Vibration measurement rotating machine diagnosis method, system and device and storage medium

Abstract

The invention relates to a vibration measurement rotating machine diagnosis method, system and device and a storage medium, and relates to the technical field of bearing fault diagnosis, and the method comprises the steps: obtaining a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on the sampling input of a vibration sensor; performing preprocessing based on the vibration waveform characteristic signal to form sampling output information; analyzing and determining a fault reference database according to the bearing characteristic signal; judging whether the sampling output information can be matched from the fault reference database or not; if yes, bearing fault reason information is determined according to the consistency condition of the sampling output information and the fault reference database, and the bearing fault reason information is output to a display screen; and if not, continuing to obtain the vibration waveform characteristic signal. The method has the effect of improving the accuracy of the diagnosis result of the bearing fault.

Description

Technical Field

[0001] The present invention relates to the technical field of bearing fault diagnosis, and in particular to a vibration measurement rotating machinery diagnosis method, system, device and storage medium. Background Art

[0002] Bearing fault diagnosis refers to the process of monitoring, analyzing and judging the operating status of bearings in mechanical equipment to identify potential fault hazards and take corresponding preventive and repair measures. This technology is crucial to ensure the stable operation of equipment and extend the service life of equipment.

[0003] In the related technology, bearing fault diagnosis is a multi-step process involving data collection, signal processing, feature extraction, fault identification and diagnosis, and real-time monitoring and early warning. At present, when using vibration analysis to diagnose bearing faults, vibration signals are generally collected at the key points of the shortest path of the bearing through acceleration vibration sensors. The collected vibration signals are pre-processed, filtered and converted, and then displayed on the display screen. The operator then judges the displayed waveform based on his own experience, thereby diagnosing the bearing fault.

[0004] Regarding the above-mentioned related technologies, in the process of diagnosing bearing faults, the operator is required to judge the waveform displayed by the collected vibration signal based on his own experience. When the operator is inexperienced, it is easy to cause deviations in the diagnosis results of the bearing faults. Summary of the invention

[0005] In order to improve the accuracy of the diagnosis result of bearing fault, the present invention provides a vibration measurement rotating machinery diagnosis method, system, device and storage medium.

[0006] In a first aspect, the present invention provides a vibration measurement rotating machinery diagnosis method, which adopts the following technical solution:

[0007] A vibration measurement rotating machinery diagnosis method, comprising:

[0008] Acquire a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on a sampling input of a vibration sensor;

[0009] Preprocessing is performed based on the vibration waveform characteristic signal to form sampling output information;

[0010] Determine the fault reference database based on the bearing characteristic signal analysis;

[0011] Determine whether the sampled output information can be matched from the fault reference database;

[0012] If yes, the bearing fault cause information is determined based on the consistency between the sampled output information and the fault reference database, and the bearing fault cause information is output to the display screen;

[0013] If not, continue to obtain the vibration waveform characteristic signal.

[0014] Optionally, the method for determining the fault reference database includes:

[0015] Determine whether the bearing characteristic signal can be found in the preset bearing database;

[0016] If yes, retrieve the bearing fault output information based on the bearing characteristic signal, and use the bearing fault output information as a fault reference database;

[0017] If not, the bearing geometry information is retrieved according to the bearing characteristic signal;

[0018] Determine the cage fault characteristic frequency value based on the bearing geometry information analysis;

[0019] According to the characteristic frequency value of cage failure, the characteristic frequency value of inner and outer ring failure and the characteristic frequency value of rolling element failure are determined;

[0020] Based on the cage fault characteristic frequency value, the inner and outer ring fault characteristic frequency value and the rolling element fault characteristic frequency value, they are combined and used as comprehensive fault characteristic frequency information;

[0021] According to the corresponding relationship between the comprehensive fault characteristic frequency information and the preset comprehensive fault output information, the comprehensive fault output information corresponding to the comprehensive fault characteristic frequency information is determined, and the comprehensive fault output information is used as a fault reference database.

[0022] Optionally, a method for determining bearing failure cause information includes:

[0023] Determine whether the sampled output information is consistent with the fault reference database;

[0024] If yes, the information in the fault reference database that is consistent with the sampled output information is taken as the sampled consistent fault output information;

[0025] According to the correspondence between the sampling consistent fault output information and the preset sampling consistent fault cause information, the sampling consistent fault cause information corresponding to the sampling consistent fault output information is determined, and the sampling consistent fault cause information is used as the bearing fault cause information;

[0026] If not, then analyze the similarity between the sampled output information and the fault benchmark database and use it as the sampled output benchmark similarity;

[0027] The estimated fault cause information is determined based on whether the sampled output benchmark similarity falls within the preset similarity benchmark interval, and the estimated fault cause information is used as the bearing fault cause information.

[0028] Optionally, the method further includes steps after outputting the bearing failure cause information to the display screen, which are as follows:

[0029] Determine the sampling position point based on the vibration waveform characteristic signal;

[0030] According to the correspondence between the sampling position point, the bearing characteristic signal and the preset detection equipment information, the detection equipment information corresponding to the sampling position point and the bearing characteristic signal is determined;

[0031] Based on the detection equipment information, the bearing failure cause information is stored and a detection equipment failure cause database is formed.

[0032] Optionally, the method further includes steps after outputting the bearing failure cause information to the display screen, which are as follows:

[0033] Get the server IP address information;

[0034] Send the bearing failure cause information to the address corresponding to the server IP address information.

[0035] In a second aspect, the present invention provides a vibration measurement rotating machinery diagnostic system, which adopts the following technical solution:

[0036] A vibration measurement rotating machinery diagnostic system, comprising:

[0037] A vibration sampling module, used to obtain a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on a sampling input of a vibration sensor;

[0038] A memory for storing a program of the vibration measurement rotating machinery diagnosis method as described in any one of the first aspects;

[0039] The processor loads and executes the program in the memory and implements the vibration measurement rotating machinery diagnosis method as described in any one of the first aspects.

[0040] In a third aspect, the present invention provides a vibration measurement rotating machinery diagnostic device, which adopts the following technical solution:

[0041] A vibration measurement rotating machinery diagnosis device comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the vibration measurement rotating machinery diagnosis method as described in any one of the first aspects.

[0042] In a fourth aspect, the present invention provides a computer storage medium capable of storing a corresponding program, which has the characteristic of facilitating improving the accuracy of the diagnosis result of the bearing fault, and adopts the following technical solution:

[0043] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute the vibration measurement rotating machinery diagnosis method as described in any one of the first aspects.

[0044] In summary, the present invention includes at least one of the following beneficial technical effects:

[0045] 1. The acquired vibration waveform characteristic signal is pre-processed to form sampling output information, and the acquired bearing characteristic signal is analyzed to determine the fault reference database. The sampling output information is judged to see whether it can be matched from the fault reference database. When it is matched, the consistency between the sampling output information and the fault reference database is analyzed to determine the bearing fault cause information and output it to the display screen. When it is not matched, the vibration waveform characteristic signal is continuously acquired, so that the operator can directly understand the fault cause without relying on his own experience, thereby improving the accuracy of the bearing fault diagnosis result;

[0046] 2. It is judged whether the bearing characteristic signal can be queried from the preset bearing database. When it can be queried, the bearing fault output information is retrieved through the bearing characteristic signal and used as the fault reference database. When it cannot be queried, the bearing geometric dimension information is retrieved through the bearing characteristic signal and analyzed to determine the cage fault characteristic frequency value, and then the inner and outer ring fault characteristic frequency values ​​and the rolling element fault characteristic frequency values ​​are determined by analyzing the cage fault characteristic frequency value, and then the cage fault characteristic frequency values, the inner and outer ring fault characteristic frequency values ​​and the rolling element fault characteristic frequency values ​​are combined and used as comprehensive fault characteristic frequency information, and the comprehensive fault output information is determined by querying the comprehensive fault characteristic frequency information and used as the fault reference database, thereby improving the accuracy of the acquired fault reference database;

[0047] 3. Determine the server IP address information through sampling location point query, and then determine the 5G module transmission control information through server IP address information query, and use the 5G module to transmit the bearing fault cause information to the address corresponding to the server IP address information, so as to use 5G technology to transmit the fault cause in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flow chart of a method for vibration measurement of rotating machinery diagnosis according to an embodiment of the present application;

[0049] Figure 2is a method flow chart of a method for determining a fault reference database according to an embodiment of the present application;

[0050] Figure 3 is a method flow chart of a method for determining bearing fault cause information in an embodiment of the present application;

[0051] Figure 4 This is the method flow of the step after outputting the bearing fault cause information to the display screen in the embodiment of the present application. Figure 1 ;

[0052] Figure 5 This is the method flow of the step after outputting the bearing fault cause information to the display screen in the embodiment of the present application. Figure 2 ;

[0053] Figure 6 It is a system flow chart of vibration measurement rotating machinery diagnosis in an embodiment of the present application.

[0054] Explanation of the accompanying drawings: 1. Vibration sampling module; 2. Memory; 3. Processor. DETAILED DESCRIPTION

[0055] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0056] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0057] As described above, in the current process of bearing fault diagnosis, when the operator is inexperienced, it is easy to cause the problem of deviation in the diagnosis result of bearing fault. A vibration measurement rotating machinery diagnosis method obtains the vibration waveform characteristic signal and the bearing characteristic signal, and analyzes and processes them respectively to obtain the sampling output information and the normal reference output information, and when the two are inconsistent, analyzes and determines the fault reference database, and analyzes and determines the bearing fault cause information based on the consistency between the sampling output information and the fault reference database and outputs it to the display screen, and retrieves the sampling position point for analysis, so that the bearing fault cause information is sent to the address corresponding to the server IP address information according to the 5G module transmission control information, so that the operator does not need to rely on his own experience to directly understand the cause of the fault, thereby improving the accuracy of the bearing fault diagnosis result.

[0058] The embodiment of the invention discloses a vibration measurement rotating machinery diagnosis method.

[0059] Reference Figure 1 , a vibration measurement rotating machinery diagnosis method comprising:

[0060] Step S100: Acquire a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on sampling input from a vibration sensor.

[0061] Among them, the vibration waveform characteristic signal refers to the sampling information obtained by vibration detection of the bearing in the equipment that needs to be fault detected. The vibration waveform characteristic signal can be obtained by receiving the signal output after the detection from the accelerometer, microphone, thermocouple and other sensors. The bearing characteristic signal refers to the characteristic information corresponding to the vibration bearing during the current detection. The bearing characteristic signal is obtained after the operator pre-inputs. In this embodiment, the vibration waveform characteristic signal is a four-channel vibration acceleration signal sampling.

[0062] When acquiring the vibration waveform characteristic signal, the sampling frequency must be greater than or equal to twice the highest frequency of the analog signal so that the spectrum of the sampled signal does not produce spectrum aliasing, and the number of frequency domain sampling points must be greater than or equal to the length of the time domain discrete signal so that no aliasing occurs in the time domain.

[0063] Step S200: Preprocessing is performed based on the vibration waveform characteristic signal to form sampling output information.

[0064] Among them, the sampling output information refers to the information after the received sampling signal is amplified, filtered, FFT transformed, etc. The sampling output information is formed by amplifying, filtering, and FFT transforming the vibration waveform characteristic signal, which is convenient for subsequent use.

[0065] Step S300: determining a fault reference database based on bearing characteristic signal analysis.

[0066] Among them, the fault reference database refers to the reference output information under different fault causes. By analyzing the bearing characteristic signal, the normal reference output information is determined to facilitate subsequent use.

[0067] Step S400: Determine whether the sampled output information can be matched from the fault reference database. If yes, execute step S500; if no, execute step S600.

[0068] Here, it is determined whether the sampled output information can be matched in the fault reference database, thereby determining whether the currently sampled bearing has a fault.

[0069] Step S500: Determine the bearing fault cause information based on the consistency between the sampled output information and the fault reference database, and output the bearing fault cause information to the display screen.

[0070] Among them, the bearing fault cause information refers to the cause information corresponding to the bearing fault and other abnormalities. When the sampled output information can be matched from the fault reference database, it means that the currently sampled bearing has a fault. Therefore, by analyzing the consistency between the sampled output information and the fault reference database, the bearing fault cause information is determined and output to the display screen, so that the operator can directly understand the cause of the fault without relying on his own experience, thereby improving the accuracy of the bearing fault diagnosis results.

[0071] Step S600: Continue to obtain the vibration waveform characteristic signal.

[0072] When the sampled output information cannot be matched from the fault reference database, it means that the bearing currently sampled does not have a fault, so the vibration waveform characteristic signal continues to be obtained.

[0073] exist Figure 1 In step S300, in order to further ensure the rationality of the fault reference database, it is necessary to further analyze and calculate the fault reference database. Figure 2 The steps shown are explained in detail.

[0074] exist Figure 1 In step S600, in order to further ensure the rationality of the fault reference database, it is necessary to further analyze and calculate the fault reference database. Figure 2 The steps shown are explained in detail.

[0075] Reference Figure 2 , the method for determining the fault reference database includes the following steps:

[0076] Step S310: Determine whether the bearing characteristic signal can be found in the preset bearing database. If yes, execute step S320; if no, execute step S330.

[0077] The bearing database refers to a database that stores data related to bearings of various specifications. The bearing database can be obtained through pre-input by the operator, or retrieved by querying a bearing-related website.

[0078] By determining whether the bearing characteristic signal can be queried from the preset bearing database, it is determined whether the fault output information of the detected bearing can be directly obtained.

[0079] Step S320: retrieve bearing fault output information based on the bearing characteristic signal, and use the bearing fault output information as a fault reference database.

[0080] The bearing fault output information refers to the output information when various bearing faults are detected. The bearing fault output information is obtained by querying from a preset fault database based on the bearing characteristic signal. The fault database is obtained and stored after the operator performs fault tests on bearings of various specifications.

[0081] When the bearing characteristic signal can be queried from the preset bearing database, it means that the fault output information of the detected bearing can be directly obtained at this time. Therefore, the bearing fault output information is retrieved through the bearing characteristic signal, and the bearing fault output information is used as the fault reference database, thereby improving the accuracy of the acquired fault reference database.

[0082] Step S330: Retrieve bearing geometry information according to the bearing characteristic signal.

[0083] Among them, the bearing characteristic signal includes bearing geometric dimension information, which refers to the various dimension information of the detected bearing in geometric shape. When the bearing characteristic signal cannot be queried from the preset bearing database, it means that the fault output information of the detected bearing cannot be directly obtained at this time, so the bearing geometric dimension information is retrieved through the bearing characteristic signal for subsequent use.

[0084] Step S340: Analyze and determine the cage fault characteristic frequency value based on the bearing geometry information.

[0085] Among them, the cage fault characteristic frequency value refers to the characteristic frequency value when the cage in the bearing is detected to have a fault. The bearing pitch circle diameter value, rolling element diameter value, rolling element number value, contact angle, inner steel ring speed value and outer steel ring speed value are retrieved according to the bearing geometric dimension information, and the bearing pitch circle diameter value, rolling element diameter value, rolling element number value, contact angle, inner steel ring speed value and outer steel ring speed value are calculated based on the preset cage fault characteristic frequency value calculation formula to obtain the cage fault characteristic frequency value.

[0086] The calculation formula for the characteristic frequency value of the cage fault refers to the formula for calculating the characteristic frequency value of the cage fault. The calculation formula for the characteristic frequency value of the cage fault is obtained after the operator pre-enters. The calculation formula for the characteristic frequency value of the cage fault is: Where: FTF is the characteristic frequency of bearing cage failure; D is the bearing pitch diameter; d is the rolling element diameter; N is the number of rolling elements; α is the contact angle, R pmi is the speed value of the inner steel ring; R pmo It is the speed value of the outer steel ring.

[0087] Step S350: determining inner and outer ring fault characteristic frequency values ​​and rolling element fault characteristic frequency values ​​according to cage fault characteristic frequency value analysis.

[0088] Among them, the inner and outer ring fault characteristic frequency value refers to the characteristic frequency value when the inner and outer rings of the bearing are faulty, and the rolling element fault characteristic frequency value refers to the characteristic frequency value when the rolling element of the bearing is faulty. The inner and outer ring fault characteristic frequency values ​​include the bearing inner ring fault characteristic frequency value and the bearing outer ring fault characteristic frequency value. Based on the cage fault characteristic frequency value, the bearing inner ring fault characteristic frequency value and the bearing outer ring fault characteristic frequency value are analyzed and calculated respectively. At this time, the bearing inner ring fault characteristic frequency value is Among them, BPI is the characteristic frequency value of the inner ring fault of the bearing; the characteristic frequency value of the outer ring fault of the bearing is Among them, BPO is the characteristic frequency value of the bearing outer ring fault.

[0089] Based on the characteristic frequency value of the cage failure, the characteristic frequency value of the rolling element failure is analyzed and calculated. Among them, BSF is the characteristic frequency value of rolling element failure.

[0090] Step S360: combining the cage fault characteristic frequency value, the inner and outer ring fault characteristic frequency value, and the rolling element fault characteristic frequency value as comprehensive fault characteristic frequency information.

[0091] Among them, the comprehensive fault characteristic frequency information refers to the information after integrating the various fault frequencies of the detected bearing. The cage fault characteristic frequency value, the inner and outer ring fault characteristic frequency value and the rolling element fault characteristic frequency value are combined, and the combined information is used as the comprehensive fault characteristic frequency information for subsequent use.

[0092] Step S370: Determine the fault comprehensive output information corresponding to the comprehensive fault characteristic frequency information according to the corresponding relationship between the comprehensive fault characteristic frequency information and the preset fault comprehensive output information, and use the fault comprehensive output information as a fault reference database.

[0093] Among them, the fault comprehensive output information refers to the output information corresponding to each fault detected in the bearing, and the fault comprehensive output information is obtained by querying from a database storing comprehensive fault characteristic frequency information and comprehensive fault output information. The comprehensive fault output information is determined by querying the comprehensive fault characteristic frequency information, and the comprehensive fault output information is used as a fault reference database, so as to facilitate the acquisition of the fault reference database and improve the accuracy of the acquired fault reference database.

[0094] exist Figure 1 In step S500, in order to further ensure the rationality of the bearing fault cause information, it is necessary to further analyze and calculate the bearing fault cause information separately, specifically by Figure 3 The steps shown are explained in detail.

[0095] Reference Figure 3 , the method for determining the cause information of the bearing failure includes the following steps:

[0096] Step S510: Determine whether the sampled output information is consistent with the fault reference database. If yes, execute step S520; if no, execute step S540.

[0097] Here, it is determined whether the sampling output information is consistent with the fault reference database, thereby determining whether the cause of the fault can be directly obtained.

[0098] Step S520: The information in the fault reference database that is consistent with the sampled output information is used as sampled consistent fault output information.

[0099] Among them, sampling consistent fault output information refers to the output information corresponding to the situation when the output obtained by sampling is consistent with the reference output. When the sampling output information is consistent with the fault reference database, it means that the cause of the fault can be directly obtained at this time. Therefore, the information in the fault reference database that is consistent with the sampling output information is used as sampling consistent fault output information, so as to facilitate subsequent use.

[0100] Step S530: Determine the sampling consistent fault cause information corresponding to the sampling consistent fault output information according to the correspondence between the sampling consistent fault output information and the preset sampling consistent fault cause information, and use the sampling consistent fault cause information as the bearing fault cause information.

[0101] The sampling consistent fault cause information refers to the fault cause information corresponding to the output obtained by sampling and the reference output being consistent. The sampling consistent fault cause information is obtained by querying from a database storing the sampling consistent fault output information and the sampling consistent fault cause information. The sampling consistent fault cause information is determined by querying the sampling consistent fault output information and used as the bearing fault cause information, thereby improving the accuracy of the acquired bearing fault cause information.

[0102] Step S540: Analyze the similarity between the sampled output information and the fault reference database and use it as the sampled output reference similarity.

[0103] Among them, the sampling output benchmark similarity refers to the similarity value when the sampled output is similar to the benchmark output. When the sampling output information is not consistent with the fault benchmark database, it means that the cause of the fault cannot be directly obtained at this time. Therefore, the similarity between the sampling output information and the fault benchmark database is analyzed and used as the sampling output benchmark similarity for subsequent use.

[0104] Step S550: Determine the estimated fault cause information according to whether the sampled output benchmark similarity falls within a preset similarity benchmark interval, and use the estimated fault cause information as the bearing fault cause information.

[0105] Among them, the similarity reference interval refers to the reference interval that the similarity needs to be in when the cause of the fault can be determined, and the similarity reference interval is obtained after being pre-input by the operator. The estimated fault cause information refers to the estimated information for estimating the cause of the fault, by analyzing the falling of the sampled output reference similarity and the preset similarity reference interval, according to the fault reference database corresponding to the sampled output reference similarity falling within the similarity reference interval, the corresponding fault cause is retrieved and combined to determine the estimated fault cause information and use it as the bearing fault cause information, thereby improving the accuracy of the acquired bearing fault cause information.

[0106] exist Figure 1 After step S500, in order to further ensure the rationality of outputting the bearing fault cause information to the display screen, it is necessary to perform further separate analysis and calculation on the bearing fault cause information after outputting the bearing fault cause information to the display screen. Figure 4 The steps shown are explained in detail.

[0107] Reference Figure 4, the steps after outputting the bearing fault cause information to the display screen include the following steps:

[0108] Step S710: Retrieve sampling position points based on the vibration waveform characteristic signal.

[0109] The vibration waveform characteristic signal includes a sampling position point, which refers to the position point where the operator is located when sampling is performed at the current time. The sampling position point is detected by a position sensor on the sampling device and then acquired and stored. The sampling position point is retrieved through the vibration waveform characteristic signal, so as to facilitate subsequent use.

[0110] Step S720: According to the correspondence between the sampling position points, the bearing characteristic signal and the preset detection equipment information, the detection equipment information corresponding to the sampling position points and the bearing characteristic signal is determined.

[0111] Among them, the detection equipment information refers to the equipment information of the bearing currently being tested, and the detection equipment information is obtained by querying from a database that stores sampling position points, bearing characteristic signals and detection equipment information. The detection equipment information is determined by querying the sampling position points and bearing characteristic signals, which is convenient for subsequent use.

[0112] Step S730: storing bearing fault cause information based on the detection equipment information and forming a detection equipment fault cause database.

[0113] Among them, the detection equipment failure cause database refers to a database that stores the corresponding causes when bearing failures occur in the equipment where each bearing is located. The bearing failure cause information is stored through the detection equipment information to form a detection equipment failure cause database, which is convenient for subsequent direct retrieval of the detection equipment failure cause database for use.

[0114] Furthermore, in order to improve the accuracy of the acquired bearing fault cause information, after step S550, the following steps are also included.

[0115] Step S551: Retrieve the information on devices affected by the fault cause based on the estimated fault cause information.

[0116] Among them, the device information affected by the fault cause refers to the device information that will produce the corresponding impact of the estimated fault cause. The device information affected by the fault cause queries the device that will produce the fault cause through the estimated fault cause information and retrieves it, so as to facilitate subsequent use.

[0117] Step S552: Determine whether the detection device information is consistent with the fault cause-affecting device information. If yes, execute step S553; if no, execute step S554.

[0118] Among them, by judging whether the detection equipment information is consistent with the equipment information affecting the cause of the fault, it is judged whether the current fault cause is caused by the equipment where the bearing is located.

[0119] Step S553: ​​Continue to output bearing failure cause information.

[0120] Among them, when the detection equipment information is consistent with the equipment information affected by the fault cause, it means that the current fault cause is caused by the equipment where the bearing is located, so the bearing fault cause information continues to be output.

[0121] Step S554: Analyze the device similarity between the detection device information and the device information affected by the fault cause and use it as the device similarity.

[0122] Among them, equipment similarity refers to the similarity value when there is similarity between the detection equipment and the equipment affecting the cause of the fault. When the detection equipment information is inconsistent with the equipment information affecting the cause of the fault, it means that the current fault cause is not caused by the equipment where the bearing is located. Therefore, the equipment similarity between the detection equipment information and the equipment information affecting the cause of the fault is analyzed and used as the equipment similarity to facilitate subsequent use.

[0123] Step S555: Determine the detection device influencing cause information according to whether the device similarity falls within the preset device similarity reference interval, and add the detection device influencing cause information to the bearing fault cause information to form new bearing fault cause information.

[0124] The equipment similarity benchmark interval refers to the benchmark similarity interval corresponding to the addition of influencing causes when there are similarities between the equipments. The equipment similarity benchmark interval is obtained through pre-input by the operator.

[0125] By analyzing the situation where the equipment similarity falls into the preset equipment similarity benchmark interval, when the equipment similarity falls into the equipment similarity benchmark interval, it means that the influencing cause corresponding to the equipment information affected by the fault cause needs to be retrieved and added. Therefore, based on the equipment information affected by the fault cause, the influencing cause information of the detection equipment is retrieved, and the influencing cause information of the detection equipment is added to the bearing fault cause information to form new bearing fault cause information, thereby improving the accuracy of the acquired bearing fault cause information.

[0126] exist Figure 1 After step S500, in order to further ensure the rationality of outputting the bearing fault cause information to the display screen, it is necessary to perform further separate analysis and calculation on the bearing fault cause information after outputting the bearing fault cause information to the display screen. Figure 5 The steps shown are explained in detail.

[0127] Reference Figure 5, the steps after outputting the bearing fault cause information to the display screen include the following steps:

[0128] Step S810: Obtain server IP address information.

[0129] Among them, the server IP address information refers to the IP address information corresponding to the server when 5G transmission is performed at the sampling location, and the server IP address information is obtained by querying from a database storing the server IP address information.

[0130] Step S820: Send the bearing failure cause information to the address corresponding to the server IP address information.

[0131] Among them, by sending the bearing failure cause information to the address corresponding to the server IP address information, 5G is used to transmit the bearing failure cause information, and then the signal is transmitted in time, so that the operator can remotely and timely understand the bearing failure cause information.

[0132] Reference Figure 6 Based on the same inventive concept, an embodiment of the present invention provides a vibration measurement rotating machinery diagnosis system, comprising:

[0133] A vibration sampling module 1 is used to obtain a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on a sampling input of a vibration sensor;

[0134] Memory 2, used to store Figures 1 to 5 A program for a vibration measurement rotating machinery diagnostic method as described in any one of the above;

[0135] Processor 3 loads the program in the execution memory and implements the following Figures 1 to 5 The vibration measurement rotating machinery diagnosis method described in any one of the above.

[0136] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, wherein the memory stores a program that can be loaded and executed by the processor. Figures 1 to 5 A computer program for the vibration measurement rotating machinery diagnosis method as described in any one of the above.

[0137] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0138] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded and executed by a processor. Figures 1 to 5 A computer program for the vibration measurement rotating machinery diagnosis method as described in any one of the above.

[0139] The present disclosure relates to methods, computing devices, computer-readable storage media, and / or computer program products. The computer program product may include computer-readable program instructions for executing various aspects of the present disclosure.

[0140] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0141] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge computing devices. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0142] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed entirely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0143] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0144] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0145] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0146] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the equipment, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0147] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

[0148] The above are only optional embodiments of the present disclosure and are not intended to limit the present disclosure. For those skilled in the art, the present disclosure may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A vibration measurement rotating machinery diagnosis method, characterized in that: include: Acquire a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on a sampling input of a vibration sensor; Preprocessing is performed based on the vibration waveform characteristic signal to form sampling output information; Determine the fault reference database based on the bearing characteristic signal analysis; Determine whether the sampled output information can be matched from the fault reference database; If yes, the bearing fault cause information is determined based on the consistency between the sampled output information and the fault reference database, and the bearing fault cause information is output to the display screen; If not, continue to obtain the vibration waveform characteristic signal.

2. The vibration measurement rotating machinery diagnosis method according to claim 1, characterized in that: The method for determining the fault reference database includes: Determine whether the bearing characteristic signal can be found in the preset bearing database; If yes, retrieve the bearing fault output information based on the bearing characteristic signal, and use the bearing fault output information as a fault reference database; If not, the bearing geometry information is retrieved according to the bearing characteristic signal; Determine the cage fault characteristic frequency value based on the bearing geometry information analysis; According to the characteristic frequency value of cage failure, the characteristic frequency value of inner and outer ring failure and the characteristic frequency value of rolling element failure are determined; Based on the cage fault characteristic frequency value, the inner and outer ring fault characteristic frequency value and the rolling element fault characteristic frequency value, they are combined and used as comprehensive fault characteristic frequency information; According to the corresponding relationship between the comprehensive fault characteristic frequency information and the preset comprehensive fault output information, the comprehensive fault output information corresponding to the comprehensive fault characteristic frequency information is determined, and the comprehensive fault output information is used as a fault reference database.

3. The vibration measurement rotating machinery diagnosis method according to claim 2, characterized in that: Methods for determining bearing failure cause information include: Determine whether the sampled output information is consistent with the fault reference database; If yes, the information in the fault reference database that is consistent with the sampled output information is taken as the sampled consistent fault output information; According to the correspondence between the sampling consistent fault output information and the preset sampling consistent fault cause information, the sampling consistent fault cause information corresponding to the sampling consistent fault output information is determined, and the sampling consistent fault cause information is used as the bearing fault cause information; If not, then analyze the similarity between the sampled output information and the fault benchmark database and use it as the sampled output benchmark similarity; The estimated fault cause information is determined based on whether the sampled output benchmark similarity falls within the preset similarity benchmark interval, and the estimated fault cause information is used as the bearing fault cause information.

4. The vibration measurement rotating machinery diagnosis method according to claim 1, characterized in that: The steps after outputting the bearing failure cause information to the display screen are as follows: Determine the sampling position point based on the vibration waveform characteristic signal; According to the correspondence between the sampling position point, the bearing characteristic signal and the preset detection equipment information, the detection equipment information corresponding to the sampling position point and the bearing characteristic signal is determined; Based on the detection equipment information, the bearing failure cause information is stored and a detection equipment failure cause database is formed.

5. The vibration measurement rotating machinery diagnosis method according to claim 1, characterized in that: The steps after outputting the bearing failure cause information to the display screen are as follows: Get the server IP address information; Send the bearing failure cause information to the address corresponding to the server IP address information.

6. A vibration measurement rotating machinery diagnostic system, characterized in that: include: A vibration sampling module (1) is used to obtain a vibration waveform characteristic signal and a bearing characteristic signal of a rotating equipment bearing based on a sampling input of a vibration sensor; A memory (2) for storing a program of the vibration measurement rotating machinery diagnosis method according to any one of claims 1 to 5; A processor (3) is configured to load and execute a program in a memory and implement a vibration measurement rotating machinery diagnosis method according to any one of claims 1 to 5.

7. A vibration measurement rotating machinery diagnostic device, characterized in that: The invention comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and executes the vibration measurement rotating machinery diagnosis method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the vibration measurement rotating machinery diagnosis method according to any one of claims 1 to 5.

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