Stall Detection Within the Low Pressure Compressor of a Twin-Spool Turbofan Engine by Tip Flow Analysis Available to Purchase

In order to preserve fossil resources aviation industry faces major challenges to reduce engine fuel consumption. Therefore efforts are concentrated to increase efficiency of any engine component. Investigations at the Institute of Jet Propulsion at the University of Federal Armed Forces in Munich focus on the compressor module. The compression system is designed to work at very high loads and due to this it is one of the most critical components during transient engine operation. Occurring instabilities are mostly limited to the tip region of the compressor blades because of the tip clearance and low momentum fluid from the casing boundary layer. Prior to instability onset such as rotating stall and even surge, some so-called stall precursors commonly occur in this area. In order to predict and avoid those critical engine operations a stall detection algorithm was developed and combined with an active compressor stabilization system. As a research vehicle the Larzac 04 twin-spool turbofan engine is used at the test facility of the Institute of Jet Propulsion. The test vehicle is equipped with additional instrumentation and control systems exceeding those of conventional engine monitoring systems by far. Providing input data to the stall detection algorithm flush mounted Kulite sensors are installed within the casing of the first stage of the low pressure compressor, where stall usually arises in the Larzac 04. The described algorithm is based on the spike theory being the dominant stall precursor in nearly all operating ranges of the test engine. After the detection of an upcoming stall event active countermeasures are triggered to avoid critical engine operation. For this reason an air injection system was attached in front of the fan stage to affect the blade tip region by injecting additional air at a high velocity to re-establish the blade flow. The main emphasis of this paper is to illustrate the signal conditioning used for stall detection and to prove the reliable function of the algorithm in combination with an active countermeasure at an aircraft engine.