NL2024358B1 - Method for quantitatively evaluating dynamic quality of rolling bearing based on permutation entropy - Google Patents
Method for quantitatively evaluating dynamic quality of rolling bearing based on permutation entropy Download PDFInfo
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- NL2024358B1 NL2024358B1 NL2024358A NL2024358A NL2024358B1 NL 2024358 B1 NL2024358 B1 NL 2024358B1 NL 2024358 A NL2024358 A NL 2024358A NL 2024358 A NL2024358 A NL 2024358A NL 2024358 B1 NL2024358 B1 NL 2024358B1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M13/00—Testing of machine parts
- G01M13/04—Bearings
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
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- General Engineering & Computer Science (AREA)
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- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
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Abstract
The present invention discloses a method for quantitatively evaluating dynamic quality of a rolling bearing based on a permutation entropy. First, an outer ring deformation signal representing dynamic performance of a rolling bearing is obtained through an eddy current displacement sensor; then a time series of the obtained outer ring deformation signal is initialized, a phase space is reconstructed and elements are rearranged in ascending order; a permutation entropy of the obtained outer ring deformation signal is calculated; and normalization processing is performed. In the present invention; by researching a technology for obtaining a high signal-to-noise ratio test signal representing dynamic performance of a bearing based on detection information about outer ring deformation of the bearing; characteristics of bearings of different quality are accurately reflected. On the basis of obtaining a high signal-to-noise ratio signal; a method for quantitatively evaluating dynamic performance of a rolling bearing based on a permutation entropy is researched; to evaluate design that influences quality of a bearing; and effective fault classification and fault degree in a manufacturing process.
Description
BACKGROUND Technical Field The present invention relates to the field of mechanical fault diagnosis, and specifically, to a method for quantitatively evaluating dynamic quality of a rolling bearing based on a permutation entropy. Related Art Rolling bearings are components widely applied to rotary machines. Dynamic quality and an operating state of a rolling bearing have a direct impact on performance of a device. A high signal-to-noise ratio detection technology can reduce difficulty in subsequent signal processing and is a basis of signal feature extraction and tendency assessment. Faced with demands for fault prediction and quality assessment of bearings being typical basic components, a conventional detection method based on an acceleration signal has shortcomings such as many noise interference sources and a low signal-to-noise ratio, and can hardly satisfy a demand for bearing performance evaluation. Therefore, it is of great significance to research quantitative evaluation of dynamic quality of a rolling bearing.
SUMMARY An objective of the present invention is to provide a method for quantitatively evaluating dynamic quality of a rolling bearing based on a permutation entropy, which overcomes the above shortcomings in the prior art, reflects characteristics of bearings of different quality and 1s of great significance to quantitatively evaluate dynamic quality of a rolling bearing, The objective of the present invention may be achieved through the following technical solution.
A method for quantitatively evaluating dynamic quality of a rolling bearing based on a permutation entropy includes the following steps.
A first step is to obtain, through an eddy current displacement sensor, an outer ring deformation signal representing quality and dynamic performance of a rolling bearing, A second step is to calculate a permutation entropy.
A third step is to perform normalization processing on a value of the permutation entropy: 0 < Hp, = Hp/In(m!) < 1, where 0 < Hp <1.
A fourth step is to output a permutation entropy result, consult an evaluation result table of dynamic performance of a permutation entropy of a tested bearing and obtain a classification of dynamic quality of an experimented bearing.
Further, the calculating the permutation entropy includes the following steps: 1) initializing a time series, where the obtained outer ring deformation signal is divided to a plurality of sub-series with a length of w and a quantity of length selection segments of the sub-series is equal to 10+1; 2) reconstructing a phase space, where phase-space reconstruction is performed on each sub-series and a vector space of a sub-time series is obtained: X(i) = {x(i), x(i + 3) arranging elements, where m elements in X(i) are arranged in ascending order of values of the elements and elements of equal values are arranged in original order; and 4) calculating the permutation entropy, where a parameter of the permutation entropy is selected, a probability of appearance of each element in X(i) is calculated and a value of a permutation entropy of each sub-time series is calculated: Hp(m) = — XX P,InP;. Beneficial effects of the present invention: By researching a technology for obtaining a high signal-to-noise ratio test signal representing dynamic performance of a bearing based on detection information about outer ring deformation of the bearing, characteristics of bearings of different quality are accurately reflected. On the basis of obtaining a high signal-to-noise ratio signal, a method for quantitatively evaluating dynamic performance of a rolling bearing based on a permutation entropy is researched, to evaluate design that influences quality of a bearing, and effective fault classification and fault degree in a manufacturing process.
BRIEF DESCRIPTION OF THE DRAWINGS The following further describes the present invention with reference to the accompanying drawings. FIG. 1 is a flowchart of the present invention; FIG. 2 is a schematic diagram of installing an eddy current displacement sensor; FIG. 3 is a flowchart of obtaining a signal by a vibration acceleration sensor; FIG. 4 is a flowchart of obtaining a signal by an eddy current displacement sensor; FIG. 5 is a diagram of steps of calculating a permutation entropy; FIG. 6 is a diagram of selecting a parameter of a permutation entropy; and FIG. 7 is an evaluation result table of dynamic performance of a permutation entropy of a tested bearing
DETAILED DESCRIPTION The following clearly and completely describes the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments instead of all embodiments of the present invention. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. In the description of the present invention, it should be understood that orientation or position relationships indicated by the terms such as "opening", "on", "below", "thickness",
"top", "middle", "length", "inside", and "around" are used only for ease and brevity of description of the present invention, rather than indicating or implying that the mentioned assembly or component must have a particular orientation or must be constructed and operated in a particular orientation. Therefore, such terms should not be construed as S limiting of the present invention.
A method for quantitatively evaluating dynamic quality of a rolling bearing based on a permutation entropy, as shown in FIG. 1, includes the following steps.
A first step 1s to obtain, through an eddy current displacement sensor, an outer ring deformation signal representing quality and dynamic performance of a rolling bearing. As shown in FIG. 2, an eddy current displacement sensor is installed. The eddy current displacement sensor 4 is fixed on a bearing seat 1 through a set screw 2 and a nut 3. The outer ring deformation signal representing quality and dynamic performance of the rolling bearing is obtained through the eddy current displacement sensor. The signal carries information about the quality and the dynamic performance of the rolling bearing.
A transmission chain of a vibration acceleration sensor whose signals are more than those of an eddy current displacement sensor is selected. As shown in FIG. 3, in a process in which a vibration acceleration sensor obtains a fault signal, the fault signal needs to pass through a transmission chain from a fault source, a loaded rolling element, and an outer ring of a bearing, to a housing of a bearing seat, so that the vibration acceleration sensor obtains the fault signal. As shown in FIG. 4, in a process in which an eddy current displacement sensor obtains a fault signal, the fault signal needs to pass through a signal transmission chain from a fault source, and a loaded rolling element, to an outer ring of a bearing, so that the eddy current displacement sensor obtains the fault signal. Therefore, a transmission chain of an eddy current displacement sensor in which a bearing seat is omitted compared with that of a vibration acceleration sensor is selected.
A second step is to calculate a permutation entropy, as shown in FIG. 5, including the following steps. 1) A time series 1s initialized. The obtained outer ring deformation signal is divided into a plurality of sub-series with a length of w.
The length of the sub-series depends on a reasonable choice between a signal processing time and stability of a permutation entropy result.
This specification follows precedents of engineering application and a quantity of selection segments is equal to 10+1. 5 2) A phase space is reconstructed.
Phase-space reconstruction is performed on each sub-series and a vector space of a sub-time series is obtained: X(i) = {x(i),x(i + Tt), ‚x(i + (m — I)T)}. Phase-space reconstruction is a prerequisite for calculation of the value of the permutation entropy. 3) Elements are arranged, where m elements in X(i) are arranged in ascending order of values of the elements and elements of equal values are arranged in original order.
In a practical operation process, it is found that when a signal has more than five digits (including the decimal point), a calculation time of the permutation entropy is excessively long and output consistency is poor, which is not conducive to on-line detection.
Therefore, during the arrangement, precision of the permutation entropy and output consistency should be considered comprehensively and then signals are arranged after phase-space reconstruction is performed. 4) The permutation entropy is calculated.
A parameter of the permutation entropy is selected, a probability of appearance of each element in X(i) is calculated, and a value of a permutation entropy of each sub-time series is calculated: Hp(m) = — XK P;inP,. A third step is to perform normalization processing on a value of the permutation entropy: 0 < Hp, = Hp/In (m!) < 1, where: 0 < Hp <1. A fourth step is to output a permutation entropy result, consult an evaluation result table of dynamic performance of a permutation entropy of a tested bearing shown in FIG. 7 and obtain a classification of dynamic quality of an experimented bearing.
In the descriptions of this specification, descriptions using reference terms "an embodiment”, "an example", and "a specific example" mean that specific characteristics, structures, materials, or features described with reference to the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic descriptions of the foregoing terms are not necessarily directed at a same embodiment or example. In addition, the described specific characteristics, structures, materials, or features can be combined in a proper manner in any one or more embodiments or examples.
The above illustrates and describes the fundamental principles, major characteristics and advantages of the present invention. A person skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and the descriptions in the specification describe only the principles of the present invention.
There may be various alterations and improvements made to the present invention without departing from the spirit and scope of the present invention. All these alterations and improvements shall fall into the protection scope of the present invention.
Claims (2)
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910474907.4A CN110188486A (en) | 2019-06-03 | 2019-06-03 | A kind of rolling bearing dynamic mass method for quantitatively evaluating based on arrangement entropy |
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| NL2024358B1 true NL2024358B1 (en) | 2020-12-08 |
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| NL2024358A NL2024358B1 (en) | 2019-06-03 | 2019-12-02 | Method for quantitatively evaluating dynamic quality of rolling bearing based on permutation entropy |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113252348A (en) * | 2021-05-13 | 2021-08-13 | 盾构及掘进技术国家重点实验室 | Dynamic performance test and evaluation method for main drive bearing of tunnel boring machine |
| CN114782453A (en) * | 2022-06-23 | 2022-07-22 | 张家港Aaa精密制造股份有限公司 | Bearing quality detection method and system based on intelligent manufacturing |
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| CN108364021A (en) * | 2018-02-08 | 2018-08-03 | 西北工业大学 | A kind of bearing fault characteristics extracting method arranging entropy based on level |
| CN109253882A (en) * | 2018-10-08 | 2019-01-22 | 桂林理工大学 | A kind of rotor crack fault diagnostic method based on variation mode decomposition and gray level co-occurrence matrixes |
| DE102017120756A1 (en) * | 2017-09-08 | 2019-03-14 | Schaeffler Technologies AG & Co. KG | Sensor bearing unit with rolling bearing and measuring ring |
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| CN102252843B (en) * | 2011-07-21 | 2013-01-09 | 河南科技大学 | Assessment method for rolling bearing performance variation |
| CN105758644A (en) * | 2016-05-16 | 2016-07-13 | 上海电力学院 | Rolling bearing fault diagnosis method based on variation mode decomposition and permutation entropy |
| CN106487359B (en) * | 2016-10-14 | 2019-02-05 | 石家庄铁道大学 | The building method of Morphologic filters based on self-adapting multi-dimension AVG-Hat transformation |
| CN108760300A (en) * | 2018-04-19 | 2018-11-06 | 西安工业大学 | A method of intelligent fault diagnosis being carried out to it according to bearing vibration signal |
| CN108869145B (en) * | 2018-04-26 | 2020-03-24 | 中国水利水电科学研究院 | Pump station unit diagnosis method based on composite characteristic index and depth limit learning machine |
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- 2019-06-03 CN CN201910474907.4A patent/CN110188486A/en active Pending
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102017120756A1 (en) * | 2017-09-08 | 2019-03-14 | Schaeffler Technologies AG & Co. KG | Sensor bearing unit with rolling bearing and measuring ring |
| CN108364021A (en) * | 2018-02-08 | 2018-08-03 | 西北工业大学 | A kind of bearing fault characteristics extracting method arranging entropy based on level |
| CN109253882A (en) * | 2018-10-08 | 2019-01-22 | 桂林理工大学 | A kind of rotor crack fault diagnostic method based on variation mode decomposition and gray level co-occurrence matrixes |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113252348A (en) * | 2021-05-13 | 2021-08-13 | 盾构及掘进技术国家重点实验室 | Dynamic performance test and evaluation method for main drive bearing of tunnel boring machine |
| CN113252348B (en) * | 2021-05-13 | 2023-12-12 | 盾构及掘进技术国家重点实验室 | Tunnel boring machine main driving bearing dynamic performance test evaluation method |
| CN114782453A (en) * | 2022-06-23 | 2022-07-22 | 张家港Aaa精密制造股份有限公司 | Bearing quality detection method and system based on intelligent manufacturing |
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| CN110188486A (en) | 2019-08-30 |
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