Tutorials

This tutorial explores the fundamentals and cutting-edge applications of Distributed Optical Fiber Sensing (DOFS) technologies, specifically focusing on Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS/DTGS). Based on Rayleigh and Raman s principles and phase-sensitive OTDR (phi-OTDR), these technologies enable real-time, high-sensitivity monitoring of acoustic, strain, and temperature variations along several kilometers of standard optical fibers. Participants will gain insights into the implementation challenges and technical specifications of these systems, longside practical case studies in critical sectors. The session highlights diverse applications including leak detection in pipelines and refineries, structural health monitoring of dams and offshore wells, seismic tomography, and thermal imaging of power generators, demonstrating the transformative potential of DOFS for the safety and efficiency of modern energy and infrastructure systems.

Prepared by a top expert in the field with many developments, real world applications and patents, this lecture will be an invaluable resource for physicists, electronics engineers, teachers, students, technicians and anyone working in the field of sensors. In this presentation, the advantages and possibilities of fiber optic sensors in research and industry will be presented, including two technologies, plastic optical fiber (POF) and the silica fiber. In addition to presenting various technologies that use POF as a sensor, this tutorial will also focus on another type of technology, Fiber Bragg Grating (FBG). FBGs can be found in many industrial applications and we will present our experiences in applying FBGs in many types of sensors for the power industry.

The tutorial will start with the theory of fiber optic sensors using both POF and FBG. It will then cover various practical applications of sensors, including successful field applications developed by our lab in areas such as oil & gas, biotechnology and electrical energy.

The following topics will be presented and discussed in the lecture: Fiber optic sensing technologies; temperature sensing; strain and force sensing; refractive index sensing; high voltage switch monitoring; current and voltage sensing; gas sensing; chemical and biological sensing; oil leak detection; high voltage and high current sensing; gas flow velocity sensing.

Soft sensors are models that allow estimating the values of a variable based on other process information, without having to measure this variable directly. The main benefits of soft sensors are (1) they represent a low-cost alternative when compared to physical sensors, (2) they can work together with physical sensors, including to identify when they fail, (3) they allow implementation on existing devices, and (4) they provide real-time estimates, being an option for measurements where physical sensors depend on time-consuming analysis. In this tutorial, we are going to learn how to develop a data-driven soft sensor using Python taking into account data-driven techniques such as neural networks, decision trees, and other regression techniques. Besides the soft sensor development, we will discuss 10 good practices to develop safer, more reliable and more efficient models. The good practices involves the understanding of the risk of not taking care of models extrapolation, the effect of data quality and data quantity while building the models, and the importance of error distribution besides general metrics. After building the models, we will discuss good practices to improve efficiency, how to monitor performance and how to perform models calibration. Real data from industrial processes will be used in this hands-on tutorial.

Quantum sensing represents a paradigm shift in the science of measurement. It leverages the intrinsic quantum properties of particles and their wave functions, such as superposition, entanglement, and coherence, to achieve unparalleled sensitivity, precision, and miniaturization. This talk will present a practical engineering perspective on quantum sensing, linking fundamental quantum principles to real-world applications. Key enabling technologies will be reviewed, such as single-photon detectors, nitrogen-vacancy (NV) centers in diamond, and Rydberg atoms. Additionally, we will examine the integration of quantum sensing approaches with optical fiber systems, highlighting advances in distributed sensing capabilities enabled by quantum detectors. The discussion emphasizes the advantages of quantum measurement techniques over classical methods. Finally, we will outline the emerging domain of quantum sensing applications alongside the ongoing miniaturization and cost reduction of quantum devices, demonstrating their potential to transform multiple scientific and industrial fields.