CN104792459A - Rotor dynamic balance variable step size optimizing method based on fuzzy control - Google Patents

Rotor dynamic balance variable step size optimizing method based on fuzzy control Download PDF

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Publication number
CN104792459A
CN104792459A CN201510130898.9A CN201510130898A CN104792459A CN 104792459 A CN104792459 A CN 104792459A CN 201510130898 A CN201510130898 A CN 201510130898A CN 104792459 A CN104792459 A CN 104792459A
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China
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trimf
length
fuzzy
rotor dynamic
amplitude excursion
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CN201510130898.9A
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Chinese (zh)
Inventor
徐娟
张建军
魏振春
张利
陈时桢
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Hefei University of Technology
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Hefei University of Technology
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Abstract

The invention discloses a rotor dynamic balance variable step size optimizing method based on fuzzy control and particularly relates to the rotor dynamic balance variable step size optimizing method based on the fuzzy control. A step size is calculated by using a fuzzy control principle and the step size is adjusted according to a position feedback signal; a step size optimizing control policy is combined to finish rotor dynamic balance. Compared with a traditional influence coefficient method and an improved influence coefficient method, a lot of matrix solutions are saved, the greater errors which are possibly generated in a calculation process are avoided, and the rotor dynamic balance precision is improved; compared with a traditional automatic optimizing method, the method has higher efficiency of improving the dynamic balance and has a wide applicable range; the computer control is easy to realize and the rotor dynamic balance variable step size optimizing method has a good actual application value.

Description

Based on the rotor dynamic balancing varied step optimization method of fuzzy control
Technical field
The present invention relates to Fault Diagnosis of Rotating Equipment Based and control method field, specifically a kind of rotor dynamic balancing varied step optimization method based on fuzzy control.
Background technology
At present, rotating machinery is widely used in the various aspects of industry, and because rotor unbalance reason makes rotating machinery produce vibration, serious may damage machinery, causes loss unnecessary in engineering.In order to reduce these unnecessary losses, reduce the vibration of rotor, must to balancing rotor.
Method at present for rotor dynamic balancing has influence coefficient method, Mode analysis method, and automatic seeking is excellent.Wherein the influence coefficient method of influence coefficient method and improvement has equilibrium rate faster, but its computation process may produce comparatively big error, and easily produces vibration aggravation, and control accuracy is not high.Because the principle of automatic optimal strategy is simple, without the need to founding mathematical models, and the advantage such as easily to be automated, be widely used in rotor dynamic balancing, but its balance efficiency is relatively low, so also need further improvement, because fuzzy control has stronger robustness and dirigibility is higher, itself and automatic optimal strategy are combined and realizes varied step optimization, good control effects can be reached.
Summary of the invention
The object of this invention is to provide a kind of rotor dynamic balancing varied step optimization method based on fuzzy control, long to overcome traditional automatic optimizing method equilibration time, the defect that balance quality is not high.
In order to achieve the above object, the technical solution adopted in the present invention is:
Based on the rotor dynamic balancing varied step optimization method of fuzzy control, it is characterized in that: utilize fuzzy controller material calculation, and adjust this step-length according to position feed back signal, realize rotor dynamic balancing varied step optimization control strategy, comprise the following steps:
(1), using amplitude excursion and amplitude excursion variable quantity as fuzzy controller input quantity;
(2), to fuzzy controller input quantity carry out stepping and set membership function: the domain of amplitude excursion as [-26 ,+26], points 7 grades NB, NM, NS, ZO, PS, PM, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter
NB Trimf [-26-20-14]
NM Trimf [-17-11-5]
NS Trimf [-10-50]
ZO Trimf [-303]
PS Trimf [0510]
PM Trimf [51117]
PB Trimf [142026]
The domain of amplitude excursion variable quantity is [-2.2 ,+2.2], points 5 grades NB, NS, ZO, PS, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter
NB Trimf [-2.2-1.5-0.8]
NS Trimf [-1.2-0.60]
ZO Trimf [-0.400.4]
PS Trimf [00.61.2]
PB Trimf [0.81.52.2]
(3), with presetting step-length λ 1as fuzzy controller output quantity, stepping is carried out to it and sets membership function: presetting step-length λ 1domain be [-15 ,+15], points 7 grades NB, NM, NS, ZO, PS, PM, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter
NB Trimf [-18-14-10]
NM Trimf [-12-8-4]
NS Trimf [-8-40]
ZO Trimf [-404]
PS Trimf [048]
PM Trimf [4812]
PB Trimf [101418]
(4) control rule table, setting up fuzzy controller is as follows to determine the fuzzy set of output quantity:
(5), ambiguity solution operation, by gained output quantity degree of membership and its correspondence theory thresholding sum of products divided by degree of membership sum, acquired results is the accurate output quantity of fuzzy controller, i.e. presetting step-length λ 1.
The described rotor dynamic balancing varied step optimization method based on fuzzy control, is characterized in that: described step (5) obtains step-length λ 1after, it can be used as a controlled quentity controlled variable of implementation controller; Implementation controller adopts varied step optimization strategy, process following steps:
(6) two direction of motor rotation, are set identical;
(7), presetting step-length λ is obtained 1, and judge amplitude excursion variable quantity, if amplitude excursion variable quantity is less than 0, then repeat step 6 to step 9; If amplitude excursion variable quantity is greater than 0, carry out step 10;
(8), according to step length regulating method by presetting step-length λ 1be adjusted to λ 2;
(9), according to step-length λ 2drive motor rotates;
(10), change direction of motor rotation, make two direction of motor rotation contrary;
(11), presetting step-length λ is obtained 1, and judge amplitude excursion variable quantity, if amplitude excursion variable quantity is less than 0, then repeat step 10 to step 13; If amplitude excursion variable quantity is greater than 0, then terminate;
(12), according to step length regulating method by presetting step-length λ 1be adjusted to λ 2;
(13), according to step-length λ 2drive motor rotates.
The described rotor dynamic balancing varied step optimization method based on fuzzy control, is characterized in that: the step length regulating method following steps of described step 8 and step 12:
(14), by position transducer obtain single job front and rear angles changing value Δ θ, calculate actual step size last time, λ=k Δ θ, wherein coefficient k is determined by counterweight block structure and the parameter of electric machine;
(15), Δ λ=λ is calculated 2'-λ, wherein λ ' 2for last time adjusts step-length;
(16), λ is calculated 2=λ 1+ Δ λ, is the rear step-length of adjustment.
Compared with traditional automatic optimizing method, the present invention adopts variable step strategy, can the larger minimizing transient equilibrium time, improves balance efficiency.Adopt fuzzy controller to carry out material calculation, make system have good robustness and stability, add position feedback element in addition, improve dynamically balanced precision.
Accompanying drawing explanation
Fig. 1 is rotor dynamic balancing system construction drawing.
Fig. 2 is implementation controller operational flowchart.
Fig. 3 is vibration amplitude variation diagram.
Embodiment
The rotor dynamic balancing varied step optimization method based on fuzzy control adopting the present invention to propose below is specifically implemented the dynamic balance system that designed, designed is built, and the efficiency and applicability of the inventive method is described.
Rotor dynamic balancing system construction drawing as shown in Figure 1, topworks comprises drive motor and balancing weight; Control module comprises fuzzy controller and implementation controller; Vibration transducer is for obtaining amplitude, and position transducer is poor for obtaining balancing weight position angle.
For the dynamic balance system that designed, designed is built, rotor is directly driven through shaft coupling by motor, and rotating speed is 1800rpm, transient equilibrium desired value 8um, and initial unbalance is 25.3um.
According to the rotor dynamic balancing varied step optimization method based on fuzzy control, utilize fuzzy controller material calculation, and adjust this step-length according to position feed back signal, realize rotor dynamic balancing varied step optimization control strategy, mainly comprise the following steps:
Step 1, using amplitude excursion and amplitude excursion variable quantity as fuzzy controller input quantity, wherein amplitude excursion is the difference of actual amplitude and transient equilibrium desired value, and amplitude excursion variable quantity is drawn by amplitude excursion differentiate;
Step 2, stepping is carried out to fuzzy controller input quantity and sets membership function: the domain of amplitude excursion as [-26 ,+26], points 7 grades NB, NM, NS, ZO, PS, PM, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter
NB Trimf [-26-20-14]
NM Trimf [-17-11-5]
NS Trimf [-10-50]
ZO Trimf [-303]
PS Trimf [0510]
PM Trimf [51117]
PB Trimf [142026]
The domain of amplitude excursion variable quantity is [-2.2 ,+2.2], points 5 grades NB, NS, ZO, PS, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter
NB Trimf [-2.2-1.5-0.8]
NS Trimf [-1.2-0.60]
ZO Trimf [-0.400.4]
PS Trimf [00.61.2]
PB Trimf [0.81.52.2]
Step 3, with presetting step-length λ 1as fuzzy controller output quantity, stepping is carried out to it and sets membership function: presetting step-length λ 1domain be [-15 ,+15], points 7 grades NB, NM, NS, ZO, PS, PM, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter
NB Trimf [-18-14-10]
NM Trimf [-12-8-4]
NS Trimf [-8-40]
ZO Trimf [-404]
PS Trimf [048]
PM Trimf [4812]
PB Trimf [101418]
Step 4, the control rule table setting up fuzzy controller is as follows to determine the fuzzy set of output quantity:
Step 5, ambiguity solution operates, and by the domain value sum of products corresponding with it for gained output quantity degree of membership divided by degree of membership sum, acquired results is the accurate output of fuzzy controller, i.e. presetting step-length λ 1;
The above-mentioned rotor dynamic balancing varied step optimization method based on fuzzy control, is characterized in that: described step 5 obtains step-length λ 1after, it can be used as a controlled quentity controlled variable of implementation controller; Implementation controller adopts varied step optimization strategy, and its operating process as shown in Figure 2, comprises,
Step 6, sets two direction of motor rotation identical;
Step 7, obtains presetting step-length λ 1, and judge amplitude excursion variable quantity, if amplitude excursion variable quantity is less than 0, then repeat step 6 to step 9; If amplitude excursion variable quantity is greater than 0, carry out step 10;
Step 8, according to step length regulating method by presetting step-length λ 1be adjusted to λ 2;
Step 9, according to step-length λ 2drive motor rotates;
Step 10, changes direction of motor rotation, makes two direction of motor rotation contrary;
Step 11, obtains presetting step-length λ 1, and judge amplitude excursion variable quantity, if amplitude excursion variable quantity is less than 0, then repeat step 10 to step 13; If amplitude excursion variable quantity is greater than 0, then terminate;
Step 12, according to step length regulating method by presetting step-length λ 1be adjusted to λ 2;
Step 13, according to step-length λ 2drive motor rotates;
The above-mentioned rotor dynamic balancing varied step optimization method based on fuzzy control, is characterized in that: the step length regulating method of described step 8 and step 12 comprises,
Step 14, obtains single job front and rear angles changing value Δ θ by position transducer, calculates actual step size last time, λ=k Δ θ,
Wherein coefficient k is determined by counterweight block structure and the parameter of electric machine;
Step 15, calculates Δ λ=λ 2'-λ, wherein λ ' 2for last time adjusts step-length;
Step 16, calculates λ 2=λ 1+ Δ λ, is the rear step-length of adjustment.
Based on the implementation result of the rotor dynamic balancing varied step optimization method of fuzzy control
Fig. 3 is the vibration amplitude change curve carrying out rotor dynamic balancing process record according to the rotor dynamic balancing varied step optimization method based on fuzzy control, as can be seen from the figure within 12.5 second time, the uneven vibration caused drops to 7.8um from 25.3um, equilibrium rate is very fast, and equilibrium process does not vibrate aggravation, reach good counterbalance effect.This demonstrates validity of the present invention and accuracy.

Claims (3)

1. based on the rotor dynamic balancing varied step optimization method of fuzzy control, it is characterized in that: utilize fuzzy controller material calculation, and adjust this step-length according to position feed back signal, realize rotor dynamic balancing varied step optimization control strategy, comprise the following steps:
(1), using amplitude excursion and amplitude excursion variable quantity as fuzzy controller input quantity;
(2), to fuzzy controller input quantity carry out stepping and set membership function: the domain of amplitude excursion as [-26 ,+26], points 7 grades NB, NM, NS, ZO, PS, PM, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter NB Trimf [-26 -20 -14] NM Trimf [-17 -11 -5] NS Trimf [-10 -5 0] ZO Trimf [-3 0 3] PS Trimf [0 5 10] PM Trimf [5 11 17] PB Trimf [14 20 26]
The domain of amplitude excursion variable quantity is [-2.2 ,+2.2], points 5 grades NB, NS, ZO, PS, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter NB Trimf [-2.2 -1.5 -0.8] NS Trimf [-1.2 -0.6 0] ZO Trimf [-0.4 0 0.4] PS Trimf [0 0.6 1.2] PB Trimf [0.8 1.5 2.2]
(3), with presetting step-length λ 1as fuzzy controller output quantity, stepping is carried out to it and sets membership function: presetting step-length λ 1domain be [-15 ,+15], points 7 grades NB, NM, NS, ZO, PS, PM, PB}, its membership function is set as follows:
Fuzzy set Membership function Function parameter NB Trimf [-18 -14 -10] NM Trimf [-12 -8 -4] NS Trimf [-8 -4 0] ZO Trimf [-4 0 4] PS Trimf [0 4 8] PM Trimf [4 8 12] PB Trimf [10 14 18]
(4) control rule table, setting up fuzzy controller is as follows to determine the fuzzy set of output quantity:
(5), ambiguity solution operation, by gained output quantity degree of membership and its correspondence theory thresholding sum of products divided by degree of membership sum, acquired results is the accurate output quantity of fuzzy controller, i.e. presetting step-length λ 1.
2. the rotor dynamic balancing varied step optimization method based on fuzzy control according to claim 1, is characterized in that: described step (5) obtains step-length λ 1after, it can be used as a controlled quentity controlled variable of implementation controller; Implementation controller adopts varied step optimization strategy, process following steps:
(6) two direction of motor rotation, are set identical;
(7), presetting step-length λ is obtained 1, and judge amplitude excursion variable quantity, if amplitude excursion variable quantity is less than 0, then repeat step 6 to step 9; If amplitude excursion variable quantity is greater than 0, carry out step 10;
(8), according to step length regulating method by presetting step-length λ 1be adjusted to λ 2;
(9), according to step-length λ 2drive motor rotates;
(10), change direction of motor rotation, make two direction of motor rotation contrary;
(11), presetting step-length λ is obtained 1, and judge amplitude excursion variable quantity, if amplitude excursion variable quantity is less than 0, then repeat step 10 to step 13; If amplitude excursion variable quantity is greater than 0, then terminate;
(12), according to step length regulating method by presetting step-length λ 1be adjusted to λ 2;
(13), according to step-length λ 2drive motor rotates.
3. the rotor dynamic balancing varied step optimization method based on fuzzy control according to claim 2, is characterized in that: the step length regulating method following steps of described step 8 and step 12:
(14), by position transducer obtain single job front and rear angles changing value Δ θ, calculate actual step size last time, λ=k Δ θ, wherein coefficient k is determined by counterweight block structure and the parameter of electric machine;
(15), Δ λ=λ is calculated 2'-λ, wherein λ ' 2for last time adjusts step-length;
(16), λ is calculated 2=λ 1+ Δ λ, is the rear step-length of adjustment.
CN201510130898.9A 2015-03-24 2015-03-24 Rotor dynamic balance variable step size optimizing method based on fuzzy control Pending CN104792459A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106406100A (en) * 2016-11-23 2017-02-15 合肥工业大学 Rotor dynamic balancing control system based on fuzzy self-tuning single neure PID control and method thereof
CN109959486A (en) * 2019-03-11 2019-07-02 浙江大学 A kind of polar coordinates type grinding wheel on-line dynamic balancing system quick high accuracy balance method
CN114614730A (en) * 2022-05-12 2022-06-10 南昌航空大学 Magnetic bearing compensation control algorithm based on rotor unbalanced mass position online identification

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Publication number Priority date Publication date Assignee Title
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CN109959486A (en) * 2019-03-11 2019-07-02 浙江大学 A kind of polar coordinates type grinding wheel on-line dynamic balancing system quick high accuracy balance method
CN114614730A (en) * 2022-05-12 2022-06-10 南昌航空大学 Magnetic bearing compensation control algorithm based on rotor unbalanced mass position online identification

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