Ricardo Moreno

Comparison of Minimum Detectable Crack Size in a Geared System From Three Different Vibration Transducer Types

Acoustic and vibration signals contain distinctive patterns useful for detecting defects in machinery. A number of signal processing strategies have been proposed for detecting and quantifying incipient defects in gears. Nonintrusive measurement techniques like those based on laser Doppler vibrometry (LDV) and microphones need to be studied in order to help users in selecting the appropriate transducer according to the application. This article presents an experimental design to determine, as a novel contribution, the minimum detectable crack size in a geared system comparing three different transducers: a microphone, an accelerometer, and an LDV. The comparison intends to discriminate the three transducers with respect to its early detection capability. Experiments were conducted in a closed loop torque test rig for several torque levels and speeds. Experimental factorial design was used to determine the main effects and their interactions in the detection process. The well-known Hilbert and wavelet transforms have been used as signal processing technique. Their advantages in the detection of incipient defects are highlighted in this article. The results indicate that the acoustic signal stands out as the method that first detects an incipient progressive crack in gears (it detected 1.3-mm-long cracks), although, as a drawback, the results obtained using the microphone signal are more sensitive to speed and torque. The second place was for LDV with 1.8-mm crack detection, and the third place for the accelerometer with 2.3-mm crack detection.

Prediction of NOx Emissions and Fuel Consumption of a City Bus under Real Operating Conditions by Means of Biharmonic Maps

AbstractThe prediction of pollutant emissions and fuel consumption under real operating conditions of any motor vehicle requires the use of complex mathematical models and experimental tools. In the present research, biharmonic maps (BM) were used to predict NOx (nitrogen oxides) emissions and relative fuel–air ratio (Fr) of a passenger city bus. For the collection of experimental data, an instrumented city bus was tested during real passenger transportation. The data were classified into four dynamic sequences: acceleration, idling, deceleration with fuel consumption, and deceleration without fuel consumption. Among them, the acceleration sequence was selected due to high NOx emissions and high fuel consumption. Experimental results were in good agreement with BM predictions. Significant parameters for predicting NOx concentration were vehicle velocity and relative fuel–air ratio (Fr). While for predicting Fr, significant parameters were the exhaust gas flow (EGF) rate, vehicle velocity, and NOx concentr...