SENSING IN THE CONSTRUCTION INDUSTRY

• TUNNELING – SHM AND GAS SENSING
• UNDERGROUND GRID – GPR, EMI, AND ACOUSTIC SENSOR
• HAVS (MSD) – REAL-TIME MONITORING

ANTO OVID

LONG-TERM CONSTRUCTION INJURIES�

• Long-term damage to the body is common in construction work. Because these injuries don’t arise from a single tragic event but develop slowly over years or decades of work, they can greatly impact sufferers’ lives.
• Safety education often focuses on sudden, catastrophic accidents – such as falls, explosions, trench collapses, and vehicle accidents. However, another category of injuries takes place over time.
• The following are among the most prominent long-term injuries.
• Repetitive stress injuries – Hand Arm Vibration Syndrome
• Musculo-skeletal disorder – Back pain
• Hearing loss
• Toxic exposure – Exposure to lead

MSD – MUSCULO SKELETAL DISORDER

Musculoskeletal Disorders or MSDs are injuries and disorders that affect the human body’s movement or musculoskeletal system (i.e. muscles, tendons, ligaments, nerves, discs, blood vessels, etc.).

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• Musculoskeletal Disorders (MSDs) are a common and costly problem for people and companies across the US
• MSDs are the single largest category of workplace injuries and are responsible for almost 30% of all worker’s compensation costs. (source: BLS)
• U.S. companies spent 50 billion dollars on direct costs of MSDs in 2011. (source: CDC)
• Indirect costs can be up to five times the direct costs of MSDs. (source: OSHA)
• The average MSD comes with a direct cost of almost $15,000. (source: BLS)
•  Musculoskeletal disorders are preventable.

MS-DISORDERS:

• Carpal Tunnel Syndrome
• Tendonitis
• Muscle / Tendon strain
• Ligament Sprain
• Tension Neck Syndrome
• Thoracic Outlet Compression
• Radial Tunnel Syndrome

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HAVS – HAND ARM VIBRATION SYNDROME

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• Vibration White Finger (VWF) / Hand-Arm Vibration Syndrome (HAVS) is a secondary form of Raynaud's syndrome, also known as a dead finger.
• Injury – Permanent and can occur at frequencies between 5 and 2000 Hz but the greatest risk for fingers is between 50 and 300 Hz.
• ISO 5349-1:2001 says the maximum damage occurs between 8 and 16 Hz and reduces with a frequency greater than 16 Hz, but research shows both medium and higher frequencies also have chances of producing HAVS.
• An estimated 1.45 million workers use vibrating tools in the United States. In a working population that has used vibrating tools, the prevalence of HAVS ranges from 6% to 100%, with an average of about 50%.
•  It indeed affects the nervous system – Check out this article with Rat experimentations! [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4694567]

HAVS – SAFETY MONITORING WEARABLES

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1. Automated Hand-Arm Vibration Monitoring of Construction Workers Using Smartwatch and Machine Learning [Khandakar M. Rashid- Oregon State University]

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2) AGIS: [Denys J.C. Matthies , Gerald Bieber , Uwe Kaulbars]

LIMITATIONS:

• Not in contact with Equipment
• Not accurate
• Needs battery
• Very narrow frequency range

Measurement results with the use of hand-attached accelerometers show a clear tendency of underestimating vibration exposures compared with measurements with the use of tool-attached accelerometers. One of the reasons for this is that workers often use a different grip compared with the recommendations in the measurement standard ISO-5349-2. (Clemm et al. 2021)

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AGIS can only recognize vibrations up to 25Hz, which is

insufficient for tools such as a grinder that is running at

150rpm. These constraints disable us to provide an accurate calculation of actual HAV intensity.

(Matthies et al. 2016)

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1) PTCNG-BASED SELF-POWERED VIBRATION SENSOR FOR MONITORING WORKER’S EXPOSURE TO HAV.

WORKING PRINCIPLEs:

SENSOR RATIONALE

FABRICATION STEPS:

DESIGN

1. Fabricate the piezoelectric layer:
• Use a polarized PVDF film with AL electrodes
• Attach it to a PET film, creating an outer structure for support.
2. Fabricate the triboelectric layer with micro-patterned structures:
• Silicon rubber curing solution on a copper mesh pattern.
• Remove bubbles, cure, and peel off the cured silicone rubber.
3. Assemble the hybrid NG:
• Attach the silicone rubber membrane to an aluminum electrode and PET film.
• Stack the piezoelectric layer on top of the triboelectric layer, sharing the aluminum electrodes to increase energy output.

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(2) PENG-BASED WEARABLE VIBRATION SENSOR

1. PVDF – BT Solution – Electro spun
2. Hot pressed electro-spun fibers at 150’c
3. ITO-coated PET as supporting structure and Electrode

BaTi03 largely increases the piezoelectric property of the flexible PVDF.

Structures can be optimized into micropillars or voids to increase piezoelectricity.

(3) V-Q-A-BASED TENG ACCELERATION SENSOR�

1. The triboelectric layers consist of ITO/PET/SF layer and the ITO/PET layer.

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• Silk-fibroin patches are deposited on the ITO/PET film

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• After coating the silk fibroin solution, the ITO/PET film is cured

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• TENG is designed to have an arch-shaped geometry to support the mass.

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EXPERIMENTS

• Parameters:
• Different Tools – Hammers, Saws, Grinders, etc.
• User Feedback – Comfort Analysis
• Data Analysis – Reliability, Sensitivity, Durability

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Set of Experiments:

• FEA – Structural Optimization of the components
• COMSOL – Simulation for Output Voltage vs Working Frequency
• Measure the sensitivity of the sensor against working objects/surfaces
• Measure the self-powered workability of the sensor on different tools
• Comparison of the three sensors with Conventional Accelerometer-based sensors

ADVANTAGES

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• Self-powered
• Real - Time Monitoring
• Comfortable
• Accurate than the conventional method
• Wide frequency range

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CHALLENGES

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• In (1) TENG – prone to mechanical wear
• For (2) calibration

SOLUTIONS

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• Proper calibration
• Experiment with other materials

POTENTIAL FUNDINGS:

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• NIH&NIOSH - OCCUPATIONAL SAFETY AND HEALTH RESEARCH (R01)
• CPWR – CENTRE FOR CONSTRUCTION RESEARCH & TRAINING SMALL STUDIES PROGRAM

REFERENCE

1. Lemm, T., K.-C. Nordby, L.-K. Lunde, B. Ulvestad, and M. Bråtveit. 2021. “Hand-Arm Vibration Exposure in Rock Drill Workers: A Comparison between Measurements with Hand-Attached and Tool-Attached Accelerometers.” Ann. Work Expo. Health, 65 (9): 1123–1132. https://doi.org/10.1093/annweh/wxab051.
2. He, J., T. Wen, S. Qian, Z. Zhang, Z. Tian, J. Zhu, J. Mu, X. Hou, W. Geng, J. Cho, J. Han, X. Chou, and C. Xue. 2018. “Triboelectric-piezoelectric-electromagnetic hybrid nanogenerator for high-efficient vibration energy harvesting and self-powered wireless monitoring system.” Nano Energy, 43: 326–339. https://doi.org/10.1016/j.nanoen.2017.11.039.
3. Liu, C., Y. Wang, N. Zhang, X. Yang, Z. Wang, L. Zhao, W. Yang, L. Dong, L. Che, G. Wang, and X. Zhou. 2020. “A self-powered and high sensitivity acceleration sensor with V-Q-a model based on triboelectric nanogenerators (TENGs).” Nano Energy, 67: 104228. https://doi.org/10.1016/j.nanoen.2019.104228.
4. Matthies, D. J. C., G. Bieber, and U. Kaulbars. 2016. “AGIS: automated tool detection & hand-arm vibration estimation using an unmodified smartwatch.” Proc. 3rd Int. Workshop Sens.-Based Act. Recognit. Interact., 1–4. Rostock Germany: ACM.
5. Athira, B. S., A. George, K. Vaishna Priya, U. S. Hareesh, E. B. Gowd, K. P. Surendran, and A. Chandran. 2022. “High-Performance Flexible Piezoelectric Nanogenerator Based on Electrospun PVDF-BaTiO ₃ Nanofibers for Self-Powered Vibration Sensing Applications.” ACS Appl. Mater. Interfaces, 14 (39): 44239–44250. https://doi.org/10.1021/acsami.2c07911.

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