This study presents a portable multi-component gas sensing system based on Fiber-Enhanced Raman Spectroscopy (FERS). The system achieves efficient gas collection, precise analysis, and rapid response times by leveraging the unique advantages of hollow-core optical waveguides. The large aperture and high reflectivity of silver-coated capillary (SCC) minimize optical power loss and improve the collection efficiency of Raman signals, ensuring high sensitivity and accuracy in gas detection. And by combining SCC and lens with the gas chamber, the integration of the probe has been improved. Additionally, The system's fiber optic probe structure seamlessly connects the Raman probe to the laser and spectrometer via multimode fiber, streamlining signal transmission, allowing it to function as an independent portable probe. Experimental results demonstrate the system's capability for qualitative and quantitative analysis of multi-component gases, achieving detection limits in the low hundreds of parts per million (ppm) for gases such as CH₄, C₂H₄, and C₂H₂, along with other flammable industrial gases. Notably, the system exhibits a rapid response time of 1.5 seconds. This portable FERS-based gas sensing system offers exceptional performance for real-time gas analysis, making it a valuable tool for industrial and environmental monitoring applications due to its compact design, high sensitivity, versatility, and fast response.
In order to effectively maintain and operate the smart substations, a data mining and analysing method for defects of secondary equipment based on the FP-Growth algorithm is proposed.The basic ideas of association rules and FP-Growth algorithm are introduced firstly, then the defect model and the system framework are proposed to mine and analyze the defect data. Through the analysis of the actual defect data of a substation using the proposed method, it shows that the proposed method can effectively find the relationship among secondary devices, manufactories, defect properties, defect causes and other factors. By data mining, it can provide valuable information for efficient maintaining and operation of the substations. Some auxiliary suggestions are given for operation of secondary device finally.
High-sensitivity sensing of multi-component gases has important applications in environmental monitoring, industrial process control, and biomedical analysis. Fiber-enhanced gas Raman spectroscopy based on node-less anti-resonant hollow-core fibers (AR-HCFs) has advantages for the detection of multi-component gases. AR-HCFs can significantly improve the collection efficiency of gas signals, but the diffusion rate of gas in AR-HCFs is slow under normal pressure, and the gas exchange in AR-HCFs requires the help of gas pressure control devices. In this work, a reflective fiber-enhanced gas Raman system is designed and only one end of the hollow-core fiber is coupled to the optical path, the other end is placed in free space which facilitates rapid gas exchange. Various gases such as CH4, H2, N2, NH3, etc. are injected into optical fibers for systematic research. It takes 70 s to fill the 0.5m-long AR-HCFs with hydrogen at 1.2 Bar, but only 8 s at 1.6 Bar. Due to the influence of the gas viscosity coefficient, the time required for CH4 to fulfill 1m-long AR-HCFs is about 1.4 times that of H2 under the same environment. It is proved that such an optical fiber-enhanced gas Raman system can realize fast gas filling and exchange, and has good detection ability for multi-component gas, which can be used in fields requiring the quick response of gas sensing.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.