Agusmian Partogi Ompusunggu

Kalman-Filtering-Based Prognostics for Automatic Transmission Clutches

Demands of low-cost prognostics tool for automatic transmission clutches (i.e., based on measurement data from sensors typically available) by industry have increased since the last few years. In this paper, a prognostics tool is developed by fusing a newly developed degradation model with the measurable pre-lockup feature under the extended Kalman filtering framework. As this feature can be extracted from sensory data typically available in wet clutch applications, the developed prognostics tool, hence, does not require extra cost for any additional sensor. New history data of commercially available wet clutches obtained from accelerated life tests using a fully instrumented SAE#2 test setup have been acquired and processed. The experimental results show that the prognostics algorithm developed in this paper outperforms the early developed prognostics algorithm, which is based on the weighted mean slope method (i.e., data-driven approach). It is shown that the clutch remaining useful life estimations with the novel prognostics algorithm remain in the desired accuracy region of 20% with relatively small uncertainty interval in comparison with the early developed prognostics algorithm.

Influence of adhesive wear and thermal degradation on the frictional characteristics of paper-based friction materials: A comparative study

This paper discusses the effects of adhesive wear and thermal degradation on the dry frictional characteristics of paper-based friction materials against steel material. Some commercial paper-based friction materials typically used for clutch applications were subjected to adhesive wear and thermal degradation and the dry frictional characteristics were then measured at different states on a rotational tribometer. The experimental results reveal that both adhesive wear and thermal degradation have opposite effects on the frictional characteristics, where the static and kinetic coefficients of friction increase due to adhesive wear but decrease due to thermal degradation.

Engagement behavior of degrading wet friction clutches

This paper presents modeling, simulation and experimental validation of the friction material degradation effects on the dynamic engagement behavior of a wet friction clutch system. The clutch system is modeled as a 3 DOF lumped-mass-spring-damper incorporating an extension of the Generalized Maxwell Slip (GMS) friction model. The effects of the dynamic sliding velocity (relative velocity between the input and output shafts) and changing normal load are taken into account in the friction model. As the degradation progresses, the Stribeck-function parameters and the tangential contact stiffness change, so affecting the friction characteristics. These parameters are then used in the simulations to investigate their effects on the engagement behavior of the clutch. The simulation results show that the sliding velocity profile and the post-lockup torsional vibration response change. Furthermore, in order to verify and validate the simulation results, the experimental data obtained from accelerated lifetime tests, carried out on two different paper-based wet friction clutches using a fully instrumented SAE#2 test setup, are analyzed and discussed. The experimental results show qualitative agreement with the simulation results.

Condition-based maintenance for OEM’s by application of data mining and prediction techniques

Increasing the products service life and reducing the number of service visits are becoming more and more top priorities for Original Equipment Manufacturer companies (OEM’s). Condition-based maintenance is often proposed as a solution to reach this goal. However, this latter, is often hampered by the lack of the right information that gives a good indication of the health of the equipment. Furthermore, the processing power needed to compute this information is often not afforded by machine’s processor. In this paper, a remote platform which connects the OEM’s to the customer’s premises is described, allowing thus a local computation of available information. Two approaches are then combined to process the optimal maintenance time. First, data mining techniques and reliability estimation are applied to historical databases of machines running in the field in order to extract the relevant features together with their associated thresholds. Second, prediction algorithm is applied to the selected features in order to estimate the optimal time to preventively perform a maintenance action. The proposed method has been applied to a database of more than 2000 copy machines running in the field and proved to identify easily the relevant features to be forecasted and to offer an accurate prediction of the maintenance action.

Friction Behavior of a Wet Clutch Subjected to Accelerated Degradation

This study aims at experimentally investigating the sliding friction characteristics of a wet clutch during its lifetime. More precisely, the objective is to understand how the Stribeck and the frictional lag (i.e, sliding hysteresis) parameters evolve as the clutch degradation progresses. For this purpose, a novel test procedure has been proposed and a set of experiments has been carried out on a fully assembled (commercial) clutch using a modified SAE#2 test setup. Furthermore, a systematic methodology for the Stribeck and the frictional lag parameters identification is developed. Regardless of the applied pressure, it appears that the first three identified Stribeck parameters tend to decrease with the progression of the degradation, while the last parameter tends to increase. In regard to the frictional lag parameter, the trend shows pressure dependency.

On improving low-cost IMU performance for online trajectory estimation

We have developed an automatic mitigation method for compensating drifts occurring in low-cost Inertial Measurement Units (IMU), using MEMS (Microelectromechanical systems) accelerometers and gyros, and applied the method for online trajectory estimation of a moving robot arm. The method is based on an automatic detection of system’s states which triggers an online (i.e. automatic) recalibration of the sensors parameters. Stationary tests have proven an absolute reduction of drift, mainly due to random walk noise at ambient conditions, up to ~50% by using the recalibrated sensor parameters instead of using the nominal parameters obtained from sensor’s datasheet. The proposed calibration methodology works online without needing manual interventions and adaptively compensates drifts under different working conditions. Notably, the proposed method requires neither any information from an aiding sensor nor a priori knowledge about system’s model and/or constraints. It is experimentally shown in this paper that the method improves online trajectory estimations of the robot using a low-cost IMU consisting of MEMS-based accelerometer and gyroscope. Applications of the proposed method cover automotive, machinery and robotics industries.

Motion blur characterization and compensation for line scan (1D) cameras

Line sensors (1D) are often used for quality monitoring of moving objects in industrial environments. They are, for instance, used to derive dimensional and geometrical information of moving objects or products. Their high sampling rate makes them well suited for retrieving information of fast moving objects. However, in fast motion the 1D sensor, as any other kind of image sensor, introduces artefacts commonly referred to as motion blur. In this paper, we discuss (1D) sensor motion blur and methods to compensate for it. An experimental set-up and a simulation tool have been developed to characterize motion blur of (1D) sensors. Once properly characterized, a deblurring algorithm (based on a non-blind deconvolution method) has been developed to reconstruct a deblurred image. The results are validated using experimental data collected from a vibrating string. Comparison between dimensional feature measurements of the vibrating string, without and with deblurring methods are illustrated. The analysis shows that a decrease by a factor of two on the measurement variance can be achieved by applying the proposed deblurring method.

Adaptive Transient Event Detection for Industrial Applications

Foreign elements may destroy sensitive parts of mobile industrial machines such as harvesters. When such undesired transient events shall be detected, varying machine noise scenarios demand adaptive algorithms that allow for a robust detection performance. Moreover, a detection system that is too responsive reduces the machine’s speed of operation. We have evaluated three algorithms that are capable of detecting transient events, and that allow for timely precautionary measures. Two of the methods apply a fixed and adaptive threshold to the short-time energies of the high-pass filtered sensor signal, respectively, while a new method employs linear prediction-based filtering and an adaptive frame-energy threshold, and incorporates the variance of the high-frequency frame content enabling the distinction between events resulting from foreign elements and events originated by the machine. The algorithms were applied to four types of transient events that were combined with a set of machine noise recordings at different signal-to-noise-ratio (SNR) levels. Our results show that the new method provides 95 % correct detections down to a SNR of −1 dB, and that all methods provide a very low rate of misdetected events.

Theoretical and Experimental Contact Stiffness Characterisation of Nominally Flat Surfaces

In this study the tangential contact stiffness between two elastic bodies having nominally flat surfaces with different material combinations is investigated. The tangential contact stiffness between these two elastic bodies is first calculated based on the Greenwood-Williamson-McCool contact theory. Then, the tangential contact stiffness is determined by experimental investigation on a tribometer under the effect of different values of normal load and tangential displacement amplitude. The tangential contact stiffnesses obtained from the experimental data show a good agreement with the theoretical results, where the trends are similar and they are in the same order of magnitude.