A portable rotating equipment fault diagnosis instrument and a diagnosis method

Abstract

The present invention discloses a portable rotating equipment fault diagnosis instrument and a diagnosis method, which obtains the original vibration waveform signal of the tested equipment during stable operation, and performs feature extraction on the processed waveform signal; obtains the speed information and speed fluctuation range configured after preprocessing, obtains the bandwidth when the frequency amplitude is obtained according to the speed fluctuation range, extracts the required frequency amplitude characteristic value by using the peak-finding method, and calculates the effective value of the through-frequency speed; matches the rule base according to the calculated characteristic value, and generates a diagnosis conclusion according to the rule base. The constructed rule base has been built into the handheld diagnostic instrument, and the rule base is not limited to equipment imbalance, common equipment faults such as misalignment, bearing inner ring, outer ring, cage, rolling element fault, bearing looseness, base looseness and other fault rules. This improves the defect that the fault location cannot be automatically determined during equipment inspection, realizes automatic equipment diagnosis, and ensures the accuracy of the equipment diagnosis conclusion.

Description

Technical Field

[0001] The present application relates to the technical field of fault diagnosis of rotating equipment, and in particular to a portable fault diagnosis instrument and a diagnosis method for rotating equipment. Background Art

[0002] Offline inspection of industrial equipment refers to a method of inspecting and evaluating equipment during operation through regular shutdown or specific maintenance cycles. Offline inspection usually includes inspection of equipment appearance, component wear, lubrication, vibration, etc. to ensure the normal operation and safety of the equipment.

[0003] Offline inspection of industrial equipment is completed through manual visual inspection and experience-based evaluation. With the development of technology, modern offline inspection of industrial equipment has gradually introduced various intelligent equipment and technologies. For example, the use of vibration sensors, infrared thermometers, ultrasonic detectors and other equipment, combined with data collection and analysis technology, can achieve more accurate monitoring and evaluation of the equipment's operating status.

[0004] Currently, the inspection equipment used by equipment inspectors on industrial sites all has a single vibration indicator. They can only judge whether the vibration of the equipment exceeds the standard based on the threshold, but cannot locate the specific fault of the equipment.

[0005] If the above equipment problems need to be analyzed specifically, it is also necessary to collect the equipment vibration data separately and copy it to the computer for relevant spectrum analysis. Data extraction, spectrum conversion and other related operations require relatively high work skills, and there is also a certain time lag. Summary of the invention

[0006] The technical problem to be solved by the present application is to provide a portable rotating equipment fault diagnosis instrument and diagnosis method to improve the defect that the fault location cannot be automatically determined during equipment inspection, realize automatic equipment diagnosis, and ensure the accuracy of the equipment diagnosis conclusion.

[0007] In order to solve the above technical problems, this application adopts the following technical solutions:

[0008] A portable rotating equipment fault diagnosis method, characterized by comprising the following steps:

[0009] S1: Obtain the original vibration waveform signal of the equipment under test when it is running stably, and set the time length for each waveform acquisition;

[0010] S2: preprocessing the original waveform signal to obtain the root mean square of the original waveform signal, and obtaining a data set of the root mean square absolute value;

[0011] S3: Set the root mean square coefficient, count the number of data in the data set of the absolute value that is greater than the product of the root mean square coefficient and the absolute value, and calculate the ratio of the number of data to the number of data of the original waveform signal;

[0012] S4: setting the root mean square coefficient, counting the number of data in the data set of the absolute value that is greater than the product of the root mean square coefficient and the absolute value, and calculating the ratio of the number of data to the number of data of the original waveform signal;

[0013] S5: If the ratio is greater than a preset threshold, it is determined that the data is abnormal. At the same time, the position of the data greater than the product of the root mean square coefficient and the absolute value in the data set of the absolute value is used to replace the corresponding data in the original waveform signal with the mean value of the original waveform signal to obtain a processed waveform signal;

[0014] S6: extracting features from the processed waveform signal; obtaining the speed information and speed fluctuation range configured after preprocessing, obtaining the bandwidth at the frequency amplitude according to the speed fluctuation range, extracting the required frequency amplitude feature value using the peak search method, and calculating the effective value of the through-frequency speed;

[0015] S7: Setting the fault type setting rule base, the rule base is set to determine the fault type of the device under test by calculating the relationship between the amplitudes of each frequency harmonic; the fault type is one of rotor imbalance, misalignment, bearing inner ring, outer ring, cage, rolling element failure, bearing looseness, base looseness; matching the rule base according to the calculated characteristic value, and generating a diagnostic conclusion according to the rule base.

[0016] In the above technical solution, S3: the root mean square coefficient is between 3 and 8.

[0017] In the above technical solution, S6 uses a feature extraction method to extract 1 to 5 times frequency amplitude data.

[0018] In the above technical solution, S6 first calculates the rotational frequency according to the input rotational speed. = speed / 60, use the sliding window to intercept the processed waveform signal, and form the spectrum data with one frequency and amplitude corresponding to each other; calculate the bandwidth w when searching for peaks = speed fluctuation value / 60; use the unilateral bandwidth w as the bandwidth for searching for peaks, and search for the frequency in the frequency sequence w, w] corresponds to the maximum value in the amplitude range, forming a frequency-doubling sequence , calculate the mean of the amplitude sequence = ; Calculate the amplitude from 1 to 5 times the rotation frequency[ ].

[0019] In the above technical solution, the frequency amplitude characteristic value extracted in step S7 is identified according to the entered equipment information. When the input speed information is set to extract the rotational frequency and its harmonic amplitude, the bearing model is input and set to extract and calculate the bearing characteristic frequency. When the waveform pass-frequency speed effective value is greater than the set pass-frequency speed effective value threshold, continue to judge. When the ratio of the 1-fold frequency amplitude to the 2-fold frequency amplitude is greater than the threshold sequence ratio threshold, a fault conclusion is obtained. Otherwise, other rule models are called to continue the judgment.

[0020] In the above technical solution, in S7, for the equipment rotor imbalance fault, the configured equipment type parameters are the motor equipment input speed, the number of rotor bars, the bearing model, and the power supply frequency; when the waveform pass-frequency speed effective value is greater than the set pass-frequency speed effective value threshold, continue to judge, and when the ratio of the 1-fold frequency amplitude to the 2-fold frequency amplitude is greater than the threshold sequence ratio threshold, it is set as a rotor imbalance fault.

[0021] In the above technical solution, the effective value threshold of the passband speed is 2.8.

[0022] In the above technical solution, the threshold sequence ratio threshold is 2.5.

[0023] Furthermore, the present invention also provides a portable rotating equipment fault diagnosis instrument that adopts the above-mentioned diagnosis method, and when the portable rotating equipment fault diagnosis instrument is working, it is used to execute the steps of the above-mentioned method.

[0024] Furthermore, the present invention also provides a storage medium storing a computer program, characterized in that: when the computer program is executed, it is used to implement any of the portable rotating device fault diagnosis methods described above.

[0025] The beneficial effects of the present application are as follows: the present application can avoid offline inspection, and can judge whether the vibration of the equipment exceeds the standard according to the threshold value, and can also locate the specific fault of the equipment. There is no need to collect the vibration data of the equipment separately and copy it to the computer for relevant graph analysis. Compared with the existing technology, the present application is convenient to operate and easy to promote on site.

[0026] Secondly, the present invention integrates data extraction, spectrum conversion and other related operations into the system, which runs automatically and has low technical requirements for on-site operators. On-site operators only need to input the rotation speed information of the device to obtain the diagnosis result, which is easy to use.

[0027] The present invention can integrate existing expert experience into a rule base for on-site use. The expert rule base is stored in the device in advance based on the experience so as to automatically detect and analyze on-site and give conclusions. It is suitable for on-site detection of various faults and has scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 The basic flow chart of the portable rotating equipment fault diagnosis method of the present invention.

[0030] Figure 2 Flowchart of feature extraction steps of the method of the present invention.

[0031] Figure 3 This is a specific implementation flow of the method of the present invention for determining a fault.

[0032] Figure 4 Parameter flow chart for configuring a device for the method and apparatus of the present invention.

[0033] Figure 5 This is a waveform diagram of an original signal according to another embodiment of the present invention.

[0034] Figure 6 The time domain and spectrum diagram after data preprocessing of the present invention.

[0035] Figure 7 This is the data point diagram after feature extraction. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0037] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0038] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0039] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the product of the application is usually placed when in use. They are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific position, be constructed and operated in a specific position, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0040] In addition, the terms "horizontal", "vertical", "overhanging" and the like do not mean that the components are required to be absolutely horizontal or overhanging, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0041] In the description of this application, it should also be noted that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0042] In the present application, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may include that the first and second features are in direct contact, or may include that the first and second features are not in direct contact but are in contact through another feature between them. Moreover, a first feature being "above", "above" and "above" a second feature includes that the first feature is directly above and obliquely above the second feature, or simply indicates that the first feature is higher in level than the second feature. A first feature being "below", "below" and "below" a second feature includes that the first feature is directly below and obliquely below the second feature, or simply indicates that the first feature is lower in level than the second feature.

[0043] The features and performance of the present application are further described in detail below in conjunction with the embodiments.

[0044] Example 1

[0045] The portable rotating equipment fault diagnosis method implemented according to the present invention comprises the following main steps:

[0046] S1: Data Collection

[0047] Obtain the original vibration waveform signal of the equipment under test when it is running stably, and each waveform is obtained for 3.2 seconds;

[0048] S2: Data calculation module

[0049] (1) Data preprocessing

[0050] 1. Calculation The root mean square of:

[0051] ;

[0052] 2. Calculation ;

[0053] 3. Set the RMS coefficient , The value of is between 3 and 8;

[0054] 4. Statistics Medium or larger Number of , and calculate ;

[0055] 5. If Greater than a preset threshold , then the data is judged to be abnormal, and the Medium or larger The location of the data will The corresponding data in is replaced by The mean of

[0056] (2) Feature extraction

[0057] Using the waveform signal processed in the above steps, feature extraction is performed;

[0058] 1. Calculate the speed based on the input speed , ;

[0059] 2. Assume that the processed waveform data is ; The signal is intercepted by sliding window method, the window length is 1s, the step length is 0.2 seconds, and FFT (Fast Fourier Transform) is used to calculate to form spectrum data. The spectrum data is divided into two parts: frequency , amplitude , the frequency and amplitude correspond one to one;

[0060] 3. Calculate the bandwidth when searching for peaks, w = (speed fluctuation value) / 60;

[0061] 4. Use the single-sided w as the bandwidth for peak search and find the frequency in the frequency sequence w, w] corresponds to the maximum value in the amplitude range, forming a frequency-doubling sequence , calculate the mean of the amplitude sequence = ;

[0062] 5. Use the above method to calculate the amplitude of 1 to 5 times the rotation frequency

[0063] [ ];

[0064] 6. Calculate the frequency amplitude of other components in the same way;

[0065] (3) Building a rule base

[0066] Based on the experience of industry experts and knowledge of equipment mechanisms, a mechanism model is constructed to identify the fault type.

[0067] Take the imbalance of the equipment rotor as an example to build a mechanism model:

[0068] S3: Configuration Module

[0069] The portable collector has a built-in rule base. When performing daily inspections, the inspector enters relevant information about the equipment corresponding to the measured point, such as the speed, number of rotor bars, bearing model, power supply frequency and other related information for motor equipment.

[0070] After the collection diagnosis is performed, analysis is automatically performed and diagnostic conclusions and maintenance suggestions are generated.

[0071] The method and apparatus of the present invention have the following important improvements:

[0072] 1. The constructed rule base has been built into the handheld diagnostic instrument. The rule base is not limited to equipment imbalance. Common equipment failures such as misalignment, bearing inner ring, outer ring, cage, rolling element failure, bearing looseness, base looseness and other fault rules are included.

[0073] 2. The extracted characteristic values ​​are identified based on the entered information. For example, the input speed information can extract the rotational frequency and its harmonic amplitude. The input bearing model can calculate the bearing characteristic frequency.

[0074] 3. Match the rule base according to the calculated feature values ​​and generate diagnostic conclusions based on the rule base.

[0075] Embodiment 2:

[0076] 1. Obtain 3.2s waveform data, the data sampling frequency is 32768Hz, the equipment speed is 1490r / min, such as Figure 5 shown.

[0077] 2. Data Preprocessing

[0078] Using the above preprocessing method, the sudden jump points in the waveform are filtered out. Figure 6 6a and 6b.

[0079] 3. Feature extraction

[0080] (1) Based on the above signal, the 1 to 5 times frequency amplitude data are extracted using the feature extraction method as shown in the following table. The distribution is as follows: Figure 7 shown.

[0081]

[0082] (2) Use the above data to perform integral transformation and calculate the effective value of the frequency conversion speed

[0083] The effective value of the through-frequency speed is: 10.84mm / s;

[0084] 4. Enforcement of rules

[0085] First, determine whether the effective value of the through-frequency speed is greater than 2.8, and then calculate that the ratio of the 1-fold frequency amplitude to the 2-fold frequency amplitude is greater than 2.5; the output diagnostic conclusion is that the equipment rotor is unbalanced.

[0086] The embodiments described above are part of the embodiments of the present application, rather than all of the embodiments. The detailed description of the embodiments of the present application is not intended to limit the scope of the present application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

Claims

1. A portable rotating equipment fault diagnosis method, characterized in that The steps include: S1: Obtain the original vibration waveform signal of the equipment under test when it is running stably, and set the time length for each waveform acquisition; S2: preprocessing the original waveform signal to obtain the root mean square of the original waveform signal, and obtaining a data set of the root mean square absolute value; S3: Set the root mean square coefficient, count the number of data in the data set of the absolute value that is greater than the product of the root mean square coefficient and the absolute value, and calculate the ratio of the number of data to the number of data of the original waveform signal; S4: If the ratio is greater than a preset threshold, it is determined to be data abnormality, and at the same time, the corresponding data in the original waveform signal is replaced with the mean value of the original waveform signal by using the position of the data greater than the product of the root mean square coefficient and the absolute value in the data set of the absolute value, so as to obtain a processed waveform signal; S5: extracting features from the processed waveform signal; obtaining the speed information and speed fluctuation range configured after preprocessing, obtaining the bandwidth of the frequency amplitude according to the speed fluctuation range, extracting the required frequency amplitude characteristic value by using the peak search method, and performing integral transformation on the frequency amplitude characteristic value to calculate the effective value of the through-frequency speed; The extracted frequency amplitude characteristic value is identified according to the entered equipment information. When the input speed information is set to extract the rotation frequency and its harmonic amplitude, the bearing model is entered and set to extract and calculate the bearing characteristic frequency; When the effective value of the waveform frequency passing speed is greater than the set effective value threshold of the frequency passing speed, the judgment continues. When the ratio of the 1-fold frequency amplitude to the 2-fold frequency amplitude is greater than the threshold sequence ratio threshold, a fault conclusion is obtained. Otherwise, other rule models are called to continue the judgment. S6: Setting a fault type setting rule base, the rule base is set to determine the fault type of the device under test by calculating the relationship between the amplitudes of each frequency multiplication; the fault type is one of rotor imbalance, misalignment, bearing inner ring, outer ring, cage, rolling element failure, bearing looseness, and base looseness; matching the rule base according to the calculated characteristic value, and generating a diagnostic conclusion according to the rule base; For equipment rotor imbalance faults, the configured equipment type parameters are the motor equipment input speed, number of rotor bars, bearing model, and power supply frequency; when the waveform pass-frequency speed effective value is greater than the set pass-frequency speed effective value threshold, continue to judge, and when the ratio of the 1-fold frequency amplitude to the 2-fold frequency amplitude is greater than the threshold sequence ratio threshold, it is set as a rotor imbalance fault.

2. The portable rotating equipment fault diagnosis method according to claim 1, characterized in that The RMS coefficient in S3 is between 3 and 8.

3. The portable rotating equipment fault diagnosis method according to claim 1, characterized in that S5 uses feature extraction method to extract 1 to 5 times frequency amplitude data.

4. The portable rotating equipment fault diagnosis method according to claim 1, characterized in that S5 first calculates the speed based on the input speed = speed / 60, use the sliding window to intercept the processed waveform signal, and form the spectrum data with one frequency and amplitude corresponding to each other; calculate the bandwidth w when searching for peaks = speed fluctuation value / 60; use the unilateral bandwidth w as the bandwidth for searching for peaks, and search for the frequency in the frequency sequence w, w] corresponds to the maximum value in the amplitude range, forming a frequency-doubling sequence , calculate the mean of the amplitude sequence = ; Calculate the amplitude from 1 to 5 times the rotation frequency[ ].

5. The portable rotating equipment fault diagnosis method according to claim 1, characterized in that The effective value threshold of the through-frequency speed is 2.

8.

6. The portable rotating equipment fault diagnosis method according to claim 1, characterized in that The threshold sequence ratio threshold is 2.

5.

7. A portable rotating equipment fault diagnosis instrument using the portable rotating equipment fault diagnosis method according to any one of claims 1 to 6, which is used to execute the steps of the above method when the portable rotating equipment fault diagnosis instrument is in operation.

8. A storage medium storing a computer program, characterized in that: When the computer program is executed, it is used to implement the portable rotating device fault diagnosis method described in any one of claims 1 to 6.

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