CN108270057A - A kind of automatic tuning system of cavity body filter - Google Patents
A kind of automatic tuning system of cavity body filter Download PDFInfo
- Publication number
- CN108270057A CN108270057A CN201711464436.6A CN201711464436A CN108270057A CN 108270057 A CN108270057 A CN 108270057A CN 201711464436 A CN201711464436 A CN 201711464436A CN 108270057 A CN108270057 A CN 108270057A
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- Prior art keywords
- cavity body
- body filter
- data
- tuning
- output end
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01P—WAVEGUIDES; RESONATORS, LINES, OR OTHER DEVICES OF THE WAVEGUIDE TYPE
- H01P1/00—Auxiliary devices
- H01P1/20—Frequency-selective devices, e.g. filters
- H01P1/207—Hollow waveguide filters
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01P—WAVEGUIDES; RESONATORS, LINES, OR OTHER DEVICES OF THE WAVEGUIDE TYPE
- H01P1/00—Auxiliary devices
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Abstract
The present invention relates to a kind of automatic tuning systems of the cavity body filter based on adaptive learning, the Network Analyzer being connect including the signal output end with cavity body filter, the network port of Network Analyzer and the signal input part of data collector connect, the signal output end of data collector and the signal input part of data processor connect, the signal output end of data processor and the signal input part of motion controller connect, the signal output end of motion controller and the signal input part of executing agency connect, the tuning screw of executing agency's connection cavity wave filter.The present invention automatically can be adjusted tuning screw by adaptive learning, multiple-objection optimization, improve tuning precision and tuning efficiency.
Description
Technical field
The present invention relates to cavity body filter technical fields, are related to a kind of cavity body filter more particularly to a kind of based on adaptive
It should learn the automatic tuning system of cavity body filter.
Background technology
Existing cavity body filter is a kind of device or circuit for having processing to act on to signal, and main function is：Allow useful letter
It is number as zero-decrement as possible to pass through, the attenuation as big as possible to garbage signal.It is Remote Radio Unit (Remote Radio
Unit, abbreviation RRU), RF filtering unit (Radio and Filter Unit, RFU) and antenna active system (Active
Antenna System, abbreviation AAS) etc. the indispensable critical component of wireless base stations product.
Due to the difference of cavity body filter manufacture machining accuracy, the reasons such as uneven of resonance cavity wall coating cause humorous
The local frequency of chamber of shaking changes, it is therefore desirable to it is adjusted by the tuning screw on cavity body filter, it is humorous so as to correct
It shakes the local frequency of chamber.In the prior art by manually by virtue of experience adjusting tuning screw, this manufal tuning mode exists
The problem of tuning precision is low, efficiency is low, time-consuming, it is difficult to carry out the quick production of high-volume.
Invention content
In order to solve the above technical problems, the object of the present invention is to provide it is a kind of based on adaptive learning cavity body filter from
Dynamic tuning system, the automatic tuning system of the cavity body filter are not only able to automatically be adjusted tuning screw, improve and adjust
Humorous precision and tuning efficiency, and multiple target can be optimized and tuned speed and precision are accelerated by adaptive learning.
The automatic tuning system of the cavity body filter of the present invention, the net being connect including the signal output end with cavity body filter
Network analyzer, the network port of the Network Analyzer and the signal input part of data collector connect, and the data are adopted
The signal output end of storage and the signal input part of data processor connect, the signal output end and fortune of the data processor
The signal input part connection of movement controller, the signal output end of the motion controller and the signal input part of executing agency connect
It connects, the tuning screw of executing agency's connection cavity wave filter, the Network Analyzer is used to acquire cavity body filter
S-matrix parameter, the data processor is used to carry out subsequent iteration processing, the data to the s-matrix parameter
Processor is used to the data result that subsequent iteration is handled being sent to motion controller, and the motion controller is according to the data
Executing agency described in output control is adjusted the tuning screw of the cavity body filter.
Further, the data collector is High-Speed Data Acquisition Board, and the High-Speed Data Acquisition Board carries net
Network interface or gpib interface, the High-Speed Data Acquisition Board quickly read Network Analyzer by network interface or gpib interface
Data, and the data processor is passed to after treatment.
Further, the Network Analyzer is vector network analyzer (VNA), the vector network analyzer
Signal output end is connect with the signal input part of the data acquisition card.
Further, the data processor is PC computers.
Further, the cavity body filter carries adaptive optimization module, and the adaptive optimization module provides
Then the tuning setting initial value of each tuning screw of cavity body filter is joined according to the working frequency of cavity body filter, frequency range and S
Number provides theoretical model, the transfer function of cavity body filter network structure is calculated then according to the theoretical model, then with each
The tuning setting of a tuning screw is variable, using the S parameter characteristic in working frequency, frequency range as object function, is iterated
It practises, adaptive optimization.
Further, the executing agency includes the fixture being fixedly connected with the end face of tuning screw, is connect with fixture
Coordinate robots and driving coordinate robots motor, the motor passes through motor driver and the motion controller
Connection.
According to the above aspect of the present invention, the present invention by by Network Analyzer, data collector, data processor, motion controller,
The tuning screw of executing agency and cavity body filter organically combines the automatic tuning for constituting a kind of cavity body filter
System, as a result of above-mentioned technical solution, the present invention has at least the following advantages：
The present invention can by the s-matrix continuous parameters iterative processing to cavity body filter, and by data processor according to
Handling result persistently adjusts tuning screw by motion controller and executing agency, until reaching tuning requirement, greatly improves
Tuning precision and tuning efficiency, present invention may apply to various types of cavity body filters, have versatile, flexibility
The characteristics of high.
The present invention has incorporated the adaptive optimization module based on artificial intelligence, and multiple target can be optimized, and passes through
Continuous evolutionary learning accelerates the speed of optimization, improves the precision of optimization, is particularly suitable for the multi-parameters such as duplexer filter requirement cavity
The tuning of wave filter.
Above description is only the general introduction of technical solution of the present invention, in order to better understand the technological means of the present invention,
And can be implemented in accordance with the contents of the specification, below with presently preferred embodiments of the present invention and after attached drawing is coordinated to be described in detail such as.
Description of the drawings
Fig. 1 is the work block diagram of the present invention.
Specific embodiment
With reference to the accompanying drawings and examples, the specific embodiment of the present invention is described in further detail.Implement below
Example is used to illustrate the present invention, but be not limited to the scope of the present invention.
Referring to Fig. 1, the automatic tuning system given by the present invention, including being connect with the signal output end of cavity body filter 1
Network Analyzer 2, the network port of Network Analyzer 2 connect with the signal input part of data collector 3, data collector 3
Signal output end connect with the signal input part of data processor 4, the signal output end and motion controller of data processor 4
5 signal input part connection, the signal output end of motion controller 5 are connect with the signal input part of executing agency 6, executing agency
The tuning screw of connection cavity wave filter, Network Analyzer 2 are used to acquire the s-matrix parameter of cavity body filter, data processor 4
For carrying out subsequent iteration processing to s-matrix parameter, data processor is used to the data result that subsequent iteration is handled being sent to
Motion controller, motion controller according to the data result control executing agency to the tuning screw of the cavity body filter into
Row adjustment.
As the preferred embodiment of the present invention, data collector 4 is High-Speed Data Acquisition Board, and High-Speed Data Acquisition Board carries
Network interface or gpib interface, High-Speed Data Acquisition Board quickly read Network Analyzer number by network interface or gpib interface
According to, and data processor is passed to after treatment.
As the preferred embodiment of the present invention, Network Analyzer 2 is vector network analyzer (VNA), vector network analysis
The signal output end of instrument and the signal input part of data acquisition card connect.
As the further improvement of the present invention, cavity body filter is provided with adaptive optimization module, adaptive optimization mould
Block provides the tuning setting initial value of each tuning screw of cavity body filter, then according to the working frequency of cavity body filter, frequency
Section and S parameter provide theoretical model, and the transfer function of cavity body filter network structure is calculated then according to the theoretical model, with
Afterwards using the tuning setting of each tuning screw as variable, using the S parameter characteristic in working frequency, frequency range as object function, carry out
Iterative learning, adaptive optimization.
As the preferred embodiment of the present invention, executing agency include be fixedly connected with the end face of tuning screw fixture, with
The coordinate robots of fixture connection and the motor of driving coordinate robots, the motor pass through motor driver and the fortune
Movement controller connects.
The operation principle of the present invention is as follows：The acquisition of data collector 3 is first passed through to filter by the cavity that Network Analyzer 2 obtains
Then the s-matrix parameter of wave device 1 carries out subsequent iteration processing by data processor 4 to the s-matrix parameter of data collector 3,
And control instruction is sent to motion controller 5 by result, then executing agency 6 is controlled to tuning screw 11 by motion controller 5
It is adjusted.
The above is only the preferred embodiment of the present invention, is not intended to restrict the invention, it is noted that for this skill
For the those of ordinary skill in art field, without departing from the technical principles of the invention, can also make it is several improvement and
Modification, these improvements and modifications also should be regarded as protection scope of the present invention.
Claims (6)
1. a kind of cavity body filter automatic tuning system based on adaptive learning, it is characterised in that：Including with cavity body filter
Signal output end connection Network Analyzer, the signal of the network port of the Network Analyzer and data collector inputs
End connection, the signal output end of the data collector and the signal input part of data processor connect, at the data
The signal input part of signal output end and motion controller for managing device connects, and the signal output end of the motion controller is with holding
The signal input part connection of row mechanism, the tuning screw of executing agency's connection cavity wave filter, the network analysis
Instrument is used to acquire the s-matrix parameter of cavity body filter, and the data processor is used to carry out the s-matrix parameter continuous
Iterative processing, the data processor is used to the data result that subsequent iteration is handled being sent to motion controller, described
Motion controller adjusts the tuning screw of the cavity body filter according to the data result control executing agency
It is whole.
2. the automatic tuning system of cavity body filter according to claim 1, it is characterised in that：The data collector
For High-Speed Data Acquisition Board, the High-Speed Data Acquisition Board carries network interface or gpib interface, and the high speed signal is adopted
Truck quickly reads Network Analyzer data by network interface or gpib interface, and passes to the data after treatment
Processor.
3. the automatic tuning system of cavity body filter according to claim 1, it is characterised in that：The Network Analyzer
For vector network analyzer (VNA), the letter of the signal output end of the vector network analyzer and the data acquisition card
The connection of number input terminal.
4. the automatic tuning system of cavity body filter according to claim 1, it is characterised in that：The data processor
For PC computers.
5. the automatic tuning system of cavity body filter according to claim 1, it is characterised in that：The cavity body filter
With adaptive optimization module, at the beginning of the adaptive optimization module provides the tuning setting of each tuning screw of cavity body filter
Then initial value provides theoretical model according to the working frequency of cavity body filter, frequency range and S parameter, then according to the theoretical model
The transfer function of cavity body filter network structure is calculated, then using the tuning setting of each tuning screw as variable, with work
S parameter characteristic in frequency, frequency range is object function, is iterated study, adaptive optimization.
6. according to the automatic tuning system of claim 1-5 any one of them cavity body filters, it is characterised in that：Described holds
Row mechanism includes the fixture being fixedly connected with the end face of tuning screw, the coordinate robots being connect with fixture and driving coordinate machinery
The motor of hand, the motor are connect by motor driver with the motion controller.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711464436.6A CN108270057A (en) | 2017-12-28 | 2017-12-28 | A kind of automatic tuning system of cavity body filter |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711464436.6A CN108270057A (en) | 2017-12-28 | 2017-12-28 | A kind of automatic tuning system of cavity body filter |
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| CN108270057A true CN108270057A (en) | 2018-07-10 |
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| Application Number | Title | Priority Date | Filing Date |
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| CN201711464436.6A Pending CN108270057A (en) | 2017-12-28 | 2017-12-28 | A kind of automatic tuning system of cavity body filter |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020242367A1 (en) * | 2019-05-28 | 2020-12-03 | Telefonaktiebolaget Lm Ericsson (Publ) | Cavity filter tuning using imitation and reinforcement learning |
| CN112736380A (en) * | 2020-12-14 | 2021-04-30 | 北京配天技术有限公司 | Automatic tuning system, automatic tuning method and storage device of dielectric filter |
| WO2023047168A1 (en) | 2021-09-27 | 2023-03-30 | Telefonaktiebolaget Lm Ericsson (Publ) | Offline self tuning of microwave filter |
| EP4296698A1 (en) * | 2022-06-10 | 2023-12-27 | Tektronix, Inc. | Automated cavity filter tuning using machine learning |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN202839933U (en) * | 2012-05-19 | 2013-03-27 | 合肥博仑微波器件有限公司 | Automatic debugging system for cavity filter |
| CN104659460A (en) * | 2013-11-25 | 2015-05-27 | 中国科学院深圳先进技术研究院 | Automatic tuning method and system for cavity filter |
| CN204631201U (en) * | 2015-05-27 | 2015-09-09 | 魏军 | A kind of Partial Discharge in High Voltage Transformer detection system |
| CN105789812A (en) * | 2015-12-31 | 2016-07-20 | 中国科学院深圳先进技术研究院 | Automatic adjustment method and system for cavity filter |
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2017
- 2017-12-28 CN CN201711464436.6A patent/CN108270057A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN202839933U (en) * | 2012-05-19 | 2013-03-27 | 合肥博仑微波器件有限公司 | Automatic debugging system for cavity filter |
| CN104659460A (en) * | 2013-11-25 | 2015-05-27 | 中国科学院深圳先进技术研究院 | Automatic tuning method and system for cavity filter |
| CN204631201U (en) * | 2015-05-27 | 2015-09-09 | 魏军 | A kind of Partial Discharge in High Voltage Transformer detection system |
| CN105789812A (en) * | 2015-12-31 | 2016-07-20 | 中国科学院深圳先进技术研究院 | Automatic adjustment method and system for cavity filter |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020242367A1 (en) * | 2019-05-28 | 2020-12-03 | Telefonaktiebolaget Lm Ericsson (Publ) | Cavity filter tuning using imitation and reinforcement learning |
| CN112736380A (en) * | 2020-12-14 | 2021-04-30 | 北京配天技术有限公司 | Automatic tuning system, automatic tuning method and storage device of dielectric filter |
| WO2023047168A1 (en) | 2021-09-27 | 2023-03-30 | Telefonaktiebolaget Lm Ericsson (Publ) | Offline self tuning of microwave filter |
| EP4296698A1 (en) * | 2022-06-10 | 2023-12-27 | Tektronix, Inc. | Automated cavity filter tuning using machine learning |
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Application publication date: 20180710 |