CN109048082A - A kind of distance controlling method based on Kalman filtering - Google Patents
A kind of distance controlling method based on Kalman filtering Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
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- B23K—SOLDERING OR UNSOLDERING; WELDING; CLADDING OR PLATING BY SOLDERING OR WELDING; CUTTING BY APPLYING HEAT LOCALLY, e.g. FLAME CUTTING; WORKING BY LASER BEAM
- B23K26/00—Working by laser beam, e.g. welding, cutting or boring
- B23K26/70—Auxiliary operations or equipment
- B23K26/702—Auxiliary equipment
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Abstract
The present invention relates to laser cutting fields, more particularly to a kind of distance controlling method based on Kalman filtering, the distance controlling method is the following steps are included: be periodically sent out instruction, then obtain feedback signal, and Kalman filtering processing is carried out to feedback signal, obtain the estimated distance of Kalman filtering；Judge the stage locating for cutting head；According to the stage locating for the estimated distance of Kalman filtering and cutting head, parameter setting is completed, and carries out servo output.After obtaining the estimated distance of Kalman filtering, judge the stage locating for cutting head at this time, corresponding servo output is carried out again, Kalman filtering processing can remove the noise jamming that feedback signal is subject to, and different phase corresponds to different parameter output, it can more guarantee to stablize servo output, cutting head and plate surface are constantly in same certain height.
Description
Technical field
The present invention relates to laser cutting fields, and in particular to a kind of distance controlling method based on Kalman filtering.
Background technique
Planar laser cutting is a kind of noncontact procession, in whole process, do not need workpiece and cutter it
Between generate contact, transmitting light is focused by laser head, hot-working is carried out to workpiece surface.In this course, it removes
Except the adjustment of laser head focus, cutting head is also an important control amount at a distance from workpiece surface.
, usually will not be substantially flat for plate to be processed, and during cutting, it can be deformed,
Plate surface height is caused to rise and fall.It is maintained at plate surface focusing in order to guarantee to emit optical focus, then needs to allow cutting head whole
One is kept with plate surface in a process specifically apart from constant, therefore the Z axis where cutting head is needed according to cutting
Head is adjusted with the feedback of plate surface distance, here it is in laser cutting apart from servo antrol.
The principle of distance controlling is to be adjusted in real time by the feedback of the equidistant sensor of voltage to adjust the distance.Tradition
Way be by pid algorithm, the error adjusted the distance carries out dynamic compensation, and this method is when feedback signal is more stable
It waits, there is preferable dynamic property, and being capable of fast and stable.But in actual process, the feedback letter of sensor
It number will receive a large amount of interference, will lead to the distorted signals of feedback.In addition to this, since the processing speed of sample devices is lower than fortune
The communication cycle of movement controller, the signal that will lead to sampling generate certain delay.If this, carried out using traditional pid algorithm
It adjusts, the concussion that will lead in movement is very violent, is unable to satisfy the demand of practical application.
Summary of the invention
The technical problem to be solved in the present invention is that in view of the above drawbacks of the prior art, providing a kind of based on Kalman
The distance controlling method of filtering solves the problems, such as that cutting head and plate surface are not able to maintain specific range.
To solve this technical problem, the present invention provides a kind of distance controlling method based on Kalman filtering, the distance
Control method the following steps are included:
It is periodically sent out instruction, then obtains feedback signal, and Kalman filtering processing is carried out to feedback signal, obtains karr
The estimated distance of graceful filtering；
Judge the stage locating for cutting head；
According to the stage locating for the estimated distance of Kalman filtering and cutting head, parameter setting is completed, and it is defeated to carry out servo
Out.
Wherein, preferred version is that the distance controlling method is further comprising the steps of: state machine obtains cutting head and workpiece
The distance of cut surface judges the stage locating for cutting head.
Wherein, preferred version is that the stage locating for the cutting head includes four-stage, respectively close to stage, adjustment rank
Section, flexible adjusting stage and fast reaction stage；When the distance reaches adjusting range, to approach the stage；When the distance
It is the adjusting stage when in adjusting range；When the distance is close to target range, for the flexible adjusting stage；When the distance
It is the fast reaction stage when less than target range.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
Acceleration, calculating speed and displacement are obtained according to the estimated distance of Kalman filtering, if being in close to rank
Section, acceleration are constant；If being in the adjusting stage, acceleration is constant；If in the flexible adjusting stage, acceleration is set as three points
One of times acceleration；If being in the fast reaction stage, acceleration is set as three times acceleration.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
The Prediction distance of Kalman filtering, the measurement distance of Kalman's coefficient and Kalman filtering are periodically acquired, with this
Obtain the estimated distance of Kalman filtering.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
Construct the estimated distance formula of Kalman filtering:
EstimatedDisti=ForeDisti+Kg*(MeasureDisti-ForeDisti),
Wherein, EstimatedDist is the estimated distance of Kalman filtering, and ForeDist is the pre- ranging of Kalman filtering
From Kg is Kalman's coefficient, and MeasureDis t is the measurement distance of Kalman filtering, and the Kalman of current period is obtained with this
The estimated distance of filtering.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
Average value filtering processing is carried out to feedback signal；
Reference distance calibration scale substitutes into average value filtering, obtains the measurement distance of Kalman filtering.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
Construct the Prediction distance formula of Kalman filtering:
ForeDisti=ForeDisti-1+Si,
Wherein, S is the displacement in the i-th period, with the Prediction distance of this Kalman filtering for obtaining current period.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
Construct the prediction formula of variance of Kalman filtering:
ForecastVari=MeasureVari-1+ Q,
Wherein, ForecastVar is the prediction variance of Kalman filtering, and MeasureVar is the measurement side of Kalman filtering
Difference, Q is prediction noise variance, with the prediction variance of this Kalman filtering for obtaining current period.
Construct Kalman's coefficient formula:
Wherein, R is measurement noise variance, and Kalman's coefficient of current period is obtained with this.
Wherein, preferred version is that the distance controlling method is further comprising the steps of:
Construct the measurement formula of variance of Kalman filtering:
MeasureVa ri=(1-Kg)2*ForecastVa ri+Kg2* R,
With the measurement variance of this Kalman filtering for obtaining current period.
The beneficial effects of the present invention are compared with prior art, the present invention is a kind of based on Kalman filtering by designing
Distance controlling method, after obtaining the estimated distance of Kalman filtering, judgement stage locating for cutting head at this time, then carry out corresponding
Servo output, Kalman filtering processing can remove the noise jamming that feedback signal is subject to, and different phase correspond to it is different
Parameter output can more guarantee that stablizing servo exports, and cutting head and plate surface are constantly in same certain height.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples, in attached drawing:
Fig. 1 is the flow diagram of distance controlling method of the present invention；
Fig. 2 is the flow diagram that the present invention judges the locating stage；
Fig. 3 is the flow diagram of parameter setting of the present invention；
Fig. 4 is the flow diagram for the estimated distance that the present invention obtains Kalman filtering.
Specific embodiment
Now in conjunction with attached drawing, elaborate to presently preferred embodiments of the present invention.
As shown in Figures 1 to 4, the present invention provides a kind of preferred implementation of distance controlling method based on Kalman filtering
Example.
Specifically, with reference to Fig. 1, a kind of distance controlling method based on Kalman filtering, the distance controlling method includes
Following steps:
Step 1 is periodically sent out instruction, then obtains feedback signal, and carries out Kalman filtering processing to feedback signal, obtains
The estimated distance of card taking Kalman Filtering；
Step 2 judges the stage locating for cutting head；
Step 3, the stage according to locating for the estimated distance of Kalman filtering and cutting head are completed parameter setting, and are carried out
Servo output.
Wherein, cutting head carries out cutting operation to workpiece, the cycle sensor transmitting detection letter being mounted on cutting head
Number arrive work piece cut face, workpiece reflection feedback signal to sensor, after sensor receives feedback signal, to feedback signal progress
Kalman filtering processing, removes noise jamming, prevents feedback signal to be distorted, and obtain the estimated distance of Kalman filtering, described
Estimated distance is the estimated distance of cutting head and work piece cut face；Then, judge the stage locating for the period internal cutting head, and root
Estimated distance and locating stage according to Kalman filtering complete relative parameters setting, and send cutting head for parameter, cut
Head at a distance from workpiece, carries out servo output according to parameter adjustment, carries out cutting operation to the cutting surfaces of workpiece.Such one
Come, by the distance controlling method, Kalman filtering can be rapidly converged near true value, be avoided because constant
Concussion caused by alignment error in movement, adjusts the position of cutting head again later, can adjust cutting head and workpiece in real time
The distance of cut surface guarantees that the laser spot of cutting head transmitting is maintained at the focusing of work piece cut face so that the distance remains unchanged,
It realizes and stablizes cutting.
Further, with reference to Fig. 2, the distance controlling method is further comprising the steps of:
Step 21, state machine obtain cutting head at a distance from work piece cut face, judge the stage locating for cutting head.
Wherein, sensor obtains cutting head at a distance from work piece cut face, and is sent to state machine, the state machine according to
The distance judges the stage locating for cutting head.
In the present embodiment, the stage locating for the cutting head includes four-stage, respectively close to the stage, the adjusting stage,
Flexible adjusting stage and fast reaction stage；When the distance reaches adjusting range, to approach the stage, it is greater than 10mm,
Next normal adjustment；It is the adjusting stage when the distance is in adjusting range, e.g., less than or equal to 10mm connects
Get off and normally adjusts；When the distance is close to target range, for the flexible adjusting stage, next need to make adjustment
Modification；It is the fast reaction stage when the distance is less than target range, next needs to make modification to adjustment.The mesh
Subject distance is from the value set, and visual concrete condition adjusts.
Still further, the distance controlling method is further comprising the steps of with reference to Fig. 3:
Step 31 obtains acceleration, calculating speed and displacement according to the estimated distance of Kalman filtering, if being in
Close to the stage, acceleration is constant；If being in the adjusting stage, acceleration is constant；If in the flexible adjusting stage, acceleration is set
For one third times acceleration；If being in the fast reaction stage, acceleration is set as three times acceleration.
Wherein, the setting of correlation output parameter, such as the acceleration of cutting head are carried out according to the estimated distance of Kalman filtering
Degree, calculating speed and displacement, and judge the moving direction of cutting head, cutting head, may each week in cycle movement
Phase is in different phase, then respectively corresponds different parameter settings, if the acceleration of cutting head is constant in close to the stage；
If being in the adjusting stage, the acceleration of cutting head is constant；If in the flexible adjusting stage, the acceleration of cutting head is set as three
/ mono- times of acceleration is the acceleration by setting multiplied by one third；If being in the fast reaction stage, cutting head adds
Speed is set as three times acceleration, is by the acceleration of setting multiplied by three times.Next, cutting head then according to the parameter of setting into
Row movement, realizes the distance controlling to cutting head and work piece cut face.Multiple stages are set, cutting head present position can be directed to
Different control processes is carried out, while meeting quick model- following control, additionally it is possible to feedback signal lags bring error is reduced, from
And the stability of cutting head can be further improved, guarantee that cutting head quickly and accurately moves.
Specifically, with reference to Fig. 4, the distance controlling method is further comprising the steps of:
Step 11, the Prediction distance for periodically acquiring Kalman filtering, Kalman's coefficient and Kalman filtering measurement away from
From obtaining the estimated distance of Kalman filtering with this.
Wherein, the measurement of the Prediction distance, Kalman's coefficient and Kalman filtering of Kalman filtering is obtained in each period
Distance calculates the estimated distance of Kalman filtering according to the data of above-mentioned acquisition.
Here, providing the acquisition process of the estimated distance of Kalman filtering.
Construct the estimated distance formula of Kalman filtering:
EstimatedDisti=ForeDisti+Kg*(MeasureDisti-ForeDisti),
Wherein, EstimatedDist is the estimated distance of Kalman filtering, and ForeDist is the pre- ranging of Kalman filtering
From Kg is Kalman's coefficient, and MeasureDis t is the measurement distance of Kalman filtering, and the Kalman of current period is obtained with this
The estimated distance of filtering.It was currently the i-th period, and EstimatedDistiFor the estimated distance of current period Kalman filtering,
It is the value that this needs to acquire, ForeDistiFor the Prediction distance of current period Kalman filtering, MeasureDis tiTo work as
The measurement distance of preceding period Kalman filtering.
Firstly, obtaining feedback signal, which, which mixes, multiple signals, first carries out average value filtering processing, then join
Range substitutes into average value filtering, obtains the measurement distance MeasureDits of Kalman filtering from calibration scalei。
Then, the Prediction distance formula of Kalman filtering is constructed:
ForeDisti=ForeDisti-1+Si,
Wherein, ForeDistiFor the Prediction distance of current period, ForeDisti-1For the Prediction distance in last period,
It is given value, it is given value that S, which is the displacement in the i-th period, and by above-mentioned formula, the Kalman of available current period is filtered
The Prediction distance ForeDist of wavei。
Then, the prediction formula of variance of Kalman filtering is constructed:
ForecastVari=MeasureVari-1+ Q,
Wherein, ForecastVar is the prediction variance of Kalman filtering, ForecastVariFor the Kalman of current period
The prediction variance of filtering, MeasureVar are the measurement variance of Kalman filtering, MeasureVari-1For last period Kalman
The measurement variance of filtering is given value, and it is given value that Q, which is prediction noise variance, by above-mentioned formula, available current week
The prediction variance ForecastVar of the Kalman filtering of phasei。
Then, Kalman's coefficient formula is constructed:
Wherein, ForecastVariIt for the prediction variance of current period Kalman filtering, has been acquired above-mentioned, R is to survey
Noise variance is measured, is given value, by above-mentioned formula, Kalman's COEFFICIENT K g of current period is obtained with this.
It should be noted that the measurement variance of the Kalman filtering of current period can be acquired first, it is supplied to next period
It is used, for this purpose, the measurement formula of variance of construction Kalman filtering:
MeasureVa ri=(1-Kg)2*ForecastVa ri+Kg2* R,
Wherein, Kg is current period Kalman coefficient, has been acquired above-mentioned, ForecastVa riFor current period card
The prediction variance of Kalman Filtering, has been acquired above-mentioned, and it is given value that R, which is measurement noise variance,, can be with by above-mentioned formula
Obtain the measurement variance MeasureVa r of the Kalman filtering of current periodi。
It is noted that the prediction noise variance Q and measurement noise variance R of given Kalman filtering, above-mentioned the two
It is unrelated with the time, and error complies with standard normal distribution, after substituting into formula, obtained value is accurate.
Therefore, in the Prediction distance ForeDist for acquiring current period Kalman filteringi, current period Kalman's coefficient
Kg, the measurement distance MeasureDis t of current period Kalman filteringi, the estimation of current period Kalman filtering can be acquired
Distance EstimatedDisti。
In conclusion the above is merely preferred embodiments of the present invention, being not intended to limit the scope of the present invention.
Any modification made all within the spirits and principles of the present invention, equivalent replacement, improve etc., it should be included in guarantor of the invention
It protects in range.
Claims (10)
1. a kind of distance controlling method based on Kalman filtering, which is characterized in that the distance controlling method includes following step
It is rapid:
It is periodically sent out instruction, then obtains feedback signal, and Kalman filtering processing is carried out to feedback signal, obtains Kalman's filter
The estimated distance of wave；
Judge the stage locating for cutting head；
According to the stage locating for the estimated distance of Kalman filtering and cutting head, parameter setting is completed, and carries out servo output.
2. distance controlling method according to claim 1, which is characterized in that the distance controlling method further includes following step
It is rapid:
State machine obtains cutting head at a distance from work piece cut face, judges the stage locating for cutting head.
3. distance controlling method according to claim 2, which is characterized in that the stage locating for the cutting head includes four ranks
Section, respectively close to stage, adjusting stage, flexible adjusting stage and fast reaction stage；When the distance reaches adjusting range
When, to approach the stage；It is the adjusting stage when the distance is in adjusting range；When the distance is close to target range, it is
The flexible adjusting stage；It is the fast reaction stage when the distance is less than target range.
4. distance controlling method according to claim 3, which is characterized in that the distance controlling method further includes following step
It is rapid:
Acceleration, calculating speed and displacement are obtained according to the estimated distance of Kalman filtering, if adding in close to the stage
Speed is constant；If being in the adjusting stage, acceleration is constant；If in the flexible adjusting stage, acceleration is set as one third
Times acceleration；If being in the fast reaction stage, acceleration is set as three times acceleration.
5. according to claim 1 to distance controlling method described in 4, which is characterized in that the distance controlling method further include with
Lower step:
The Prediction distance of Kalman filtering, the measurement distance of Kalman's coefficient and Kalman filtering are periodically acquired, is obtained with this
The estimated distance of Kalman filtering.
6. distance controlling method according to claim 5, which is characterized in that the distance controlling method further includes following step
It is rapid:
Construct the estimated distance formula of Kalman filtering:
EstimatedDisti=ForeDisti+Kg*(MeasureDisti-ForeDisti),
Wherein, EstimatedDist is the estimated distance of Kalman filtering, and ForeDist is the Prediction distance of Kalman filtering,
Kg is Kalman's coefficient, and MeasureDist is the measurement distance of Kalman filtering, and the Kalman filtering of current period is obtained with this
Estimated distance.
7. distance controlling method according to claim 6, which is characterized in that the distance controlling method further includes following step
It is rapid:
Average value filtering processing is carried out to feedback signal；
Reference distance calibration scale substitutes into average value filtering, obtains the measurement distance of Kalman filtering.
8. distance controlling method according to claim 6, which is characterized in that the distance controlling method further includes following step
It is rapid:
Construct the Prediction distance formula of Kalman filtering:
ForeDisti=ForeDisti-1+Si,
Wherein, S is the displacement in the i-th period, with the Prediction distance of this Kalman filtering for obtaining current period.
9. distance controlling method according to claim 8, which is characterized in that the distance controlling method further includes following step
It is rapid:
Construct the prediction formula of variance of Kalman filtering:
ForecastVari=MeasureVari-1+ Q,
Wherein, ForecastVar is the prediction variance of Kalman filtering, and MeasureVar is the measurement variance of Kalman filtering, Q
To predict noise variance, with the prediction variance of this Kalman filtering for obtaining current period.
Construct Kalman's coefficient formula:
Wherein, R is measurement noise variance, and Kalman's coefficient of current period is obtained with this.
10. distance controlling method according to claim 9, which is characterized in that the distance controlling method further includes following
Step:
Construct the measurement formula of variance of Kalman filtering:
MeasureVari=(1-Kg)2*ForecastVari+Kg2* R,
With the measurement variance of this Kalman filtering for obtaining current period.
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| CN109623162A (en) * | 2019-01-31 | 2019-04-16 | 中国地质大学（武汉） | A kind of two-dimensional laser engraving machine of view-based access control model servo and Kalman filtering compensation |
| CN111002858A (en) * | 2019-12-18 | 2020-04-14 | 中兴新能源汽车有限责任公司 | Wireless charging guiding and positioning system and method and vehicle-mounted equipment |
| CN112097622A (en) * | 2020-09-14 | 2020-12-18 | 上海维宏电子科技股份有限公司 | Method and device for realizing distance measurement of capacitive displacement sensor based on Kalman filter |
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| CN115319311A (en) * | 2022-10-13 | 2022-11-11 | 扬州皓月机械有限公司 | Laser cutting equipment |
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| CN113927157A (en) * | 2021-12-17 | 2022-01-14 | 武汉锐科光纤激光技术股份有限公司 | Method and device for controlling output power of laser equipment, computer equipment and medium |
| CN115319311A (en) * | 2022-10-13 | 2022-11-11 | 扬州皓月机械有限公司 | Laser cutting equipment |
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