Rotary mechanical equipment vibration online monitoring device and detection method

Abstract

The invention discloses a rotary mechanical equipment vibration on-line monitoring device and a detection method, belongs to the technical field of monitoring, and adopts a multipath diversity communication technology to improve signal transmission stability and receiving quality and solve the problem of limited signal transmission distance. And meanwhile, a feature mode decomposition method based on noise compensation is creatively proposed, the problem of noise signal interference is solved, and the recognition accuracy of the composite fault of the rotary mechanical equipment is improved.

Description

Technical Field

[0001] The present invention belongs to the field of monitoring technology, and in particular relates to an online vibration monitoring device and a detection method for rotating mechanical equipment. Background Art

[0002] Rotating mechanical equipment such as motors, fans, and reducers are widely used in industry as key transmission mechanical devices. These devices play a key role in production, and safety and reliability need to be considered during operation. Especially when running at high speeds or under heavy loads, safety measures and monitoring systems must be taken to avoid accidents.

[0003] As a preventive maintenance method, vibration detection is of great significance for the early diagnosis of rotating equipment failures. The reliability, real-time and stability of the data collected are directly related to the results of equipment detection and diagnosis. At present, the vibration signal acquisition instruments on the market can obtain vibration signals in two ways: wired transmission and wireless transmission. Wired transmission has the disadvantages of high wiring cost, limited installation location, large size and difficult maintenance. Wireless transmission has certain flexibility compared to wired transmission and is the future development direction of vibration signal acquisition, but it has limitations such as limited signal transmission distance, signal interference and power supply dependence.

[0004] In order to solve the existing problems of wireless vibration signal acquisition devices, the present invention provides an online vibration monitoring device and detection method for rotating mechanical equipment. The device can monitor, process and analyze vibration signals in real time, and perform online diagnosis of the fault type and fault location of the equipment. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an online vibration monitoring device and a detection method for rotating mechanical equipment, which solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for online monitoring and detection of vibration of rotating mechanical equipment, the core algorithm of the algorithm used to implement the equipment is a characteristic mode decomposition method based on noise compensation, and the characteristic mode decomposition method based on noise compensation includes the following steps:

[0007] S1. Define the simulation signal x(t) of the vibration model:

[0008]

[0009] in, represents a periodic pulse, and the parameter υ is set to 1%-2% of the periodic fault period. represents random pulses, represents the harmonics generated by gear meshing, A, B, C represent the amplitudes of different signal components, M represents the number of pulses and harmonics, T and Tb represents the time interval between adjacent pulses, f and Indicates frequency and phase;

[0010] S2. Define the correlation kurtosis calculation function CK(T):

[0011]

[0012] T k (n) Subject to:

[0013] Where T k (n) is the periodic function of the kth decomposition mode, f k is the kth filter, its length is L, M represents the number of displacements;

[0014] S3, introducing the decomposed signal x(t) into the Gaussian white noise ρ obtained by the sound wave acquisition component 3 k n j (t), and perform eigenmode decomposition:

[0015] CK M (x(t)+ρ k n j (t)) = CK j (t)+r j (t)

[0016] Among them, CK j (t) is the characteristic mode phasor, r j (t) is the decomposition amount, the number of noise additions j = 1, 2, ..., K, the K value is equal to the number of segments of the original signal frequency interval, and the one-dimensional probability density of Gaussian white noise is expressed as:

[0017]

[0018] Where u is the mean (mathematical expectation) of the Gaussian distribution, σ 2 is the variance of the Gaussian distribution. When u=0, σ 2 =1, it is a standard normal distribution;

[0019] The frequency interval is defined as:

[0020]

[0021] When all Gaussian white noise ρ k n j When (t) is added and decomposed, the characteristic mode decomposition algorithm ends, and the original signal x(t) is decomposed into:

[0022]

[0023] S4. Use the autocorrelation function to describe the periodic fault characteristics to determine the final decomposition mode. The autocorrelation function expression of the signal x(n) is:

[0024]

[0025] A method for online monitoring and detection of vibration of rotating mechanical equipment adopts an algorithm implementation device with a characteristic mode decomposition method based on noise compensation as the core algorithm, comprising the following steps:

[0026] Step 1: Utilize a multi-antenna system to receive multiple groups of signal signals from a wireless vibration collection device and transmit them to a radio frequency front end to pre-amplify and preliminarily process the signals received by the multi-antenna system;

[0027] The preliminary processing refers to the filtering operation of the received signal by the filter to ensure that only the signal of a specific frequency band can pass through and filter out the interference of non-required frequencies;

[0028] Step 2: Receive the signal from the RF front end using the signal processing unit and digitally process, analyze and merge the signal;

[0029] Step 3: Utilize the diversity receiver to receive the signal processed by the signal processing unit and perform weighting and combining to maximize the quality and strength of the received signal;

[0030] Step 4: Using the algorithm to implement the device to perform algorithm processing on the signal processed in step 3;

[0031] Step 5: Use the terminal device receiving algorithm to implement the signal processing results of the device and display the vibration analysis results, and perform vibration alarm monitoring at the same time;

[0032] Step 6: Manage and control the collaboration and communication between various hardware components through the control unit and the interface device;

[0033] The diversity method of the diversity device adopts the Selective Maximum Ratio Combining (SMRC) diversity method, which uses the quality of the received signal (such as the signal-to-noise ratio) of each receiving antenna to weightedly combine all received signals.

[0034] A rotating mechanical equipment vibration online monitoring and detection device, using the above rotating mechanical equipment vibration online monitoring and detection method, comprises a housing and a screw, the housing comprises an upper housing and a lower housing, the lower housing is threadedly connected to the upper housing, and further comprises:

[0035] The base is detachably mounted on the bottom end of the lower shell, and grooves are provided on the upper and lower parts of the base;

[0036] The sound wave collection component is embedded in a groove located at the upper part of the base and is used to obtain noise data;

[0037] A piezoelectric element is embedded and installed in the lower housing and is located above the base and is threadedly connected to the screw rod, and is used to collect the original vibration data of the device;

[0038] A mass block is installed above the piezoelectric element and is provided with a first through hole for the screw to pass through;

[0039] A compression spring is fixedly connected to the top of the mass block and is provided with a second through hole for the screw rod to pass through;

[0040] The fastening block is threadedly connected to the screw rod and is used to cause the compression spring, the mass fastener and the piezoelectric element to perform resistance limiting;

[0041] A wireless communication layer, on which a signal collection layer for receiving and sending vibration and noise data is connected and is threadedly connected to the screw rod, and is used to upload the data collected by the signal collection layer to the multi-antenna system;

[0042] The power supply layer is installed on the upper shell of the housing and adopts dual power supply to power the device.

[0043] Further technical solution: the base is magnetic and can be adsorbed on the vibration measuring point of the equipment for use.

[0044] Further technical solution: The lower groove of the base is used to receive the noise generated when the device rotates.

[0045] The present invention provides an online vibration monitoring device and detection method for rotating mechanical equipment, which has the following beneficial effects compared with the prior art:

[0046] 1. The online monitoring and detection device proposed by the present invention introduces a noise detection component inside, which can compensate for the signal error caused by the equipment's own noise during the vibration monitoring process and reduce the signal acquisition error.

[0047] 2. The power supply component of the online monitoring and detection device proposed by the present invention adopts a split modular design, and the power supply component can be replaced at any time, solving the problem of difficulty in replacing the power supply of the wireless vibration collection device.

[0048] 3. The online vibration monitoring and detection method for rotating mechanical equipment proposed in the present invention adopts multi-path diversity communication technology to improve the stability and reception quality of signal transmission and solve the problem of limited signal transmission distance.

[0049] 4. The characteristic mode decomposition method in the online vibration monitoring and detection method of rotating mechanical equipment proposed in the present invention introduces noise signals, takes the correlation kurtosis as the objective function, takes into account the impulse and periodicity of the signal, and performs noise compensation on the signal, thereby greatly improving the accuracy of vibration signal acquisition.

[0050] 5. The online vibration monitoring and detection method for rotating mechanical equipment proposed in the present invention is not limited by the filter shape, bandwidth, and center frequency, can accurately decompose mechanical fault information, and has a high recognition rate for complex and compound faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of characteristic mode decomposition based on noise compensation in the present invention.

[0052] Figure 2 It is a signal data transmission path diagram of the online vibration monitoring and detection method of rotating mechanical equipment in the present invention.

[0053] Figure 3 It is the time domain diagram and spectrum diagram of the one-dimensional vibration signal after weighted combination by the diversity device of the present invention.

[0054] Figure 4 The present invention performs denoising by characteristic mode decomposition and introduces white noise, and the number of decomposition modes is set to 5, thereby obtaining 5 decomposition modes and their envelope spectra.

[0055] Figure 5 It is a schematic diagram of the three-dimensional structure of the online vibration monitoring and detection device for rotating mechanical equipment of the present invention.

[0056] Figure 6 It is a schematic diagram of the overall structure of the online vibration monitoring and detection device for rotating mechanical equipment of the present invention.

[0057] Notes on the figure markings: 1. Shell; 101. Lower shell; 102. Upper shell; 2. Base; 3. Sound wave collection component; 4. Piezoelectric element; 5. Mass block; 6. Compression spring; 7. Fastening block; 8. Signal collection layer; 9. Wireless communication layer; 10. Power supply layer. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0059] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0060] Example 1

[0061] See also Figure 1 , Figure 3 as well as Figure 4 , provided in one embodiment of the present invention, is a method for online monitoring and detecting vibration of rotating mechanical equipment, wherein the core algorithm of the algorithm used to implement the equipment is a characteristic mode decomposition method based on noise compensation, and the characteristic mode decomposition method based on noise compensation comprises the following steps:

[0062] S1. Define the simulation signal x(t) of the vibration model:

[0063]

[0064] in, represents a periodic pulse, and the parameter υ is set to 1%-2% of the periodic fault period. represents random pulses, represents the harmonics generated by gear meshing, A, B, C represent the amplitudes of different signal components, M represents the number of pulses and harmonics, T and T b represents the time interval between adjacent pulses, f and Indicates frequency and phase;

[0065] S2. Define the correlation kurtosis calculation function CK(T):

[0066]

[0067] T k (n) Subject to:

[0068] Where T k (n) is the periodic function of the kth decomposition mode, f k is the kth filter, its length is L, M represents the number of displacements;

[0069] S3, introducing the decomposed signal x(t) into the Gaussian white noise ρ obtained by the sound wave acquisition component 3 k n j (t), and perform eigenmode decomposition:

[0070] CK M (x(t)+ρ k n j (t)) = CK j (t)+r j (t)

[0071] Among them, CK j (t) is the characteristic mode phasor, r j (t) is the decomposition amount, the number of noise additions j = 1, 2, ..., K, the K value is equal to the number of segments of the original signal frequency interval, and the one-dimensional probability density of Gaussian white noise is expressed as:

[0072]

[0073] Where u is the mean (mathematical expectation) of the Gaussian distribution, σ 2 is the variance of the Gaussian distribution. When u=0, σ 2 =1, it is a standard normal distribution;

[0074] The frequency interval is defined as:

[0075]

[0076] When all Gaussian white noise ρ k n j When (t) is added and decomposed, the characteristic mode decomposition algorithm ends, and the original signal x(t) is decomposed into:

[0077]

[0078] S4. Use the autocorrelation function to describe the periodic fault characteristics to determine the final decomposition mode. The autocorrelation function expression of the signal x(n) is:

[0079]

[0080] The above-mentioned characteristic mode decomposition method introduces a noise signal and takes the correlation kurtosis as the objective function. It also considers the impulse and periodicity of the signal and performs noise compensation on the signal, thereby greatly improving the accuracy of vibration signal acquisition.

[0081] Example 2

[0082] See also Figure 2 A method for online monitoring and detecting vibration of rotating mechanical equipment is provided, which adopts an algorithm implementation device with a characteristic mode decomposition method based on noise compensation as the core algorithm, and comprises the following steps:

[0083] Step 1: Utilize a multi-antenna system to receive multiple groups of signal signals from a wireless vibration collection device and transmit them to a radio frequency front end to pre-amplify and preliminarily process the signals received by the multi-antenna system;

[0084] The preliminary processing refers to the filtering operation of the received signal by the filter to ensure that only the signal of a specific frequency band can pass through and filter out the interference of non-required frequencies;

[0085] Step 2: Receive the signal from the RF front end using the signal processing unit and digitally process, analyze and merge the signal;

[0086] Step 3: Utilize the diversity receiver to receive the signal processed by the signal processing unit and perform weighting and combining to maximize the quality and strength of the received signal;

[0087] Step 4: The algorithm implementation device can evaluate the signal quality and obtain the signal conditions, and adjust the signal processing parameters according to the signal quality evaluation results and the signal conditions, and finally implement the algorithm;

[0088] The specific steps of step 4 are:

[0089] The algorithm implementation device uses two indicators, signal-to-noise ratio and bit error rate, to evaluate signal quality. The signal-to-noise ratio (SNR) is used to measure the strength of the signal relative to the background noise, and the bit error rate (BER) is used to measure the proportion of error bits in the received data.

[0090] When the signal-to-noise ratio is lower than the preset signal-to-noise ratio threshold, the algorithm implementation device uses the least mean square algorithm (LMS) to optimize the signal;

[0091] When the signal-to-noise ratio is higher than the signal-to-noise ratio threshold, the recursive least squares (RLS) method is used for signal optimization;

[0092] When the bit error rate (BER) is higher than the preset bit error rate threshold, quadrature phase keying (QPSK) is preferentially selected for modulation processing. If the bit error rate continues to exceed the bit error rate threshold after the quadrature phase keying (QPSK) modulation processing, the 16-order quadrature amplitude modulation (16-QAM) mode is used for modulation processing;

[0093] The algorithm implements the device receiving the modulated signal and outputting the algorithm result;

[0094] Step 5: Use the terminal device receiving algorithm to implement the signal processing results of the device and display the vibration analysis results, and perform vibration alarm monitoring at the same time;

[0095] Step 6: Manage and control the collaboration and communication between various hardware components through the control unit and the interface device;

[0096] The diversity method of the diversity device adopts the Selective Maximum Ratio Combining (SMRC) diversity method, which uses the quality of the received signal (such as the signal-to-noise ratio) of each receiving antenna to weightedly combine all received signals.

[0097] Multipath diversity communication technology is used to improve the stability of signal transmission and the reception quality, and to solve the problem of limited signal transmission distance. This method is not limited by the filter shape, bandwidth, and center frequency, can accurately decompose mechanical fault information, and has a high recognition rate for complex and compound faults.

[0098] pass Figure 4It can be seen that the selection of the number of decomposition modes plays an important role in the feature extraction of faults. Too few modes will cause the decomposition to lose some potential fault information. The characteristic mode decomposition method can quickly and accurately identify complex fault characteristics in industrial noise environments after noise compensation, effectively improving the accuracy and robustness of rotating machinery fault diagnosis.

[0099] Example 3

[0100] See also Figure 5 as well as Figure 6 , a rotating mechanical equipment vibration online monitoring detection device, using the above rotating mechanical equipment vibration online monitoring detection method, including a housing and a screw, the housing including an upper housing 102 and a lower housing 101, the lower housing 101 is threadedly connected with the lower housing 101, and also includes:

[0101] The base 2 is detachably mounted on the bottom end of the lower housing 101, and grooves are provided on the upper and lower parts thereof;

[0102] The sound wave collection component 3 is embedded in a groove located at the upper part of the base 2 and is used to obtain noise data;

[0103] The piezoelectric element 4 is embedded in the lower housing 101 and is located above the base 2 and is threadedly connected to the screw rod, and is used to collect the original vibration data of the device;

[0104] The mass block 5 is mounted above the piezoelectric element 4 and is provided with a first through hole for the screw to pass through;

[0105] A compression spring 6 is fixedly connected to the mass block 5 and is provided with a second through hole for the screw to pass through;

[0106] The fastening block 7 is threadedly connected to the screw rod and is used to cause the compression spring 6, the mass fastener and the piezoelectric element 4 to perform resistance limiting;

[0107] A wireless communication layer 9, on which a signal collection layer 8 for receiving and sending vibration and noise data is connected and threadedly connected to the screw, is used to upload the data collected by the signal collection layer 8 to the multi-antenna system;

[0108] The power supply layer 10 is installed on the upper shell 102 of the housing and uses a dual power supply to power the device;

[0109] The base 2 has magnetic properties and can be adsorbed on the vibration measuring point of the equipment for use;

[0110] The lower groove of the base 2 is used to receive the noise generated when the device rotates.

[0111] In an embodiment of the present invention, the noise data obtained by the sound wave collection component 3 and the vibration data obtained by the piezoelectric element 4 are transmitted to the signal collection layer 8. The signal collection layer 8 receives and sends vibration and noise data. The wireless communication layer 9 uploads the collected data to the signal processing unit (multi-antenna system), which is further displayed and alarmed on the vibration monitoring platform. At the same time, the power supply layer 10 adopts dual power supply, which on the one hand prolongs the power supply replacement time, and on the other hand avoids the impact of a single power supply failure on the power supply of the device.

[0112] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0113] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for online monitoring and detection of vibration of rotating mechanical equipment, wherein the core algorithm of the algorithm used to implement the equipment is a characteristic mode decomposition method based on noise compensation, characterized in that: The noise compensation-based eigenmode decomposition method comprises the following steps: S1. Define the simulation signal x(t) of the vibration model: in, represents a periodic pulse, and the parameter υ is set to 1%-2% of the periodic fault period. represents random pulses, represents the harmonics generated by gear meshing, A, B, C represent the amplitudes of different signal components, M represents the number of pulses and harmonics, T and T b represents the time interval between adjacent pulses, f and Indicates frequency and phase; S2. Define the correlation kurtosis calculation function CK(T): T k (n) Subject to: Where T k (n) is the periodic function of the kth decomposition mode, f k is the kth filter, its length is L, M represents the number of displacements; S3, introducing the decomposed signal x(t) into the Gaussian white noise ρ obtained by the sound wave acquisition component (3) k n j (t), and perform eigenmode decomposition: CK M (x(t)+ρ k n j (t))=CK j (t)+r j (t) Among them, CK j (t) is the characteristic mode phasor, r j (t) is the decomposition amount, the number of noise additions j = 1, 2, ..., K, the K value is equal to the number of segments of the original signal frequency interval, and the one-dimensional probability density of Gaussian white noise is expressed as: Where u is the mean (mathematical expectation) of the Gaussian distribution, σ 2 is the variance of the Gaussian distribution. When u=0, σ 2 =1, it is a standard normal distribution; The frequency interval is defined as: When all Gaussian white noise ρ k n j When (t) is added and decomposed, the characteristic mode decomposition algorithm ends, and the original signal x(t) is decomposed into: S4. Use the autocorrelation function to describe the periodic fault characteristics to determine the final decomposition mode. The autocorrelation function expression of the signal x(n) is:

2. The method for online monitoring vibration of rotating mechanical equipment according to claim 1 adopts an algorithm implementation device with a characteristic mode decomposition method based on noise compensation as the core algorithm, characterized in that: The following steps are involved: Step 1: Utilize a multi-antenna system to receive multiple groups of signal signals from a wireless vibration collection device and transmit them to a radio frequency front end to pre-amplify and preliminarily process the signals received by the multi-antenna system; The preliminary processing refers to the filtering operation of the received signal by the filter to ensure that only the signal of a specific frequency band can pass through and filter out the interference of non-required frequencies; Step 2: Receive the signal from the RF front end using the signal processing unit and digitally process, analyze and merge the signal; Step 3: Utilize the diversity receiver to receive the signal processed by the signal processing unit and perform weighting and combining to maximize the quality and strength of the received signal; Step 4: Using the algorithm to implement the device to perform algorithm processing on the signal processed in step 3; Step 5: Use the terminal device receiving algorithm to implement the signal processing results of the device and display the vibration analysis results, and perform vibration alarm monitoring at the same time; Step 6: Manage and control the collaboration and communication between various hardware components through the control unit and interface devices.

3. The method for online monitoring and detecting vibration of rotating mechanical equipment according to claim 2, characterized in that: The diversity method of the diversity device adopts a selective maximum ratio combining diversity method, and weightedly combines all received signals using the quality of the received signal of each receiving antenna.

4. A rotating mechanical equipment vibration online monitoring and detection device, using the rotating mechanical equipment vibration online monitoring and detection method according to claim 3, characterized in that: The invention comprises a housing and a screw, wherein the housing comprises an upper housing (102) and a lower housing (101), wherein the lower housing (101) is threadedly connected to the upper housing (101), and further comprises: A base (2) is detachably mounted on the bottom end of the lower shell (101), and grooves are provided on the upper and lower parts of the base; A sound wave collection component (3) is embedded in a groove located at the upper part of the base (2) and is used to obtain noise data; A piezoelectric element (4) is embedded in the lower housing (101), is located above the base (2), and is threadedly connected to the screw rod, and is used to collect raw vibration data of the device; A mass block (5) is mounted above the piezoelectric element (4) and is provided with a first through hole for the screw to pass through; A compression spring (6) is fixedly connected to the top of the mass block (5) and is provided with a second through hole for the screw rod to pass through; A fastening block (7) is threadedly connected to the screw rod and is used to cause the compression spring (6), the mass fastener and the piezoelectric element (4) to perform resistance limiting; A wireless communication layer (9) is connected to a signal collection layer (8) for receiving and sending vibration and noise data and is threadedly connected to the screw rod, and is used to upload the data collected by the signal collection layer (8) to the multi-antenna system; The power supply layer (10) is installed on the upper shell (102) of the housing and adopts dual power supply to provide power supply for the device.

5. The rotating mechanical equipment vibration online monitoring and detection device according to claim 4 is characterized in that: The base (2) has magnetism and can be adsorbed on a vibration measuring point of the equipment for use.

6. The rotating mechanical equipment vibration online monitoring and detection device according to claim 4 is characterized in that: The lower groove of the base (2) is used to receive the noise generated when the device rotates.

Images