Structural Control and Health Monitoring

Aims & Scope

The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures.

The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications.

Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics.

Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.

Metrics & Ranking

Abstracting & Indexing

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

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

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

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Engineering, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 2,370.00 USD. Learn more.

Explore journals without APCs for alternative publishing options.

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.

• Bayesian system identification based on probability logic

  Citation: 526

  Authors: James L.

• A literature review of next-generation smart sensing technology in structural health monitoring

  Citation: 475

  Authors: Sandeep, Shea, Ayan

• Smart sensing technology: opportunities and challenges

  Citation: 428

  Authors: B. F., Manuel E., Narito

• The unscented Kalman filter and particle filter methods for nonlinear structural system identification with non-collocated heterogeneous sensing

  Citation: 374

  Authors: Eleni N., Andrew W.

• Convolutional neural network-based data anomaly detection method using multiple information for structural health monitoring

  Citation: 350

  Authors: Zhiyi, Zhicheng, Yuequan, Hui

• Technology innovation in developing the structural health monitoring system for Guangzhou New TV Tower

  Citation: 338

  Authors: Y. Q., Y., W. Y., J. M.

• An adaptive extended Kalman filter for structural damage identification

  Citation: 285

  Authors: Jann N., Silian, Hongwei, Li

• Optimal tuned mass-damper-inerter (TMDI) design for seismically excited MDOF structures with model uncertainties based on reliability criteria

  Citation: 267

  Authors: A., A.A.

• Instrumentation and health monitoring of cable-supported bridges

  Citation: 258

  Authors: Kai-Yuen

• Target-free approach for vision-based structural system identification using consumer-grade cameras

  Citation: 256

  Authors: Hyungchul, Hazem, Hajin, Mani, Billie F.