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Title: A vibro-haptic human-machine interface for structural health monitoring

Journal Article · · Structural Health Monitoring
 [1];  [2];  [2];  [3];  [4];  [5];  [6];  [1];  [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  2. Univ. of New Mexico, Albuquerque, NM (United States)
  3. Colorado School of Mines, Golden, CO, (United States)
  4. Univ. of Maryland, College Park, MD (United States)
  5. Georgia Inst. of Technology, Atlanta, GA (United States)
  6. Univ. of California, Berkeley, CA (United States)
+ Show Author Affiliations

The structural health monitoring (SHM) community’s goal has been to endow physical systems with a nervous system not unlike those commonly found in living organisms. Typically the SHM community has attempted to do this by instrumenting structures with a variety of sensors, and then applying various signal processing and classification procedures to the data in order to detect the presence of damage, the location of damage, the severity of damage, and to estimate the remaining useful life of the structure. This procedure has had some success, but we are still a long way from achieving the performance of nervous systems found in biology. This is primarily because contemporary classification algorithms do not have the performance required. In many cases expert judgment is superior to automated classification. This work introduces a new paradigm. We propose interfacing the human nervous system to the distributed sensor network located on the structure and developing new techniques to enable human-machine cooperation. Results from the field of sensory substitution suggest this should be possible. This study investigates a vibro-haptic human-machine interface for SHM. The investigation was performed using a surrogate three-story structure. The structure features three nonlinearity-inducing bumpers to simulate damage. Accelerometers are placed on each floor to measure the response of the structure to a harmonic base excitation. The accelerometer measurements are preprocessed. As a result, the preprocessed data is then encoded encoded as a vibro-tactile stimulus. Human subjects were then subjected to the vibro-tactile stimulus and asked to characterize the damage in the structure.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
AC52-06NA25396
OSTI ID:
1238613
Report Number(s):
LA-UR-13-29256
Journal Information:
Structural Health Monitoring, Vol. 13, Issue 6; ISSN 1475-9217
Publisher:
SAGE PublicationsCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 14 works
Citation information provided by
Web of Science

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A Dynamic Health Assessment Approach for Shearer Based on Artificial Immune Algorithm journal January 2016

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