CN116735201A

CN116735201A - Oil film whirl monitoring method, system, storage medium and electronic equipment

Info

Publication number: CN116735201A
Application number: CN202310558845.1A
Authority: CN
Inventors: 刘景明; 刘洋; 张重阳; 屈世栋; 山崧; 蔡国娟; 姚晓燕; 高丽岩; 张雅贤; 黄静
Original assignee: China Petroleum and Chemical Corp
Current assignee: China Petroleum and Chemical Corp
Priority date: 2023-05-17
Filing date: 2023-05-17
Publication date: 2023-09-12

Abstract

The application relates to the technical field of rotating machinery and sliding bearings, and discloses an oil film whirl monitoring method, an oil film whirl monitoring system, a storage medium and electronic equipment. The method comprises the following steps: acquiring first operation data of a bearing in a normal state and second operation data of the bearing under the condition of oil film whirl fault, and respectively preprocessing the first operation data and the second operation data to acquire preprocessed first operation data and preprocessed second operation data; determining a first alarm baseline according to a preset mechanical vibration standard; determining a second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data; determining a target alarm baseline according to the first alarm baseline and the second alarm baseline; and monitoring the running state of the target bearing through the target alarm baseline. The defect that the setting of the fixed threshold value extremely depends on manual experience and expertise is overcome, the accuracy is improved, and the method has better universality.

Description

Oil film whirl monitoring method, system, storage medium and electronic equipment

Technical Field

The present application relates to the technical field of rotating machinery and sliding bearings, and in particular, to an oil film whirl monitoring method, an oil film whirl monitoring system, a storage medium, a computer program product, and an electronic device.

Background

The background description provided herein is for the purpose of generally presenting the context of the disclosure, and the statements in this section merely provide background of the disclosure and do not necessarily constitute prior art.

The oil film whirl fault is a hydrodynamic instability condition which generally occurs in the sliding bearing at a speed higher than the first order critical speed, and belongs to a sub-synchronous oscillation phenomenon that the center of the rotor rotates around the center of the sliding bearing.

Because the bearing is one of the key components of the rotary machine, whether the running state of the bearing is normal directly affects the performance parameters such as the machining precision, the running reliability, the service life and the like of the whole large-scale mechanical equipment. The development of the state monitoring of the bearing is a basis for ensuring the safe and stable operation of mechanical equipment.

In the prior art, the alarm value is a threshold value or a specified vibration value which is set according to the prior experience, and when the alarm value is reached or a significant change occurs, corresponding remedial measures are required. Generally, the machine will continue to operate for a period of time in the event of an early warning condition, while studies should be conducted to determine the cause of the vibration change and to develop corresponding remedial action.

Current state monitoring methods are based on a rule of thumb with fixed thresholds (e.g., limit values set based on prior experience or specified vibration values) that define a range of variation of a main parameter of the system, the thresholds typically being set to an early warning value and an alarm value, and when the monitored parameter exceeds the range, the machine is considered to be malfunctioning. The method is simple to operate, small in calculated amount and convenient for a program to monitor the sensor signals of the machine in real time.

Under the existing conditions, oil film whirl fault often occurs to the sliding bearing due to various reasons such as design, manufacture and use, equipment is damaged slightly, production efficiency is reduced, production safety and economy are directly affected, and even accidents are caused, so that life is endangered. Therefore, it is important to monitor the working condition of the sliding bearing of the large rotary machine in real time so as to grasp the current state of the sliding bearing.

Under the existing conditions, the threshold value is set extremely depending on manual experience and expertise when the state monitoring is carried out, and errors exist in the set threshold value due to factors such as complex working conditions of a machine, environmental changes and the like when the state monitoring is actually applied, and the threshold value is manually debugged on site for a plurality of times, and is basically not updated after the threshold value is set.

Disclosure of Invention

In order to solve the problems, the application provides an oil film whirl monitoring method, an oil film whirl monitoring system, a storage medium, a computer program product and electronic equipment. The defect that the setting of the fixed threshold value extremely depends on manual experience and expertise is overcome, the accuracy is improved, and the method has better universality.

In a first aspect of the present application, there is provided a method of monitoring oil film whirl, the method comprising:

acquiring first operation data of a bearing in a normal state and second operation data of the bearing under the condition of oil film whirl fault, and respectively preprocessing the first operation data and the second operation data to acquire preprocessed first operation data and preprocessed second operation data;

determining a first alarm baseline according to a preset mechanical vibration standard;

determining a second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data;

determining a target alarm baseline according to the first alarm baseline and the second alarm baseline;

and monitoring the running state of the target bearing through the target alarm baseline.

Further, the preprocessing the first operation data and the second operation data respectively includes:

And respectively converting the first operation data and the second operation data into root mean square data.

Further, after the monitoring of the operation state of the target bearing through the target alarm baseline, the method further comprises:

and sending out an alarm message under the condition that the running state meets the preset condition.

Further, the second alarm baseline includes a second early warning baseline, and the determining the second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data includes:

determining a current acquisition period value when an abnormal state occurs;

and determining a ratio of a short-period root mean square value to a long-period root mean square value according to the current acquisition period value, the preprocessed first operation data and the preprocessed second operation data, and determining a second early warning baseline according to the ratio of the short-period root mean square value to the long-period root mean square value.

Further, the second alarm baseline includes a second alarm baseline, and the determining the second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data includes:

and determining an alarm value according to the preprocessed second operation data through a preset dominant regression model, and determining a second alarm baseline according to the alarm value.

determining fault data under the condition that the running state meets a preset condition;

training the preset dominant regression model according to the fault data, redefining an alarm value, and updating the second alarm baseline according to the redetermined alarm value.

In a second aspect of the present application, there is provided an oil film whirl monitoring system, comprising:

the device comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring first operation data of a bearing in a normal state and second operation data of the bearing under the condition of oil film whirl fault, and respectively preprocessing the first operation data and the second operation data to acquire preprocessed first operation data and preprocessed second operation data;

the first determining module is used for determining a first alarm baseline according to a preset mechanical vibration standard;

the second determining module is used for determining a second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data;

a third determining module, configured to determine a target alarm baseline according to the first alarm baseline and the second alarm baseline;

And the detection module is used for monitoring the running state of the target bearing through the target alarm baseline.

In a third aspect of the application, there is provided a computer program product comprising a computer program or instructions which, when executed by a processor, implement the steps of the method as described above.

In a fourth aspect of the application, a computer-readable storage medium is provided, storing a computer program executable by one or more processors for implementing the steps of the method as described above.

In a fifth aspect of the application, an electronic device is provided comprising a memory and one or more processors, said memory having stored thereon a computer program which, when executed by said one or more processors, performs the steps of the method as described above.

Compared with the prior art, the technical scheme of the application has the following advantages or beneficial effects:

(1) Compared with a method for fixing the threshold, the method can reduce the setting of the fixed threshold extremely depending on manual experience and expertise, inputs data with the root mean square value larger than 4.5 into a preset linear regression model to continue training to obtain a better alarm baseline, and realizes the self-adaptive update of the alarm baseline;

(2) Combining the selected time domain feature expression and the conditional expression, and combining according to the mechanical vibration national standard GB/T6075.1-2012 and the ratio of the short period average value to the long period average value of the time domain feature to obtain an early warning baseline without setting an accurate early warning value, wherein the expression is clearer than a fixed threshold method, and the early warning baseline has better accuracy;

(3) Compared with a fixed alarm threshold method, the method has the advantages that by constructing a linear regression model, inputting oil film whirl fault data to obtain a fitting equation, obtaining an initial alarm baseline y2 by the lowest point value of the fitting equation, and obtaining a final alarm baseline by combining y2 with the initial alarm baseline y1 set by the national standard, a more accurate alarm threshold can be obtained;

(4) Compared with a fixed threshold method, the designed conditional expression is subjected to logic operation, so that the method has accurate value early warning and alarm baselines and statistical early warning and alarm baselines, and can carry out alarm or early warning treatment only by meeting any one of the conditions, thereby having better universality;

(5) Compared with a fixed threshold method, the method has the advantages that the early warning and alarm base line set by the mechanical vibration national standard GB/T6075.1-2012 is used as a bottom protection strategy, the ratio k of the average value of the short-period root mean square value to the average value of the long-period root mean square value and the lowest point of the fitting equation are used as an advance strategy, and the method has better accuracy and safety.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort to a person of ordinary skill in the art.

It should be further noted that, for convenience of description, only a portion relevant to the present disclosure is shown in the drawings. The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a undue limitation on the application, wherein:

FIG. 1 is a flow chart of an oil film whirl monitoring method provided by an embodiment of the application;

FIG. 2 is a schematic diagram of a national standard for root mean square values of mechanical vibration speeds;

FIG. 3 is a schematic view of a root mean square curve according to an embodiment of the present application;

FIG. 4 is a schematic diagram of a ratio of a short period root mean square value to a long period root mean square value according to an embodiment of the present application;

FIG. 5 is a schematic view of a linear regression model according to an embodiment of the present application;

fig. 6 is a connection block diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The following will describe embodiments of the present application in detail with reference to the drawings and examples, thereby solving the technical problems by applying technical means to the present application, and realizing the corresponding technical effects can be fully understood and implemented accordingly. The embodiment of the application and the features in the embodiment can be mutually combined on the premise of no conflict, and the formed technical scheme is within the protection scope of the application.

It should be understood that the embodiments described below are only some, but not all, embodiments of the application. All other embodiments, based on the embodiments of the application, which are obtained by a person skilled in the art without making any inventive effort, are within the scope of the application.

Example 1

The embodiment provides a method for monitoring oil film whirl, fig. 1 is a flowchart of the method for monitoring oil film whirl provided by the embodiment of the application, and as shown in fig. 1, the method disclosed by the embodiment comprises the following steps:

Step 110, acquiring first operation data of the bearing in a normal state and second operation data of the bearing under the condition of oil film whirl fault, and respectively preprocessing the first operation data and the second operation data to acquire preprocessed first operation data and preprocessed second operation data.

Optionally, a vibration sensor is installed on the bearing, vibration data of the bearing are collected, the collected data comprise normal operation and oil film whirl fault operation occurrence data, and finally all the data are stored as a data set D. Meanwhile, normal data and oil film whirl fault data are distinguished, and the data structure can be json format:

in some embodiments, the preprocessing the first and second operation data, respectively, includes:

Optionally, the preset mechanical vibration standard comprises mechanical vibration national standard GB/T6075.1-2012.

The use of root mean square value velocity measurements to characterize the vibration response characteristics of machines in the mechanical vibration national standard GB/T6075.1-2012 was very successful, with root mean square values generally adequately describing the operating condition of a rotating shaft assembly operating without failure, and vibration data being more evident in the graphical representation of root mean square values when anomalies or failures occur. Therefore, the root mean square value is selected as a characteristic expression of the present invention, while the data in the data set D is converted into an expression form of the root mean square value.

An alternative expression for the root mean square value is as follows:

where X is denoted as the root mean square value, N is a time series of N data points, and X (N) is denoted as the nth data.

Further, a short-period root mean square value average curve with the acquisition period of a first preset period value and a long-period root mean square value average curve with the acquisition period of a second preset period value can be drawn in the same coordinate system according to the preprocessed first operation data and the preprocessed second operation data, and a graph of root mean square values is drawn in another same coordinate system; the abscissa of the coordinate system is an acquisition period value, and the ordinate is a vibration amplitude.

It should be noted that the first preset period value may be set to 3, and the second preset period value may be set to 20.

For example, a graph of the root mean square values is plotted correspondingly from the root mean square values X converted in the data set D, and a period of 20 (long period root mean square value average curve 1) and a period of 3 (short period root mean square value average curve 2) are plotted on the root mean square value graph. And further drawing a ratio graph of the short-period root mean square value to the long-period root mean square value on the other graph.

For example, a short-period rms average curve 1 with period 3, a long-period rms average curve 2 with period 20, and a rms graph (refer to fig. 4, fig. 4 is a schematic diagram of a ratio of a short-period rms to a long-period rms) are drawn by selecting rms as a feature expression, and a short-period rms to long-period rms ratio graph (refer to fig. 3, fig. 3 is a schematic diagram of a rms graph according to an embodiment of the present application).

Step 120, determining a first alarm baseline according to a preset mechanical vibration standard.

In some embodiments, the first alert baseline comprises a first alert baseline; wherein, the first early warning baseline includes:

y1＝(x≥k ₁ )？1:0

wherein y1 represents whether early warning is performed or not, k ₁ Is constant, x is a root mean square value.

Optionally, a first early warning baseline y1, k is obtained according to the mechanical vibration national standard GB/T6075.1-2012 ₁ The value of (2) may be set to 4.5.

For example, referring to fig. 2, it is recommended that the early warning value should be lower than the lower limit value of the region C in the national standard. Thus, a first pre-warning baseline y1 can be obtained:

if X>＝4.5，

y＝1；

else y＝0。

wherein, X is a root mean square value, y=1 indicates that early warning is performed, and y=0 indicates that early warning is not performed. Thus, the expression y1 means: if the root mean square value is more than or equal to 4.5, the device needs to perform early warning treatment; otherwise, the machine runs normally, and early warning processing is not needed.

In some embodiments, the first alert baseline further comprises a first alert baseline; wherein the first alarm baseline comprises:

b1＝(x≥k ₂ )？1:0

wherein b1 represents whether to alarm, k ₂ Is constant, x is a root mean square value.

Alternatively, k ₁ The value of (2) may be set to 9.3.

For example, the national standard recommended alarm should be a certain amount above the baseline, equal in magnitude to a certain proportional number of the upper limit of region B in the vibration national standard GB/T6075.1-2012. If the baseline is low, the alarm value may be lower than in zone C, the machine bearings may be different, and the alarm value may be set differently, reflecting the difference in dynamic load and bearing support stiffness. A first initial alarm baseline b1 may be designed here:

if X>＝9.3，

b＝1；

else b＝0。

wherein X is a root mean square value, b=1 is an alarm, and y=0 is no alarm. Thus b1 expression means: if the root mean square value is more than or equal to 9.3, the equipment needs to carry out alarm processing; otherwise, alarm processing is not needed.

And 130, determining a second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data.

In some embodiments, the second alert baseline includes a second alert baseline, and the determining the second alert baseline from the preprocessed first operational data and the preprocessed second operational data includes:

Determining a current acquisition period value when an abnormal state occurs;

Optionally, according to the root mean square value graph and the ratio graph of the short period and the long period, analyzing and processing the graph, mining out the graph which can represent machine early warning, and designing a conditional expression for the mined information to obtain a second early warning base line y2.

For example, in connection with fig. 3 and 4, it is possible to obtain that the sliding bearing is normally operated in the 1 st to 531 th cycles, an abnormal state is occurred after the 531 th cycle, or a sign of occurrence of an oil film whirl failure is observed. The design condition expression can be used for early warning of the sliding bearing, when the current period is 531, the short period root mean square value d1=2.42, and the long period root mean square value d2=1.85, so that the ratio k=1.3 of the current short period root mean square value to the long period root mean square value. Thus, a second pre-warning baseline y2 is available:

if k>＝1.3，

y＝1；

else y＝0。

Thus, the expression of y2 means: if the ratio of the current short-period root mean square value to the long-period root mean square value is more than or equal to 1.3, early warning can be carried out; otherwise, the machine runs normally, and early warning processing is not needed.

In some embodiments, the second alert baseline includes a second alert baseline, the determining a second alert baseline from the preprocessed first operational data and the preprocessed second operational data includes:

In some embodiments, the preset dominant regression model includes:

wherein, the liquid crystal display device comprises a liquid crystal display device,i is the i-th scattered point, beta _i Fitting coefficient delta for ith scattered point _i Fitting additional parameters for the ith scatter point, X _i Is the mean square value of the ith scatter.

Optionally, a second alarm condition expression b2 is obtained according to the data marked as oil film whirl fault. A built pre-set linear regression model, the expression of which is as follows:

wherein F is represented as an independent variable, X is represented as an independent variable,expressed as the total number of scattered points, i is the ith scattered point, beta is the fitting coefficient, delta _i To fit the additional parameters Xi is denoted as the i-th data. Inputting the data marked as the oil film whirl fault in the data set into a preset linear regression model, obtaining a fitting equation through a least square method, and drawing a fitted scatter diagram.

In some embodiments, the second alarm baseline comprises:

b＝(x>f _min )？1:0

wherein b represents whether to perform early warning, f _min And x is a root mean square value.

Further, setting the alarm value as the lowest point value of the fitting equation in the scatter diagram, and obtaining a second alarm baseline b2:

if X>＝f _min ，

b＝1；

else b＝0。

wherein f _min Is the lowest point value of the fit equation. b2 means: if the root mean square value is greater than or equal to the lowest point value of the fitting equation, alarm processing can be carried out; otherwise, alarm processing is not needed.

For example, a linear regression model is constructed, data for marking oil film whirl fault in the collected data set is input into a preset linear regression model, a fitting equation is obtained through a least square method, and a scatter diagram and a fitting curve are drawn as shown in fig. 5. The available alarm value is 4.8, and a second alarm base line b2 is obtained:

if X>＝4.8，

b＝1；

else b＝0。

and 4.8 is the minimum value in the fitting equation, and if the value of the root mean square value is more than or equal to 4.8, the machine can perform alarm processing.

And 140, determining a target alarm baseline according to the first alarm baseline and the second alarm baseline.

Further, logically combining the early warning baselines Y1 and Y2 to obtain an early warning baseline Y; and carrying out logic operation on the alarm baselines B1 and B2 to obtain a final alarm baseline B.

For example, the final pre-warning baseline can be obtained by logically combining the pre-warning baselines y1 and y 2.

Therefore, the early warning baseline Y may be set as:

if X>＝4.5|k>＝1.3，

y＝1；

else y＝0。

thus, the early warning baseline Y means: if the value of the root mean square value is more than or equal to 4.5 or the ratio of the current short-period root mean square value to the long-period root mean square value is more than or equal to 1.3, the machine can perform early warning treatment; otherwise, the machine operates normally without early warning treatment.

Further, B2 is combined with B1 in the national standard to perform logic operation, so as to obtain an alarm base line B:

if X>＝9.3|X>＝4.5，

b＝1；

else b＝0。

it should be noted that 4.8 obtained in step 130 is the value of the lowest point in the fitted curve, and since this value is greater than the standard limit of vibration in the C region specified in the national standard of mechanical vibration GB/T6075.1-2012, a logical operation is performed in combination with the national standard, and the alarm value is set to 4.5.

Alarm baseline B means: if the root mean square value is more than or equal to 9.3 or more than or equal to the lowest point value of the fitting equation, early warning processing can be performed, otherwise, no warning processing is needed.

In some embodiments, after the monitoring of the operational state of the target bearing by the target alert baseline, further comprising:

Further, the alarm base line B is updated according to the first alarm base line B1 and the updated second alarm base line B2.

And 150, monitoring the running state of the target bearing through the target alarm baseline.

Optionally, after the early warning baseline and the alarm baseline are obtained, the two baselines are derived, and a preset linear regression model for training the alarm baseline is also derived. The exported model and baseline need to be saved, in a storable device.

Further, the baseline and model in the storable device are deployed into a production site to monitor the operational state of the target bearing.

Further, after the monitoring base line is obtained, the bearing is monitored in real time on site by using the early warning base line and the alarm base line. If the acquired data are converted into the root mean square values, the data with the root mean square value being more than or equal to 4.5 appear, the data are automatically marked as oil film whirl fault data, the fault data are input into a preset linear regression model for training, the value of the lowest point in a new fitting equation is obtained as a new alarm value, and then the alarm value in an alarm baseline is updated, so that the self-adaptive updating of the alarm value is realized.

The alarm is performed when the corresponding conditions of the early warning base line Y and/or the alarm base line B are satisfied.

As will be appreciated by those skilled in the art, the preset conditions include:

the value of the root mean square value is more than or equal to 4.5 or the ratio of the current short-period root mean square value to the long-period root mean square value is more than or equal to 1.3; and/or the number of the groups of groups,

the root mean square value is greater than or equal to 9.3 or greater than or equal to the lowest point value of the fitting equation.

The oil film whirl monitoring method provided by the embodiment can solve the defect that the setting of the fixed threshold value extremely depends on manual experience and professional knowledge, improves the accuracy and has better universality. The method specifically comprises the following steps: acquiring first operation data of a bearing in a normal state and second operation data of the bearing under the condition of oil film whirl fault, and respectively preprocessing the first operation data and the second operation data to acquire preprocessed first operation data and preprocessed second operation data; determining a first alarm baseline according to a preset mechanical vibration standard; determining a second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data; determining a target alarm baseline according to the first alarm baseline and the second alarm baseline; and monitoring the running state of the target bearing through the target alarm baseline. The application takes the early warning and alarming base line set by the mechanical vibration national standard GB/T6075.1-2012 as a bottom protection strategy, takes the ratio k of the short-period root mean square value average value to the long-period root mean square value average value and the lowest point of the fitting equation as an advance strategy, and has better accuracy and safety.

Example two

The embodiment provides an oil film whirl monitoring system. The present system embodiment may be used to perform the method embodiment of the present application, and for details not disclosed in the present system embodiment, please refer to the method embodiment of the present application. The system disclosed in this embodiment includes:

In some embodiments, the acquisition module further comprises a preprocessing unit for converting the first and second operation data into root mean square data, respectively.

In some embodiments, the system further comprises an alarm module, configured to send out an alarm message when the running state of the target bearing meets a preset condition after the running state of the target bearing is monitored through the target alarm baseline.

In some embodiments, the second determination module includes a first determination unit and a second determination unit; wherein, the liquid crystal display device comprises a liquid crystal display device,

the first determining unit is used for determining a current acquisition period value when an abnormal state occurs;

and the second determining unit is used for determining the ratio of the short-period root mean square value to the long-period root mean square value according to the current acquisition period value, the preprocessed first operation data and the preprocessed second operation data, and determining a second early warning baseline according to the ratio of the short-period root mean square value to the long-period root mean square value.

In some embodiments, the second determining module includes a third determining unit configured to determine an alarm value according to the preprocessed second operation data through a preset dominant regression model, and determine a second alarm baseline according to the alarm value.

In some embodiments, the preset dominant regression model includes:

In some embodiments, the second alarm baseline comprises:

b＝(x>f _min )？1:0

In some embodiments, the system further comprises a fault determination unit and an update unit; wherein, the liquid crystal display device comprises a liquid crystal display device,

the fault determining unit is used for determining fault data under the condition that the running state meets the preset condition;

and the updating unit is used for training the preset dominant regression model according to the fault data, redefining an alarm value, and updating the second alarm baseline according to the redetermined alarm value.

As an example, the oil film whirl monitoring system disclosed in this embodiment may specifically include the following modules:

the system comprises a data acquisition and preprocessing module, a data set storage module, a data conversion and visualization module, a linear model module, an alarm updating module, a monitoring baseline module, an early warning judging module, an alarm judging module, a computer and the like. Wherein:

the data acquisition module and the preprocessing module are used for acquiring data of machine vibration, marking the data as normal data and preprocessing operation of oil film whirl fault data, storing the normal data and the fault data as a data set, and storing the data in the data storage module;

The data set storage module is used for storing the data obtained by the data acquisition module and combining the data into a data set comprising normal data and oil film whirl fault data;

the data conversion and visualization module is used for converting the original vibration waveform data into a root mean square value and drawing a time domain graph of the root mean square value;

the linear model module is used for constructing a linear regression model, inputting oil film whirl data into the model, drawing a fitting equation, and outputting the minimum point value of the fitting equation;

the alarm updating module reads the lowest point value f of the fitting equation in the linear model module _min According to f _min Updating an alarm baseline in the monitoring baseline module according to the value;

the monitoring baseline module is used for storing an early warning baseline and an alarm baseline;

the early warning judging module is used for reading the early warning baselines in the monitoring baselines and judging whether the root mean square value meets the condition expression of the early warning baselines, if the root mean square value meets the condition, early warning processing can be performed, and if the root mean square value does not meet the condition, the early warning processing is not performed;

the alarm judging module is used for reading the alarm baselines in the monitoring baselines, judging whether the root mean square value meets the condition expression of the alarm baselines, and if not, not carrying out alarm processing;

The judging module is used for judging the conditions: whether the root mean square value is greater than 4.5, if the condition is satisfied, inputting data with the root mean square value greater than 4.5 into a linear model module; if the condition is not satisfied, not processing;

and the computer is used for deploying and training the linear regression model and storing the acquired data.

It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, and they may be centralized on a single computing device, or distributed across a network of computing devices. Alternatively, they may be implemented in program code executable by a computing device, such that they are stored in a storage device for execution by the computing device, and in some cases, the steps shown or described may be performed in a different order than what is shown or described, or they may be separately fabricated into individual integrated circuit modules, or a plurality of modules or steps in them may be fabricated into a single integrated circuit module.

Example III

The present embodiment provides a computer-readable storage medium. The computer readable storage medium stores a computer program, which when executed by a processor, may implement the method steps as in the foregoing method embodiments, which are not repeated herein.

The computer-readable storage medium may also include, among other things, computer programs, data files, data structures, etc., alone or in combination. The computer readable storage medium or computer program may be specifically designed and understood by those skilled in the art of computer software, or the computer readable storage medium may be well known and available to those skilled in the art of computer software. Examples of the computer readable storage medium include: magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CDROM discs and DVDs; magneto-optical media, such as optical disks; and hardware means, specifically configured to store and execute computer programs, such as read-only memory (ROM), random Access Memory (RAM), flash memory; or a server, app application mall, etc. Examples of computer programs include machine code (e.g., code produced by a compiler) and files containing higher level code that may be executed by the computer using an interpreter. The described hardware devices may be configured to act as one or more software modules to perform the operations and methods described above, and vice versa. In addition, the computer readable storage medium may be distributed among networked computer systems, and the program code or computer program may be stored and executed in a decentralized manner.

Example IV

The present embodiment provides a computer program product. The computer program product comprises a computer program or instructions which, when executed by a processor, implement all or part of the steps of the method as in the previous method embodiments, which are not repeated here.

Further, the computer program product may include one or more computer-executable components configured to perform embodiments when the program is run; the computer program product may also include a computer program tangibly embodied on a medium readable thereby, the computer program including program code for performing any of the methods of the embodiments of the present disclosure. In such an embodiment, the computer program may be downloaded and installed from a network via a communication portion, and/or installed from a removable medium.

Example five

The embodiment provides an electronic device. Fig. 6 is a connection block diagram of an electronic device according to an embodiment of the present application, and as shown in fig. 6, the electronic device 600 may include: one or more processors 601, memory 602, multimedia components 603, input/output (I/O) interfaces 604, and communication components 605.

Wherein the one or more processors 601 are adapted to perform all or part of the steps of the method embodiments as described above. The memory 602 is used to store various types of data, which may include, for example, instructions for any application or method in the electronic device, as well as application-related data.

The one or more processors 601 may be application specific integrated circuits (Application Specific Integrated Circuit, ASIC), digital signal processors (Digital Signal Processor, DSP), digital signal processing devices (Digital Signal Processing Device, DSPD), programmable logic devices (Programmable Logic Device, PLD), field programmable gate arrays (Field Programmable Gate Array, FPGA), controllers, microcontrollers, microprocessors or other electronic component implementations for performing the methods as in the method embodiments described above.

The Memory 602 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as static random access Memory (Static Random Access Memory, SRAM for short), electrically erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), erasable programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM for short), programmable Read-Only Memory (Programmable Read-Only Memory, PROM for short), read-Only Memory (ROM for short), magnetic Memory, flash Memory, magnetic disk, or optical disk.

The multimedia component 603 may include a screen, which may be a touch screen, and an audio component for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in a memory or transmitted through a communication component. The audio assembly further comprises at least one speaker for outputting audio signals.

The I/O interface 604 provides an interface between the one or more processors 601 and other interface modules, which may be a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.

The communication component 605 is used for wired or wireless communication between the electronic device 600 and other devices. The wired communication comprises communication through a network port, a serial port and the like; the wireless communication includes: wi-Fi, bluetooth, near field communication (Near Field Communication, NFC for short), 2G, 3G, 4G, 5G, or a combination of one or more of them. The corresponding communication component 605 may thus comprise: wi-Fi module, bluetooth module, NFC module.

In summary, the application provides an oil film whirl monitoring method, an oil film whirl monitoring device, a computer readable storage medium, a computer program product and electronic equipment. The method comprises the following steps: acquiring first operation data of a bearing in a normal state and second operation data of the bearing under the condition of oil film whirl fault, and respectively preprocessing the first operation data and the second operation data to acquire preprocessed first operation data and preprocessed second operation data; determining a first alarm baseline according to a preset mechanical vibration standard; determining a second alarm baseline according to the preprocessed first operation data and the preprocessed second operation data; determining a target alarm baseline according to the first alarm baseline and the second alarm baseline; and monitoring the running state of the target bearing through the target alarm baseline. The defect that the setting of the fixed threshold value extremely depends on manual experience and expertise is overcome, the accuracy is improved, and the method has better universality.

It should be further understood that the methods and systems disclosed in the embodiments of the present application may be implemented in other manners. The above-described method or system embodiments are merely illustrative, for example, flow diagrams and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of methods and apparatus according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, a computer program segment, or a portion of a computer program, which comprises one or more computer programs for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures, and in fact may be executed substantially concurrently, or in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer programs.

In the present disclosure, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, 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, article, 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, apparatus or device comprising such elements; if any, the terms "first," "second," etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of features indicated or implicitly indicating the precedence of features indicated; in the description of the present application, unless otherwise indicated, the terms "plurality", "multiple" and "multiple" mean at least two; if the description is to a server, it should be noted that the server may be an independent physical server or terminal, or may be a server cluster formed by a plurality of physical servers, or may be a cloud server capable of providing basic cloud computing services such as a cloud server, a cloud database, a cloud storage, a CDN, and the like; in the present application, if an intelligent terminal or a mobile device is described, it should be noted that the intelligent terminal or the mobile device may be a mobile phone, a tablet computer, a smart watch, a netbook, a wearable electronic device, a personal digital assistant (Personal Digital Assistant, PDA for short), an augmented Reality device (Augmented Reality, AR for short), a Virtual Reality device (VR for short), a smart television, a smart stereo, a personal computer (Personal Computer, PC for short), etc., but the present application is not limited thereto.

Finally it is pointed out that in the description of the present specification, the terms "one embodiment," "some embodiments," "example," "one example," or "some examples," etc., refer to particular features, structures, materials, or characteristics described in connection with the embodiment or example as being included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the present application have been illustrated and described above, it should be understood that the above embodiments are illustrative and that the present application is not limited to the embodiments described above for the purpose of facilitating understanding of the present application. Any person skilled in the art can make any modification and variation in form and detail without departing from the spirit and scope of the present disclosure, but the scope of the present disclosure is still subject to the scope of the present disclosure as defined by the appended claims.

Claims

1. A method for monitoring oil film whirl, the method comprising:

2. The oil film whirl monitoring method of claim 1, wherein said preprocessing said first and second operation data, respectively, comprises:

3. The oil film whirl monitoring method of claim 1, further comprising, after said monitoring of the operational state of the target bearing by said target warning baseline:

4. The oil film whirl monitoring method of claim 1, wherein said second alert baseline comprises a second pre-warning baseline, said determining a second alert baseline from said pre-processed first operational data and said pre-processed second operational data comprising:

determining a current acquisition period value when an abnormal state occurs;

5. The oil film whirl monitoring method of claim 1, wherein said second alarm baseline comprises a second alarm baseline, said determining a second alarm baseline from said preprocessed first operational data and said preprocessed second operational data comprising:

6. The oil film whirl monitoring method as claimed in claim 5, further comprising, after said monitoring of the operation state of the target bearing by said target warning baseline:

7. An oil film whirl monitoring system, comprising:

8. A computer program product comprising a computer program or instructions which, when executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.

9. A computer readable storage medium storing a computer program which, when executed by one or more processors, performs the steps of the method of any of claims 1 to 6.

10. An electronic device comprising a memory and one or more processors, the memory having stored thereon a computer program, the memory and the one or more processors being communicatively coupled to each other, the computer program, when executed by the one or more processors, performing the steps of the method of any of claims 1-6.