The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Traditional industrial robots have been widely used in automotive manufacturing for nearly 30 years. However, there have been very few attempts to automate mobile robotic systems for final assembly operations, despite their potential for high flexibility and capability. This paper focuses on methods of tracking a dynamic moving vehicle that is similar to the vehicle body on a moving assembly line...
Time based preventive maintenance not only helps in uncovering defects but also commencement of these defects resulting in defects mitigation. Time based preventive maintenance helps in identifying defects in track geometry and can prevent them happening in future. Such effective time based maintenance helps in identifying trends for track geometry. One such way for effective predictive condition...
Preventive maintenance finds the commencement of failure and helps them in mitigating them. It can also help in uncovering hidden failures. Preventive maintenance management can be used to determine defects in rail profile and prevent them happening in future. Such system helps in identifying trends for effective and efficient maintenance of rail profile. One such way is an in depth by information...
Track maintenance policies have traditionally been looked on as engineering led decisions. Maintenance actions have been typically based on use of exceedence thresholds each measurement is compared against a preset threshold such that if it exceeds the threshold then maintenance is done. This paper make two significant contribution one explaining various track geometry parameters in UK rail industry...
Time based track maintenance, in context of rail profile and track geometry, has conventionally been looked as engineering decisions. Current rail track maintenance activities are typically based on use of exceedence thresholds each measurement is compared against a pre-set threshold such that if it exceeds the threshold then maintenance is done on either of rail profile or track geometry. Time based...
Condition based monitoring system can be used to determine how and why there were defects in rail profile. Such system helps in identifying trends for effective and efficient condition monitoring of rail profile. One such way is an in depth by information analysis of rail profile parameters by correlation analysis thus finding significant correlations among various parameters of Rail Profile. Such...
To measure a vehiclepsilas lateral position relative to the lane of the road a low cost system can be developed to measure it. While operating the system during day and night it has the capability to track white or orange lines, solid or dashed edge lines. The system is comprised of two ldquooff the shelf ldquoblack and white charge coupled devices (CCD) video cameras along with commonly available...
The problem of detecting an anomaly (or abnormal event) is such that the distribution of observations is different before and after an unknown onset time, and the objective is to detect the change by statistically matching the observed pattern with that predicted by a model. In the context of asymmetric threats, the detection of an abnormal situation refers to the discovery of suspicious activities...
The probability hypothesis density (PHD) filter is a practical alternative to the optimal Bayesian multi-target Alter based on finite set statistics. It propagates the PHD function, a first-order moment of the full multi-target posterior density. The peaks of the PHD function give estimates of target states. However, the PHD filter keeps no record of target identities and hence does not produce track-valued...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.