM, possible improvements in built heritage conservation are shown and discussed suggesting a general framework for safety assessment and damage identification of existing structures.

Specifications and applications of the technical code for monitoring of building and bridge structures in China

Recently, the exclusive compulsory technical code (GB 50982-2014) for structural health monitoring of buildings and bridges in China has been developed and implemented. This code covers the majority of the field monitoring methods and stipulates the corresponding technical parameters for monitoring of high-rise structures, large-span spatial structures, bridges and base-isolated structures. This article first presents the comprehensive review and linear comparison of existing structural health monitoring codes and standards. Subsequently, the progress of the codification of GB 50982-2014 is imparted and its main features and specifications are summarized. Finally, in accordance with GB50982-2014, several representative structural health monitoring practical applications of large-scale infrastructures in China are exemplified to illustrate how this national code can bridge the gap between theory and practical applications of structural health monitoring. This technical code is an important milestone in the application of well-established structural health monitoring techniques into the realistic and complex engineering projects. Also, it can provide abundant and authoritative information for practitioners and researchers involving the structural health monitoring techniques.

Monitoring and time-dependent analysis of vertical deformations of the tallest building in China

Ping-An Finance Center (PAFC) in Shenzhen, with a structural height of 597 m and a total height of 660 m, is currently the second tallest building in the world and the tallest in China. In this paper, based on the outputs of a structural health monitoring system installed in PAFC, a combined study of both on-site measurements and numerical analysis of the vertical deformations (axial shortenings) of the super tall building during its various construction stages is carried out. It is worth noting that a novel strategy to adjust the elevation of each floor of PAFC was implemented in the design and construction of the super tall building, in which the floor-to-floor height is modestly increased to compensate for the axial shortenings of gravity load bearing elements during the construction process and in-service stage. This design strategy is referred to as elevation reservation, and its effectiveness is verified through the field measurements of the vertical deformations in this study. A good agreement is found between the numerical results and the field measurements, which validates the finite element models of PAFC at different construction stages. The finite element models are further used to investigate the time-dependent effects due to the construction sequence and the shrinkage and creep of concrete on the vertical deformations. The numerical results show that the vertical deformations would be seriously underestimated without consideration of the time-dependent effects. The outcomes of this study would be of interest and practical use for engineers and researchers involved in the structural design, construction, and structural health monitoring of super tall buildings.

Damage evaluation in high-rise buildings using one modal eigenpair

A development of the ‘first-order storey pseudo-stiffness-based damage index’ of high-rise buildings is presented in this article. The proposed damage index is based on identification of an input set of one modal eigenpair, consisting of one modal frequency and the corresponding mode shape, overcoming the need and the difficulties of identifying multiple sets of eigenpairs in operational modal analyses of multistorey buildings. The calculation of first-order storey pseudo-stiffness-based damage index is expressed as a simple numerical procedure for comparison between the dynamic parameters of undamaged and damaged structures. The accuracy of the proposed damage assessment approach has been verified in two different tests – numerical and experimental. The numerical tests are based on the calculation of first-order storey pseudo-stiffness-based damage index in numerical models in which the structural damage is simulated with previously defined storey stiffness degradation. The experimental test consists of first-order storey pseudo-stiffness-based damage index accuracy test on the structure of the Urban Disaster Prevention Research Center, located in Tsukuba, Japan, and comparison to the results obtained by previously proven accurate damage detection method. The test results have shown that the proposed first-order storey pseudo-stiffness-based damage index index, based on the first modal eigenpair, can be applied as an instant damage detection method in structural health monitoring of multistorey buildings, providing the location and severity of structural damage.

Structural Health Monitoring of Buildings and Infrastructure

Structural Health Monitoring of Buildings and Infrastructure

Node Scheduling Control Inspired by Epidemic Theory for Data Dissemination in Wireless Sensor-Actuator Networks With Delay Constraints

Wireless sensor-actuator networks (WSANs) enhance the existing wireless sensor networks (WSNs) by equipping sensor nodes with actuators. The actuators work with the sensor nodes to perform application-specific operations. The WSAN systems have several applications such as disaster relief, intelligent building management, military surveillance, health monitoring, and infrastructure security. These applications require the capability of fast data dissemination in order to act responsively to events. However, due to strict resource constraints of the nodes, WSANs pose significant challenges in network protocol design to support applications with delay requirements. Biologically inspired modeling techniques have received considerable attention for achieving robustness, scalability, and adaptability, while retaining individual simplicity. Specifically, data dissemination, packet routing, and broadcasting protocols for wireless networks have been modeled by epidemic theory. However, existing bio-inspired algorithms are mostly based on predefined heuristics and fixed parameters, and thus it is difficult for them to achieve the desired level of performance under dynamic environments. In order to solve this problem, we propose an epidemic-inspired algorithm for data dissemination in WSANs which automatically controls node states to meet the delay requirements while minimizing energy consumption. Through mathematical analysis, behavior of the algorithm in terms of converge time and steady state can be predicted. Also, the analysis shows that the system achieves stability, and derives parameter conditions for achieving the stability. Finally, extensive simulation results indicate that the proposed scheme outperforms existing protocols in achieving delay requirements and conserving energy.