A rotating equipment bearing fault detection method, device, equipment and storage medium

Abstract

The application relates to the technical field of fault detection, and discloses a rotating equipment bearing fault detection method, device, equipment and storage medium, the method comprising the following steps: determining a vibration sampling frequency and a rotating speed sampling frequency; collecting vibration information of a rotating equipment in a start-stop process based on the vibration sampling frequency, and obtaining a vibration signal; collecting rotating speed information of the rotating equipment in the start-stop process based on the rotating speed sampling frequency, and obtaining a rotating speed signal; associating the vibration signal and the rotating speed signal, and obtaining a bearing demodulation spectrum; and judging whether a bearing to be analyzed has a fault based on the bearing demodulation spectrum. The application can effectively extract low-frequency characteristics of early bearing faults, enhance the distinguishability of fault signals, and effectively improve the diagnosis precision of bearing faults.

Description

Technical Field

[0001] This invention relates to the field of fault detection technology, and specifically to a method, apparatus, equipment, and storage medium for detecting faults in rotating equipment bearings. Background Technology

[0002] Resonance demodulation technology based on vibration response signals from specific parts of rotating equipment is a highly efficient detection method that separates fault impact signals through resonance characteristics. It is a commonly used method in industry for detecting early faults or defects in bearing supports. This technology leverages the amplification characteristics of the "impact" load generated by the bearing's motion based on the resonant response of the support structure. It identifies the degree and location of bearing defects by utilizing the periodicity of defects in the bearing components and the modulation relationship of the resonant response. In the specific signal processing, considering the modulation relationship of the support structure resonance on the vibration response of the defective component, as well as the influence of the low-frequency response excited by the rotation of the rotating component on the feature extraction of the bearing defect signal, and using a bandpass filter to extract the modulation signal components containing the structural resonance and defect motion frequency from the original vibration response for analysis, is the core of the resonance demodulation method and the foundation for subsequent signal processing.

[0003] For general low-speed rotating equipment, since the resonant frequency of the support structure is much higher than the fault frequency characteristic of the bearing components, when using a bandpass filter to extract the modulated signal of the components, the filter bandwidth will not drop into the low-frequency signal range where the rotor rotation frequency and the bearing component rotation frequency are located, under the condition of covering the bearing fault detection requirements, and will not affect the accuracy of signal extraction. However, for high-speed or ultra-high-speed rotating equipment, on the one hand, the resonant frequency of the support structure cannot be increased indefinitely, and on the other hand, since the filter bandwidth will increase relatively when the component rotation frequency is too high, in actual analysis, the bandpass filter can easily drop into the low-frequency range of rotor rotation or bearing component excitation, thus affecting the accuracy of subsequent signal extraction. Summary of the Invention

[0004] In view of this, the present invention provides a method, apparatus, device and storage medium for detecting bearing faults in rotating equipment, in order to solve the problem in the prior art that it is difficult to accurately extract the bearing fault signal in the bearing fault diagnosis of high-speed or ultra-high-speed rotating equipment by means of resonance demodulation method, which affects the accuracy of the diagnosis results.

[0005] In a first aspect, the present invention provides a method for detecting bearing faults in rotating equipment, the method comprising:

[0006] Determine the vibration sampling frequency and the rotational speed sampling frequency;

[0007] Vibration information of rotating equipment during start-up and shutdown is collected based on vibration sampling frequency to obtain vibration signals;

[0008] The rotational speed signal is obtained by collecting rotational speed information during the start-up and shutdown process of the rotating equipment based on the rotational speed sampling frequency.

[0009] The vibration signal and the rotational speed signal are correlated to obtain the bearing demodulation spectrum;

[0010] Based on the bearing demodulation spectrum, determine whether the bearing to be analyzed has a fault.

[0011] This invention proposes an early fault detection method for bearings in ultra-high-speed rotating equipment based on start-up and shutdown data analysis. By utilizing the vibration response of low-speed operating conditions during start-up and shutdown, the method improves the distance relationship between the operating frequency of bearing components and the resonant frequency of the support structure, making it better meet the implementation conditions of the resonance demodulation method. This enables the effective extraction of low-frequency characteristics of early bearing faults, enhances the identifiability of fault signals, and thus improves the accuracy of bearing fault diagnosis.

[0012] In one alternative implementation, the vibration sampling frequency is determined through the following steps:

[0013] Determine the high-frequency resonant frequency of the rotating equipment during start-up and shutdown;

[0014] Based on the high-frequency resonant frequency and the modulation carrier relationship function, the bearing passage frequency used for demodulation is determined; where the modulation carrier relationship function is: k1=FA / (FR / 2), where k1 represents the modulation signal pulse width coefficient, FA represents the high-frequency resonant frequency, and FR represents the bearing passage frequency;

[0015] The vibration sampling frequency is determined based on the high-frequency resonant frequency and the bearing passage frequency.

[0016] In this embodiment, the vibration sampling frequency is determined based on the high-frequency resonant frequency from the bearing to the sensor installation position and the bearing passing frequency. This effectively avoids signal distortion and aliasing, helps to accurately capture early fault signals, and improves the sensitivity and reliability of fault diagnosis.

[0017] In one optional implementation, the vibration sampling frequency is determined based on the high-frequency resonant frequency and the bearing passage frequency, including:

[0018] Substitute the high-frequency resonant frequency and the bearing passage frequency into the vibration sampling frequency determination function to determine the vibration sampling frequency.

[0019] The vibration sampling frequency determination function is: FS≥2.56(FA+(FR / 2));

[0020] FS represents the minimum vibration sampling frequency.

[0021] In this embodiment, the rotational speed sampling frequency is a preset multiple of the vibration sampling frequency, and the preset multiple is an integer greater than or equal to 1; at the same time, the rotational speed sampling frequency FD is greater than SH / 60×k2×k3. This can ensure that key vibration characteristics are effectively captured under high speed conditions, which helps to avoid signal loss and aliasing, thereby improving the accuracy and reliability of early fault diagnosis.

[0022] In one optional implementation, the rotational speed sampling frequency is a preset multiple of the vibration sampling frequency and is greater than (SH / 60)×k2×k3; the preset multiple is greater than or equal to 1;

[0023] Where k2 represents the transmission ratio between the speed measuring shaft and the bearing shaft to be evaluated, and k3 represents the number of pulses obtained by the speed sensor in each rotation cycle of the speed measuring shaft.

[0024] This implementation method helps reduce data redundancy and optimize signal processing by rationally controlling the timing of vibration and speed signal acquisition during the start-up and stop of rotating equipment. Furthermore, setting the maximum low-temperature operating speed suitable for resonance demodulation to ((FR / 2) / k4)×60 ensures effective capture of fault characteristics within the critical frequency range, improving the accuracy of fault diagnosis.

[0025] In one alternative implementation, during the start-up process of the rotating equipment, the acquisition of vibration and speed signals is stopped when the highest speed under low operating conditions is reached.

[0026] Vibration and speed signals are collected when the rotating equipment stops and reaches the highest speed under low operating conditions.

[0027] The maximum speed under low operating conditions is: SH=((FR / 2) / k4)×60, where k4 is greater than or equal to 3 times the bearing passing frequency.

[0028] In this embodiment, the low-frequency characteristics of the bearing fault signal are effectively extracted through bandpass filtering and envelope analysis, improving the accuracy of fault diagnosis. Finally, speed tracking processing compensates for the influence of speed changes on the target signal, enabling accurate extraction of fault-related vibration orders and further enhancing the reliability of fault diagnosis.

[0029] In one alternative implementation, before associating the vibration signal and the rotational speed signal, the method further includes:

[0030] A bandwidth filter is constructed based on the vibration sampling frequency, high-frequency resonant frequency, bearing passage frequency, and modulation signal pulse width coefficient.

[0031] A low-pass filter is constructed based on the bearing's passing frequency.

[0032] The vibration signal is passed through a bandwidth filter to obtain the first vibration signal;

[0033] The first vibration signal is processed by envelope analysis to obtain the second vibration signal;

[0034] The second vibration signal is passed through a low-pass filter to obtain the target vibration signal, which is then used to correlate with the rotational speed signal.

[0035] In one optional implementation, the vibration signal and the rotational speed signal are correlated to obtain the bearing demodulation spectrum, including:

[0036] Based on the vibration sampling frequency, rotational speed sampling frequency, and rotational speed impulse information, the target vibration signal is tracked in order to obtain an equal-phase sampling sequence.

[0037] Fourier transform is performed based on the equiphase sampling sequence to obtain the bearing demodulation spectrum of the corresponding order.

[0038] In this embodiment, by tracking the order based on vibration sampling frequency, rotational speed sampling frequency, and rotational speed impulse information, the vibration signal can be correlated with the rotational speed, accurately extracting the vibration order features related to bearing faults and avoiding interference from rotational speed fluctuations on the analysis results. Furthermore, by processing the equiphase sampling sequence using Fourier transform, a clear bearing demodulation spectrum can be obtained, making the bearing fault characteristics more apparent in the frequency domain, further improving the sensitivity of fault detection and the accuracy of diagnosis.

[0039] In a second aspect, the present invention provides a rotating equipment bearing fault detection device, the device comprising:

[0040] The determination module is used to determine the vibration sampling frequency and the rotational speed sampling frequency;

[0041] The vibration signal acquisition module is used to acquire vibration information of rotating equipment during the start-up and shutdown process based on the vibration sampling frequency, and obtain vibration signals.

[0042] The rotational speed signal acquisition module is used to acquire rotational speed information of rotating equipment during start-up and shutdown based on the rotational speed sampling frequency, and obtain the rotational speed signal.

[0043] The tracking module is used to correlate the vibration signal and the rotational speed signal to obtain the bearing demodulation spectrum;

[0044] The analysis module is used to determine whether the bearing under analysis has a fault based on the bearing demodulation spectrum.

[0045] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the rotating equipment bearing fault detection method described in the first aspect or any corresponding embodiment.

[0046] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the rotating equipment bearing fault detection method of the first aspect or any corresponding embodiment described above.

[0047] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the rotating equipment bearing fault detection method described in the first aspect or any corresponding embodiment.

[0048] It should be noted that the rotating equipment bearing fault detection device, computer equipment, computer-readable storage medium, and computer program product provided by this invention correspond to the aforementioned rotating equipment bearing fault detection method. Therefore, regarding the beneficial effects of the rotating equipment bearing fault detection device, computer equipment, computer-readable storage medium, and computer program product, please refer to the description of the corresponding beneficial effects of the rotating equipment bearing fault detection method above, and will not be repeated here. Attached Figure Description

[0049] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0050] Figure 1 This is a schematic flowchart of a method for detecting bearing failures in rotating equipment according to an embodiment of the present invention;

[0051] Figure 2 This is a structural block diagram of a rotating equipment bearing fault detection device according to an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0053] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] According to an embodiment of the present invention, a method for detecting bearing failures in rotating equipment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0055] This embodiment provides a method for detecting bearing faults in rotating equipment, which can be executed by devices such as servers, terminals, and mobile terminals. Figure 1 This is a flowchart of a rotating equipment bearing fault detection method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0056] Step S101: Determine the vibration sampling frequency and the rotational speed sampling frequency.

[0057] In this embodiment, the vibration sampling frequency is determined by the high-frequency resonant frequency from the bearing to the sensor mounting position in the rotating equipment and the bearing's passing frequency; the rotational speed sampling frequency is determined by the vibration sampling frequency. If multiple high-frequency resonant frequencies exist from the bearing to the sensor mounting position, the vibration sampling frequency and rotational speed sampling frequency corresponding to each high-frequency resonant frequency can be determined separately, and the signal acquisition process can be repeated according to the vibration sampling frequency and rotational speed sampling frequency. Furthermore, setting different bandpass and low-pass filters in subsequent sampling sequences can facilitate resonance demodulation processing at multiple resonant points.

[0058] Regarding sensors, speed sensors and vibration sensors can be installed on high-speed or ultra-high-speed rotating equipment. The speed and vibration sensors are fixed to specific locations on the equipment using bolts or mounting brackets. They are connected to a signal acquisition unit using dedicated cables, which can be mounted on a server, terminal, mobile terminal, or similar device. During operation, the signal acquisition unit powers the speed and vibration sensors and collects their signal responses. The signal acquisition unit operates according to a preset mode, performing tasks such as filtering, detection, order tracking, and bearing feature extraction and evaluation of signals associated with specific operating conditions as needed.

[0059] The vibration sampling frequency and rotational speed sampling frequency in this embodiment are suitable for capturing early fault characteristics of bearings in high-speed or ultra-high-speed rotating equipment under low operating conditions.

[0060] Step S102 collects vibration information of the rotating equipment during the start-up and shutdown process based on the vibration sampling frequency to obtain vibration signals.

[0061] Under normal rated operating conditions, the vibration signal of the bearing is relatively stable and the frequency range of the signal is relatively clear. However, when the bearing has an early failure, the signal becomes more complex and difficult to identify. Especially at high speeds, the early failure signal is often weak and easily drowned out by other high-frequency noise.

[0062] For example, if the rotation frequency of a rotating device reaches 1000Hz, it means that the device will undergo 1000 rotations per second. This implies that the frequency of the vibration signal may also be at the same level or higher. Therefore, the sampling frequency needs to be much higher than the frequency of the fault signal, possibly between 20kHz and 50kHz, to ensure that high-frequency details are captured and to avoid undersampling.

[0063] Therefore, in this embodiment, vibration information of the rotating equipment during start-up and shutdown is collected using a vibration sampling frequency determined based on the high-frequency resonant frequency and the bearing's passing frequency. Furthermore, this embodiment collects vibration information under low operating conditions, i.e., during start-up and shutdown, and processes it to more accurately diagnose early bearing failures.

[0064] Among them, the maximum speed suitable for resonance demodulation under low operating conditions can be ((FR / 2) / k4)×60, where k4 is related to the bearing component's passing frequency and is recommended to be no less than 3 times the bearing's passing frequency FR. Considering the weak characteristics of the bearing signal under low operating conditions, the minimum speed parameter SL under low operating conditions can also be set as the lower speed line for vibration signal processing.

[0065] Step S103: Based on the rotational speed sampling frequency, collect the rotational speed information of the rotating equipment during the start-up and stop process to obtain the rotational speed signal.

[0066] In this embodiment, since low-condition data is used to extract bearing fault characteristics, speed signals also need to be acquired in addition to vibration signal acquisition. To facilitate accurate speed measurement, speed signal acquisition needs to be timed. The timer is triggered to start when the speed sensor detects the pulse response moment, and the speed signal stops timing when the speed sampling pulse arrives. The timing value is set to zero after being read by the speed pulse.

[0067] Step S104 correlates the vibration signal and the rotational speed signal to obtain the bearing demodulation spectrum.

[0068] In this embodiment, before associating the vibration signal and the rotational speed signal, the vibration sampling signal Q1 needs to be enveloped by a bandpass filter. The processing method is to take the absolute value of each value in the sequence to obtain the envelope component Q2. Then, the envelope component Q2 is put into a low-pass filter to obtain a new vibration sequence Q3. The vibration sequence Q3 is a demodulated signal, but it is affected by the rotational speed change. In order to extract the vibration order related to the bearing fault, the vibration sequence Q3 signal needs to be processed by rotational speed tracking, that is, associating it.

[0069] Based on the bearing resonance demodulation speed range, the vibration sequence Q3 signal is extracted and subjected to Fourier transform to obtain its order spectrum, i.e., the bearing demodulation spectrum.

[0070] Step S105 determines whether the bearing to be analyzed has a fault based on the bearing demodulation spectrum. In this embodiment, bearing-related frequency indicators can be extracted from the bearing demodulation spectrum to evaluate the health status of the bearing.

[0071] Bearings are a crucial component of rotating mechanical equipment, their core function being to reduce friction between moving and stationary structures and ensure the accuracy of rotating parts' movements. Like other mechanical parts, bearings, especially rolling bearings, can fail due to manufacturing defects, improper installation, misuse, and prolonged exposure to alternating loads. Early bearing failure manifests as increased equipment vibration due to reduced accuracy of rotating parts' movements; later failures can lead to serious accidents due to unrestrained movement in non-rotational directions.

[0072] This embodiment primarily focuses on using the resonance demodulation method to detect early-stage bearing defects. According to the evolution of bearing failures, in the early stages, wear or surface imperfections during normal use alter the lubrication state and generate weak "impact signals." The resonance demodulation method utilizes the amplification effect of the "impact" induced by the defect on the bearing component at the resonant frequency of the sensor mounting support to supplement the bearing failure characteristics. Although impact detection methods are also used for early bearing failure identification, these methods rely on the sensor's own resonant response to capture the impact characteristics corresponding to the bearing failure. Both methods utilize resonant amplification features, but the difference lies in the method: resonance demodulation utilizes the resonance of the equipment support structure, while impact detection relies on the sensor's resonant response. From an installation perspective, impact detection requires the sensor to be closer to the "impact source," and its sensor resonance frequency relative to the bearing support's resonant frequency is relatively higher. Resonance demodulation, while having lower installation requirements due to its reliance on the bearing housing's resonant frequency response, demands a higher magnitude of impact, requiring detection to be performed later than impact detection. As mentioned above, for the resonance demodulation method, the sensor's response in the high-frequency band is characterized by the bearing support resonant frequency as the carrier wave, and the defective bearing part as the modulated signal through the frequency response (the amplitude of the modulated signal depends on the magnitude of the impact and the amplitude-frequency characteristics of the resonant point of the transmission structure). The bearing defect or fault information can be obtained by bandpass filtering and envelope demodulation near the structure's natural frequency.

[0073] As the bearing continues to operate and the damaged surface deteriorates, the bearing failure gradually enters the middle to late stages. At this point, the frequency and amplitude of the impact signal captured near the support resonance or impact detection sensor resonance change, and the corresponding bearing fault frequency characteristics in the associated demodulated spectrum are gradually submerged by noise. Meanwhile, bearing component passing frequency components gradually appear in the acceleration and velocity response spectra corresponding to the bearing passing frequency. Due to the increase in bearing vibration energy, the vibration intensity response corresponding to the associated frequency band also increases. Signal analysis at this stage mainly uses conventional spectrum analysis, supplemented by signal calculus and specific frequency band RMS values ​​(vibration energy monitoring) for evaluation.

[0074] As the fault continues to develop, on the one hand, large particles exist between the moving and stationary structural components, and the squeezing action of the moving parts will cause scratches on the inner and outer rings of the bearing. On the other hand, as particles peel off, the dimensional accuracy of the bearing changes, the unevenness of the rolling element load-bearing capacity further deteriorates, and the dynamic response characteristics of the moving parts show frictional characteristics between the moving and stationary structural components, with occasional increases in the low-frequency response of the sensor. At the end of the bearing's life, abnormal responses can be detected through low-frequency vibration intensity monitoring. Feature extraction at this stage still mainly relies on spectrum analysis, calculus, and low-frequency vibration energy monitoring.

[0075] As for the problem of loosening of the inner and outer rings of bearings, the early stage is mainly characterized by shaft frequency and its harmonic response characteristics, while friction phenomena will also appear in the middle and late stages. The monitoring of its abnormal characteristics still mainly relies on spectrum and vibration energy statistics.

[0076] In summary, for bearing fault diagnosis, the vibration characteristics required for different fault stages will vary. For early-stage fault diagnosis, resonance demodulation remains a relatively effective detection method. This invention focuses on addressing the problem of identifying early-stage bearing faults using resonance demodulation methods in ultra-high-speed rotating equipment.

[0077] In the fault diagnosis of bearings in ultra-high-speed rotating equipment, the main factor affecting the application of the envelope demodulation method is that, at the rated speed of the equipment, the operating frequency of the bearing components (low-frequency signal) in the modulated signal is too high relative to the resonant frequency of the support structure (carrier signal). This severely affects the accuracy of the recovered low-frequency signal during demodulation, especially its frequency parameters. To meet the application requirements of the resonance demodulation method, while considering the immutability of the support structure's resonant frequency, adjusting the operating frequency of the high-speed rotating equipment becomes the only solution. Therefore, this invention introduces the low-condition vibration response during start-up and shutdown and processes it to meet the application conditions of the early bearing fault demodulation algorithm, thus realizing early fault diagnosis of bearings in ultra-high-speed rotating equipment.

[0078] In other words, the relationship between the resonant frequency of the support structure and the rotational frequency of the bearing components is the fundamental reason affecting the application of the resonance demodulation method in the fault detection of bearing components in ultra-high-speed rotating equipment. Considering the immutability of the resonant frequency of the support structure, this invention adopts a method to reduce the rotational frequency of the bearing components to better leverage the role of resonance demodulation technology in the fault detection of bearings in ultra-high-speed rotating equipment. Based on this, this invention proposes an early fault detection method for bearings in ultra-high-speed rotating equipment based on start-up and shutdown data analysis. It utilizes the vibration response under low-speed conditions during start-up and shutdown to improve the distance relationship between the operating frequency of the bearing components and the resonant frequency of the support structure, making it better meet the implementation conditions of the resonance demodulation method. This effectively extracts the low-frequency characteristics of early bearing faults, enhances the identifiability of fault signals, and thus improves the accuracy of bearing fault diagnosis.

[0079] In some alternative implementations, the vibration sampling frequency is determined by the following steps:

[0080] Determine the high-frequency resonant frequency of the rotating equipment during start-up and shutdown.

[0081] Based on the high-frequency resonant frequency and the modulation carrier relationship function, the bearing passage frequency used for demodulation is determined. The modulation carrier relationship function is: k1 = FA / (FR / 2), where k1 represents the modulation signal pulse width coefficient, FA represents the high-frequency resonant frequency, and FR represents the bearing passage frequency. The bearing passage frequency refers to the bearing operating frequency that demodulation techniques (such as envelope demodulation) focus on during fault diagnosis.

[0082] The vibration sampling frequency is determined based on the high-frequency resonant frequency and the bearing passage frequency.

[0083] When a bearing fails, it typically generates high-frequency resonances. These resonances may reflect internal wear, cracks, or other malfunctions within the equipment. The high-frequency resonant frequency can be obtained from vibration signals acquired by vibration sensors. These signals may contain high-frequency resonant components, which are usually related to the bearing's natural frequency, the bearing failure frequency, and the resonant frequency at the sensor's location. By analyzing the vibration signal's spectrum, the high-frequency components can be identified, and the frequency corresponding to the resonant frequency between the bearing and the sensor—the high-frequency resonant frequency—can be found.

[0084] If there are multiple high-frequency resonant frequencies between the bearing and the sensor installation location, the vibration sampling frequency and rotational speed sampling frequency corresponding to the high-frequency resonant frequencies can be determined respectively, and the signal acquisition process can be repeated according to the vibration sampling frequency and rotational speed sampling frequency.

[0085] Considering the relationship between the modulation signal and the carrier, in this embodiment, we can let k1 = FA / (FR / 2), where k1 is the pulse width coefficient of the modulation signal. A sufficiently large pulse width coefficient is an important guarantee for ensuring that the signal can be demodulated. When the high-frequency resonant frequency FA is determined, the pass frequency FR of the bandpass filter can be determined based on the pulse width coefficient k1, thereby obtaining a suitable pass frequency for demodulation. Considering the influence of bandpass filter attenuation and resonant carrier amplitude variation, it is recommended that K1 be no less than 20.

[0086] In some optional implementations, the vibration sampling frequency is determined based on the high-frequency resonant frequency and the bearing passage frequency, including:

[0087] Substituting the high-frequency resonant frequency and the bearing passage frequency into the vibration sampling frequency determination function, the vibration sampling frequency is determined. The vibration sampling frequency determination function is: FS ≥ 2.56(FA + (FR / 2)); FS represents the minimum value of the vibration sampling frequency.

[0088] That is, based on the high-frequency resonant frequency FA at the installation location and the bearing passing frequency FR, the vibration sampling frequency FS is determined to be greater than or equal to 2.56(FA+FR / 2).

[0089] In this embodiment, the vibration sampling frequency is determined based on the high-frequency resonant frequency from the bearing to the sensor installation position and the bearing's passing frequency. This effectively avoids signal distortion and aliasing, helps to accurately capture early fault signals, and improves the sensitivity and reliability of fault diagnosis.

[0090] In some optional implementations, the rotational speed sampling frequency is a preset multiple of the vibration sampling frequency and is greater than (SH / 60)×k2×k3; the preset multiple is greater than or equal to 1;

[0091] Where k2 represents the transmission ratio between the speed measuring shaft and the bearing shaft to be evaluated, and k3 represents the number of pulses obtained by the speed sensor in each rotation cycle of the speed measuring shaft.

[0092] Since low-operating-condition data is used to extract bearing fault characteristics, speed signals also need to be acquired in addition to vibration signal acquisition. In this embodiment, the speed sampling frequency is a preset multiple of the vibration sampling frequency, where the preset multiple is an integer and greater than or equal to 1; simultaneously, the speed sampling frequency FD is greater than SH / 60×k2×k3. This ensures that key vibration characteristics are effectively captured under high-speed conditions, helps avoid signal loss and aliasing, and thus improves the accuracy and reliability of early fault diagnosis.

[0093] In some alternative implementations, during the start-up process of the rotating equipment, the acquisition of vibration and speed signals is stopped when the maximum speed under low operating conditions is reached; during the shutdown process of the rotating equipment, the acquisition of vibration and speed signals is started when the maximum speed under low operating conditions is reached.

[0094] The maximum speed under low operating conditions is: SH=((FR / 2) / k4)×60, where k4 is greater than or equal to 3 times the bearing passing frequency.

[0095] In this embodiment, the maximum speed suitable for resonance demodulation under low operating conditions is ((FR / 2) / k4)×60, where k4 is related to the bearing component's passing frequency, and it is recommended to be no less than 3 times the bearing's passing frequency.

[0096] This embodiment helps reduce data redundancy and optimize signal processing by rationally controlling the timing of vibration and speed signal acquisition during the start-up and stop of rotating equipment. Furthermore, setting the maximum low-temperature operating speed suitable for resonance demodulation to ((FR / 2) / k4)×60 ensures effective capture of fault characteristics within the critical frequency range, improving the accuracy of fault diagnosis.

[0097] In some alternative implementations, before correlating the vibration signal and the rotational speed signal, the method further includes:

[0098] A bandwidth filter is constructed based on the vibration sampling frequency, high-frequency resonant frequency, bearing passing frequency, and modulation signal pulse width coefficient.

[0099] A low-pass filter is constructed based on the bearing's passing frequency.

[0100] The vibration signal is passed through a bandwidth filter to obtain the first vibration signal.

[0101] The second vibration signal is obtained by performing envelope analysis on the first vibration signal.

[0102] The second vibration signal is passed through a low-pass filter to obtain the target vibration signal, which is then used to correlate with the rotational speed signal.

[0103] The center frequency of a bandpass filter is typically set near the structural resonant frequency, while its bandwidth needs to cover the operating frequency of the defective bearing component. In this embodiment, a bandpass filter PF is constructed based on the vibration sampling frequency FS, the high-frequency resonant frequency FA, ​​the bearing passage frequency FR, and the modulation signal pulse width coefficient k1. The stopband of the bandpass filter is controlled by its order; a filter order of at least four stages is recommended.

[0104] In this embodiment, a low-pass filter LF also needs to be constructed. The passband of the low-pass filter is controlled at FR / 2, and the -20dB attenuation frequency of the low-pass filter is recommended not to be higher than 2×FR.

[0105] In this embodiment, signals from the vibration sensor and the speed sensor are acquired based on the vibration sampling frequency FS and the speed sampling frequency FD. The acquired vibration signals are then passed through a bandpass filter PF to obtain a new vibration signal Q1, i.e., the first vibration signal. Envelope analysis is then performed on the vibration sampling signal Q1 obtained through the bandpass filter PF. The processing method involves taking the absolute value of each value in the sequence to obtain the envelope component Q2, i.e., the second vibration signal. The envelope component Q2 is then placed into a low-pass filter to obtain the target vibration signal Q3, which is the demodulated signal. However, the target vibration signal Q3 is affected by changes in speed. To extract the vibration order related to bearing failure, speed tracking processing is required for the target vibration signal Q3.

[0106] In this embodiment, the low-frequency characteristics of the bearing fault signal are effectively extracted through bandpass filtering and envelope analysis, improving the accuracy of fault diagnosis. Finally, speed tracking processing compensates for the influence of speed changes on the target signal, enabling accurate extraction of fault-related vibration orders and further enhancing the reliability of fault diagnosis.

[0107] In some optional implementations, the vibration signal and the rotational speed signal are correlated to obtain the bearing demodulation spectrum, including:

[0108] Based on the vibration sampling frequency, rotational speed sampling frequency, and rotational speed impulse information, the target vibration signal is tracked in order to obtain an equal-phase sampling sequence.

[0109] Fourier transform is performed based on the equiphase sampling sequence to obtain the bearing demodulation spectrum of the corresponding order.

[0110] In this embodiment, the vibration signal and the rotation speed signal are correlated, that is, the vibration signal is subjected to rotation speed tracking processing. Specifically, the rotation speed tracking is processed at intervals of three whole rotation cycles. The three whole cycle signals are defined as the zero moment when the rotation speed sequence first experiences the second impulse trigger moment, and the timing ends when the pulse trigger moment occurs 3×k5 times. The resulting vibration sequence is P3 and the rotation speed sequence is D3, where k5 is a constant.

[0111] Based on the above counting and zero-time definition principle, the accurate time Ti of the speed sensor corresponding to position i in sequence D3 after the pulse trigger time (non-zero value) should be the sampling time ti (determined by the sampling position sequence i and the speed sampling frequency FD) minus the counter timing difference di (obtained by converting the counter value and its timing frequency). At this time, the speed sensor passes through k5 pulses in each rotation cycle, and the corresponding rotation angle of the speed monitoring shaft is 2π. According to the transmission ratio relationship, the rotation angle of the tracked shaft is 2π / k2.

[0112] Based on the time sequences obtained after compensation for each pulse trigger signal, the first cubic spline interpolation is performed using the corresponding rotational phase sequence [0, 2π / k5, 4π / k5, 6π / k5, ..., 6π] and the corresponding time sequence [t0, t1, t2, ..., t3×k5] (taking the data of the speed monitoring shaft rotating three times as an example). This yields the interpolated time sequence [0, p1, p2, ..., pn] corresponding to the equal angle interval [0, φ, 2×φ, ..., n×φ]. The equal angle value φ is calculated according to the formula φ = 2π / k6, where k6 > 3×k4.

[0113] By connecting the interpolated time sequence [0, p1, p2, ..., pn] with the corresponding rotation phase φ, the rotational speed value and rotational speed sequence [s0, s1, s2, ..., sn] corresponding to each rotational moment can be calculated, and a decision can be made on whether it is within the range of rotational speed tracking [SL, SH].

[0114] The time sequence TF and vibration sequence P3 are obtained based on the vibration sampling frequency FS. A second cubic spline interpolation calculation is performed to calculate the vibration signal [V0,V1,V2,……Vn] corresponding to the time sequence [0,p1,p2,……pn], which is the vibration sequence after angular domain resampling. The angular interval between the sequences is φ.

[0115] For angle domain resampling of a single data segment, the first and last derivatives of the spline curve interpolation are replaced with zeros, which affects the actual calculation accuracy. In the specific calculation process, the first derivative is calculated by interpolating the three points before and after the existing data sequence, and the first point is discarded to reduce the impact of inaccurate derivatives on the calculation results.

[0116] After the initial three rotational cycles of vibration tracking are completed, three more cycle signals can be extracted from the target vibration signal Q3 sequence and the above steps can be repeated to complete the tracking of other cycle signals.

[0117] By querying the speed sequence and the corresponding speed value, the V sequence can be truncated and Fourier transformed as needed to obtain the bearing demodulation spectrum response information at the corresponding speed.

[0118] In addition, the above-mentioned order tracking process can be combined with other start-stop feature analyses without significantly increasing the signal processing steps.

[0119] In this embodiment, by tracking the order based on vibration sampling frequency, rotational speed sampling frequency, and rotational speed impulse information, the vibration signal can be correlated with the rotational speed, accurately extracting the vibration order features related to bearing faults and avoiding interference from rotational speed fluctuations on the analysis results. Furthermore, by processing the equiphase sampling sequence using Fourier transform, a clear bearing demodulation spectrum can be obtained, making the bearing fault characteristics more apparent in the frequency domain, further improving the sensitivity of fault detection and the accuracy of diagnosis.

[0120] In this embodiment, the complete implementation steps of the method for detecting early-stage bearing failures in ultra-high-speed rotating equipment are as follows:

[0121] Based on the bearing installation location and the resonant frequency response information of the sensor's vibration measurement points, as well as the bearing's passing frequency parameters, a suitable speed tracking range and bandpass filter parameters before demodulation of the vibration signal are selected, along with low-pass filter parameters during demodulation. Based on the pre-calculated filter parameters, the frequency indices for vibration and speed acquisition signals are set. Simultaneously, the corresponding vibration signals are fed into the bandpass filter and undergo analysis and low-pass filtering to obtain the demodulated target vibration signal containing the bearing's passing frequency parameters. Based on the relationship between the vibration sampling frequency, speed sampling frequency, and speed impulse, the order of the low-pass filtered vibration signal is tracked to obtain an isophase sampling sequence. Within the isophase sampling sequence, based on its compatibility with the bearing resonance demodulation speed range, the signal is truncated and subjected to Fourier transform to obtain its order spectrum. Bearing-related frequency indices are extracted to evaluate the bearing's health status and determine the presence of faults.

[0122] This embodiment provides a method for early fault detection of bearings in ultra-high-speed rotating equipment. It captures early fault characteristics of bearings under low operating conditions when the rated operating conditions do not meet the resonance demodulation requirements, providing a new approach for fault inspection of ultra-high-speed bearings. At the same time, it effectively advances the fault detection opportunity compared to vibration analysis under only rated operating conditions, thus realizing early fault diagnosis of bearings in ultra-high-speed rotating equipment.

[0123] This embodiment also provides a rotating equipment bearing fault detection device, which is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0124] This embodiment provides a rotating equipment bearing fault detection device, such as... Figure 2 As shown, the device includes:

[0125] The determination module 201 is used to determine the vibration sampling frequency and the rotational speed sampling frequency; the rotational speed sampling frequency is a preset multiple of the vibration sampling frequency and is greater than (SH / 60)×k2×k3; the preset multiple is greater than or equal to 1; where k2 represents the transmission ratio between the rotational speed measuring shaft and the shaft of the bearing to be evaluated, and k3 represents the number of pulses obtained by the rotational speed sensor in each rotation cycle of the rotational speed measuring shaft.

[0126] The vibration signal acquisition module 202 is used to acquire vibration information of rotating equipment during the start-up and shutdown process based on the vibration sampling frequency, and obtain vibration signals.

[0127] The speed signal acquisition module 203 is used to acquire the speed information of the rotating equipment during the start-up and stop process based on the speed sampling frequency, and obtain the speed signal; during the start-up process of the rotating equipment, the acquisition of vibration signal and speed signal stops when the maximum speed under low operating conditions is reached; during the stop process of the rotating equipment, the acquisition of vibration signal and speed signal starts when the maximum speed under low operating conditions is reached; the maximum speed under low operating conditions is: SH=((FR / 2) / k4)×60, where k4 is greater than or equal to 3 times the bearing passing frequency.

[0128] The tracking module 204 is used to correlate the vibration signal and the rotational speed signal to obtain the bearing demodulation spectrum;

[0129] The analysis module is used to determine whether the bearing under analysis has a fault based on the bearing demodulation spectrum.

[0130] In some alternative implementations, the determining module 201 includes:

[0131] A determination unit is used to determine the high-frequency resonant frequency of the rotating equipment during start-up and shutdown. Based on the high-frequency resonant frequency and the modulation carrier relationship function, the bearing passage frequency used for demodulation is determined. The modulation carrier relationship function is: k1 = FA / (FR / 2), where k1 represents the modulation signal pulse width coefficient, FA represents the high-frequency resonant frequency, and FR represents the bearing passage frequency. Based on the high-frequency resonant frequency and the bearing passage frequency, the vibration sampling frequency is determined. Specifically, the high-frequency resonant frequency and the bearing passage frequency are substituted into the vibration sampling frequency determination function to determine the vibration sampling frequency. The vibration sampling frequency determination function is: FS ≥ 2.56(FA + (FR / 2)).

[0132] In some alternative implementations, the tracking module 204 includes:

[0133] The demodulation module is used to construct a bandwidth filter based on the vibration sampling frequency, high-frequency resonant frequency, bearing passage frequency, and modulation signal pulse width coefficient; construct a low-pass filter based on the bearing passage frequency; pass the vibration signal through the bandwidth filter to obtain a first vibration signal; perform envelope analysis processing on the first vibration signal to obtain a second vibration signal; and pass the second vibration signal through the low-pass filter to obtain a target vibration signal, which is used to correlate with the rotational speed signal.

[0134] The tracking module is used to perform order tracking of the target vibration signal based on the vibration sampling frequency, rotational speed sampling frequency, and rotational speed per second information to obtain an equal-phase sampling sequence; and to perform Fourier transform based on the equal-phase sampling sequence to obtain the bearing demodulation spectrum of the corresponding order.

[0135] The rotating equipment bearing fault detection device in this embodiment is presented in the form of a functional unit. Here, a unit refers to an ASIC circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0136] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0137] This invention also provides a computer device having the above-described features. Figure 2 The rotating equipment bearing fault detection device shown is shown.

[0138] Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 3As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 3 Take a processor 10 as an example.

[0139] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0140] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0141] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0142] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0143] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0144] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0145] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0146] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for detecting bearing faults in rotating equipment, characterized in that, The method includes: Determining the vibration sampling frequency and the rotational speed sampling frequency includes the following steps: determining the vibration sampling frequency through the following steps: determining the high-frequency resonant frequency of the rotating equipment during start-up and shutdown; determining the bearing passage frequency for demodulation based on the high-frequency resonant frequency and the modulation carrier relationship function; wherein the modulation carrier relationship function is: k1=FA / (FR / 2), where k1 represents the modulation signal pulse width coefficient, FA represents the high-frequency resonant frequency, and FR represents the bearing passage frequency; substituting the high-frequency resonant frequency and the bearing passage frequency into the vibration sampling frequency determination function to determine the vibration sampling frequency; wherein the vibration sampling frequency determination function is: FS≥2.56(FA+(FR / 2)); FS represents the minimum value of the vibration sampling frequency; Vibration information of the rotating equipment during the start-up and stop process is collected based on the vibration sampling frequency to obtain vibration signals; Based on the speed sampling frequency, the rotational speed information of the rotating equipment during the start-up and stop processes is collected to obtain a speed signal; wherein, during the start-up process of the rotating equipment, the collection of the vibration signal and the speed signal is stopped when the maximum speed under low operating conditions is reached; during the stop process of the rotating equipment, the collection of the vibration signal and the speed signal is started when the maximum speed under low operating conditions is reached; the maximum speed under low operating conditions is: SH=((FR / 2) / k4)×60, where k4 is greater than or equal to 3 times the bearing passing frequency; The vibration signal and the rotational speed signal are correlated to obtain the bearing demodulation spectrum; Based on the demodulated spectrum of the bearing, it is determined whether the bearing to be analyzed has a fault.

2. The method according to claim 1, characterized in that, The rotational speed sampling frequency is a preset multiple of the vibration sampling frequency and is greater than (SH / 60)×k2×k3; the preset multiple is greater than or equal to 1; Where k2 represents the transmission ratio between the speed measuring shaft and the bearing shaft to be evaluated, and k3 represents the number of pulses obtained by the speed sensor in each rotation cycle of the speed measuring shaft.

3. The method according to claim 1, characterized in that, Before associating the vibration signal and the rotational speed signal, the method further includes: A bandwidth filter is constructed based on the vibration sampling frequency, the high-frequency resonant frequency, the bearing passing frequency, and the modulation signal pulse width coefficient. Construct a low-pass filter based on the bearing's passing frequency; The vibration signal is passed through a bandwidth filter to obtain a first vibration signal; The first vibration signal is processed by envelope analysis to obtain the second vibration signal; The second vibration signal is passed through the low-pass filter to obtain the target vibration signal, which is used to correlate with the rotational speed signal.

4. The method according to claim 3, characterized in that, The step of correlating the vibration signal and the rotational speed signal to obtain the bearing demodulation spectrum includes: Based on the vibration sampling frequency, the rotational speed sampling frequency, and the rotational speed pulse information, the target vibration signal is subjected to order tracking to obtain an equal-phase sampling sequence; Based on the equal-phase sampling sequence, a Fourier transform is performed to obtain the bearing demodulation spectrum of the corresponding order.

5. A bearing fault detection device for rotating equipment, characterized in that, The device includes: A determination module is used to determine the vibration sampling frequency and the rotational speed sampling frequency. The determination module includes a determination unit used to determine the high-frequency resonant frequency of the rotating equipment during start-up and shutdown. Based on the high-frequency resonant frequency and the modulation carrier relationship function, the bearing passage frequency used for demodulation is determined. The modulation carrier relationship function is: k1 = FA / (FR / 2), where k1 represents the modulation signal pulse width coefficient, FA represents the high-frequency resonant frequency, and FR represents the bearing passage frequency. The high-frequency resonant frequency and the bearing passage frequency are substituted into the vibration sampling frequency determination function to determine the vibration sampling frequency. The vibration sampling frequency determination function is: FS ≥ 2.56(FA + (FR / 2)); FS represents the minimum value of the vibration sampling frequency. The vibration signal acquisition module is used to acquire vibration information of the rotating equipment during the start-up and stop process based on the vibration sampling frequency, and obtain vibration signals. The rotational speed signal acquisition module is used to acquire rotational speed information of the rotating equipment during start-up and shutdown based on the rotational speed sampling frequency, and obtain a rotational speed signal; wherein, during the start-up process of the rotating equipment, the acquisition of the vibration signal and the rotational speed signal is stopped when the maximum speed under low operating conditions is reached; during the shutdown process of the rotating equipment, the acquisition of the vibration signal and the rotational speed signal is started when the maximum speed under low operating conditions is reached; the maximum speed under low operating conditions is: SH=((FR / 2) / k4)×60, where k4 is greater than or equal to 3 times the bearing passing frequency; The tracking module is used to correlate the vibration signal and the rotational speed signal to obtain the bearing demodulation spectrum; The analysis module is used to determine whether the bearing to be analyzed has a fault based on the bearing demodulation spectrum.

6. A computer device, characterized in that, include: The device includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the rotating equipment bearing fault detection method according to any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the rotating equipment bearing fault detection method according to any one of claims 1-4.

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