Structural Health Monitoring

Aims & Scope

Structural Health Monitoring publishes peer-reviewed papers that contain theoretical, analytical, and experimental investigations that advance the body of knowledge and its application in the discipline of structural health monitoring.

The journal has a broad topical coverage and it serves as a primary reference for the structural health monitoring of aeronautical, mechanical, civil, electrical, and other systems.

The multidisciplinary nature of the journal is intended to foster the intersection of different technologies to address the varied needs and applications for structural health monitoring.

Papers are sought that explore the following issues and areas related to structural health monitoring: self-diagnostics, prognostics, condition-based maintenance and performance vibration and wave propagation methods for damage assessment advanced signal processing and interpretation techniques for monitoring and diagnostics sensor design, self-powered and low power sensors data mining, data management the use of smart materials and new sensor materials monitoring of composite, metallic, new, and aging structures and infrastructure monitoring of structural repairs sensor network design, data transmission, wired and wireless communication embedding technology, sensor/structure integration technology development of self-repairable structures monitoring of survivability and readiness assessment structural integrity and remaining life predictions based on sensor management design of multifunctional structures and integration of structural health monitoring and control sensors for high temperature applications, in-situ sensors monitoring of biomechanical, electromechanical, and thermal systems fault diagnosis of avionics, propulsion, power, and electronic systems structural health monitoring system integration and validation, etc.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	5.7
2024	5.70

SJR (SCImago Journal Rank)

Year	Value
2024	1.831

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	97

Journal Rank

Year	Value
2024	1694

Journal Citation Indicator

Year	Value
2024	5259

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Biochemistry, Genetics and Molecular Biology and Engineering, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Vibration-based Damage Identification Methods: A Review and Comparative Study

  Citation: 1670

  Authors:

• Vibration Based Condition Monitoring: A Review

  Citation: 1220

  Authors: E. Peter, Paul

• Review Paper: Health Monitoring of Civil Infrastructure

  Citation: 763

  Authors: Peter C., Alison, S. C.

• A review of computer vision–based structural health monitoring at local and global levels

  Citation: 585

  Authors: Chuan-Zhi, F Necati

• Computer vision and deep learning–based data anomaly detection method for structural health monitoring

  Citation: 491

  Authors: Yuequan, Zhiyi, Hui, Yufeng

• Pitch-catch Active Sensing Methods in Structural Health Monitoring for Aircraft Structures

  Citation: 490

  Authors: Jeong-Beom, Fu-Kuo

• Structural Health Monitoring in mainland China: Review and Future Trends

  Citation: 455

  Authors:

• Piezoelectric Wafer Embedded Active Sensors for Aging Aircraft Structural Health Monitoring

  Citation: 428

  Authors: Victor, Andrei, Jing

• Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights

  Citation: 377

  Authors: Arman, Ekin, Mohammad, Mark

• Machine learning algorithms for damage detection under operational and environmental variability

  Citation: 363

  Authors: Eloi, Gyuhae, Charles R, Keith, Joaquim

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