CN115539378B - Fault diagnosis method, device and medium for hydraulic gear pump of automobile production line - Google Patents
Fault diagnosis method, device and medium for hydraulic gear pump of automobile production line Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 149
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- 238000005299 abrasion Methods 0.000 claims abstract description 44
- 238000012545 processing Methods 0.000 claims abstract description 24
- 238000004364 calculation method Methods 0.000 claims description 28
- 239000010720 hydraulic oil Substances 0.000 claims description 27
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04C—ROTARY-PISTON, OR OSCILLATING-PISTON, POSITIVE-DISPLACEMENT MACHINES FOR LIQUIDS; ROTARY-PISTON, OR OSCILLATING-PISTON, POSITIVE-DISPLACEMENT PUMPS
- F04C14/00—Control of, monitoring of, or safety arrangements for, machines, pumps or pumping installations
- F04C14/28—Safety arrangements; Monitoring
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention relates to the field of data processing, and discloses a method, a device and a medium for diagnosing faults of a hydraulic gear pump of an automobile production line. The method comprises the following steps: acquiring the current measured pressure of the hydraulic gear pump, and calculating pollution abrasion volumetric efficiency according to the current measured pressure; acquiring vibration signals of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate; acquiring weight values preset for pollution abrasion volumetric efficiency and diagnosis accuracy respectively; and correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value to obtain corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy. The invention ensures that the diagnosis accuracy rate better accords with the current performance condition of the hydraulic gear pump.
Description
Technical Field
The invention relates to the field of hydraulic gear pumps, in particular to a method, a device and a medium for diagnosing faults of a hydraulic gear pump of an automobile production line.
Background
The hydraulic gear pump has the advantages of simple and compact structure, good manufacturability, impact resistance and load resistance, is a heart of a hydraulic system, and is widely applied to a power transmission system of an automobile. The vehicle-mounted hydraulic component has the characteristics of complex structure, high precision, high concentration and the like, and has strict index requirements on structure and performance. When the hydraulic gear pump is applied to a vehicle-mounted system, the hydraulic gear pump has a severe operation environment, complex working conditions and serious performance challenges. Nowadays, with the gradual development of hydraulic transmission technology to high precision and high speed, higher requirements are put on the working reliability of hydraulic gear pumps. Studies have shown that hydraulic oil contamination causes wear of hydraulic components and is a major cause of impeding the development of hydraulic components and hydraulic systems. Therefore, the problems of hydraulic component abrasion and hydraulic pump failure caused by hydraulic oil pollution are needed to be studied in depth, so that the hydraulic pump and corresponding engineering machinery equipment can be ensured to run safely, reliably and stably, and the method has important economic value and engineering significance.
However, the current fault diagnosis research for the vehicle-mounted hydraulic gear pump is less, and most of the fault diagnosis research is only aimed at a certain specific working condition, and the running conditions of the hydraulic gear pump are different under different environments of different working conditions, so that the model generalization capability is insufficient, and the popularization is not realized. In addition, the data analysis process needs to collect a large amount of data of different types, such as hydraulic pump operation parameters, environment parameters, personnel operation parameters and the like, the visible data types are more, and the data amount is larger, so that the data collection work is complicated, the collection cost is high, and the diagnosis precision is difficult to ensure.
Disclosure of Invention
In order to solve at least one technical problem, the invention provides a fault diagnosis method, device and medium for a hydraulic gear pump of an automobile production line.
According to a first aspect, an embodiment of the present invention provides a method for diagnosing a fault of a hydraulic gear pump in an automobile production line, including:
acquiring the current measured pressure of a hydraulic gear pump, and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current measured pressure;
acquiring a vibration signal of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump according to the vibration signal, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate;
acquiring weight values preset for the pollution abrasion volumetric efficiency and the diagnosis accuracy rate respectively;
and correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value to obtain corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy.
According to a second aspect, an embodiment of the present invention provides a fault diagnosis device for a hydraulic gear pump of an automobile production line, including:
the first acquisition module is used for acquiring the current actual measured pressure of the hydraulic gear pump and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current actual measured pressure;
the first acquisition module is used for acquiring vibration signals of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump according to the vibration signals, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate;
the second acquisition module is used for acquiring weight values preset for the pollution abrasion volumetric efficiency and the diagnosis accuracy rate respectively;
the first correction module is used for correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value, obtaining corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy.
According to a third aspect, an embodiment of the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method provided in the first aspect.
The embodiment of the invention has the following technical effects: and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current actually measured pressure, and inputting vibration characteristic data of a vibration signal of the hydraulic gear pump into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate. And then correcting the diagnosis accuracy based on the pollution abrasion volumetric efficiency to obtain the corrected diagnosis accuracy. The pollution abrasion volumetric efficiency reflects the performance loss condition of the hydraulic gear pump, so that the diagnosis accuracy is corrected according to the pollution abrasion volumetric efficiency, the diagnosis accuracy can be more in line with the current performance condition of the hydraulic gear pump, and the accuracy of the diagnosis accuracy is improved. The process does not need to collect different types of data, so that the data collection work is simpler, and the influence on the diagnosis precision due to complicated data collection is avoided. The data-driven fault diagnosis model is not limited to fault diagnosis under certain working conditions, and is suitable for fault diagnosis under various working conditions, so that the generalization capability is high, and the generalization capability is high.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for diagnosing faults of a hydraulic gear pump of an automobile production line according to one embodiment of the present invention;
fig. 2 is a block diagram showing a construction of a hydraulic gear pump failure diagnosis apparatus for an automobile production line according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the invention, are within the scope of the invention.
In a first aspect, an embodiment of the invention provides a fault diagnosis method for a hydraulic gear pump of an automobile production line. Referring to fig. 1, the method includes the following steps S110 to S140:
s110, acquiring the current actual measured pressure of a hydraulic gear pump, and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current actual measured pressure;
the pollution abrasion volumetric efficiency refers to the ratio of the actual flow rate of the hydraulic gear pump to the leakage-free flow rate. The magnitude of the dye wear volumetric efficiency reflects the change in hydraulic gear pump performance. The pollution abrasion volumetric efficiency is smaller, the actual flow is small, the leakage amount is large, the clearance of the kinematic pair is large, the pollution abrasion is serious, and the performance loss of the hydraulic gear pump is large.
In a hydraulic gear pump, hydraulic oil plays various roles of a transmission medium, a coolant, a lubricant and the like, and pollutants generated during the operation of the hydraulic gear pump also need to be taken away by the hydraulic oil. Therefore, the viscosity of the hydraulic oil directly affects the working efficiency of the hydraulic gear pump. The viscosity of the hydraulic oil is sensitive to the change of temperature and pressure, and when the temperature and the pressure change, the viscosity of the hydraulic oil also changes. The change relation (1) of the viscosity of hydraulic oil with temperature and pressure can be expressed as:
wherein, the liquid crystal display device comprises a liquid crystal display device,
the viscosity of the hydraulic oil liquid is the viscosity of the hydraulic oil liquid when the pressure is P and the temperature is T;
is at a pressure of 101.325Kpa and a temperature of
The viscosity of the hydraulic oil; a is the pressure viscosity coefficient, and the unit is Pa -1 The method comprises the steps of carrying out a first treatment on the surface of the b is the temperature viscosity coefficient; p is the current measured pressure of the hydraulic gear pump,
is the initial temperature.
Neglecting the flow of compression loss, wherein the relation (2) of the leakage quantity of the hydraulic gear pump and the viscosity of the hydraulic oil is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
is the volume loss flow;
is the leakage coefficient;
the pressure difference is the pump body pressure cavity pressure difference;
is the meshing gap between the gear end face of the hydraulic gear pump and the end face of the pump body; h is the radial clearance between the tooth top of the hydraulic gear pump and the shell;
the viscosity of the hydraulic oil;
the contact tooth number of the tooth top of the hydraulic gear pump and the shell is as follows; s is the tooth top thickness of the hydraulic gear pump; b is the temperature viscosity coefficient.
Processing the relation (2) to obtain a relation (3):
in the process, let
K is a leakage constant and K is a constant term for a hydraulic gear pump, so that the relation (3) is reduced to the following relation (4):
based on the relation (1) and the relation (4), the relation (5) can be obtained:
the expression of the contaminating wear volumetric efficiency is the following relation (6):
in the method, in the process of the invention,
for said contaminating wear volumetric efficiency, Q is the actual flow of the hydraulic gear pump,
is the theoretical flow of the hydraulic gear pump without leakage.
In a hydraulic gear pump, the theoretical flow rate may be expressed by the following relation (7):
wherein z is the number of teeth of the gear of the hydraulic gear pump; m is the gear modulus of the hydraulic gear pump; and n is the gear speed of the hydraulic gear pump. (1.06-1.12) means that a numerical value is taken in the range of (1.06-1.12).
Based on the above relations (5), (6) and (7), the relation (8) between the contaminating wear volumetric efficiency and the pressure, temperature can be obtained:
the following relation (9) is simplified from the relation (8), and the relation (9) may be referred to as a first calculation formula:
in the method, in the process of the invention,
for the contaminating wear volumetric efficiency, p is the current measured pressure,
in order to calculate a first related parameter according to the viscosity of the hydraulic oil and the gear parameter of the hydraulic gear pump,
is the viscosity coefficient of the pressure and the viscosity coefficient of the pressure,
is a second related parameter calculated according to the temperature viscosity coefficient and the temperature.
The following relation (10), also referred to as a second calculation formula, can be obtained from the above derivation process:
in the method, in the process of the invention,
is the first relevant parameter; k is a leakage constant;
is at a pressure of 101.325Kpa and a temperature of
Viscosity of hydraulic oil; z is the number of teeth of the gear of the hydraulic gear pump; m is the gear modulus of the hydraulic gear pump; n is the gear speed of the hydraulic gear pump,
as a result of the initial temperature being set,
the pump body pressure cavity pressure difference is (1.06-1.12) a numerical value within the range of (1.06-1.12).
Further, the following relational expression (11), also referred to as a third calculation expression, can be obtained from the above-described derivation process:
wherein K is the leakage constant;
in order for the leakage coefficient to be a function of,
a meshing gap between the gear end face of the hydraulic gear pump and the end face of the pump body; b is the temperature viscosity coefficient; h is a radial clearance between the tooth top of the hydraulic gear pump and the shell; s is the tooth top thickness of the hydraulic gear pump;
is the contact tooth number between the tooth top of the hydraulic gear pump and the shell.
Wherein, the derivation process can be obtained by the following steps: b 2 =a。
The following relation (12), also called fourth calculation formula, can be obtained from the above derivation process:
in the method, in the process of the invention,
b is the temperature viscosity coefficient, T is the current temperature,
is the initial temperature.
Thus, in one embodiment, the contaminated wear volumetric efficiency may be calculated using the first calculation formula described above, the first correlation parameter may be calculated using the second calculation formula, and the second correlation parameter may be calculated using the fourth calculation formula.
For example, in one practical scenario, the calculation by the three calculation formulas can be obtained:
the first calculation can thus be expressed as:
it will be appreciated that in the above embodiments the relevant parameters are calculated by a plurality of calculations, resulting in a pollution wear volumetric efficiency. The calculation of the various relevant parameters and the contaminating wear volumetric efficiency may be different for other scenarios.
S120, collecting vibration signals of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump according to the vibration signals, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate;
specifically, the vibration signal can be collected by a vibration acceleration sensor installed directly above the engagement of the two gears of the hydraulic gear pump. After the vibration signals are acquired, vibration characteristic data are extracted from the vibration signals, and then the vibration characteristic data are input into a data driving fault diagnosis model which is trained in advance, and the model outputs a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate. For example, the diagnostic result is: the hydraulic gear pump has a fault, and the diagnosis accuracy of the hydraulic gear pump has a fault is 80%.
In one embodiment, the determining the vibration characteristic data of the hydraulic gear pump according to the vibration signal may specifically include:
(11) Performing dimension reduction processing on the vibration signal to obtain a dimension reduction sequence, and combining the dimension reduction sequence with an original sequence of the vibration signal to obtain a vibration data sequence;
it is understood that the vibration signal acquired from the vibration acceleration sensor is the original sequence. The vibration signal can be subjected to dimension reduction by an empirical formula dimension reduction method to obtain a dimension reduction sequence. And then combining the dimension reduction sequence and the original sequence to obtain a vibration data sequence.
(12) Performing noise reduction treatment on the vibration data sequence, performing standardization treatment on the vibration data sequence after the noise reduction treatment, and eliminating abnormal values in the vibration data sequence after the standardization treatment;
it can be appreciated that the vibration data sequence can be denoised using an ensemble empirical mode decomposition method to reduce noise interference on the signal. The vibration data series after the noise reduction processing may be normalized using a data normalization method. The normalized vibration data sequence may be subjected to outlier processing using the outlier processing method, 3 sigma criterion.
After multiple treatments, a high quality vibration data sequence can be obtained.
(13) And extracting time domain features, frequency domain features and time-frequency domain features from the vibration data sequence from which the abnormal values are removed, and forming vibration feature data according to each extracted feature.
Wherein the time domain features may include: at least one of a maximum value, a minimum value, a peak-to-peak value, a mean value, an absolute mean value, a variance, a standard deviation, a root mean square value, a square root amplitude, a peak factor, a pulse factor, a margin factor, a waveform factor, a kurtosis factor, and a skewness factor.
Wherein the frequency domain features include at least one of center of gravity frequency, average frequency, mean square frequency, root mean square frequency, frequency variance, and frequency standard deviation.
The time-frequency domain features comprise energy duty ratios and energy entropy in different frequency bands. The energy duty ratio of different frequency bands, for example, the energy duty ratio of frequency bands 1-8, so that the time-frequency domain features include 9-dimensional features.
The method specifically can use a tree model feature selection method and a regular term feature selection method to screen vibration feature data, so that feature quality is improved.
After the vibration characteristic data are obtained through the steps (11) - (13), the vibration characteristic data can be input into a data driving fault diagnosis model.
It can be appreciated that, before the data-driven fault diagnosis model is applied to fault diagnosis, the data-driven fault diagnosis model is first required to be trained, and the training process of the data-driven fault diagnosis model may generally include:
(21) The data set formed from the vibration signals acquired from the vibration acceleration sensor over the historical period of time is diversity. Specifically, a volumetric efficiency threshold is set, data in the data set is divided into a normal data set and a fault data set according to the volumetric efficiency threshold, 60% of the data in the normal data set and the fault data set are selected as training sets, and the number of the remaining 40% of the data sets is used as a test set.
(22) And performing feature extraction after performing the dimension reduction and merging processing, the noise reduction processing, the standardization processing and the outlier processing on the data in the training set and the test set to obtain vibration feature data.
(23) And establishing a support vector machine algorithm model, and training the support vector machine algorithm model according to vibration characteristic data corresponding to the training set to obtain a data-driven fault diagnosis model.
(24) Testing the data-driven fault diagnosis model by adopting vibration characteristic data corresponding to the test set, and obtaining a final data-driven fault diagnosis model after the test meets the requirements; otherwise, parameter adjustment is carried out on the data driving fault diagnosis model, and the data driving fault diagnosis model after parameter adjustment is tested again until the data driving fault diagnosis model meeting the requirements is obtained.
S130, acquiring weight values preset for the pollution abrasion volumetric efficiency and the diagnosis accuracy rate respectively;
that is, it is necessary to set weight values in advance for the pollution wear volumetric efficiency and the diagnosis accuracy of the data-driven failure diagnosis model. For example, the weight value of the pollution abrasion volumetric efficiency is 30%, and the weight value of the diagnosis accuracy of the data-driven failure diagnosis model is 70%.
And S140, correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value to obtain corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy.
That is, the embodiment of the invention corrects the diagnosis accuracy of the data-driven fault diagnosis model by utilizing the pollution abrasion volumetric efficiency, so that the diagnosis accuracy of the data-driven fault diagnosis model is more in line with the current pollution abrasion condition of the hydraulic gear pump, thereby improving the accuracy of the diagnosis accuracy.
In one embodiment, S140 may specifically include:
multiplying the pollution abrasion volumetric efficiency by a corresponding weight value to obtain a first product;
multiplying the diagnosis accuracy by the corresponding weight value to obtain a second product;
and adding the first product and the second product to obtain the corrected diagnosis accuracy.
For example, the pollution abrasion volumetric efficiency is 50%, the weight value corresponding to the pollution abrasion volumetric efficiency is 30%, the diagnosis result output by the data driving fault diagnosis model is that faults exist, the diagnosis accuracy is 80%, the weight value of the diagnosis accuracy of the data driving fault diagnosis model is 70%, and the corrected diagnosis accuracy is: 50% + 30% +80% + 70% = 71%. The diagnosis result of the data-driven fault diagnosis model is that the diagnosis accuracy of the fault is corrected from 80% to 71%.
In summary, the pollution and abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump is calculated according to the current actual measured pressure, and vibration characteristic data of a vibration signal of the hydraulic gear pump is input into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy. And then correcting the diagnosis accuracy based on the pollution abrasion volumetric efficiency to obtain the corrected diagnosis accuracy. The pollution abrasion volumetric efficiency reflects the performance loss condition of the hydraulic gear pump, so that the diagnosis accuracy is corrected according to the pollution abrasion volumetric efficiency, the diagnosis accuracy can be more in line with the current performance condition of the hydraulic gear pump, and the accuracy of the diagnosis accuracy is improved. The process does not need to collect different types of data, so that the data collection work is simpler, and the influence on the diagnosis precision due to complicated data collection is avoided. The data-driven fault diagnosis model is not limited to fault diagnosis under certain working conditions, and is suitable for fault diagnosis under various working conditions, so that the generalization capability is high, and the generalization capability is high.
In a second aspect, an embodiment of the present invention provides a fault diagnosis device for a hydraulic gear pump of an automobile production line, referring to fig. 2, the device includes:
the first acquisition module is used for acquiring the current actual measured pressure of the hydraulic gear pump and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current actual measured pressure;
the first acquisition module is used for acquiring vibration signals of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump according to the vibration signals, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate;
the second acquisition module is used for acquiring weight values preset for the pollution abrasion volumetric efficiency and the diagnosis accuracy rate respectively;
the first correction module is used for correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value, obtaining corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy.
In one embodiment, the first acquisition module is specifically configured to: calculating the contaminated wear volumetric efficiency using a first calculation formula comprising:
in the method, in the process of the invention,
for the contaminating wear volumetric efficiency, p is the current measured pressure,
in order to calculate a first related parameter according to the viscosity of the hydraulic oil and the gear parameter of the hydraulic gear pump,
is the viscosity coefficient of the pressure and the viscosity coefficient of the pressure,
is a second related parameter calculated according to the temperature viscosity coefficient and the temperature.
In one embodiment, the first acquisition module is specifically configured to: calculating the first related parameter by adopting a second calculation formula, wherein the second calculation formula is as follows:
in the method, in the process of the invention,
is the first relevant parameter; k is a leakage constant;
is at a pressure of 101.325Kpa and a temperature of
Viscosity of hydraulic oil; z is the number of teeth of the gear of the hydraulic gear pump; m is the gear modulus of the hydraulic gear pump; n is the gear speed of the hydraulic gear pump,
as a result of the initial temperature being set,
the pump body pressure cavity pressure difference is (1.06-1.12) a numerical value within the range of (1.06-1.12).
In one embodiment, the first acquisition module is specifically configured to: calculating a leakage constant using a third calculation formula, the third calculation formula being:
wherein K is the leakage constant;
in order for the leakage coefficient to be a function of,
a meshing gap between the gear end face of the hydraulic gear pump and the end face of the pump body; b is the temperature viscosity coefficient; h is a radial clearance between the tooth top of the hydraulic gear pump and the shell; s is the tooth top thickness of the hydraulic gear pump;
is the contact tooth number between the tooth top of the hydraulic gear pump and the shell.
In one embodiment, the first acquisition module is specifically configured to: calculating the second related parameter by using a fourth calculation formula:
in the method, in the process of the invention,
b is the temperature viscosity coefficient, T is the current temperature,
is the initial temperature.
In one embodiment, the first acquisition module comprises:
the first processing unit is used for carrying out dimension reduction processing on the vibration signals to obtain a dimension reduction sequence, and combining the dimension reduction sequence with the original sequence of the vibration signals to obtain a vibration data sequence;
the second processing unit is used for carrying out noise reduction processing on the vibration data sequence, carrying out standardization processing on the vibration data sequence after the noise reduction processing, and eliminating abnormal values in the vibration data sequence after the standardization processing;
the feature extraction unit is used for extracting time domain features, frequency domain features and time-frequency domain features from the vibration data sequence with the abnormal values removed, and forming vibration feature data according to each extracted feature.
In one embodiment, the time domain features include: at least one of a maximum value, a minimum value, a peak-to-peak value, a mean value, an absolute mean value, a variance, a standard deviation, a root mean square value, a square root amplitude, a peak factor, a pulse factor, a margin factor, a waveform factor, a kurtosis factor, and a skewness factor; and/or the frequency domain features include at least one of center of gravity frequency, average frequency, mean square frequency, root mean square frequency, frequency variance, and frequency standard deviation; and/or the time-frequency domain features comprise energy duty ratios and energy entropies in different frequency bands.
In one embodiment, the first correction module includes:
the first calculation unit is used for multiplying the pollution abrasion volumetric efficiency by the corresponding weight value to obtain a first product;
the second calculation unit is used for multiplying the diagnosis accuracy and the corresponding weight value to obtain a second product;
and a third calculation unit, configured to add the first product and the second product to obtain a corrected diagnostic accuracy.
It will be appreciated that the apparatus provided in the second aspect corresponds to the method provided in the first aspect, and that explanations, illustrations, examples, embodiments, etc. of the second aspect may refer to corresponding parts in the first aspect.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method provided in the first aspect.
Specifically, a system or apparatus provided with a storage medium on which a software program code realizing the functions of any of the above embodiments is stored, and a computer (or CPU or MPU) of the system or apparatus may be caused to read out and execute the program code stored in the storage medium.
In this case, the program code itself read from the storage medium may realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code form part of the present invention.
Examples of the storage medium for providing the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD+RW), a magnetic tape, a nonvolatile memory card, and a ROM. Alternatively, the program code may be downloaded from a server computer by a communication network.
Further, it should be apparent that the functions of any of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform part or all of the actual operations based on the instructions of the program code.
Further, it is understood that the program code read out by the storage medium is written into a memory provided in an expansion board inserted into a computer or into a memory provided in an expansion module connected to the computer, and then a CPU or the like mounted on the expansion board or the expansion module is caused to perform part and all of actual operations based on instructions of the program code, thereby realizing the functions of any of the above embodiments.
It may be appreciated that, for explanation, specific implementation, beneficial effects, examples, etc. of the content in the computer readable medium provided by the embodiment of the present invention, reference may be made to corresponding parts in the method provided in the first aspect, and details are not repeated herein.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments in part.
Those skilled in the art will appreciate that in one or more of the examples described above, the functions described in the present invention may be implemented in hardware, software, a pendant, or any combination thereof. When implemented in software, these functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present application. As used in the specification and in the claims, the terms "a," "an," "the," and/or "the" are not specific to a singular, but may include a plurality, unless the context clearly dictates otherwise. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method or apparatus comprising such elements.
It should also be noted that the positional or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the positional or positional relationship shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. Unless specifically stated or limited otherwise, the terms "mounted," "connected," and the like are to be construed broadly and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.
Claims (8)
1. The fault diagnosis method for the hydraulic gear pump of the automobile production line is characterized by comprising the following steps of:
acquiring the current measured pressure of a hydraulic gear pump, and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current measured pressure;
acquiring a vibration signal of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump according to the vibration signal, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate;
acquiring weight values preset for the pollution abrasion volumetric efficiency and the diagnosis accuracy rate respectively;
correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value to obtain corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy;
the determining the vibration characteristic data of the hydraulic gear pump according to the vibration signal comprises the following steps:
performing dimension reduction processing on the vibration signal to obtain a dimension reduction sequence, and combining the dimension reduction sequence with an original sequence of the vibration signal to obtain a vibration data sequence;
carrying out noise reduction treatment on the vibration data sequence, carrying out standardization treatment on the vibration data sequence after the noise reduction treatment, and eliminating abnormal values in the vibration data sequence after the standardization treatment;
extracting time domain features, frequency domain features and time-frequency domain features from the vibration data sequence from which abnormal values are removed, and forming vibration feature data according to each extracted feature;
the correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value comprises the following steps:
multiplying the pollution abrasion volumetric efficiency by a corresponding weight value to obtain a first product;
multiplying the diagnosis accuracy by the corresponding weight value to obtain a second product;
and adding the first product and the second product to obtain the corrected diagnosis accuracy.
2. The method of claim 1, wherein the contaminated wear volumetric efficiency is calculated using a first calculation formula comprising:
wherein eta is the pollution abrasion volumetric efficiency, p is the current measured pressure, b 1 B, calculating a first related parameter according to the viscosity of the hydraulic oil and the gear parameter of the hydraulic gear pump 2 Is the pressure viscosity coefficient, b 3 Is a second related parameter calculated according to the temperature viscosity coefficient and the temperature.
3. The method of claim 2, wherein the first correlation parameter is calculated using a second calculation formula:
wherein b is 1 Is the first relevant parameter; k is a leakage constant; mu (mu) 0 Is at a pressure of 101.325Kpa and a temperature of T 0 Viscosity of hydraulic oil; z is the number of teeth of the gear of the hydraulic gear pump; m is the gear modulus of the hydraulic gear pump; n is the gear speed of the hydraulic gear pump, T 0 For the initial temperature, ΔP is pump body pressure cavity pressure difference, (1.06-1.12) is a numerical value in the range of (1.06-1.12).
4. A method according to claim 3, wherein the leakage constant is calculated using a third calculation formula:
K＝K 1 δ 3 +bh 3 /6SZ 0
wherein K is the leakage constant; k (K) 1 Delta is the engagement gap between the gear end face of the hydraulic gear pump and the end face of the pump body; b is the temperature viscosity coefficient; h is a radial clearance between the tooth top of the hydraulic gear pump and the shell; s is the tooth top thickness of the hydraulic gear pump; z is Z 0 Is the contact tooth number between the tooth top of the hydraulic gear pump and the shell.
5. The method of claim 2, wherein the second correlation parameter is calculated using a fourth calculation formula:
b 3 ＝-b(T-T 0 )
wherein b is 3 For the second related parameter, b is the temperature viscosity coefficient, T is the current temperature, T 0 Is the initial temperature.
6. The method of claim 1, wherein the time domain features comprise: at least one of a maximum value, a minimum value, a peak-to-peak value, a mean value, an absolute mean value, a variance, a standard deviation, a root mean square value, a square root amplitude, a peak factor, a pulse factor, a margin factor, a waveform factor, a kurtosis factor, and a skewness factor; and/or the frequency domain features include at least one of center of gravity frequency, average frequency, mean square frequency, root mean square frequency, frequency variance, and frequency standard deviation; and/or the time-frequency domain features comprise energy duty ratios and energy entropies in different frequency bands.
7. The utility model provides a car production line hydraulic gear pump fault diagnosis device which characterized in that includes:
the first acquisition module is used for acquiring the current actual measured pressure of the hydraulic gear pump and calculating the pollution abrasion volumetric efficiency of the hydraulic oil to the hydraulic gear pump according to the current actual measured pressure;
the first acquisition module is used for acquiring vibration signals of the hydraulic gear pump, determining vibration characteristic data of the hydraulic gear pump according to the vibration signals, and inputting the vibration characteristic data into a data driving fault diagnosis model to obtain a diagnosis result of whether the hydraulic gear pump has faults or not and a corresponding diagnosis accuracy rate;
the second acquisition module is used for acquiring weight values preset for the pollution abrasion volumetric efficiency and the diagnosis accuracy rate respectively;
the first correction module is used for correcting the diagnosis accuracy corresponding to the diagnosis result according to the pollution abrasion volumetric efficiency, the corresponding weight value, the diagnosis accuracy and the corresponding weight value to obtain corrected diagnosis accuracy, and outputting the diagnosis result and corrected diagnosis accuracy;
the first acquisition module comprises:
the first processing unit is used for carrying out dimension reduction processing on the vibration signals to obtain a dimension reduction sequence, and combining the dimension reduction sequence with the original sequence of the vibration signals to obtain a vibration data sequence;
the second processing unit is used for carrying out noise reduction processing on the vibration data sequence, carrying out standardization processing on the vibration data sequence after the noise reduction processing, and eliminating abnormal values in the vibration data sequence after the standardization processing;
the feature extraction unit is used for extracting time domain features, frequency domain features and time-frequency domain features from the vibration data sequence with the abnormal values removed, and forming vibration feature data according to each extracted feature;
the first correction module includes:
the first calculation unit is used for multiplying the pollution abrasion volumetric efficiency by the corresponding weight value to obtain a first product;
the second calculation unit is used for multiplying the diagnosis accuracy and the corresponding weight value to obtain a second product;
and a third calculation unit, configured to add the first product and the second product to obtain a corrected diagnostic accuracy.
8. A computer readable storage medium, having stored thereon a computer program which, when executed in a computer, causes the computer to perform the method of any of claims 1 to 6.
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