CN116893036A - Plunger pump leakage diagnosis method with smooth acceleration signal sequence time window characteristics - Google Patents
Plunger pump leakage diagnosis method with smooth acceleration signal sequence time window characteristics Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 35
- 238000000034 method Methods 0.000 title claims abstract description 28
- 108010076504 Protein Sorting Signals Proteins 0.000 title claims abstract description 15
- 238000012545 processing Methods 0.000 claims abstract description 10
- 238000009499 grossing Methods 0.000 claims abstract description 9
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 2
- 238000012544 monitoring process Methods 0.000 abstract description 5
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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
- G01M3/00—Investigating fluid-tightness of structures
- G01M3/02—Investigating fluid-tightness of structures by using fluid or vacuum
- G01M3/04—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point
- G01M3/24—Investigating fluid-tightness of structures by using fluid or vacuum by detecting the presence of fluid at the leakage point using infrasonic, sonic, or ultrasonic vibrations
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- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/213—Feature extraction, e.g. by transforming the feature space; Summarisation; Mappings, e.g. subspace methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
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Abstract
The application discloses a plunger pump leakage diagnosis method with smooth time window characteristics of an acceleration signal sequence, which is characterized in that a vibration acceleration signal of a plunger pump is subjected to standardized processing, a series of time windows with equal length are designed to cut off the signal, pulse factor characteristic values of the signal are calculated in each time window, calculation results of all the time windows are averaged to obtain current input smooth characteristics, the values are used as plunger pump leakage fault characteristic values of current point detection input data, and finally the occurrence time of plunger pump leakage is accurately identified in a series of plunger pump point detection data by determining data acquisition time corresponding to the abnormal characteristic values. The method for smoothing the sectional characteristics of the acceleration signals avoids leakage diagnosis interference caused by fluctuation of the effective value of the measured plunger pump under the variable working condition and influence of sporadic impact characteristics on spot inspection data characteristic extraction, simultaneously can accurately extract the characteristic value of the acceleration pulse factor containing the leakage information of the plunger pump, can complete automatic windowing and diagnosis only by a small amount of parameter presetting, greatly improves the monitoring and diagnosis efficiency of the plunger pump, ensures more accurate analysis of the plunger state and more reliable diagnosis result; through example evidence, the application can effectively diagnose the leakage fault of the plunger, and has wide practicability.
Description
Technical Field
The application relates to a plunger pump leakage diagnosis method with smooth acceleration signal sequence time window characteristics, and belongs to the field of mechanical fault diagnosis and signal processing.
Background
The plunger pump is used as an important device of a hydraulic system, and the running state of the plunger pump directly influences the working efficiency of the whole system. Therefore, the method has a key meaning for fault diagnosis and state monitoring of the plunger pump. The plunger leakage is one of the most common faults of the plunger pump, and once the plunger pump has leakage faults, the pump body is often vibrated, the noise is increased, and the working efficiency is reduced; and in severe cases, the hydraulic system cannot normally output, so that work stagnation and industrial accidents are caused. Vibration monitoring is the most dominant and most widely used form of fault diagnosis at present, and is one of the most effective methods. The time sequence analysis of the vibration signal characteristic parameters can be used for effectively measuring the running state of the equipment, and important positions are occupied in vibration monitoring. However, since the motion state of the plunger pump is complex, the reciprocating impact waveform usually dominates the vibration signal, the signal characteristic change is covered by impact caused by early leakage fault, and the characteristic analysis on the vibration acceleration signal of the plunger pump cannot be reliably associated with the leakage fault, so that an effective method for diagnosing the leakage fault of the plunger pump is still lacking.
Disclosure of Invention
The application provides a plunger pump leakage diagnosis method with smooth acceleration signal sequence time window characteristics, which is used for extracting signal leakage diagnosis characteristic values to diagnose plunger leakage.
The technical scheme of the application is as follows: the method for diagnosing the leakage of the plunger pump comprises the steps of smoothing the time window characteristics of an acceleration signal sequence; the method comprises the following steps:
s1, performing signal high-pass filtering processing on acceleration signals of a reciprocating plunger pump in a period of time acquired by a vibration sensor, and extracting effective signal components required by analysis;
s2, performing standardized processing on acceleration signals of the reciprocating plunger pump in a period of time acquired by the vibration sensor, and eliminating plunger pump leakage diagnosis interference caused by effective value fluctuation;
s3, designing a series of time windows with equal length to equally divide plunger pump data, and respectively calculating pulse factors of a series of windowed plunger pump vibration acceleration data;
s4, calculating an average value of pulse factor characteristic values calculated in the time window sequence, and taking the average value as a plunger pump leakage fault characteristic value of current spot inspection input data;
s5, judging abnormal values of the leakage fault characteristic values of the plunger pump, and diagnosing the leakage condition of the plunger pump.
The step S1 specifically comprises the following steps:
and eliminating shutdown data of the speed signal of the reciprocating plunger pump in a period of time, which is acquired by the vibration sensor, selecting a 4-order Butterworth filter for the speed signal of which the shutdown data is eliminated, setting the lower cut-off frequency to be 1000Hz, and performing high-pass filtering to obtain the preprocessed effective acceleration vibration component.
The step S2 is specifically as follows
And performing z-score data standardization algorithm processing on the filtered signals, and eliminating the influence of effective value fluctuation under variable working conditions on the leakage diagnosis of the plunger pump.
The method for eliminating the shutdown data specifically comprises the following steps: and setting a threshold according to the signal effective value, and rejecting the data with the effective value lower than 1 as shutdown data.
The step S3 specifically comprises the following steps:
dividing the whole section of signal with the data length N equally by a series of time windows with the design number of T and the length of l, and obtaining T section of sub-signals after downward rounding, whereinThe arbitrary length T is left after rounding f As the t+1 (last) th signal. Then, pulse factor characteristic calculation is carried out on the T-section sub-signal with the length of l, and a pulse factor characteristic value set P= { P is obtained 1 ,P 2 ,P 3 ,…,P T-1 ,P T }。
The step S4 specifically comprises the following steps:
calculating average value of pulse factor characteristic value set P to obtainTo->As a leak diagnosis characteristic value of the current spot check input data.
The number of time window sequences is preset to 5.
The step S5 specifically comprises the following steps:
and analyzing the leakage diagnosis characteristic value P of the spot check data, and diagnosing that the water injection pump leaks when the abnormality is lower than the normal value.
The beneficial effects of the application are as follows: according to the application, interference of effective value fluctuation on plunger pump leakage fault diagnosis under variable working conditions is eliminated through a data standardization method, a series of equal-length time windows are established to equally divide signals, then pulse factor characteristic values are obtained in each time window, finally pulse factor characteristic values of sub-signal segments in all time windows are averaged, and the average value is taken as the leakage fault characteristic value of current spot inspection data for diagnosis. The method for smoothing the sectional characteristics of the acceleration signals avoids leakage diagnosis interference caused by fluctuation of the effective value of the measured plunger pump under the variable working condition and influence of sporadic impact characteristics on spot inspection data characteristic extraction, simultaneously can accurately extract the characteristic value of the acceleration pulse factor containing the leakage information of the plunger pump, can complete automatic windowing and diagnosis only by a small amount of parameter presetting, greatly improves the monitoring and diagnosis efficiency of the plunger pump, ensures more accurate analysis of the plunger state and more reliable diagnosis result; through example evidence, the application can effectively diagnose the leakage fault of the plunger, and has wide practicability.
Drawings
FIG. 1 is a flow chart of the present application;
FIG. 2 is a time domain waveform of acceleration signals for a set of non-shutdown conditions of a plunger pump of an oil production plant in an application embodiment of the present application;
FIG. 3 is an enlarged view of a portion of the signal of FIG. 2;
FIG. 4 is a high pass filtered result of the signal of FIG. 3;
FIG. 5 is a waveform of a complete acceleration time domain signal after high pass filtering and data normalization;
FIG. 6 is a representation of a time domain signal before windowing and a windowing position;
FIG. 7 is a graph showing the result of windowing the signal of FIG. 6;
FIG. 8 is a time domain waveform obtained after 25 pieces of spot check data are spliced;
fig. 9 is a leakage fault characteristic value trend chart obtained by extracting 25 pieces of spot inspection data.
Detailed Description
Example 1: as shown in fig. 1-9, the method for diagnosing the leakage of the plunger pump with smooth time window characteristics of the acceleration signal sequence comprises the following steps:
s1, performing signal high-pass filtering processing on acceleration signals of a reciprocating plunger pump in a period of time acquired by a vibration sensor, and extracting effective signal components required by analysis;
s2, performing standardized processing on acceleration signals of the reciprocating plunger pump in a period of time acquired by the vibration sensor, and eliminating plunger pump leakage diagnosis interference caused by effective value fluctuation;
s3, designing a series of time windows with equal length to equally divide plunger pump data, and respectively calculating pulse factors of a series of windowed plunger pump vibration acceleration data;
s4, calculating an average value of pulse factor characteristic values calculated in the time window sequence, and taking the average value as a plunger pump leakage fault characteristic value of current spot inspection input data;
s5, judging abnormal values of the leakage fault characteristic values of the plunger pump, and diagnosing the leakage condition of the plunger pump.
Further, the application provides the following implementation procedures:
the plunger pump data is 35 groups of data acquired by a plunger pump of a certain oil extraction factory in 10 months in 2020, wherein 18 groups of data are acquired under the working condition that three plungers 1#, 3#, 5# have leakage faults, and 17 groups of data are acquired after normal plungers are replaced. The plunger pump has 5 plungers to participate in acting, the data sampling frequency is 51.2kHz, the collection time length is 0.8s, and the collection signal unit is gravity acceleration g.
Step 1: selecting a 4-order Butterworth filter for vibration acceleration signals of the reciprocating plunger pump in a period of time acquired by the vibration sensor, setting the lower cut-off frequency to be 1000Hz, and performing high-pass filtering to obtain preprocessed effective vibration acceleration signals; wherein, because the data is collected on the manual site, the data is known as the data under the running state, and the shutdown data removing step described in the method S1 is not performed.
Specific: and selecting a 4-order Butterworth filter for the acceleration signal, setting the lower cut-off frequency to 1000Hz, and performing high-pass filtering to obtain the preprocessed effective vibration acceleration signal. As shown in FIG. 2, a 4-order Butterworth filter is selected for the original signal, the high-pass filtering is performed on the original data by setting the lower cut-off frequency to 1000Hz, the visible low-frequency interference is restrained after the filtering, and the periodic impact is reserved. As shown in fig. 3 (original signal partial amplification) and fig. 4 (filtered signal partial amplification), a comparison of the two shows that the low frequency interference component of the filtered signal shown in fig. 4 is suppressed.
The lower cutoff frequency is set to be 1000Hz, so that low-frequency interference in signals is avoided to a certain extent, the amplitude of signal components higher than 1000Hz is kept higher, the frequency band containing fault information can be covered, and further analysis is facilitated.
Step 2: the signal amplitude is normalized using the z-score data normalization method. The complete signal after pretreatment is shown in fig. 5.
Step 3: since the length of single spot data is 40960 and the number of time windows is preset to 5, the calculation of the time window length is 8192, and the signals before and after windowing are shown in fig. 6 and 7, respectively. Further, pulse factor characteristic values are respectively carried out on the signals in each time window.
Step 4: calculating an average value of pulse factor characteristic values calculated in the time window sequence, and taking the average value as a plunger pump leakage fault characteristic value of current point detection input data; taking 25 pieces of point detection data before and after the occurrence of the leakage fault as an example, the spliced vibration acceleration time domain signals are shown in fig. 8, wherein the last 13 pieces of data are maintained data. The 25 leak fault signature trend graphs are shown in fig. 9.
Step 5: from fig. 9, the abnormal characteristic value is determined, and it is known that the characteristic value is continuously abnormal low value during the collection of the first 12 pieces of spot inspection data, and then the leakage fault characteristic value is obviously improved and relatively stable in a state after maintenance from the 13 th piece of data.
In conclusion, the method is successfully applied to the vibration data of the plunger pump in the industrial field, the leakage fault of the plunger pump in the industrial field is diagnosed, and the feasibility and the effectiveness of the method are proved.
While the present application has been described in detail with reference to the drawings, the present application is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present application within the knowledge of those skilled in the art.
Claims (8)
1. A plunger pump leakage diagnosis method with smooth acceleration signal sequence time window features is characterized by comprising the following steps of: the method comprises the following steps:
s1, performing signal high-pass filtering processing on acceleration signals of a reciprocating plunger pump in a period of time acquired by a vibration sensor, and extracting effective signal components required by analysis;
s2, performing standardized processing on acceleration signals of the reciprocating plunger pump in a period of time acquired by the vibration sensor, and eliminating plunger pump leakage diagnosis interference caused by effective value fluctuation;
s3, designing a series of time windows with equal length to equally divide plunger pump data, and respectively calculating pulse factors of a series of windowed plunger pump vibration acceleration data;
s4, calculating an average value of pulse factor characteristic values calculated in the time window sequence, and taking the average value as a plunger pump leakage fault characteristic value of current spot inspection input data;
s5, judging abnormal values of the leakage fault characteristic values of the plunger pump, and diagnosing the leakage condition of the plunger pump.
2. The plunger pump leakage diagnosis method for smoothing time window characteristics of acceleration signal sequence according to claim 1, characterized by comprising the steps of: the step S1 specifically comprises the following steps:
and eliminating shutdown data of the speed signal of the reciprocating plunger pump in a period of time, which is acquired by the vibration sensor, selecting a 4-order Butterworth filter for the speed signal of which the shutdown data is eliminated, setting the lower cut-off frequency to be 1000Hz, and performing high-pass filtering to obtain the preprocessed effective acceleration vibration component.
3. The plunger pump leakage diagnosis method for smoothing time window characteristics of acceleration signal sequence according to claim 1, characterized by comprising the steps of: the step S2 is specifically as follows
And performing z-score data standardization algorithm processing on the filtered signals, and eliminating the influence of effective value fluctuation under variable working conditions on the leakage diagnosis of the plunger pump.
4. The plunger pump leakage diagnosis method for smoothing time window characteristics of acceleration signal sequence according to claim 1, characterized by comprising the steps of: the method for eliminating the shutdown data specifically comprises the following steps: and setting a threshold according to the signal effective value, and rejecting the data with the effective value lower than 1 as shutdown data.
5. The plunger pump leakage diagnosis method for smoothing time window characteristics of acceleration signal sequence according to claim 1, characterized by comprising the steps of: the step S3 specifically comprises the following steps:
dividing the whole section of signal with the data length N equally by a series of time windows with the design number of T and the length of l, and obtaining T section of sub-signals after downward rounding, whereinThe arbitrary length T is left after rounding f As the t+1 (last) th signal. Then, pulse factor characteristic calculation is carried out on the T-section sub-signal with the length of l, and a pulse factor characteristic value set P= { P is obtained 1 ,P 2 ,P 3 ,…,P T-1 ,P T }。
6. The plunger pump leakage diagnosis method for smoothing time window characteristics of acceleration signal sequence according to claim 1, characterized by comprising the steps of: the step S4 specifically comprises the following steps:
calculating average value of pulse factor characteristic value set P to obtainTo->As a leak diagnosis characteristic value of the current spot check input data.
7. The plunger pump leakage diagnosis method with smooth acceleration signal sequence time window characteristics according to claim 5, wherein: the number of time window sequences is preset to 5.
8. The plunger pump leakage diagnosis method for smoothing time window characteristics of acceleration signal sequence according to claim 1, characterized by comprising the steps of: the step S5 specifically comprises the following steps:
leak diagnostic feature value for spot check dataAnd (3) analyzing, and diagnosing that the water injection pump leaks when the abnormality is lower than the normal value.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117705448A (en) * | 2024-02-05 | 2024-03-15 | 南京凯奥思数据技术有限公司 | Bearing fault degradation trend threshold early warning method and system based on fusion of moving average and 3 sigma criterion |
| CN118088429A (en) * | 2024-04-26 | 2024-05-28 | 成都凯天电子股份有限公司 | Vibration acquisition system of aviation high-pressure axial plunger pump and use method |
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- 2023-04-03 CN CN202310344976.XA patent/CN116893036A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117705448A (en) * | 2024-02-05 | 2024-03-15 | 南京凯奥思数据技术有限公司 | Bearing fault degradation trend threshold early warning method and system based on fusion of moving average and 3 sigma criterion |
| CN117705448B (en) * | 2024-02-05 | 2024-05-07 | 南京凯奥思数据技术有限公司 | Bearing fault degradation trend threshold early warning method and system based on fusion of moving average and 3 sigma criterion |
| CN118088429A (en) * | 2024-04-26 | 2024-05-28 | 成都凯天电子股份有限公司 | Vibration acquisition system of aviation high-pressure axial plunger pump and use method |
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