Research on Damage Detection of a 3D Steel Frame Model Using Smartphones

Smartphones which are built into the suite of sensors, network transmission, data storage, and embedded processing capabilities provide a wide range of response measurement opportunities for structural health monitoring (SHM). The objective of this work was to evaluate and validate the use of smartphones for monitoring damage states in a three-dimensional (3D) steel frame structure subjected to shaking table earthquake excitation. The steel frame is a single-layer structure with four viscous dampers mounted at the beam-column joints to simulate different damage states at their respective locations. The structural acceleration and displacement responses of undamaged and damaged frames were obtained simultaneously by using smartphones and conventional sensors, while the collected response data were compared. Since smartphones can be used to monitor 3D acceleration in a given space and biaxial displacement in a given plane, the acceleration and displacement responses of the Y-axis of the model structure were obtained. Wavelet packet decomposition and relative wavelet entropy (RWE) were employed to analyze the acceleration data to detect damage. The results show that the acceleration responses that were monitored by the smartphones are well matched with the traditional sensors and the errors are generally within 5%. The comparison of the displacement acquired by smartphones and laser displacement sensors is basically good, and error analysis shows that smartphones with a displacement response sampling rate of 30 Hz are more suitable for monitoring structures with low natural frequencies. The damage detection using two kinds of sensors are relatively good. However, the asymmetry of the structure’s spatial stiffness will lead to greater RWE value errors being obtained from the smartphones monitoring data.

[1]  Billie F. Spencer,et al.  System identification of a historic swing truss bridge using a wireless sensor network employing orientation correction , 2015 .

[2]  Keith Worden,et al.  On switching response surface models, with applications to the structural health monitoring of bridges , 2018 .

[3]  Gangbing Song,et al.  Health Status Monitoring of Cuplock Scaffold Joint Connection Based on Wavelet Packet Analysis , 2015 .

[4]  L. H. Yam,et al.  Online detection of crack damage in composite plates using embedded piezoelectric actuators/sensors and wavelet analysis , 2002 .

[5]  Neil A. Hoult,et al.  Long-Term Wireless Structural Health Monitoring of the Ferriby Road Bridge , 2010 .

[6]  Maria Q. Feng,et al.  Citizen Sensors for SHM: Use of Accelerometer Data from Smartphones , 2015, Sensors.

[7]  Yan Yu,et al.  A new idea: Mobile structural health monitoring using Smart phones , 2012, 2012 Third International Conference on Intelligent Control and Information Processing.

[8]  Ajay Raghavan,et al.  Guided-wave structural health monitoring , 2007 .

[9]  Thomas H. Heaton,et al.  Structural Health Monitoring of Buildings Using Smartphone Sensors , 2018 .

[10]  Maria Q. Feng,et al.  Citizen Sensors for SHM: Towards a Crowdsourcing Platform , 2015, Sensors.

[11]  Daqiang Zhang,et al.  VCMIA: A Novel Architecture for Integrating Vehicular Cyber-Physical Systems and Mobile Cloud Computing , 2014, Mobile Networks and Applications.

[12]  Gerard Goggin Adapting the mobile phone: The iPhone and its consumption , 2009 .

[13]  Guido Morgenthal,et al.  On measuring mechanical oscillations using smartphone sensors: possibilities and limitation , 2013, MOCO.

[14]  Yan Yu,et al.  Smartphone based public participant emergency rescue information platform for earthquake zone – “E-Explorer” , 2015 .

[15]  Jinping Ou,et al.  Structural Health Monitoring in mainland China: Review and Future Trends , 2010 .

[16]  Sian Lun Lau,et al.  Supporting patient monitoring using activity recognition with a smartphone , 2010, 2010 7th International Symposium on Wireless Communication Systems.

[17]  Guido Morgenthal,et al.  The application of smartphones to measuring transient structural displacements , 2012 .

[18]  Maria Q. Feng,et al.  Hybrid motion sensing and experimental modal analysis using collocated smartphone camera and accelerometers , 2017 .

[19]  MarvinB . Cohen,et al.  LESSONS LEARNED FROM THE NORTHRIDGE EARTHQUAKE , 1994 .

[20]  David E. Culler,et al.  System architecture directions for networked sensors , 2000, SIGP.

[21]  Mingchu Li,et al.  Cable force monitoring system of cable stayed bridges using accelerometers inside mobile smart phone , 2015, Smart Structures.

[22]  Billie F. Spencer,et al.  Smart sensing technology: opportunities and challenges , 2004 .

[23]  Wei-Xin Ren,et al.  Structural damage identification by using wavelet entropy , 2008 .

[24]  Tim Polzehl,et al.  Fall and emergency detection with mobile phones , 2009, Assets '09.

[25]  Seok Jae Lee,et al.  An Optical Biosensing Strategy Based on Selective Light Absorption and Wavelength Filtering from Chromogenic Reaction , 2018, Materials.

[26]  Alexandre M. Bayen,et al.  Evaluating the Reliability of Phones as Seismic Monitoring Instruments , 2014 .

[27]  Robert Szewczyk,et al.  System architecture directions for networked sensors , 2000, ASPLOS IX.

[28]  Dimitrios Gunopulos,et al.  SmartMonitor: Using Smart Devices to Perform Structural Health Monitoring , 2013, Proc. VLDB Endow..

[29]  Mingchu Li,et al.  Portable and convenient cable force measurement using smartphone , 2015 .

[30]  Yan Yu,et al.  Displacement monitoring technique using a smartphone based on the laser projection-sensing method , 2016 .

[31]  Claudio Modena,et al.  Post-earthquake controls and damage detection through structural health monitoring: applications in l’Aquila , 2018 .

[32]  Ting-Hua Yi,et al.  Structural health monitoring of innovative civil engineering structures in Mainland China , 2016 .

[33]  Jae Hong Min,et al.  Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies , 2016, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[34]  Victor Giurgiutiu,et al.  Analysis of axis symmetric circular crested elastic wave generated during crack propagation in a plate: A Helmholtz potential technique , 2018 .

[35]  Ruxu Du,et al.  FEATURE EXTRACTION AND ASSESSMENT USING WAVELET PACKETS FOR MONITORING OF MACHINING PROCESSES , 1996 .

[36]  Alexandre M. Bayen,et al.  Mobile Phones as Seismologic Sensors: Automating Data Extraction for the iShake System , 2013, IEEE Transactions on Automation Science and Engineering.

[37]  Gian Paolo Cimellaro,et al.  Rapid building damage assessment system using mobile phone technology , 2014, Earthquake Engineering and Engineering Vibration.