Carbon Fiber Reinforced Plastics (CFRP) is a material developed for its high strength and light weight in a broad variety of industries including aerospace, automotive, and leisure. Due to the rapid molding cycle time, high-pressure resin transfer molding (HP-RTM) processes are prone to molding defects and susceptible to various process variables such as the resin injection rate, pressure and temperature in the mold, vacuum, end-gap, pressing force, and binder. In recent years, process monitoring technology with various sensors has been applied to stabilize the HP-RTM process and control process variables. The field-programmable gate array (FPGA) based embedded monitoring system proposed in this study enabled high-speed real-time signal processing with multiple sensors, namely pressure, temperature, and linear variable differential transformer (LVDT), and proved feasibility in the field. In the HP-RTM process, the impregnation and curing of the resin were predicted from the cavity pressure and temperature variations during the injection and curing stages. In addition, the thickness of the CFRP specimen was deduced from the change in the end-gap through the detection of the LVDT signal. Therefore, the causes of molding defects were analyzed through process monitoring and the influence of molding defects on the molding quality of CFRP was investigated.
With the increasing demand to find new energy resources instead of using fossil fuels, for the protection of the environment, one of most attractive areas in renewable energy is hydrogen. Hydrogen gas has high energy efficiency, generates the least greenhouse gases and produces no noise. Moreover, overland transportation industries have been researching and developing hydrogen gas storage systems worldwide. Such a manner of fuel system consists of a hydrogen gas tank, high pressure regulator and solenoid valve, etc. In this paper, a test bed is suggested for ultra-high pressure systems integrating a valve and regulator with precision control. We carried out performance tests by applying voltage with wide ranges of input pressure, response time and output flow rate and pulsation repetition tests considering increases in temperature, etc. Moreover, the results indicated good potential for application in fuel charging and transporting commercial hydrogen vehicles.
Machining of difficult-to-cut materials such as titanium alloys, stainless steel, Inconel, ceramic, glass, and carbon fiber-reinforced plastics used in the aerospace, automobile, and medical industries is being actively researched. One non-traditional machining method involves the use of an abrasive waterjet, in which ultra-high-pressure water and abrasive particles are mixed and then ejected through a nozzle, and the thin jet stream cuts materials. The nozzle greatly affects the machining quality, as does the cutting tool of general machining, so it is very important to monitor the nozzle condition. If the nozzle is damaged or worn, or if the bore size increases or the bore becomes clogged with abrasive, the material may not be cut, or the surface quality of the cut may deteriorate. Here, we develop a nozzle monitoring system employing an acoustic emission sensor that detects the nozzle condition in real time.
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