CN115615684B - Pump shaft health detection method based on axis locus deformation monitoring - Google Patents
Pump shaft health detection method based on axis locus deformation monitoring Download PDFInfo
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- CN115615684B CN115615684B CN202211392643.6A CN202211392643A CN115615684B CN 115615684 B CN115615684 B CN 115615684B CN 202211392643 A CN202211392643 A CN 202211392643A CN 115615684 B CN115615684 B CN 115615684B
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- displacement data
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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
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04B—POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS
- F04B51/00—Testing machines, pumps, or pumping installations
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
- G01B21/32—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant for measuring the deformation in a solid
Abstract
The invention discloses a pump shaft health detection method based on axial center track deformation monitoring. The technical scheme of the invention detects the health of the pump shaft based on the shape change of the shaft center track of the pump shaft without depending on manual experience to determine whether the shaft center track of the pump is abnormal or not, eliminates the influence of factors such as the type, the running environment, the running working condition and the like of the pump on the shape of the shaft center track, has high precision and high sensitivity on the shape deterioration of the shaft center track, and has certain popularization value.
Description
Technical Field
The invention belongs to the field of pump shaft health, and particularly relates to a pump shaft health detection method based on axial center trajectory deformation monitoring.
Background
At the present stage, when various pumps are in a relatively stable working condition during operation, the operation condition of the pump needs to be healthy, but in the actual working process, the operation environment of the pump is complex, so that artificial real-time monitoring cannot be carried out.
However, once the pump has an abnormal problem, the production rhythm is seriously affected or potential safety hazards are brought, so that the real-time remote monitoring of whether the pump normally operates is particularly important; the pump shaft in the pump body can have wear or not to the intermediate problem owing to long-term operation, influences the operating efficiency of pump, increases the energy consumption, consequently need monitor the running state of pump shaft to give healthy early warning when the pump shaft state takes place to deviate from with normal state, reaction and handling problem that can be early reduce running risk and potential maintenance cost.
Disclosure of Invention
The invention provides a pump shaft health detection method based on axis locus deformation monitoring, which can identify the running state of a pump shaft in real time and is used as an important reference basis for pump running maintenance.
The invention provides a pump shaft health detection method based on shaft center track deformation monitoring, which comprises the following steps of:
collecting shaft vibration displacement data of pump operation;
determining an axis trajectory and axis position information based on the displacement data;
determining the angle distribution characteristics of the axle center track based on the axle center information;
comparing the axle center track angle distribution characteristic with an axle center track angle distribution characteristic standard calibrated under a stable working condition, and determining the similarity of the axle center track angle distribution characteristic and the axle center track angle distribution characteristic standard;
and comparing the similarity with a set threshold value, and judging whether the pump shaft is healthy or not based on the comparison result.
As an embodiment, the process of determining the axial center trajectory and the axial center position information is as follows:
collectingαThe collected shaft vibration displacement data is filtered according to the pump shaft vibration displacement data in the rotation period of the individual shaft, and the filtered shaft vibration displacement data V is obtained x And V y In which V is x Representing displacement data in X direction, V y Representing Y-direction displacement data;
according toαV within a rotation period of a single shaft x And V y Average value of (A) O x And O y Determining the shaft center of a pump shaft: (O) x ，O y ）。
As an embodiment, the process of determining the axial center trajectory angle distribution characteristic is as follows:
with the determined axis position as the origin, the method comprisesαThe filtered shaft vibration displacement data in the rotation period of the single shaft are equally divided intomCounting a distribution histogram of the distance from the vibration track point to the original point in each direction interval as an axis track angle distribution characteristic to obtain a common direction intervalmA distance distribution histogram.
As an embodiment, themThe determination mode of each direction interval is as follows:
data from 0 to
Are equally divided intoαA section; />
Wherein the content of the first and second substances,
and &>
Respectively pump shaft vibration data V x And V y Is measured.
As an embodiment, the process of comparing the axial center trajectory angle distribution characteristic with the axial center trajectory angle distribution characteristic standard calibrated under the stable condition is as follows:
firstly, obtain the stabilizing toolWith reference to angular distribution characteristics of the axis track calibrated under conditionsmA distance distribution histogram;
and characterised by the angular distribution of the axis trajectory in real timemOf histograms of distance distribution and of characteristic referencesmNormalizing the distance distribution histograms to obtain two groups of normalized histograms:
H 1 =（h 11 ,h 12 ,...,h 1m ）
H 2 =(h 21 ,h 22 ,...,h 2m )
h nm =（h nm (1),h nm (2),...,h nm (i),...,h 11 (α)）
wherein h is 1m And h 2m Are all represented as a histogram, h nm (i) Is a firstiThe frequency of each histogram distribution interval;
and determining the similarity between the two normalized groups of histograms, and determining the axle center track similarity between the real-time axle center track angle distribution characteristic and the axle center track angle distribution characteristic calibrated under the stable working condition.
As an embodiment, the characteristic reference of the angular distribution of the axis trajectory calibrated under the stable working condition ismThe acquisition process of the distance distribution histogram comprises the following steps:
after the pump is started to run stably, when the flow fluctuation per hour does not exceed a certain fluctuation proportion, taking the pump from the momentαPump shaft vibration displacement data in a rotation period of the shaft are filtered to obtain filtered shaft vibration displacement data;
determining the shaft center of the pump shaft at the moment according to the average value of the X-direction displacement data and the Y-direction displacement data of the shaft vibration displacement data;
averaging the filtered axial vibration displacement data into equal parts by taking the determined axial center position as an originmCounting distribution histograms of distances from the vibration track points to the origin in each direction interval as the distribution characteristics of the axis track angles to obtain a totalmA distance distribution histogram, whichmThe distance distribution histogram is the axle center track angle distribution characteristic calibrated under the stable working conditionAnd (4) reference.
As an embodiment, the process of determining the axis locus similarity includes:
obtaining a m-dimensional similarity vector S = (S) 1 ,s 2 ,...,s m ）：
As an embodiment, the judging whether the pump shaft is healthy or not based on the comparison result specifically includes:
when the axle center trajectory similarity is lower than a set threshold, that is, the shape of the axle center trajectory is greatly changed from the axle center trajectory in a stable running state of the pump, and under the condition that the working condition is not changed, the potential risk may occur to the pump shaft.
As an embodiment, the threshold setting process is:
before the initial stage of the pump is smoothly operatedβ6-sigma lower limit of distribution characteristic of shaft center track of pump shaft and reference similarity serves as alarm threshold
；
Wherein, the first and the second end of the pipe are connected with each other,
is frontβThe mean value of the similarity between the distribution characteristic of the axle center locus of the pump shaft and the reference>
Is frontβAnd standard deviation of the distribution characteristics of the axle center track of the pump shaft and the reference similarity. />
Compared with the prior art, the invention has the remarkable advantages and beneficial effects that:
(1) The pump shaft health detection starts from the shape change of the shaft center track, adopts the methods of interval statistics and similarity analysis, does not need to rely on expert experience to determine whether the shaft center track of the pump is abnormal, eliminates the influence of factors such as the type, the running environment and the running working condition of the pump on the shape of the shaft center track, and has high precision and high sensitivity on the shape deterioration of the shaft center track;
(2) According to the technical scheme, the axle center track operation reference standard of the pump shaft can be adjusted in a self-adaptive mode according to the operation condition of the pump under the stable working condition after operation, and automatic optimization of health detection of the pump shaft is achieved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a flow chart of the steps of a pump shaft health detection method based on axial center trajectory deformation monitoring according to the present invention.
Fig. 2 is a schematic diagram of a determined axial center trajectory and axial center position in an embodiment of the invention.
Fig. 3 is a schematic diagram of the determined axis track points and distribution intervals in the embodiment of the present invention.
FIG. 4 is a histogram of the distribution of axial trajectory angles in an embodiment of the present invention.
Fig. 5 is a standard distribution histogram of the axial trace angle distribution characteristics calibrated under the stable operating condition determined in the embodiment of the present invention.
Detailed Description
It is easily understood that various embodiments of the present invention can be conceived by those skilled in the art according to the technical solution of the present invention without changing the essential spirit of the present invention. Therefore, the following detailed description and the accompanying drawings are merely illustrative of the technical aspects of the present invention, and should not be construed as all of the present invention or as limitations or limitations on the technical aspects of the present invention. Rather, these embodiments are provided so that this disclosure will be thorough and complete. The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and which together with the embodiments of the invention serve to explain the innovative concepts of the invention.
Examples
With reference to fig. 1, a pump shaft health detection method based on axis locus deformation monitoring includes the following steps:
collecting shaft vibration displacement data of pump operation;
determining an axis locus and axis position information based on the displacement data;
determining an axis track angle distribution characteristic based on the axis information;
comparing the axial center track angle distribution characteristic with an axial center track angle distribution characteristic standard calibrated under a stable working condition, and determining the similarity of the axial center track angle distribution characteristic and the axial center track angle distribution characteristic standard;
and comparing the similarity with a set threshold value, and judging whether the pump shaft is healthy or not based on a comparison result.
The process of determining the axis track and the axis position information is as follows:
recording the sampling frequency fs (Hz) and the shaft rotation speed n (revolutions per minute), collecting pump shaft vibration displacement data within 100 shaft rotation periods, selecting an appropriate filter, and filtering the collected shaft vibration displacement data x And V y In which V is x Representing displacement data in the X direction, V y Representing Y-direction displacement data;
according to V within 100 shaft rotation periods x And V y Average value of (A) O x And O y Determining the shaft center of a pump shaft: (O) x ，O y ) The determined axis locus and axis position in this embodiment are shown in fig. 2;
the process for determining the angular distribution characteristics of the axial center trajectory comprises the following steps:
with reference to fig. 3 and 4, the filtered shaft vibration displacement data in 100 shaft rotation cycles are equally divided into two with the determined shaft center position as the originmCounting a distribution histogram of the distance from the vibration track point to the original point in each direction interval as an axis track angle distribution characteristic to obtain a common direction intervalmA distance distribution histogram.
The above-mentionedmThe determination mode of each direction interval is as follows:
data from 0 to
Are divided into 100 intervals;
wherein, the first and the second end of the pipe are connected with each other,
and &>
Respectively pump shaft vibration data V x And V y Is measured.
The process of comparing the axle center track angle distribution characteristic with the axle center track angle distribution characteristic standard calibrated under the stable working condition is as follows:
firstly, obtaining the calibrated axle center track angle distribution characteristic reference under the stable working conditionmA distance distribution histogram;
and characterised by the angular distribution of the axis trajectory in real timemOf histograms of distance distribution and of characteristic referencesmCarrying out normalization processing on the distance distribution histograms to obtain two groups of normalized histograms:
H 1 =（h 11 ,h 12 ,...,h 1m ）
H 2 =(h 21 ,h 22 ,...,h 2m )
h nm =（h nm (1),h nm (2),...,h nm (i),...,h 11 (α)）
wherein h is 1m And h 2m Are all represented as a histogram, h nm (i) Is as followsiThe frequency of each histogram distribution interval is normalized, and the area of the whole histogram is 1.
And determining the similarity between the two normalized groups of histograms, and determining the axle center track similarity between the real-time axle center track angle distribution characteristic and the axle center track angle distribution characteristic calibrated under the stable working condition.
The characteristic standard of the axle center track angle distribution calibrated under the stable working conditionmThe acquisition process of the distance distribution histogram comprises the following steps:
after the pump is started to run stably, when the flow fluctuation per hour does not exceed a certain fluctuation proportion, taking the pump from the momentαThe pump shaft vibration displacement data in the rotation period of the shaft are filtered to obtain filtered shaft vibration displacement data;
determining the shaft center of the pump shaft at the moment according to the average value of the X-direction displacement data and the Y-direction displacement data of the shaft vibration displacement data;
averaging the filtered axial vibration displacement data into equal parts by taking the determined axial center position as an originmCounting a distribution histogram of the distance from the vibration track point to the original point in each direction interval as an axis track angle distribution characteristic to obtain a common direction intervalmA distance distribution histogram ofmThe distance distribution histogram is a characteristic reference of the angular distribution of the axis trajectory calibrated under the stable working condition, as shown in fig. 5.
The determination process of the axle center track similarity comprises the following steps:
obtaining m-dimensional similarity vector S = (S) 1 ,s 2 ,...,s m ）：
The judgment of whether the pump shaft is healthy or not based on the comparison result specifically comprises the following steps:
when the axle center trajectory similarity is lower than a set threshold, that is, the shape of the axle center trajectory is greatly changed from the axle center trajectory in a stable running state of the pump, and under the condition that the working condition is not changed, the potential risk may occur to the pump shaft.
The threshold setting process comprises the following steps:
taking the lower limit of 6-sigma of the similarity between the distribution characteristics of the first 100 pump shaft axis tracks after the initial stable operation of the pump and the reference as an alarm threshold
；
Wherein, the first and the second end of the pipe are connected with each other,
is the mean value of the similarity between the distribution characteristics of the first 100 pump shaft axial loci and the reference>
The standard deviation of the similarity between the first 100 pump shaft axis locus distribution characteristics and the reference is shown.
The pump shaft center health detection method starts with the monitoring of the shape change of the shaft center track, adopts the methods of interval statistics and similarity analysis, does not need to rely on expert experience to determine whether the shaft center track of the pump is abnormal, eliminates the influence of factors such as the type, the running environment and the running working condition of the pump on the shape of the shaft center track, and has high precision and high sensitivity on the shape deterioration of the shaft center track.
The above description is only a preferred embodiment of the present invention, but the scope of the present invention is not limited thereto,
any changes or substitutions that may be easily made by those skilled in the art within the technical scope of the present disclosure are intended to be included within the scope of the present disclosure.
It should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes described in a single embodiment or with reference to a single figure, for the purpose of streamlining the disclosure and aiding in the understanding of various aspects of the invention by those skilled in the art. However, the present invention should not be construed to include features in the exemplary embodiments which are all the essential technical features of the patent claims.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
It should be understood that the modules, units, components, and the like included in the device of one embodiment of the present invention may be adaptively changed to be provided in a device different from that of the embodiment. The different modules, units or components comprised by the apparatus of an embodiment may be combined into one module, unit or component or may be divided into a plurality of sub-modules, sub-units or sub-components.
The modules, units or components in the embodiments of the present invention may be implemented in hardware, may be implemented in software running on one or more processors, or may be implemented in a combination thereof. Those skilled in the art will appreciate that embodiments in accordance with the present invention may be practiced using a microprocessor or Digital Signal Processor (DSP). The present invention may also be embodied as a computer program product or computer-readable medium for performing a portion or all of the methods described herein.
Claims (5)
1. A pump shaft health detection method based on axis locus deformation detection is characterized by comprising the following steps:
collecting shaft vibration displacement data of pump operation;
determining the axis track and the axis position information based on the displacement data, specifically;
collectingαThe pump shaft vibration displacement data in the rotation period of the shaft is collected and filtered to obtain filtered shaft vibration displacement data V x And V y In which V is x Representing displacement data in X direction, V y Representing Y-direction displacement data;
according toαV within a rotation period of a single shaft x And V y Average value of (A) O x And O y Determining the shaft center of a pump shaft: (O) x ，O y ）；
Determining the angle distribution characteristics of the axle center track based on the axle center information, specifically comprising the following steps:
with the determined axis position as the origin, the method comprisesαThe filtered shaft vibration displacement data in the rotation period of the single shaft are equally divided intomCounting a distribution histogram of the distance from the vibration track point to the original point in each direction interval as an axis track angle distribution characteristic to obtain a common direction intervalmA distance distribution histogram;
the above-mentionedmThe determination mode of each direction interval is as follows:
data from 0 to
Are equally divided intoαA section;
wherein the content of the first and second substances,
and &>
Respectively pump shaft vibration data V x And V y The maximum value of (a);
comparing the axle center track angle distribution characteristic with an axle center track angle distribution characteristic standard calibrated under a stable working condition, and determining the similarity of the axle center track angle distribution characteristic standard, wherein the method specifically comprises the following steps:
firstly, obtaining a calibrated axis track angle distribution characteristic standard under a stable working conditionmA distance distribution histogram;
and characterised by the angular distribution of the axis trajectory in real timemOf histograms of distance distribution and of characteristic referencesmNormalizing the distance distribution histograms to obtain two groups of normalized histograms:
H 1 =（h 11 ,h 12 ,...,h 1m ）
H 2 =(h 21 ,h 22 ,...,h 2m )
h nm =（h nm (1),h nm (2),...,h nm (i),...,h 11 (α)）
wherein h is 1m And h 2m Are all represented as a histogram, h nm (i) Is as followsiThe frequency of each histogram distribution interval;
determining the similarity between the two normalized groups of histograms, and determining the axle center track similarity between the real-time axle center track angle distribution characteristic and the axle center track angle distribution characteristic calibrated under the stable working condition;
and comparing the similarity with a set threshold value, and judging whether the shaft pump is healthy or not based on the comparison result.
2. The method for detecting the health of an axial pump based on axial trajectory deformation detection as claimed in claim 1, wherein the axial trajectory angle distribution characteristic calibrated under the stable working condition is based onmThe acquisition process of the distance distribution histogram comprises the following steps:
after the pump is started to run stably, when the flow fluctuation per hour does not exceed a certain fluctuation proportion, taking the pump from the momentαPump shaft vibration displacement data in a rotation period of the shaft are filtered to obtain filtered shaft vibration displacement data;
determining the shaft center of the pump shaft at the moment according to the average value of the X-direction displacement data and the Y-direction displacement data of the shaft vibration displacement data;
averaging the filtered axial vibration displacement data into equal parts by taking the determined axial center position as an originmCounting a distribution histogram of the distance from the vibration track point to the original point in each direction interval as an axis track angle distribution characteristic to obtain a common direction intervalmA distance distribution histogram, whichmThe distance distribution histogram is the calibrated axis track angle distribution characteristic standard under the stable working condition.
3. The method for detecting the health of the shaft pump based on the deformation detection of the shaft center track as claimed in claim 1, wherein the determination process of the similarity of the shaft center track is as follows:
obtaining a m-dimensional similarity vector S = (S) 1 ,s 2 ,...,s m ）：
。
4. The method for detecting the health of the shaft pump based on the deformation detection of the shaft center trajectory according to claim 3, wherein the judgment of whether the shaft pump is healthy or not based on the comparison result is specifically as follows:
when the axle center track similarity is lower than a set threshold value, the shape of the axle center track is represented to be changed with the axle center track when the pump is in a stable running state, and under the condition that the working condition is not changed, the potential risk occurs to the pump shaft.
5. The method for detecting the health of the shaft pump based on the deformation detection of the shaft center track as claimed in claim 4, wherein the threshold setting process comprises:
before the initial stage of the pump is smoothly operatedβTaking the 6-sigma lower limit of the distribution characteristic of the shaft axis locus of the pump shaft and the reference similarity as an alarm threshold value
；
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