Browsing by Subject "backlash"

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Access status: Open Access ,
Identification of a backlash using the modelling function method
(Wydawnictwa AGH, 2005) Szmidt, Artur; Gierulski, Wacław
The physical value of a backlash in a kinematic pair of a mechanical system can be determined using a number of methods; still the problem is considered to be difficult. The identification may involve employing a modelling function, which allows also finding out about other properties of a given mechanical system. A modelling function constitutes a mathematical model for the relationship between the solids-joints interaction and the relative displacement and the relative velocity of the solids. This study aims at identifying a backlash by means of one-dimensional modelling functions that do not take account of velocity. The functions depend on the parameters determined during the identification process. Their values result from the similarity of signals being a response of the analysed real system and its mathematical model (i.e. its modelling function). The method does not require selecting signals; any signal representing the actual operation of the system will be applicable. Signals are analysed over a time period. A special form of the modelling function should permit determining the values of the searched parameters, i.e. the backlash.
Access status: Open Access ,
The use of evolution algorithms for identification of transmission backlash
(2011) Korbel, Krzysztof; Zygmunt, Henryk
Mechanical propulsion system including, inter alia, an electric motor, shaft and transmission is characterized by certain parameters whose values cannot be calculated using mathematical methods (transmission backlash) or may vary during operation time. Such parameters have to be known to ensure proper operation of the system. In this article a method for identification of these parameters is described. The method is based on an evolution algorithm. This algorithm utilizes natural selection methods and natural transformation processes within a population, similar to those in animal world. The least-fit individuals are rejected by applying the fitness function. The population will improve, and in infinite time it will be perfect. That means that the perfect solution can be attained in a very long time. This time can be shortened by defining the termination criteria, e.g. the identification can be stopped if one of the population individuals has a very low error. Such identification requires a transition function (model), as well as reference measurement made on a real system.