Study on Remote Control and Fault Diagnosis for Ultrahigh Speed Grinding

Remote control and fault diagnosis of ultrahigh speeding grinding is studied, which is based on the theory of rough set. Knowledge acquisition and reduction rule of fault diagnosis, realization method of remote control for ultrahigh speed grinding are studied, diagnosis model is established. Based on the theoretical research and ultrahigh speed grinder with a linear speed of 250 m/s, the remote control and fault diagnosis system of ultrahigh speed grinding is developed. Results of the system running show that the environment is improved, the mental pressure of workers is relieved and the efficiency is improved. At the same time, it proves that the ability to diagnosis and the accuracy of diagnosis for the ultrahigh speed grinding are improved and the time for diagnosis is shortened by applying rough set. Introduction Ultrahigh speed grinding is an efficient cutting method for metal materials by grinding wheel spindle rotating with a very high speed. At present, ultrahigh speed grinding refers to that the linear speed of grinding wheel is more than 150 m/s [1]. Ultrahigh speed grinder whose structure is complicated, is a kind of mechanical product which is highly integrated with machine, electricity and hydraulic pressure. So, the fault rate is higher and the fault cause is more. When a fault appears the diagnosis is very difficult. In addition, the noise is bigger and danger is higher, compared with the ordinary grinding. For mentioned problem in the process of ultrahigh speed grinding, the remote control and diagnosis for ultrahigh speed grinding is studied in this paper. RS (Rough set, RS) is a theory of analyzing mathematics that is developed in 1982 by Z. Pawlak, a polish mathematician[2,3]. The theory that is a new kind mathematical treatment which can process uncertain and vague information, incomplete system, and is more widely used as a kind inductive learning method, and widely used in mashinelearning, pattern-recognition, expert system, conflict analysis etc [4, 5]. Rough Set Theory Given an information system S= (U, A, V), U is the nonempty finite object sets of S, called universe; any subset U X ⊂ , is called a concept in U, and any cluster in U, is called knowledge of U; A represents the attribute sets, which is divided into conditional attributes C and decision making attributes D; V is a set of values of A. Indiscernibility Relation. Any attribute set U R ⊆ , indiscernibility relation is defined as: { } R a ) a , y ( f ) a , x ( f : U y , x Ind(R) ∈ ∀ = ⊆ = (1) If ) R ( Ind y) , (x ∈ , then x, y are called indiscernibility relation relative to R , which is equivalence on U actually. Key Engineering Materials Vols. 359-360 (2008) pp 518-522 online at http://www.scientific.net © (2008) Trans Tech Publications, Switzerland Online available since 2007/Nov/20 All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of the publisher: Trans Tech Publications Ltd, Switzerland, www.ttp.net. (ID: 130.203.133.34-14/04/08,13:05:52) Attribute Dependence and Approximation Accuracy. Any object subset U X ⊆ and attribute subset C R ⊆ , upper approximation and lower approximation of R is : X} Y : (R) U/Ind ∈ {Y ∪ = R_(X) ⊆ (2) } ≠ X ∩ Y : (R) U/Ind ∈ {Y ∪ = (X) R ∅ (3) If (X) R R_(X) = , X is definable set of R; if (X) R ≠ R_(X) , X is rough set of R . Attribute Dependence. Attribute set R, P subset of C, then the dependence of R relative to P: ) R))/Card(U Card(Posp( kp(R) = (4) R)) Card(Posp( , Card(U) represent radix of set, Posp(R) is positive field of attribute P in U/Ind(R) . Reduction and Core Attribute Set. If attribute R r∈ , ∃ (D) POS (D) POS {r} R R = , we call attribute r relative to R indispensable, or we call it superfluous. If each attribute in R is indispensable, when R is satisfied with the following conditions: Ind(C) Ind(R) = and Ind(C) (r)) Ind(R R r ≠ ⊇ ∀ (5) We call R reduction attribute set, which is represented Red(C) . The intersection of all reduction attribute sets C is called the core attribute set, which is represented Core(C) , and Core(C) ∩ Core(C) = . Remote Fault Diagnosis of Ultrahigh Speed Grinding Fault Analysis of Ultrahigh Speed Grinding. At present, wheel spindle of ultrahigh speed grinder mostly applies hydrostatic and dynamic bearing to support it so that its structure is complicated, the pressure of the whole system is bigger andfault rate of it is higher. So, it is major researh object in this paper. Fig.1 is ultrahigh speed grinder with a linear speed of 250 mm/s that is developed independently by our laboratory. Mainfault phenomenon in the process of ultrahigh speed grinding are that wheel spindle can’t upfloat entirelly because of underpressure of hydrostatic and dynamic bearing so that wheel spindle is forced to move or is hydraulic lock, hydrostatic and dynamic bearing leakst; Tool high pressure of hydrostatic and dynamic bearing leads to stirring motion and oil temperature rising of wheel spindle; First filter is blocked up so that oil pump is exhausted, the whole system can’t reach rated working pressure; the spool of relief valve is hydraulic lock so that the pressure of the system rises; the accumulator pressure destabilization leads to the pressure fluctuation of the system; pressure switchfault causes the main motor out of control. Operating mode information of ultrahigh speed grinding machine which is got through detection, such as oil temperature, pressure and drain of hydrostatic and dynamic bearing on wheel spindle; bearing capacity, amplitude and noise of spindle; main motor’s and oil pump motor’s temperature; outlet pressure, rate of discharge, return pressure and oil reurn discharge of high-pressure oil pump, outlet pressure of relif valve, outlet pressure of acculator, tank temperature and liquid level etc characteristic parameter values, we can identify status of ultrahigh speed grinder, which is possiblefaults and their causes of ultrahigh speed grinder. Remote Fault Diagnosis of Ultrahigh Speed Grinding. Thefault diagnosis process of ultrahigh speed grinding based on RS is shown as Fig. 2. After the data field collected are preprocessed, they are input into the field computer, then they are transmitted to the remotefault diagnosis and control computer. Firstly, they are discretized to compose of decision table in the remote fault diagnosis and control computer, then the decision table is reduced to derive fault symptom and corresponding Key Engineering Materials Vols. 359-360 519