CN106546436A - A kind of auto parts and components loading spectrum is effectively compressed method - Google Patents
A kind of auto parts and components loading spectrum is effectively compressed method Download PDFInfo
- Publication number
- CN106546436A CN106546436A CN201610913188.8A CN201610913188A CN106546436A CN 106546436 A CN106546436 A CN 106546436A CN 201610913188 A CN201610913188 A CN 201610913188A CN 106546436 A CN106546436 A CN 106546436A
- Authority
- CN
- China
- Prior art keywords
- signal
- wavelet
- loading spectrum
- auto parts
- spectrum
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Wheeled or endless-tracked vehicles
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The invention discloses a kind of auto parts and components loading spectrum is effectively compressed method, including step：1）, input part original load spectrum；2）, loading spectrum is reduced before process；3）, wavelet decomposition is carried out to part original load spectrum, obtain a low-frequency wavelet coefficients and the high-frequency wavelet coefficient under N number of different scale；4）, high-frequency wavelet coefficient be reconstructed obtain Wavelet Component；5）, threshold value is set to Wavelet Component and obtains damaging the big signal segment of contribution；6）, signal segment spliced, obtain compressed signal；7）, calculate the statistical parameter of compressed signal, when statistical parameter error is more than 10%, then circulation step 5）, conversely, then jumping out circulation；8）, complete the reduction work of signal.The present invention can carry out reduction process respectively to the part loading spectrum of single shaft and multiaxis, and resulting reduction signal keeps basically identical with primary signal, it is possible to achieve load effect with primary signal identical.
Description
Technical field
The present invention relates to the road spectral editing method of auto parts and components, is especially that auto parts and components are carried out Road Simulation
The method that the loading spectrum time is compressed.
Background technology
Auto parts and components laboratory road simulation test is realized reappearing the stand under load under the actual road traveling of part indoors
Situation, with the test period it is short, test efficiency is high, repdocutbility is good the features such as and be widely used in the durable Journal of Sex Research of part.
Auto parts and components load Spectral editing is an important step for carrying out part laboratory road simulation test research, the reality of part
Border loading spectrum more accurately can reflect its actual life compared with experience loading spectrum, but the real road load of complete applying part
Spectrum, it will take a substantial amount of time and experimentation cost.Be necessary acceleration editor to be carried out to the part loading spectrum for gathering, ensureing to carry
Under the premise of lotus spectrum loading effect identical, time shorter loading spectrum is obtained, for part fatigue durability experimental study.Protect
Card reduction loading spectrum is identical to the loading effect of part with original load spectrum, it is necessary to make reduction loading spectrum in amount of damage, statistics
Parameter（Average, root-mean-square value and peak factor）, power spectral density and wear level count etc. aspect and primary signal it is basically identical.
The method of part load spectral editing has various, and basic principle is all little to damaging contribution amount in erasure signal
Circulation is to shorten test period, and ensures that the damage carrying amount of signal is basically identical with primary signal, the difference between edit methods
It is different to be mainly reflected in the method for amount of damage identification and deletion.The amount of damage of signal generally with amplitude direct proportionality, it is and right
The part that amplitude is changed greatly in signal, wavelet transformation effectively can be identified.Signal edit based on wavelet transformation
Method, cardinal principle are identification and part big to part injury contribution in stick signal, before and after being reduced by contrast signal
Statistical parameter（Root mean square, peak factor）To determine final reduction signal.
In prior art, the loading spectrum accelerated durability edit methods of auto parts and components have：Using Ncode softwares, arrange
Damaging reserved carries out the reduction of loading spectrum.The method can be reduced to the loading spectrum of auto parts and components, but resulting
Reduction signal is in statistical parameter（Average, root-mean-square value and peak factor）And the aspect such as power spectral density has larger with primary signal
Difference.It is therefore proposed that a kind of auto parts and components loading spectrum based on wavelet transformation is effectively compressed method, reduction signal is made not only
It is basically identical with primary signal on maintenance dose is damaged, and in statistical parameter（Average, root-mean-square value and peak factor）And work(
The aspects such as rate spectrum density keep basically identical with primary signal.
The content of the invention
The technical problem to be solved is：There is provided a kind of auto parts and components loading spectrum based on wavelet transformation effective
Compression method, the method enable to compressed signal with primary signal in amount of damage, statistical parameter（Average, root-mean-square value and peak
Value coefficient）, power spectral density and wear level and aspect and the primary signal such as count and be consistent, so as to realize there is phase with primary signal
Same loading effect.
To solve above-mentioned technical problem, the technical solution adopted in the present invention is：
A kind of auto parts and components loading spectrum is effectively compressed method, comprises the following steps：
1）, input part original load spectrum；
2）, loading spectrum is reduced before process, including resampling, filter, go singular value to process；
3）, specify number of plies N of wavelet type and decomposition, wavelet decomposition is carried out to the original load spectrum of part, a low frequency is obtained
High-frequency wavelet coefficient under wavelet coefficient and N number of different scale；
4）, high-frequency wavelet coefficient is reconstructed, obtain the Wavelet Component under N number of different scale；
5）, threshold value is arranged to Wavelet Component, according to set threshold value, damage composition method of identification using envelope, identification is higher than
The data of threshold value, and position the time point of corresponding data.Time point is corresponded in original load spectrum, you can obtain damaging contribution
Big signal segment；
6）, signal segment spliced, obtain compressed signal；
7）, calculate the statistical parameter of compressed signal, including root-mean-square value and peak factor, due to taking different threshold values, will be obtained
Different compressed signal, therefore when the statistical parameter error of compressed signal and primary signal is more than 10%, then circulation step 5）,
The threshold value of Wavelet Component is reset, until compressed signal is less than 10% with the statistical parameter error of primary signal, is then jumped out and is followed
Ring；
8）, complete the reduction work of signal.
Further, described wavelet type is includeddbN, Meyr wavelet function, the Decomposition order is according to wavelet function
Depending on.
Further, the step 5）In to Wavelet Component arrange threshold value the step of specifically include：For the vapour of single shaft
The loading spectrum reduction of car parts, then be respectively provided with threshold value to the Wavelet Component under N number of different scale；For the automobile zero of multiaxis
Components ' load spectrum reduction, then carry out accumulation square summation, the knot to accumulation square summation to the Wavelet Component under N number of different scale
Fruit arranges threshold value.
Further, the step 6）In specifically include the step of splicing to signal segment：Automobile to single shaft
For the loading spectrum of parts, several signal segments will be extracted based on the Wavelet Component under each yardstick, these signal patch
The section corresponding time is present occurs simultaneously, and causes signal segment to exist and repeat to extract, therefore, for the load of the auto parts and components of single shaft
The signal segment repeatedly extracted under each yardstick is taken union process when signal splicing is carried out by lotus spectrum；For the automobile zero of multiaxis
For components ' load spectrum, each passage is occured simultaneously based on accumulative wavelet coefficient and the presence of extracted signal segment, in order to ensure to lead to
Phase relation between road, need to carry out the loading spectrum of each passage and meanwhile delete, therefore, for the load of multi-wheeler parts
Each passage all signal segments for extracting are taken union process when signal splicing is carried out by lotus spectrum more.
Further, each type of wavelet decomposition includes an optimum Decomposition order, enables to final pressure
Contracting Signal Compression damages maintenance dose maximum than minimum, and the aspect such as statistical parameter and power spectral density keeps basic with primary signal
Unanimously, the statistical parameter includes average, root-mean-square value and peak factor.
Further, the signal segment extracted with multiaxis by the single shaft employs and takes the method for union and spliced,
Obtain compressed signal closest with primary signal.
The present invention compared with prior art, with advantages below：
1）The damage maintenance dose ratio of the compressed signal obtained based on wavelet transformation edit methods is obtained based on reservation edit methods are damaged
The compressed signal for arriving it is big, and more than 99% can be maintained at；
2）The statistical parameter of the compressed signal obtained based on wavelet transformation edit methods（Average, root mean square and peak factor）Mistake
Difference is than based on the big of the compressed signal for retaining that edit methods are obtained is damaged, being maintained at less than 10%；
3）The power spectral density plot of the compressed signal obtained based on wavelet transformation edit methods retains editing side with based on damage
The compressed signal that method is obtained is compared, and the former curve is closer with primary signal；
4）Grade analysis of accounts of wearing of the compressed signal obtained based on wavelet transformation edit methods retains edit methods with based on damage
The compressed signal for obtaining is compared, and the former curve is closer with primary signal；
5）All road surface operating modes of primary signal, but the editor retained based on damage can be kept based on wavelet transformation edit methods
Method will lose some road surface operating mode features.
Description of the drawings
Fig. 1 is flow chart of the present invention.
Fig. 2 is single shaft envelope damage composition identification figure in the present invention.
Fig. 3 is multiaxis envelope damage composition identification figure in the present invention.
Fig. 4 is single shaft signal spliced map in the present invention.
Fig. 5 is many axis signal spliced maps in the present invention.
Specific embodiment
The present invention is described in further detail below in conjunction with accompanying drawing embodiment.
As shown in figure 1, a kind of auto parts and components loading spectrum is effectively compressed method, comprise the following steps：
1）, input part original load spectrum；
2）, loading spectrum is reduced before process, including resampling, filter, go singular value to process；
3）, specify number of plies N of wavelet type and decomposition, wavelet decomposition is carried out to the original load spectrum of part, a low frequency is obtained
High-frequency wavelet coefficient under wavelet coefficient and N number of different scale；
4）, high-frequency wavelet coefficient is reconstructed, obtain the Wavelet Component under N number of different scale；
5）, threshold value is arranged to Wavelet Component, according to set threshold value, damage composition method of identification using envelope, identification is higher than
The data of threshold value, and the time point of corresponding data is positioned, time point is corresponded in original load spectrum, you can obtain damaging contribution
Big signal segment (see Fig. 2, Fig. 3)；
6）, signal segment spliced, obtain compressed signal；
7）, calculate the statistical parameter of compressed signal, including root-mean-square value and peak factor, due to taking different threshold values, will be obtained
Different compressed signal, therefore when the statistical parameter error of compressed signal and primary signal is more than 10%, then circulation step 5）,
The threshold value of Wavelet Component is reset, until compressed signal is less than 10% with the statistical parameter error of primary signal, is then jumped out and is followed
Ring；
8）, complete the reduction work of signal.
Specifically, described wavelet type is includeddbN, Meyr wavelet function, the Decomposition order is according to wavelet function
Depending on.
Specifically, the step 5）In to Wavelet Component arrange threshold value the step of specifically include：For the vapour of single shaft
The loading spectrum reduction of car parts, then be respectively provided with threshold value to the Wavelet Component under N number of different scale；For the automobile zero of multiaxis
Components ' load spectrum reduction, then carry out accumulation square summation, the knot to accumulation square summation to the Wavelet Component under N number of different scale
Fruit arranges threshold value.
Specifically, the step 6）In specifically include the step of splicing to signal segment：Automobile to single shaft
For the loading spectrum of parts, several signal segments will be extracted based on the Wavelet Component under each yardstick, these signal patch
The section corresponding time is present occurs simultaneously, and causes signal segment to exist and repeat to extract, therefore, for the load of the auto parts and components of single shaft
The signal segment repeatedly extracted under each yardstick is taken union and is processed (see Fig. 4) when signal splicing is carried out by lotus spectrum；For multiaxis
For auto parts and components loading spectrum, there is common factor based on accumulative wavelet coefficient and extracted signal segment in each passage, in order to
Ensure interchannel phase relation, need to carry out the loading spectrum of each passage and meanwhile delete, therefore, for multi-wheeler zero
The signal segment extracted each passage is taken union and is processed (see Fig. 5) when carrying out signal and splicing by the loading spectrum of part more.
Specifically, each type of wavelet decomposition includes an optimum Decomposition order, enables to final pressure
Contracting Signal Compression damages maintenance dose maximum than minimum, and the aspect such as statistical parameter and power spectral density keeps basic with primary signal
Unanimously, the statistical parameter includes average, root-mean-square value and peak factor.
Specifically, the signal segment extracted with multiaxis by the single shaft employs and takes the method for union and spliced,
Obtain compressed signal closest with primary signal.
The above embodiment of the present invention is only intended to clearly illustrate example of the present invention, and is not to the present invention
Embodiment restriction.For those of ordinary skill in the field, can also make on the basis of the above description
The change or variation of other multi-forms.There is no need to be exhaustive to all of embodiment.It is all the present invention
Any modification, equivalent and improvement made within spirit and principle etc., should be included in the protection of the claims in the present invention
Within the scope of.
Claims (6)
1. a kind of auto parts and components loading spectrum is effectively compressed method, it is characterised in that：Comprise the following steps：
1）, input part original load spectrum；
2）, loading spectrum is reduced before process, including resampling, filter, go singular value to process；
3）, specify number of plies N of wavelet type and decomposition, wavelet decomposition is carried out to the original load spectrum of part, a low frequency is obtained
High-frequency wavelet coefficient under wavelet coefficient and N number of different scale；
4）, high-frequency wavelet coefficient is reconstructed, obtain the Wavelet Component under N number of different scale；
5）, threshold value is arranged to Wavelet Component, according to set threshold value, damage composition method of identification using envelope, identification is higher than
The data of threshold value, and the time point of corresponding data is positioned, time point is corresponded in original load spectrum, you can obtain damaging contribution
Big signal segment；
6）, signal segment spliced, obtain compressed signal；
7）, calculate the statistical parameter of compressed signal, including root-mean-square value and peak factor, due to taking different threshold values, will be obtained
Different compressed signal, therefore when the statistical parameter error of compressed signal and primary signal is more than 10%, then circulation step 5）,
The threshold value of Wavelet Component is reset, until compressed signal is less than 10% with the statistical parameter error of primary signal, is then jumped out and is followed
Ring；
8）, complete the reduction work of signal.
2. auto parts and components loading spectrum according to claim 1 is effectively compressed method, it is characterised in that：Described small echo class
Type is includeddbN, Meyr wavelet function, depending on the Decomposition order is according to wavelet function.
3. auto parts and components loading spectrum according to claim 1 is effectively compressed method, it is characterised in that：The step 5）In
To Wavelet Component arrange threshold value the step of specifically include：For single shaft auto parts and components loading spectrum reduction, then to it is N number of not
Threshold value is respectively provided with the Wavelet Component under yardstick；For the auto parts and components loading spectrum of multiaxis reduces, then to N number of different scale
Under Wavelet Component carry out accumulation square summation, to accumulation square summation a result arrange a threshold value.
4. auto parts and components loading spectrum according to claim 1 is effectively compressed method, it is characterised in that：The step 6）In
Specifically include the step of splicing to signal segment：For the loading spectrum of the auto parts and components of single shaft, based on each chi
Wavelet Component under degree will extract several signal segments, and these signal segments corresponding time is present occurs simultaneously, and causes letter
Number fragment exists and repeats to extract, therefore, for single shaft auto parts and components loading spectrum when carrying out signal and splicing, by each yardstick
The lower signal segment for repeating to extract takes union process；For the auto parts and components loading spectrum of multiaxis, each passage is based on tired
Meter wavelet coefficient and extracted signal segment are present occurs simultaneously, and in order to ensure interchannel phase relation, needs to each passage
Loading spectrum carry out and meanwhile delete, therefore, for multi-wheeler parts loading spectrum carry out signal splice when, by each passage
The signal segment for extracting more takes union process.
5. auto parts and components loading spectrum according to claim 2 is effectively compressed method, it is characterised in that：It is each type of little
Wave Decomposition includes an optimum Decomposition order, enables to final compressed signal compression ratio minimum, damages maintenance dose most
Greatly, the aspect such as statistical parameter and power spectral density and primary signal keep basically identical, and the statistical parameter includes average, square
Root and peak factor.
6. auto parts and components loading spectrum according to claim 4 is effectively compressed method, it is characterised in that：The single shaft with it is many
The signal segment extracted by axle employs and takes the method for union and spliced, and obtains compressed signal and is connect with primary signal the most
Closely.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610913188.8A CN106546436B (en) | 2016-10-19 | 2016-10-19 | A kind of auto parts and components loading spectrum is effectively compressed method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610913188.8A CN106546436B (en) | 2016-10-19 | 2016-10-19 | A kind of auto parts and components loading spectrum is effectively compressed method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106546436A true CN106546436A (en) | 2017-03-29 |
| CN106546436B CN106546436B (en) | 2019-04-09 |
Family
ID=58369386
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610913188.8A Expired - Fee Related CN106546436B (en) | 2016-10-19 | 2016-10-19 | A kind of auto parts and components loading spectrum is effectively compressed method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106546436B (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110069875A (en) * | 2019-04-28 | 2019-07-30 | 江铃汽车股份有限公司 | A kind of generation method of the load modal data of dynamic load emulation |
| CN111581715A (en) * | 2020-03-23 | 2020-08-25 | 中国农业大学 | Method for quickly compressing acceleration load spectrum of tractor part |
| CN112539942A (en) * | 2020-11-24 | 2021-03-23 | 上海电机学院 | Characteristic load identification and acceleration test load spectrum compilation method |
| CN114034492A (en) * | 2021-11-03 | 2022-02-11 | 交通运输部公路科学研究所 | Automobile part load spectrum rapid compression method based on Hilbert-Huang transform |
| CN114235445A (en) * | 2021-11-26 | 2022-03-25 | 华南理工大学 | Vibration isolator road load spectrum time compression method based on S transformation |
| CN114577487A (en) * | 2020-11-30 | 2022-06-03 | 宝能汽车集团有限公司 | Method for simplifying vehicle test conditions, storage medium and electronic device |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103116148A (en) * | 2013-01-30 | 2013-05-22 | 上海理工大学 | Inversion method of nuclear magnetic resonance two-dimensional spectrum |
| CN103345927A (en) * | 2013-07-11 | 2013-10-09 | 暨南大学 | Processing method for detecting and locating audio time domain tampering |
| JP2014119406A (en) * | 2012-12-19 | 2014-06-30 | Nippon Telegr & Teleph Corp <Ntt> | Abnormality detection system and abnormality detection method of columnar structure |
| CN104374574A (en) * | 2014-11-14 | 2015-02-25 | 大连交大融通科技发展有限公司 | Comprehensive performance test bed for super-high-speed train bearing |
| CN105678283A (en) * | 2016-02-17 | 2016-06-15 | 云南电网有限责任公司电力科学研究院 | Noise reduction method and system for medium-voltage carrier signal through wavelet packet combining singular value |
-
2016
- 2016-10-19 CN CN201610913188.8A patent/CN106546436B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2014119406A (en) * | 2012-12-19 | 2014-06-30 | Nippon Telegr & Teleph Corp <Ntt> | Abnormality detection system and abnormality detection method of columnar structure |
| CN103116148A (en) * | 2013-01-30 | 2013-05-22 | 上海理工大学 | Inversion method of nuclear magnetic resonance two-dimensional spectrum |
| CN103345927A (en) * | 2013-07-11 | 2013-10-09 | 暨南大学 | Processing method for detecting and locating audio time domain tampering |
| CN104374574A (en) * | 2014-11-14 | 2015-02-25 | 大连交大融通科技发展有限公司 | Comprehensive performance test bed for super-high-speed train bearing |
| CN105678283A (en) * | 2016-02-17 | 2016-06-15 | 云南电网有限责任公司电力科学研究院 | Noise reduction method and system for medium-voltage carrier signal through wavelet packet combining singular value |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110069875A (en) * | 2019-04-28 | 2019-07-30 | 江铃汽车股份有限公司 | A kind of generation method of the load modal data of dynamic load emulation |
| CN111581715A (en) * | 2020-03-23 | 2020-08-25 | 中国农业大学 | Method for quickly compressing acceleration load spectrum of tractor part |
| CN111581715B (en) * | 2020-03-23 | 2023-08-08 | 中国农业大学 | Rapid compression method for accelerating load spectrum of tractor part |
| CN112539942A (en) * | 2020-11-24 | 2021-03-23 | 上海电机学院 | Characteristic load identification and acceleration test load spectrum compilation method |
| CN114577487A (en) * | 2020-11-30 | 2022-06-03 | 宝能汽车集团有限公司 | Method for simplifying vehicle test conditions, storage medium and electronic device |
| CN114034492A (en) * | 2021-11-03 | 2022-02-11 | 交通运输部公路科学研究所 | Automobile part load spectrum rapid compression method based on Hilbert-Huang transform |
| CN114034492B (en) * | 2021-11-03 | 2024-04-05 | 交通运输部公路科学研究所 | Hilbert-Huang transform-based rapid compression method for load spectrum of automobile part |
| CN114235445A (en) * | 2021-11-26 | 2022-03-25 | 华南理工大学 | Vibration isolator road load spectrum time compression method based on S transformation |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106546436B (en) | 2019-04-09 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106546436A (en) | A kind of auto parts and components loading spectrum is effectively compressed method | |
| CN111563893B (en) | Grading ring defect detection method, device, medium and equipment based on aerial image | |
| CN108021938A (en) | A kind of Cold-strip Steel Surface defect online detection method and detecting system | |
| CN106446809A (en) | Aeroengine load spectrum filtering method based on rain-flow counting method | |
| CN102254174B (en) | Method for automatically extracting information of bare area in slumped mass | |
| CN103530894A (en) | Video target tracking method based on multi-scale block sparse representation and system thereof | |
| CN107832684A (en) | A kind of intelligent vein authentication method and system with independent learning ability | |
| CN108022222A (en) | A kind of thin cloud in remote sensing image minimizing technology based on convolution-deconvolution network | |
| CN108109204A (en) | A kind of method and system for making and rendering large-scale terrain | |
| CN110472743A (en) | Processing method and processing device, equipment and the readable medium that feature is passed through in sample set | |
| CN107506710A (en) | A kind of rolling bearing combined failure extracting method | |
| CN105004722A (en) | Method for rapidly detecting maturity of tobacco leaves | |
| CN107860722A (en) | A kind of honeydew melon inside quality online test method and system | |
| CN113269680A (en) | Image restoration quality evaluation method based on sequencing learning and twin neural network | |
| CN110443303B (en) | Image segmentation and classification-based intelligent identification method for coal-rock microcomponents | |
| CN111581715A (en) | Method for quickly compressing acceleration load spectrum of tractor part | |
| CN109779622A (en) | Ultra-high water cut stage oil reservoir inefficient water filling band characterizing method and device | |
| CN105068119B (en) | The damped system and its device of face ripple in low frequency seismic data | |
| CN107247931A (en) | A kind of De-noising Technique For Vibration Signals of Rotating Machinery | |
| CN108198182A (en) | A kind of composite electric insulator core bar sheath interface performance evaluation method and device | |
| CN106770151A (en) | A kind of method and device of quick detection raman spectral signal | |
| CN109035271A (en) | Image partition method and device, analysis instrument and storage medium | |
| CN114034492B (en) | Hilbert-Huang transform-based rapid compression method for load spectrum of automobile part | |
| CN106153507A (en) | A kind of method of mini-frac proppant sphericity | |
| CN106651786B (en) | The processing method of riverbank region point cloud data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20190409 Termination date: 20211019 |