Study Of SF₆ Detection System Based On Stochastic Resonance And Aligned Multi-walled Carbon Nanotubes Gas Sensor Array

SF₆ (Sulfur Hexafluoride) has been widely used in industry, agriculture and daily life due to its unique physical and chemical characteristics since it was firstly prepared by French chemists Moissan and Lebeau in 1900. At the same time, the leakage of SF₆ does great harm to people's work condition and life security. Thus how to detect SF₆ with accuracy, convenience, and efficiency has been a serious subject from theoretical and practical aspects.SF₆ is an inactive insulated gas and it presents excellent chemical stability. Gas sensors in some mechanisms (such as adsorption-desorption, oxidation-deoxidation, etc), could not detect SF₆. GC/TCD method presents high accuracy in SF₆ detection, but this method has been almost replaced by other new method, such as GC/FID. GC-MS method also could detect microdosage SF₆ but its equipments have bulky architectures, expensive price and long detecting period, which limits the field usages of GC/MS equipments. Foreign portable SF₆ detectors, such as GasCheck5000is and DNS200, own 1～1000ppm detection range. But their prices (from 27000 to 60000 RMB) are also expensive. Other sensing methods, such as infra-red spectrum absorption method could analyze SF₆ gas in satisfying accuracy, but the detecting system is complicated, high-cost and hard to machine. UV-light ionization method and high voltage ionization method own SF₆ detecting capability, but some hazardous chemical compounds, such as H₂S and SO₂, which could do great harm to the people who are operating the equipments. So a novel SF₆ gas detecting method presents great value.Combines with modern sensing theory and developing nano-material techniques, we proposed a novel SF₆ detecting system based stochastic resonance theory and aligned multi-walled carbon nanotubes ionization gas sensor array. We utilized Anodic Aluminum Oxide (AAO) template as substrate, and Chemical Vapor Deposition (CVD) method to fast grow aligned multi-walled carbon nanotubes on substrate to fabricate substrate-carbon nanotubes integrated electrode. We used the carbon nanotubes electrode and Al electrode to assemble ionization gas sensor. Meanwhile, we explored discharge characteristics and influence factors (interelectrode distance, temperature, atmospheric pressure, relative humidity, etc) through experiments. To optimize the characteristics of ionization sensor, we studied the diameter, distance and height of carbon nanotubes when field effects of carbon nanotubes were in optimized conditions. Finally, we concluded the correlated treatments during the preparation procedure of carbon nanotubes.In order to solve the 'cross-sensitivity' problem lies in single carbon nanotubes gas sensor, we designed a carbon nanotubes gas sensor array in our SF₆ gas detecting system. Utilizing Principle Component Analysis (PCA) method and a four-sensor array, we could detect pure Ar, SF₆, N₂, and CO₂. Stochastic resonance theory has been widely studied in the last twenty years. When we detected SF₆ /Air mixtures in ppm level, the output signals were in microampere level. The key lied in how to determine SF₆ concentration according to output signals accurately and fast. Based on the research of bistable stochastic resonance, we proposed a two-sensor array combined with bistable stochastic resonance method to determine SF₆ concentration successfully. Furthermore, we set up a three-level SF₆ concentration alarm: low level (500-1000ppm), medium level (1000～2000ppm), and high level (over 2000ppm).The stochastic multi-resonance phenomenon was observed within the gas sensor system. A periodical signal (1.65MHz) presented stochastic multi-resonance induced by adding white noise to the sensor system. Here we adopted a multi-stable dynamic system to simulate the stochastic multi-resonance phenomenon observed in the sensor system. The simulation results agreed with experimental results well.Based on design of SF₆ gas detecting system, we prepared AAO template, and grew aligned multi-walled carbon nanotubes on the template to assemble ionization gas sensor. PCA and a four-sensor array were used to classify pure Ar, SF₆, N₂, and CO₂. Bistable stochastic resonance and a two-sensor array were utilized to detect microdosage SF₆ gas in low concentration. A multi-stable dynamic system was used to study the stochastic multi-resonance phenomenon of internal periodical signal within the sensor system. The SF₆ detecting system owns the characteristics of small size, high sensitivity, high stability, quick response, and low cost. It presents good theoretical and practical value.