23 research outputs found
A new approach to constructing simultaneous prediction limits on future outcomes under parametric uncertainty of underlying models
No full textEffective Optimization of Statistical Decisions for Age Replacement Problems under Parametric Uncertainty
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Dynamic Airline Seat Inventory Control
No full textDynamic booking policy for multiple fare classes that share the same seating pool on one leg of an airline flight, when seats are booked in a nested fashion and when lower fare classes book before higher ones, is determined. The dynamic policy of airline booking makes repetitive use of a static method over the booking period, based on the most recent demand and capacity information. It allows one to allocate seats dynamically and anticipatory over time
Statistical Models And Decisions In Aircraft Service
No full textAircraft structures have many components. Maintaining high reliability for these structures generally requires that the individual structure components have extremely high reliability, even after long periods of time. One of the most important problems in the fatigue analysis and design of aircraft structures is the prediction of the fatigue crack growth in service. Available in-service inspection data for various types of aircraft indicate that the fatigue crack damage accumulation in service involves considerable statistical variability. The objectives of this paper are to (i) describe possible statistical models to deal with the crack growth variability, (ii) point out their applications
CFAR vibration signal change test and its applications to real-time recognition of developing cracks in jet engine rotors
No full textThis paper introduces a new technique for early identification of fatigue cracks, namely the constant false alarm rate (CFAR) test. This test works on the null hypotheses that a target vibration signal is statistically similar to a reference vibration signal. In effect, this is a time-domain signal processing technique that compares two signals, and returns the likelihood whether the two signals are similar or not. The system monitors the vibration signal of the rotor as it cycles, and compares that vibration signal with, say, the original vibration signal. The difference vector reflects the change in vibration over time. As a crack develops, the vector changes in a characteristic way. Thus, it is possible, during CFAR test, to determine whether the two signals are similar or not. Therefore, by comparing a given vibration signal to a number of reference vibration signals (for several crack scenarios) it is possible to state which is the most likely condition of the rotor under analysis. The CFAR test not only successfully identifies the presence of the fatigue cracks but also gives an indication related to the advancement of the crack. This test, despite its simplicity, is an extremely powerful method that effectively classifies different vibration signals, allowing for its safe use as another condition monitoring techniqu
Probabilistic fatigue reliability assessment
No full textThe prediction of stochastic crack growth accumulation is important for the reliability analysis of structures as well as the scheduling of inspection and repair/replacement maintenance. Because the initial crack size, the stress, the material properties and other factors that may affect the fatigue crack growth are statistically distributed, the first-order second-moment technique is often adopted to calculate the fatigue reliability of industrial structures. In this paper, a second-order third-moment technique is presented and a three-parameter Weibull distribution is adopted to reflect the influences of skewness of the probability density function. The second-order third-moment technique that has more characteristics of those random variables that are concerned in reliability analysis is obviously more accurate than the traditional first-order second-moment techniqu
CFAR vibration signal change test and its applications to real-time recognition of developing cracks in jet engine rotors
No full textThis paper introduces a new technique for early identification of fatigue cracks, namely the constant false alarm rate (CFAR) test. This test works on the null hypotheses that a target vibration signal is statistically similar to a reference vibration signal. In effect, this is a time-domain signal processing technique that compares two signals, and returns the likelihood whether the two signals are similar or not. The system monitors the vibration signal of the rotor as it cycles, and compares that vibration signal with, say, the original vibration signal. The difference vector reflects the change in vibration over time. As a crack develops, the vector changes in a characteristic way. Thus, it is possible, during CFAR test, to determine whether the two signals are similar or not. Therefore, by comparing a given vibration signal to a number of reference vibration signals (for several crack scenarios) it is possible to state which is the most likely condition of the rotor under analysis. The CFAR test not only successfully identifies the presence of the fatigue cracks but also gives an indication related to the advancement of the crack. This test, despite its simplicity, is an extremely powerful method that effectively classifies different vibration signals, allowing for its safe use as another condition monitoring techniqu
CFAR vibration signal change test and its applications to real-time recognition of developing cracks in jet engine rotors
No full textThis paper introduces a new technique for early identification of fatigue cracks, namely the constant false alarm rate (CFAR) test. This test works on the null hypotheses that a target vibration signal is statistically similar to a reference vibration signal. In effect, this is a time-domain signal processing technique that compares two signals, and returns the likelihood whether the two signals are similar or not. The system monitors the vibration signal of the rotor as it cycles, and compares that vibration signal with, say, the original vibration signal. The difference vector reflects the change in vibration over time. As a crack develops, the vector changes in a characteristic way. Thus, it is possible, during CFAR test, to determine whether the two signals are similar or not. Therefore, by comparing a given vibration signal to a number of reference vibration signals (for several crack scenarios) it is possible to state which is the most likely condition of the rotor under analysis. The CFAR test not only successfully identifies the presence of the fatigue cracks but also gives an indication related to the advancement of the crack. This test, despite its simplicity, is an extremely powerful method that effectively classifies different vibration signals, allowing for its safe use as another condition monitoring techniqu
CFAR vibration signal change test and its applications to real-time recognition of developing cracks in jet engine rotors
No full textThis paper introduces a new technique for early identification of fatigue cracks, namely the constant false alarm rate (CFAR) test. This test works on the null hypotheses that a target vibration signal is statistically similar to a reference vibration signal. In effect, this is a time-domain signal processing technique that compares two signals, and returns the likelihood whether the two signals are similar or not. The system monitors the vibration signal of the rotor as it cycles, and compares that vibration signal with, say, the original vibration signal. The difference vector reflects the change in vibration over time. As a crack develops, the vector changes in a characteristic way. Thus, it is possible, during CFAR test, to determine whether the two signals are similar or not. Therefore, by comparing a given vibration signal to a number of reference vibration signals (for several crack scenarios) it is possible to state which is the most likely condition of the rotor under analysis. The CFAR test not only successfully identifies the presence of the fatigue cracks but also gives an indication related to the advancement of the crack. This test, despite its simplicity, is an extremely powerful method that effectively classifies different vibration signals, allowing for its safe use as another condition monitoring techniqu
