CN106354955A - Sliding bearing rigidity recognition method based on mill vibration mode parameters - Google Patents

Abstract

The invention discloses a sliding bearing rigidity recognition method based on mill vibration mode parameters. The method comprises the specific steps of 1, building a mill full finite element model; 2, designing a testing scheme; 3, utilizing operational modal analysis for recognizing modal parameters; 4, calculating a modal confidence factor analysis correlation; 5, selecting and calculating a modal confidence factor larger than 0.7, and adopting an axial rigid body modal, a radial rigid body modal and the like as main modals to be recognized; 6, selecting sliding bearing rigidity as parameters to be recognized; 7, constructing a target function; 8, performing iterative optimization, wherein the overall calculation efficiency and model precision of a mill can be improved through the recognition method, so that the model is closer to the actual structure, and due to accurate oil film rigidity recognition, later model-based response calculation, prediction and damage recognition are promoted.

Description

A kind of sliding bearing rigidity recognition methodss based on grinding machine Vibrating modal parameters

Technical field

The invention belongs to systematic parameter identifies field, particularly a kind of sliding bearing based on grinding machine Vibrating modal parameters is firm Degree recognition methodss.

Background technology

For grinder system, the oil film rigidity of base bearing is the important of the modeling of grinding machine integral power and response analyses Parameter.What it reacted is the ability of the anti-load variations of oil film, is the rate of change of bearing capacity relative displacement, its carrying with bearing Ability and oil film thickness are relevant.Currently for grinding machine dynamic and static pressure base bearing rigidity research all concentrate on excellent by oil recess structure Change and improve on bearing load carrying capacity, and the method adopting fluid calculation mechanics more.Such method calculates stream by numerical simulation Field pressure distribution, thus derive calculation bearing bearing capacity and oil film rigidity, need to be special in view of oil pocket pressure, temperature, lubricating oil Property etc. factor impact, have calculating loaded down with trivial details, impact simulation process deficiency.

But in the case of complete oil film, lubricating oil film can be substituted with multiple rows of equivalent spring unit, such that it is able to knowing Other oil film bearingses rigidity is converted into identification equivalent unit rigidity value, accelerates calculation procedure, is easy to emulate.But, in grinding machine Find in early stage process of calculation analysis, different rigidity valued combinations affect larger on FEM modal analysis and modal.Therefore, how accurately Identification base bearing oil film rigidity, is always this area for the RESPONSE CALCULATION based on model for the later stage, prediction and non-destructive tests and waits to solve Technical barrier certainly.

Content of the invention

The present invention is directed to the deficiencies in the prior art, discloses a kind of sliding bearing rigidity based on grinding machine Vibrating modal parameters Recognition methodss, it is possible to increase grinding machine overall calculation efficiency and be conducive to the RESPONSE CALCULATION based on model for the later stage, prediction and damage Identification.

The invention discloses a kind of sliding bearing rigidity recognition methodss based on grinding machine Vibrating modal parameters, specific step As follows:

1) set up grinding machine global finite element model, in finite element software, oil film be reduced to multiple rows of equivalent spring unit, This unit has tangential, axially three directions rigidity values under corresponding cylindrical coordinatess, and oil film is reduced to multiple rows of equivalent spring unit Such that it is able to identification oil film bearingses rigidity is converted into identification equivalent unit rigidity value

2) design experiment scheme: record grinding machine vibration signal with acceleration transducer, input a signal into oros data Acquisition Instrument, finally reaches computer and records；

3) Modal Parameter Identification, using the method for operational modal analysis (operationalmodal analysis, oma) Experimental result is identified, processes, the time-domain signal of gained is converted to frequency-region signal, recycle oma method identification grinding machine Primary modal parameter, can get frequency, the vibration shape and the damping ratios of each order mode state；

4) analysed for relevance: calculate Kind of Modal Confidence Factor, i.e. the dependency of analysis finite element model and the Modal Test vibration shape, Shown in computing formula such as formula (1):

${\mathrm{mac}}_{i,j}=\frac{|{\left(\right\{{\mathrm{\φ}}_i^e\left\}\right)}^t\left(\right\{{\mathrm{\φ}}_j^s\left\}\right){|}^2}{{\left(\right\{{\mathrm{\φ}}_i^e\left\}\right)}^t\left(\right\{{\mathrm{\φ}}_i^s\left\}\right){\left(\right\{{\mathrm{\φ}}_j^e\left\}\right)}^t\left(\right\{{\mathrm{\φ}}_j^s\left\}\right)}---\left(1\right)$

In formulaRepresent the i-th first order mode of test model and the jth first order mode of computation model respectively；

5) choose mode to be identified；According to the correlativity calculation result in step (4), select wherein mac value more than 0.7 with And axial direction rigid body mode, radial direction rigid body mode etc. are as main mode to be identified；

6) choose parameter to be identified: choose sliding bearing rigidity as parameter to be identified；

7) build object function: on the basis of the mode of actual measurement, including the frequency surveyed and the vibration shape, with model frequency Residual error is as target；

8) iteration optimization: with the increase of iterationses, when target function value tends towards stability or be constant, then show to calculate Result restrains, and now parameter value is the end value after identification, and target function value also tends to minimum；If cannot restrain, adjust Parameter value, carries out the modal calculation of model, specifically arranges step-length, step number, again selection initial value；Identifying purpose is exactly logical Cross adjustment simulation parameter, realize the minimum of emulation and test gap, each iteration, calculate mode under corresponding parameter value and Target function value.

Further, described step 1) in model assembly include basis, fixing end sliding bearing, free end sliding axle Hold, cylinder, gear wheel.

Further, described step 2) in acceleration transducer select pcb low frequency three-dimensional sensor.

The present invention having the beneficial effects that with respect to prior art:

1) by oil film is reduced to equivalent spring unit, improve grinding machine overall calculation efficiency；

2) selected and parameter technology of identification by Rational Parameters, improve model accuracy, make model closer to practical structures；

3) accurately the identification of oil film rigidity is conducive to the RESPONSE CALCULATION based on model for the later stage, prediction and non-destructive tests.

Brief description

Fig. 1 is the flow chart based on the sliding bearing rigidity recognition methodss of grinding machine Vibrating modal parameters for the present invention；

Fig. 2 is that the identification parameter based on the sliding bearing rigidity recognition methodss of grinding machine Vibrating modal parameters for the present invention is restrained Figure；

Fig. 3 is that the object function based on the sliding bearing rigidity recognition methodss of grinding machine Vibrating modal parameters for the present invention is restrained Figure.

Specific embodiment

The ball mill of one φ 7.32 × 12.5m of utilization of the present invention, part include basis, fixing end sliding bearing, from By end sliding bearing, cylinder, gear wheel, the component units of its finite element comprise 86164 3d units, 15603 2d units, 660 bar units and 3805 dot elements；Specifically comprise the following steps that

1) set up grinding machine global finite element model and carry out modal calculation；Limited in msc.patran＆msc.nastran In meta software, oil film is reduced to multiple rows of equivalent spring unit, this unit has radial direction, tangential, axial direction three under corresponding cylindrical coordinatess The rigidity value in direction；

2) design experiment scheme；Record grinding machine vibration signal with pcb low frequency three-dimensional sensor, input a signal into oros Data collecting instrument, finally reaches computer and records；The determination of point position and measurement direction refers to required Mode Shape. Record the mode at fixing end base bearing, transducer arrangements on four angle points of fixing end base bearing, each measuring point direction Unanimously, to corresponding to grinding machine axially, y is to corresponding grinding machine radially for sensor x.

3) only respond due in test, do not encourage, so the recognition methodss from operational modal Parameter analysis (oma) Carry out modal idenlification；Result of the test is processed, the time-domain signal of gained is converted to frequency-region signal, recycle oma method Identification grinding machine primary modal parameter, can get frequency, the vibration shape and the damping ratios of each order mode state.Here by change grinding machine mould Simulating realistic model, the first row in table 1 is simulates the calculated frequency values of realistic model to the equivalent spring rigidity of type.

4) analysed for relevance；Calculate Kind of Modal Confidence Factor, i.e. the dependency of analysis finite element model and the Modal Test vibration shape, Shown in computing formula such as formula (1), whereinRepresent the i-th first order mode of test model and the jth rank of computation model respectively The vibration shape.Before correction, FEM (finite element) model and the modal data of mode selected by Model Measured and error are as shown in table 1 it can be seen that mac Value, all close to 1, illustrates the good relationship of the vibration shape, but each order frequency all has certain frequency error, wherein radial direction rigid body Model frequency error is larger；

Table 1 identifies front modal data and error

The vibration shape	Test frequency (hz)	Finite element frequency (hz)	Error (%)	mac
					Axial rigid body	2.5592	2.4359	4.80	0.9965
Radial direction rigid body	2.9153	2.7415	5.96	0.9998
					Swing around z-axis	10.706	10.606	0.93	0.9997
Swing around y-axis	12.200	12.190	0.08	0.9997
					Swing around x-axis	12.953	12.835	0.91	0.9997

5) choose mode to be identified；According to the correlativity calculation result in step (4), the wherein axial rigid body mode of selection, Radial direction rigid body mode and around x, y, z swing three order mode states as main positive-norm state to be repaired, its mac value be both greater than 0.7；

6) choose corrected parameter: choose sliding bearing rigidity as parameter to be modified；

7) build object function: on the basis of the mode of actual measurement, including the frequency surveyed and the vibration shape, with each order mode state Frequency residual error is as correction target；

8) iteration optimization；Choosing equivalent unit axial rigidity and radial rigidity value is corrected parameter, chooses the mode in table 1 The frequency error of the vibration shape is as identification target.Here, take 1.3 times that oil film rigidity initial value is simulation value, i.e. 18000n/mm, Under the premise of normalization, arrange parameter excursion is 0.8 to 1.5 times of initial value.Iteration step length is 0.01, and iterative steps are 100 steps, are iterated calculating；Parameter convergence graph in identification process as shown in Fig. 2 object function with iterationses change such as Shown in Fig. 3.It can be seen that with the increase of iterationses, the value of object function is gradually reduced and tends towards stability, error Value tends to 0, and the value of oil film rigidity also fluctuates in a small range, tends to be steady, the final axial rigidity value obtaining sliding bearing exists Fluctuate between 14945n/mm and 15060n/mm, radial rigidity value is 1500n/mm.

Claims (3)

1. a kind of sliding bearing rigidity recognition methodss based on grinding machine Vibrating modal parameters are it is characterised in that specifically comprise the following steps that

1) set up grinding machine global finite element model, in finite element software, oil film is reduced to multiple rows of equivalent spring unit, this is single Unit has tangential, axially three directions rigidity values under corresponding cylindrical coordinatess；

2) design experiment scheme: record grinding machine vibration signal with acceleration transducer, input a signal into oros data acquisition Instrument, finally reaches computer and records；

3) Modal Parameter Identification: utilize operational modal analysis, i.e. operationalmodal analysis, the method for oma is to examination Test result to be identified, process, the time-domain signal of gained is converted to frequency-region signal, recycle oma method identification grinding machine main Modal parameter, can get frequency, the vibration shape and the damping ratios of each order mode state；

4) analysed for relevance: calculate Kind of Modal Confidence Factor, i.e. modalassurance criterion, mac analysis finite element mould Type and the dependency of the Modal Test vibration shape, shown in computing formula such as formula (1):

${\mathrm{mac}}_{ij}=\frac{|{\left(\right\{{\mathrm{\φ}}_i^e\left\}\right)}^t\left(\right\{{\mathrm{\φ}}_j^s\left\}\right){|}^2}{{\left(\right\{{\mathrm{\φ}}_i^e\left\}\right)}^t\left(\right\{{\mathrm{\φ}}_i^s\left\}\right){\left(\right\{{\mathrm{\φ}}_j^e\left\}\right)}^t\left(\right\{{\mathrm{\φ}}_j^s\left\}\right)}---\left(1\right)$

In formulaRepresent the i-th first order mode of test model and the jth first order mode of computation model respectively；

5) choose mode to be identified；According to the correlativity calculation result in step (4), wherein mac value is selected to be more than 0.7 and axle To rigid body mode, radial direction rigid body mode etc. as main mode to be identified；

6) choose identification parameter: choose sliding bearing rigidity as parameter to be identified；

7) build object function: on the basis of the mode of actual measurement, including the frequency surveyed and the vibration shape, with model frequency residual error As object function；

8) iteration optimization: with the result of experimental test as standard, be iterated calculating, finally for the purpose of target function value minimum Can get the rigidity value of sliding bearing；If cannot restrain, adjusting parameter value, re-start the modal calculation of model.

2. the sliding bearing rigidity recognition methodss based on grinding machine Vibrating modal parameters according to claim 1, its feature exists In described step 1) in model assembly include basis, sliding bearing, cylinder, gear wheel.

3. the sliding bearing rigidity recognition methodss based on grinding machine Vibrating modal parameters according to claim 1, its feature Be, described step 2) in acceleration transducer select pcb low frequency three-dimensional sensor.