We propose a method for localizing a fire source using an optical fiber distributed temperature sensor system. A section of two parallel optical fibers employed as the sensing element is installed near the ceiling of a closed room in which the fire source is located. By measuring the temperature of hot air flows, the problem of three-dimensional fire source localization is transformed to two dimensions. The method of the source location is verified with experiments using burning alcohol as fire source, and it is demonstrated that the method represents a robust and reliable technique for localizing a fire source also for long sensing ranges.

A method for localizing a fire source based on a distributed temperature sensor system is proposed. Two sections of optical fibers were placed orthogonally to each other as the sensing elements. A tray of alcohol was lit to act as a fire outbreak in a cabinet with an uneven ceiling to simulate a real scene of fire. Experiments were carried out to demonstrate the feasibility of the method. Rather large fluctuations and systematic errors with respect to predicting the exact room coordinates of the fire source caused by the uneven ceiling were observed. Two mathematical methods (smoothing recorded temperature curves and finding temperature peak positions) to improve the prediction accuracy are presented, and the experimental results indicate that the fluctuation ranges and systematic errors are significantly reduced. The proposed scheme is simple and appears reliable enough to locate a fire source in large spaces.

Calibration-free laser-induced breakdown spectroscopy can overcome the matrix effect and the huge application prospects of in-situ and on-line measurement, so it has been studied and applied to many analytical samples by numerous researchers since it was first proposed in 1999. However, its accuracy is always lower than other analytical techniques and traditional quantitative analysis methods of laser-induced breakdown spectroscopy. The goal of this paper is to review the improvement of accuracy in the experimental setup and spectral analysis, especially after 2010, but not limited to it. The main contents include the accurate measurement of spectral intensity, the spatial and temporal window of local thermodynamic equilibrium and the accurate calculation of temperature and electron density. Due to the requirement of one or more standard samples, the combination of standard samples and CF-LIBS is discussed as a separate section. Finally, a simple conclusion is offered to relevant researchers who want to use CF-LIBS for quantitative analysis.

Laser-induced breakdown spectroscopy (LIBS) is a qualitative and quantitative analytical technique with great potential in the cement industrial analysis. Calibration curve (CC) and support vector regression (SVR) methods coupled with LIBS technology were applied for the quantification of three types of cement raw meal samples to compare their analytical concentration range and the ability to reduce matrix effects, respectively. To reduce the effects of fluctuations of the pulse-to-pulse, the unstable ablation and improve the reproducibility, all of the analysis line intensities were normalized on a per-detector basis. The prediction results of the elements of interest in the three types of samples, Ca, Si, Fe, Al, Mg, Na, K and Ti, were compared with the results of the wet chemical analysis. The average relative error (ARE), relative standard deviation (RSD) and root mean squared error of prediction (RMSEP) were employed to investigate and evaluate the prediction accuracy and stability of the two prediction methods. The maximum average ARE of the CC and SVR methods is 34.62% instead of 6.13%, RSD is 40.89% instead of 7.60% and RMSEP is 1.34% instead of 0.43%. The results show that SVR method can accurately analyze samples within a wider concentration range and reduce the matrix effects, and LIBS coupled with it for a rapid, stable and accurate quantification of different types of cement raw meal samples is promising.