A Systematic Review of Advanced Sensor Technologies for Non-Destructive Testing and Structural Health Monitoring
Open accessAbstract
This paper reviews recent advances in sensor technologies for non-destructive testing (NDT) and structural health monitoring (SHM) of civil structures. The article is motivated by the rapid developments in sensor technologies and data analytics leading to ever-advancing systems for assessing and monitoring structures. Conventional and advanced sensor technologies are systematically reviewed and evaluated in the context of providing input parameters for NDT and SHM systems and for their suitability to determine the health state of structures. The presented sensing technologies and monitoring systems are selected based on their capabilities, reliability, maturity, affordability, popularity, ease of use, resilience, and innovation. A significant focus is placed on evaluating the selected technologies and associated data analytics, highlighting limitations, advantages, and disadvantages. The paper presents sensing techniques such as fiber optics, laser vibrometry, acoustic emission, ultrasonics, thermography, drones, microelectromechanical systems (MEMS), magnetostrictive sensors, and next-generation technologies.
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For SHM systems, railway traffic is monitored by static/dynamic strain gauges and high-definition video cameras.
“| Railway traffic | -Static/dynamic strain gauges -High-definition video cameras | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 4.4 (page unavailable) identifies strain gauges and vision-based cameras as SHM sensors, and Section 4 says SHM can be applied to railway tracks. The passages do not say that railway traffic is monitored with static/dynamic strain gauges and high-definition video cameras specifically. (LLM, conf=0.82)
Experimental — accuracy not yet measuredFor SHM systems, temperature is monitored by temperature sensors, fiber optic sensors, thermocouples, and barometers.
“| | | -Fiber optic sensors |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 4.4.13, “Temperature Sensors” (page unavailable), identifies thermocouples and fiber optic sensors among the sensors used to measure temperature for SHM. It does not identify barometers as temperature-monitoring sensors, so that item is unsupported. (LLM, conf=0.88)
Experimental — accuracy not yet measuredAdvanced sensing systems are less labor intensive.
“• | less labor intensivity, | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 4.4 says wireless sensing avoids labor-intensive cabling and UAV sensors reduce logistics and working hours. These examples support lower labor demands for particular advanced sensing systems, but the review does not establish that advanced sensing systems are generally less labor intensive. (LLM, conf=0.83)
Experimental — accuracy not yet measuredFor SHM systems, wind is monitored by hygrometers, ultrasonic and propeller anemometers, and visibility and precipitation sensors.
“| Wind | -Hygrometers -Ultrasonic and propeller anemometers | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 4.2 identifies wind as an environmental factor relevant to SHM and says Table 15 lists sensors for measuring such conditions. Section 4.4.1 also identifies wind as an ambient property measured in SHM. The retrieved passages do not identify hygrometers, ultrasonic or propeller anemometers, or visibility and precipitation sensors as wind-monitoring devices. (LLM, conf=0.82)
Experimental — accuracy not yet measuredAdvanced sensing systems have more accuracy and reliability.
“• | more accuracy and reliability, | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 3.3 reports improved accuracy for ultrasonic sensors, while Section 4.4 describes improved reliability for sensor networks and vision-based sensors. These examples support the general direction of the claim, but the review does not establish that advanced sensing systems as a whole have both greater accuracy and greater reliability; it also notes accuracy limitations for vision-based sensors. (LLM, conf=0.82)
Experimental — accuracy not yet measured
Advanced sensing systems are more cost-effective.
“• | more cost-effectiveness. | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 3.3 says advances in ultrasonic sensor technology have produced more cost-effective sensors, and Section 4.4 says wireless sensing avoids cost-intensive cabling. These examples support a cost benefit for particular technologies, but not the unqualified claim that advanced sensing systems generally are more cost-effective. (LLM, conf=0.84)
Experimental — accuracy not yet measuredAdvanced sensing systems are suitable for continuous monitoring.
“• | suitability for continuous monitoring, | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Advanced sensing systems have capability for remote sensing.
“• | capability for remote sensing, | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Advanced sensing systems have automatability.
“• | automatability, | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Advanced sensing systems have less sensitivity to EOC variations.
“• | less sensitivity to EOC variations, | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 4.2 describes sensitivity to EOC variations as a significant challenge for SHM systems and says EOC-robust sensors would be advantageous. Section 4.4 says independence from environmental and operational variations is an ideal, but does not establish that advanced sensing systems have less sensitivity to those variations. (LLM, conf=0.72)
Experimental — accuracy not yet measuredFor SHM systems, highway traffic is monitored by static/dynamic strain gauges, dynamic weigh-in-motion stations, and high-definition video cameras.
“| Highway traffic | -Dynamic weigh-in-motion stations | |”
From Effects of Environmental and Operational Conditions on Structural Health Monitoring and Non-Destructive Testing: A Systematic Review (2023) · cites this paper as [141]
Section 4.2 discusses how traffic loading affects structures, and Section 4.4 describes SHM sensors generally. Neither passage says highway traffic is monitored by dynamic weigh-in-motion stations; searches for “weigh-in-motion” and “WIM” found no such passage in our copy. (LLM, conf=0.70)
Experimental — accuracy not yet measured
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Cited by
Sorted by citations
Hassani, S., & Dackermann, U. (2023) · Sensors · doi:10.3390/s23063293 · Cited by 146 · see citing works
Self-citationKeshmiry, A., Hassani, S., Mousavi, M., & Dackermann, U. (2023) · Buildings · doi:10.3390/buildings13040918 · Cited by 96 · see citing works
Self-citationGuo, S., West, A., Papuga, J., Theodossiades, S., & Jiang, J. (2025) · Sensors · doi:10.3390/s25216531 · Cited by 4 · see citing works
Mohammed, B. (2026) · Sensor Review · doi:10.1108/sr-10-2025-0822 · Cited by 3 · see citing works
- Authors
- Hassani, S., & Dackermann, U.
- Affiliations
- UNSW Sydney (AU)
- Corresponding author
- Dackermann, Ulrike
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2023-02-15
- Volume
- 23
- Issue
- 4
- Pages
- 2204
- ISSN
- 1424-8220 (ISSN-L)
- PMC
- PMC9965987
- OpenAlex
- W4321099465
- Cited by
- 492
- References
- 440
- Citations by year
- 2026: 158 · 2025: 190 · 2024: 112 · 2023: 32
- FWCI
- 10.16
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sensors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Health Monitoring Techniques
- Physical Sciences › Engineering › Civil and Structural Engineering › Structural Engineering and Materials Analysis
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Fiber Optic Sensors
- Keywords
- non-destructive testing, structural health monitoring, civil engineering structures, sensor technology, fiber optic sensors, laser vibrometry, acoustic emission, ultrasonics, infrared thermography, unmanned aerial vehicles, MEMS sensors, magnetostrictive sensors, data analytics, structural health assessment
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