A bearing monitoring method, device and system

Abstract

The present invention provides a bearing monitoring method, device and system, which relates to the field of bearing monitoring technology, in order to solve the problem that conventional signal processing means have limitations on early weak fault signals of bearings. The bearing monitoring method comprises: obtaining a bearing vibration signal collected from a sensing component during the operation of the bearing, the sensing component is arranged in the bearing, and the bearing vibration signal is subjected to denoising and reconstruction using empirical modes to obtain the bearing vibration signal after denoising, and the bearing vibration signal after denoising is input into a stable state bearing chaotic oscillator model to obtain the bearing vibration step frequency, and the bearing fault is determined based on the bearing vibration step frequency and the bearing reference vibration step frequency. The electronic device and the non-transient computer-readable storage medium storing computer instructions are used to execute the bearing monitoring method. The bearing monitoring method, device and system provided by the present invention are used in bearing monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of bearing monitoring, and in particular to a bearing monitoring method, device and system. Background Art

[0002] Compared with ordinary bearings, spindle bearings have the characteristics of high speed, large load, severe cage impact, high friction heat generation and high working environment temperature during operation. It is difficult to lubricate the spindle bearings well, which leads to large-scale changes in operating conditions, slipping and other faults in the spindle bearings in a short period of time. When the spindle bearings produce fatigue, wear and other faults, abnormal vibrations will occur.

[0003] At present, the vibration monitoring method is to install a vibration sensor at an appropriate position of the bearing seat or housing, and the vibration sensor collects signals and analyzes them to determine the bearing fault. Since the installation position of the vibration sensor is limited by the engine structure, usually only one vibration sensor is installed in the casing of the aircraft engine, and the vibration signal emitted by the vibration sensor in the aircraft engine system has problems such as long vibration transmission path, complex frequency components and severe signal attenuation. At the same time, there is also a lot of noise in the vibration signal, and conventional signal processing methods have certain limitations in identifying the early weak fault signals of the bearing. Summary of the invention

[0004] The purpose of the present invention is to provide a bearing monitoring method, device and system to solve the problems of long vibration transmission path, complex frequency components and severe signal attenuation of vibration signals, and to reduce signal noise, thereby improving the recognition effect of early weak fault signals of bearings.

[0005] In a first aspect, the present invention provides a bearing monitoring method, comprising:

[0006] Acquiring a bearing vibration signal collected by a sensing component during the operation of the bearing, wherein the sensing component is disposed in the bearing;

[0007] Using empirical modes to perform noise reduction and reconstruction on the bearing vibration signal to obtain a noise-reduced bearing vibration signal;

[0008] The bearing vibration signal after noise reduction is input into the bearing chaotic oscillator model in a stable state to obtain the bearing vibration step frequency;

[0009] A bearing fault is determined based on the bearing vibration step frequency and the bearing reference vibration step frequency.

[0010] Compared with the prior art, in the bearing monitoring method provided by the present invention, when the bearing is in operation, the induction component arranged in the bearing can collect the bearing vibration signal, on this basis, the bearing vibration signal collected by the induction component is subjected to noise reduction and reconstruction using the empirical mode to obtain the bearing vibration signal after noise reduction, and the bearing vibration signal after noise reduction is input into the bearing chaotic oscillator model in the stable state to obtain the bearing vibration step frequency, based on which, the bearing vibration step frequency and the bearing reference vibration step frequency are compared, if the bearing vibration step frequency and the bearing reference vibration step frequency are equal, then the bearing is faulty, if the bearing vibration step frequency and the bearing reference vibration step frequency are not equal, then the bearing is not faulty, and the bearing fault is determined in this way, which can reduce signal noise and thus improve the recognition effect of early weak fault signals of the bearing.

[0011] At the same time, the bearing includes a bearing outer ring, a bearing inner ring, a ball and a retaining frame for fixing the ball, the retaining frame is located between the bearing outer ring and the bearing inner ring, and each of the sensing components is arranged on the bearing outer ring. Therefore, the sensing component is arranged in the bearing, which can collect the bearing vibration signal. The sensing component can collect the bearing vibration signal in real time and wirelessly transmit the bearing vibration signal to the bearing monitoring device. It can be seen that the exemplary embodiment of the present invention can shorten the signal transmission path and reduce signal attenuation by arranging the sensing component in the bearing, thereby effectively solving the problems of long vibration transmission path, complex frequency components and severe signal attenuation of the bearing vibration signal.

[0012] In a second aspect, the present invention provides a bearing monitoring device, comprising:

[0013] An acquisition module is used to acquire a bearing vibration signal collected by a sensing component during the operation of the bearing, wherein the sensing component is arranged in the bearing;

[0014] The analysis module is used to perform noise reduction and reconstruction on the bearing vibration signal by using empirical mode decomposition to obtain the bearing vibration signal after noise reduction, and is used to input the bearing vibration signal after noise reduction into the bearing chaotic oscillator model in a stable state to obtain the bearing vibration step frequency, and determine the health status of the bearing based on the bearing vibration step frequency and the bearing reference vibration step frequency.

[0015] Compared with the prior art, the beneficial effects of the bearing monitoring device provided by the present invention are the same as the beneficial effects of the bearing monitoring method described in the present invention, which will not be elaborated here.

[0016] In a third aspect, the present invention provides a bearing monitoring system, comprising:

[0017] A bearing monitoring device, at least one sensing component and a bearing, each sensing component is wirelessly connected to the bearing monitoring component, the bearing comprises a bearing outer ring, a bearing inner ring, balls and a retaining frame for fixing the balls, the retaining frame is located between the bearing outer ring and the bearing inner ring, and each sensing component is arranged on the bearing outer ring.

[0018] Compared with the prior art, the beneficial effects of the bearing monitoring system provided by the present invention are the same as the beneficial effects of the bearing monitoring method described in the present invention, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Further details, features and advantages of the invention are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0020] Figure 1 A structural diagram of a bearing according to an embodiment of the present invention is shown;

[0021] Figure 2 An exploded view of a sensing component of a bearing monitoring system according to an embodiment of the present invention is shown;

[0022] Figure 3 A structural diagram of a magnetic sensor according to an embodiment of the present invention is shown;

[0023] Figure 4 A structural diagram of a vibration acceleration sensor according to an embodiment of the present invention is shown;

[0024] Figure 5 A flow chart showing a bearing monitoring method according to an embodiment of the present invention is shown;

[0025] Figure 6 A flow chart of a method for establishing a chaotic oscillator model according to an embodiment of the present invention is shown;

[0026] Figure 7 A block diagram of a bearing monitoring device according to an embodiment of the present invention is shown;

[0027] Figure 8 A schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention is shown;

[0028] Fig. 9 A schematic diagram of the structure of a chip provided by an embodiment of the present invention is shown.

[0029] Reference numerals:

[0030] 101-bearing inner ring, 102-cage, 103-ball, 104-bearing outer ring, 105-oil filling hole, 106-sensing component, 1061-magnetic sensor, 1062-vibration acceleration sensor, 107-induction coil, 108-bayonet, 301-magnetic probe, 302-collector, 303-card foot, 401-elastic part, 402-mass block, 403-connecting part, 404-piezoelectric element, 405-base, 700-bearing monitoring device, 701-acquisition module, 702-analysis module, 703-modeling module, 810-processor, 820-memory, 830-communication interface, 840-communication route, 850-processor, 900-chip, 910-processor, 920-memory, 930-communication interface, 940-communication route. DETAILED DESCRIPTION

[0031] In order to make the technical problems, technical solutions and beneficial effects to be solved by 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.

[0032] It should be noted that when an element is referred to as being "fixed to" or "disposed on" another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element.

[0033] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. The meaning of "several" is one or more, unless otherwise clearly and specifically defined.

[0034] In the description of the present invention, it is necessary to understand that the directions or positional relationships indicated by the terms "up", "down", "front", "back", "left", "right", etc. are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as a limitation on the present invention.

[0035] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0036] Compared with ordinary bearings, spindle bearings have the characteristics of high speed, large load, severe cage impact, high friction heat generation and high working environment temperature during operation. It is difficult to lubricate the spindle bearings well, resulting in a large range of operating condition changes, slipping and other faults in the spindle bearings in a short period of time. When the spindle bearings produce fatigue, wear and other faults, abnormal vibrations will occur.

[0037] At present, the vibration monitoring method is to install a vibration sensor at an appropriate position of the bearing seat or housing, and the vibration sensor collects signals and analyzes them to determine the bearing fault. Since the installation position of the vibration sensor is limited by the engine structure, usually only one vibration sensor is installed in the casing of the aircraft engine, and the vibration signal emitted by the vibration sensor in the aircraft engine system has problems such as long vibration transmission path, complex frequency components and severe signal attenuation. At the same time, there is also a lot of noise in the vibration signal. Generally, the characteristic information in the vibration signal is extracted by first decomposing and filtering and then reconstructing and analyzing. This conventional signal processing method has certain limitations in the identification of early weak fault signals of bearings.

[0038] Based on the above problems, the present invention provides a bearing monitoring method, device and system to solve the problems of long vibration transmission path, complex frequency components and severe signal attenuation of vibration signals, and can reduce signal noise, thereby improving the recognition effect of early weak fault signals of bearings.

[0039] Figure 1 The structure diagram of the bearing according to the embodiment of the present invention is shown. Figure 2 FIG. 2 shows an exploded view of a sensing component of a bearing monitoring system according to an embodiment of the present invention. Figure 1 and Figure 2As shown, the bearing monitoring system of the embodiment of the present invention includes a bearing monitoring device, a bearing and at least one sensing component 106. It should be understood that the bearing here can be a cylindrical roller bearing, a double-flap outer ring bearing, etc., which are not listed here one by one. The bearing includes a bearing outer ring 104, a bearing inner ring 101, balls 103 and a retainer 102 for fixing the balls. The retainer 102 is located between the bearing outer ring 104 and the bearing inner ring 101. The balls 103 are fixed on the retainer 102. The retainer 102 is used to connect the bearing inner ring 101 and the bearing outer ring 101. The bearing inner ring 101 and the bearing outer ring 104 slide relative to each other under the action of the balls 103.

[0040] When the bearing monitoring system of the embodiment of the present invention includes a plurality of sensing components, each sensing component is arranged on the outer ring of the bearing. Each sensing component is wirelessly connected to the bearing monitoring device. The bearing monitoring device here can be an external computing platform or other equipment with computing functions.

[0041] In practical applications, each sensing component is fixed to the outer ring by a bayonet, and the sensing component is at least used to collect the vibration signal of the bearing. Since each sensing component is wirelessly connected to the bearing monitoring device, the sensing component can also transmit the vibration signal of the bearing to the bearing monitoring device. The bearing monitoring device provided by the exemplary embodiment of the present invention can reduce the vibration signal noise of the bearing by executing the bearing monitoring method after receiving the vibration signal of the bearing, thereby improving the recognition effect of the early weak fault signal of the bearing.

[0042] Each sensing component of the exemplary embodiment of the present invention can also collect information on the impurity content of the lubricating oil and send it to the bearing monitoring device. The bearing monitoring device can determine the wear state of the bearing by analyzing the impurity content information of the lubricating oil.

[0043] For example, Figure 2 As shown, each sensing component 106 has a magnetic sensor 1061, a vibration acceleration sensor 1062, a controller, and a wireless communication device along the radial direction of the outer ring of the bearing ( Figure 1 The controller is electrically connected to the magnetic sensor 1061, the vibration acceleration sensor 1062 and the wireless communicator through the signal circuit. The magnetic sensor 1061 is arranged in the oil filling hole, and the vibration acceleration sensor 1062 is arranged on the surface of the magnetic sensor 1061 away from the oil filling hole.

[0044] When the bearing is in operation, lubricating oil is injected into the bearing through the oil filling hole, and the magnetic sensor collects information about the impurity content of the lubricating oil (for example, it can magnetically absorb metal debris such as iron filings in the lubricating oil). At the same time, during the operation of the bearing, the bearing may vibrate. The vibration acceleration sensor on the surface away from the oil filling hole can collect the vibration signal when the bearing vibrates. The vibration acceleration sensor transmits the vibration signal to the controller through the signal circuit. The controller transmits the vibration signal to the wireless communicator through the signal circuit, and the wireless communicator then transmits the vibration signal to the bearing monitoring device.

[0045] It can be seen that the wear state of the bearing can be determined by the above-mentioned magnetic sensor, and the vibration state of the bearing can be determined by the vibration acceleration sensor, thereby realizing real-time monitoring of the bearing operation process.

[0046] In an alternative approach, Figure 3 The structure diagram of the magnetic sensor according to the embodiment of the present invention is shown as follows: Figure 3 As shown, the magnetic sensor 1061 provided by the exemplary embodiment of the present invention includes a magnetic probe 301 and a collector 302, the magnetic probe 301 is located in the oil filling hole, the collector 302 is arranged on the magnetic probe 301, the collector 302 is electrically connected to the magnetic probe 301, and the collector 302 is electrically connected to the controller through a signal circuit.

[0047] When the magnetic probe is inserted into the oil filling hole, the magnetic probe absorbs iron chips in the oil hole. The collector can determine the impurity (iron chips) content information of the lubricating oil based on the iron chips absorbed by the magnetic probe. The collector converts the collected impurity (iron chips) content information of the lubricating oil into an electrical signal. The collector transmits the electrical signal to the controller through the signal circuit, and the controller transmits the vibration signal to the bearing monitoring device through the wireless communication device. The bearing monitoring device can determine the wear state of the bearing based on the electrical signal in the collector.

[0048] In an alternative approach, Figure 4 The structure diagram of the vibration acceleration sensor according to the embodiment of the present invention is shown as follows: Figure 4 As shown, the vibration acceleration sensor 1062 provided by the exemplary embodiment of the present invention includes an elastic member 401 , a mass block 402 , a piezoelectric element 404 , a base 405 and a connecting member 403 , and one end of the mass block 402 away from the base is connected to the elastic member 401 .

[0049] like Figure 4As shown, when the bearing is a double-petal outer ring type spindle bearing, there is relative movement between the two halves of the outer ring. When the bearing is running, the elastic member 401 starts to move with the vibration of the bearing, and the elastic member 401 drives the mass block to move at the same time. At the same time, since the piezoelectric element 404 is located between the base 405 and the mass block 402, the connector 403 connects the elastic member 401, the mass block 402, the piezoelectric element 404, and the base 405 in sequence, so when the mass block 405 moves, it will generate pressure on the piezoelectric element 404. The piezoelectric element 404 will convert the pressure into a vibration signal in the form of an electrical signal when it is subjected to the pressure of the mass block 405, and transmit the vibration signal to the controller through the signal circuit, and the controller then transmits the vibration signal to the bearing monitoring device through the wireless communication device.

[0050] For example, Figure 2 As shown, the above-mentioned induction component 106 is connected with the outer ring of the bearing by interference fit through the bayonet 108, which can facilitate the disassembly and reuse of the induction component. At the same time, since the induction coil 107 is arranged between the bayonet 108 and the magnetic sensor, when the bearing rotates, it will drive the induction component to shake, and the permanent magnet in the magnetic sensor in the induction component will cut the induction coil 107 to generate electricity, and the generated electric energy will flow into the battery, and the battery will then input the magnetic sensor and the vibration acceleration sensor through the power supply circuit.

[0051] Exemplarily, the end of the connecting piece facing away from the base is connected to the magnetic probe, and the magnetic probe has a clamping pin connected to the sensing component. The connecting piece can be connected to the magnetic probe through the clamping pin. The sensing component also has a cavity for accommodating a controller and a wireless communicator. The cavity is arranged on the base of the vibration acceleration sensor. The sensing component is connected as a whole. The magnetic sensor and the vibration acceleration sensor are powered by a battery. Each sensor transmits the collected vibration signal to the controller in the sensing component in the form of signal transmission. The controller receives the bearing vibration signal collected by each sensor. The controller finally transmits the received bearing vibration signal to the bearing monitoring device in a wireless transmission manner. On this basis, when each sensor transmits the collected vibration signal to the controller, there is no need for long-path signal transmission, and at the same time, signal attenuation is reduced, effectively solving the problems of long vibration transmission path, complex frequency components and severe signal attenuation of the vibration signal.

[0052] Figure 5 A flow chart of a bearing monitoring method according to an embodiment of the present invention is shown. The bearing monitoring method provided by an exemplary embodiment of the present invention includes:

[0053] Step 501: during the operation of the bearing, a bearing vibration signal collected by a sensing component is obtained, and the sensing component is disposed in the bearing. The manner in which the sensing component is disposed in the bearing can be referred to in the previous text, and will not be described in detail here. The bearing vibration signal collected by the sensing component can be transmitted to the external computing platform described above through wireless communication.

[0054] Step 502: Use the empirical mode to perform noise reduction and reconstruction on the bearing vibration signal to obtain the noise-reduced bearing vibration signal. The empirical mode here may include ensemble empirical mode decomposition (EEMD). The signal noise of the bearing vibration signal obtained after noise reduction and reconstruction is relatively small, which can effectively reduce the impact of signal noise on the monitoring results.

[0055] Step 503: Input the noise-reduced bearing vibration signal into the bearing chaotic oscillator model in a stable state to obtain the bearing vibration step frequency. When the bearing chaotic oscillator model is in a stable state, the Lyaponuv index in the bearing chaotic oscillator model is equal to zero, and the motion state in the bearing chaotic oscillator model tends to be stable, and is insensitive to the initial state of the bearing chaotic oscillator model.

[0056] Step 504: Determine the bearing fault based on the bearing vibration step frequency and the bearing reference vibration step frequency. Here, the bearing reference vibration step frequency is the frequency of the theoretical bearing fault calculated according to the bearing fault frequency formula.

[0057] Exemplarily, an embodiment of the present invention utilizes empirical modes to perform noise reduction and reconstruction on the bearing vibration signal. When the noise-reduced bearing vibration signal is obtained, the bearing vibration signal can be decomposed using empirical modes to obtain M intrinsic mode components, and the M intrinsic mode components are weightedly summed to obtain the noise-reduced bearing vibration signal.

[0058] In practical applications, the bearing vibration signal can be decomposed into M intrinsic mode components by adding different white noises. Exemplarily, the bearing vibration signal is decomposed by empirical mode to obtain M intrinsic mode components, including: adding M white noise signals with different amplitudes to the bearing vibration signal to obtain M intrinsic mode components, performing empirical mode decomposition on each reconstructed bearing vibration signal to obtain the corresponding intrinsic mode component. In order to make the added white noise signal stable, the standard of each white noise signal conforms to the normal distribution.

[0059] Exemplarily, it can be set that M white noise signals are added to the bearing vibration signal, and the amplitudes of the M added white noise signals are different, so as to form M intrinsic mode components. The M intrinsic mode components can form a set of intrinsic mode components, and the set can be expressed as:

[0060] {c 1，j (t), c 2，j (t), c 3，j (t)...c M，j (t)}, j = 1, 2, ... j;

[0061] Among them, c 1，j (t) represents the jth eigenmode component obtained by decomposition after adding white noise for the first time, c 2，j (t) represents the jth eigenmode component obtained by decomposing after adding white noise twice, c M，j (t) represents the jth intrinsic mode component obtained by decomposing after adding white noise M times.

[0062] Taking the i-th addition of white noise signal as an example, a white noise n with standard normal distribution is added i (t) is added to the bearing vibration signal x(t) to generate an additional noise signal x i (t), which is expressed as follows:

[0063] i = 1, 2, ... M; x i (t) = x(t) + n i (t);

[0064] Among them, n i (t) represents the ith additive white noise sequence, x i (t) represents the additional noise signal of the i-th trial.

[0065] Then, the resulting additional noise signal x i (t) Perform empirical mode decomposition to obtain the i-th eigenmode component x as shown below i (t), which is expressed as follows:

[0066]

[0067] In the above formula, c i，j (t) is the jth eigenmode component obtained by decomposing after adding white noise for the i-th time, r i，j (t) is the residual function, representing the average trend of the signal, and j is the number of eigenmode components.

[0068] On this basis, we can use the principle that the statistical mean value of uncorrelated sequences is zero to perform ensemble average operation on the corresponding intrinsic mode components to obtain the final denoised bearing vibration signal after ensemble empirical mode decomposition, that is,

[0069]

[0070] Among them, c j(t) is the j-th eigenmode component of the collective empirical mode decomposition, i = 1, 2, ...M; j = 1, 2, ...j.

[0071] In an alternative approach, Figure 6 A flow chart of a method for establishing a chaotic oscillator model according to an embodiment of the present invention is shown. Figure 6 As shown, the method also includes:

[0072] Step 601: Determine an initial bearing chaotic oscillator model based on the dynamic characteristics of the bearing chaotic oscillator. It should be understood that the phase space reconstruction parameters can be determined based on the dynamic characteristics of the bearing chaotic oscillator, and the initial bearing chaotic oscillator model can be determined based on the phase space reconstruction parameters and the perturbation force parameters.

[0073] Step 602: Input the bearing vibration signal to the initial bearing chaotic oscillator model to obtain the bearing reference vibration step frequency.

[0074] Step 603: Determine the Lyaponuv index based on the initial bearing chaotic oscillator model; Here, the Lyaponuv index can be determined based on the model function of the initial bearing chaotic oscillator model. The specific determination method can refer to related technologies and will not be described in detail here.

[0075] Step 604: If the Lyaponuv index satisfies the stable state condition, the initial bearing chaotic oscillator model is determined to be a stable bearing chaotic oscillator model, otherwise, the perturbation force parameters of the initial bearing chaotic oscillator model are updated based on the Lyaponuv index. It can be seen that the Lyaponuv index can be updated by changing the perturbation force amplitude parameters in the bearing chaotic oscillator model until the Lyaponuv index satisfies the stable state condition.

[0076] In practical applications, the Lyaponuv index is used to identify the characteristics of several numerical values ​​in the motion of several bearing chaotic oscillator models. By continuously iterating the Lyaponuv index, the Lyaponuv index in the bearing chaotic oscillator model will meet the stable state condition. The de-noised bearing vibration signal is input into the stable state bearing chaotic oscillator model to obtain the bearing vibration step frequency. The bearing vibration step frequency is compared with the bearing reference vibration step frequency. If the bearing vibration step frequency is equal to the bearing reference vibration step frequency, the bearing is faulty. If the bearing vibration step frequency is not equal to the bearing reference vibration step frequency, the bearing is not faulty. This can be used to determine the bearing fault, reduce signal noise, and thus improve the recognition effect of early weak fault signals of the bearing.

[0077] The method of the exemplary embodiment of the present invention may further include: acquiring impurity content information of the lubricating oil collected from the sensing component during the operation of the bearing, and determining the wear state of the bearing based on the impurity content information.

[0078] Figure 7 A block diagram of a bearing monitoring device according to an embodiment of the present invention is shown. An exemplary embodiment of the present invention further provides a bearing monitoring device comprising:

[0079] An acquisition module 701 is used to acquire a bearing vibration signal collected from a sensing component during the operation of the bearing, wherein the sensing component is disposed in the bearing;

[0080] The analysis module 702 is used to perform noise reduction and reconstruction on the bearing vibration signal by using empirical mode decomposition to obtain the bearing vibration signal after noise reduction, input the bearing vibration signal after noise reduction into a stable state bearing chaotic oscillator model to obtain the bearing vibration step frequency, and determine the health status of the bearing based on the bearing vibration step frequency and the bearing reference vibration step frequency.

[0081] As a possible implementation, the analysis module 702 is used to decompose the bearing vibration signal using empirical modes to obtain M intrinsic mode components, and perform weighted summation on the M intrinsic mode components to obtain a noise-reduced bearing vibration signal.

[0082] As a possible implementation, the analysis module 702 is used to add M white noise signals with different amplitudes to the bearing vibration signal, respectively, to obtain M intrinsic mode components, and the standard of each white noise signal conforms to the normal distribution. As a possible implementation, the bearing monitoring device provided in the embodiment of the present invention may also include a modeling module 703, which is used to determine an initial bearing chaotic oscillator model based on the dynamic characteristics of the bearing chaotic oscillator, input the bearing vibration signal to the initial bearing chaotic oscillator model, obtain the bearing reference vibration step frequency, determine the Lyaponuv index based on the initial bearing chaotic oscillator model, if the Lyaponuv index meets the stable state condition, determine the initial bearing chaotic oscillator model as the stable state bearing chaotic oscillator model, otherwise, update the perturbation force parameters of the initial bearing chaotic oscillator model based on the Lyaponuv index.

[0083] As a possible implementation manner, the modeling module 703 is used to determine phase space reconstruction parameters based on the dynamic characteristics of the bearing chaotic oscillator, and determine an initial bearing chaotic oscillator model based on the phase space reconstruction parameters and the perturbation force parameters.

[0084] As a possible implementation, the acquisition module 701 is further used to acquire the impurity content information of the lubricating oil collected from the sensing component during the operation of the bearing, and the analysis module 702 is further used to determine the wear state of the bearing based on the impurity content information.

[0085] Figure 8FIG. 1 is a schematic diagram showing the hardware structure of an electronic device provided by an embodiment of the present invention. Figure 8 As shown, the electronic device includes a processor 810 and a communication interface 830 .

[0086] like Figure 8 As shown, the processor 810 may be a general-purpose central processing unit 810 (CPU), a microprocessor 810, an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the present invention.

[0087] There may be one or more communication interfaces 830. The communication interface 830 may use any transceiver or other device for communicating with other devices or communication networks.

[0088] like Figure 8 As shown, the electronic device may further include a communication circuit. The communication circuit may include a path to transmit information between the components.

[0089] Optional, such as Figure 8 As shown, the electronic device may further include a memory 820. The memory 820 is used to store computer-executable instructions for executing the solution of the present invention, and is controlled to execute by the processor 810. The processor 810 is used to execute the computer-executable instructions stored in the memory 820, thereby implementing the method provided by the embodiment of the present invention.

[0090] like Figure 8As shown, the memory 820 may be a read-only memory 820 (ROM) or other types of static storage devices that can store static information and instructions, a random access memory 820 (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory 820 (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical disc, laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 820 may exist independently and be connected to the processor 810 via a communication line. The memory 820 may also be integrated with the processor 810.

[0091] Optionally, the computer-executable instructions in the embodiment of the present invention may also be referred to as application program codes, which is not specifically limited in the embodiment of the present invention.

[0092] In a specific implementation, as an example, Figure 8 As shown, the processor 810 may include one or more CPUs, such as Figure 8 CPU0 and CPU1 in.

[0093] In a specific implementation, as an example, Figure 8 As shown, the terminal device may include multiple processors 810, such as Figure 8 Each of the processors 810 may be a single-core processor 810 or a multi-core processor 810.

[0094] Fig. 9 FIG. 9 is a schematic diagram of the structure of a chip 900 provided in an embodiment of the present invention. Fig. 9 As shown, the chip 900 includes one or more (including two) processors 910 and a communication interface 930 .

[0095] Optional, such as Fig. 9As shown, the chip 900 also includes a memory 920, which may include a read-only memory 920 and a random access memory 920, and provides operation instructions and data to the processor 910. A portion of the memory 920 may also include a non-volatile random access memory 920 (NVRAM).

[0096] In some embodiments, Fig. 9 As shown, the memory 920 stores the following elements, execution modules or data structures, or their subsets, or their extended sets.

[0097] In the embodiment of the present invention, Fig. 9 As shown, the corresponding operation is performed by calling the operation instruction stored in the memory 920 (the operation instruction may be stored in the operating system).

[0098] like Fig. 9 As shown, the processor 910 controls the processing operations of any one of the terminal devices, and the processor 910 can also be called a central processing unit (CPU).

[0099] like Fig. 9 As shown, the memory 920 may include a read-only memory 920 and a random access memory 920, and provide instructions and data to the processor 910. A portion of the memory 920 may also include an NVRAM. For example, in an application, the memory 920, the communication interface 930, and the memory 920 are coupled together through a bus system, wherein the bus system may include a power bus, a control bus, and a status signal bus in addition to a data bus. However, for the sake of clarity, in Fig. 9 In the specification, various buses are labeled as bus systems.

[0100] like Fig. 9As shown, the method disclosed in the above embodiment of the present invention can be applied to a processor 910, or implemented by a processor 910. The processor 910 may be an integrated circuit chip 900, which has the ability to process signals. In the implementation process, each step of the above method can be completed by an integrated logic circuit of hardware in the processor 910 or an instruction in the form of software. The above processor 910 can be a general processor 910, a digital signal processor 910 (digital signal processing, DSP), an ASIC, a field-programmable gate array (field-programmable gate array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general processor 910 can be a microprocessor 910 or the processor 910 can also be any conventional processor 910, etc. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly embodied as being executed by a hardware decoding processor 910, or can be executed by a combination of hardware and software modules in the decoding processor 910. The software module may be located in a storage medium mature in the art, such as a random access memory 920, a flash memory, a read-only memory 920, a programmable read-only memory 920, or an electrically erasable programmable memory 920, a register, etc. The storage medium is located in the memory 920, and the processor 910 reads the information in the memory 920 and completes the steps of the above method in combination with its hardware.

[0101] In one possible implementation, Fig. 9 As shown, the communication interface 930 is used to execute Figures 5 to 9 The processor 910 is used to execute Figures 5 to 9 The steps of the process in the illustrated embodiment.

[0102] On the one hand, a computer-readable storage medium is provided, in which instructions are stored. When the instructions are executed, the functions performed by the memory 920 in the above embodiment are implemented.

[0103] On the one hand, a chip 900 is provided, which is applied to a terminal device. The chip 900 includes at least one processor 910 and a communication interface 930. The communication interface 930 is coupled to at least one processor 910, and the processor 910 is used to run instructions to implement the functions performed by the processor 910 in the above embodiments.

[0104] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed on a computer, the process or function described in the embodiment of the present invention is executed in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a terminal, a user device or other programmable device. The computer program or instruction can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer program or instruction can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, a hard disk, or a tape; it can also be an optical medium, such as a digital video disc (DVD); it can also be a semiconductor medium, such as a solid state drive (SSD).

[0105] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit may implement several functions listed in the claims. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0106] Although the present disclosure has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present disclosure. Accordingly, this specification and the drawings are merely exemplary illustrations of the present disclosure as defined by the appended claims, and are deemed to have covered any and all modifications, variations, combinations or equivalents within the scope of the present disclosure. Obviously, those skilled in the art may make various modifications and variations to the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and their equivalents, the present disclosure is also intended to include these modifications and variations.

Claims

1. A bearing monitoring method, characterized in that: include: Acquiring a bearing vibration signal collected by a sensing component during the operation of the bearing, wherein the sensing component is disposed in the bearing; Using empirical modes to perform noise reduction and reconstruction on the bearing vibration signal to obtain a noise-reduced bearing vibration signal; Inputting the de-noised bearing vibration signal into a bearing chaotic oscillator model in a stable state to obtain the bearing vibration step frequency; Determining a bearing fault based on the bearing vibration step frequency and a bearing reference vibration step frequency; The method of using the empirical mode to perform noise reduction and reconstruction on the bearing vibration signal to obtain the noise-reduced bearing vibration signal includes: Decomposing the bearing vibration signal by empirical mode to obtain M eigenmode components; Perform weighted summation on the M eigenmode components to obtain the bearing vibration signal after noise reduction; The method of using empirical mode decomposition to decompose the bearing vibration signal to obtain M intrinsic mode components includes: M white noise signals with different amplitudes are added to the bearing vibration signal to obtain M intrinsic mode components, and the standard of each white noise signal conforms to the normal distribution.

2. The bearing monitoring method according to claim 1, characterized in that: The method further comprises: Determine the initial bearing chaotic oscillator model based on the dynamic characteristics of the bearing chaotic oscillator; Inputting a bearing vibration signal into the initial bearing chaotic oscillator model to obtain a bearing reference vibration step frequency; Determining a Lyaponuv index based on the initial bearing chaotic oscillator model; If the Lyaponuv index satisfies the stable state condition, the initial bearing chaotic oscillator model is determined to be the stable state bearing chaotic oscillator model; otherwise, the perturbation force parameters of the initial bearing chaotic oscillator model are updated based on the Lyaponuv index.

3. The bearing monitoring method according to claim 2, characterized in that: The method further comprises: Determine the phase space reconstruction parameters based on the dynamic characteristics of the bearing chaotic oscillator; An initial bearing chaotic oscillator model is determined based on the phase space reconstruction parameters and the perturbation force parameters.

4. The bearing monitoring method according to any one of claims 1 to 3, characterized in that: The method further comprises: Obtaining information on the impurity content of the lubricating oil collected by the sensing component during the operation of the bearing; A wear state of the bearing is determined based on the impurity content information.

5. A bearing monitoring device, applied to the bearing monitoring method according to any one of claims 1 to 4, characterized in that: include: An acquisition module, used to acquire a bearing vibration signal collected from a sensing component during the operation of the bearing, wherein the sensing component is disposed in the bearing; The analysis module is used to perform noise reduction and reconstruction on the bearing vibration signal by using empirical mode decomposition to obtain the bearing vibration signal after noise reduction, input the bearing vibration signal after noise reduction into a stable state bearing chaotic oscillator model to obtain the bearing vibration step frequency, and determine the bearing fault based on the bearing vibration step frequency and the bearing reference vibration step frequency.

6. A bearing monitoring system, characterized in that: It comprises the bearing monitoring device according to claim 5, a bearing and at least one sensing component, each of the sensing components is wirelessly connected to the bearing monitoring device, the bearing comprises a bearing outer ring, a bearing inner ring, balls and a retaining frame for fixing the balls, the retaining frame is located between the bearing outer ring and the bearing inner ring, and each of the sensing components is arranged on the bearing outer ring.

7. The bearing monitoring system according to claim 6, characterized in that: Each of the sensing components has a magnetic sensor, a vibration acceleration sensor, a controller, a signal circuit and a wireless communicator. The controller is electrically connected to the magnetic sensor, the vibration acceleration sensor and the wireless communicator through the signal circuit. The magnetic sensor is arranged in the oil filling hole, and the dynamic acceleration sensor is arranged on the surface of the magnetic sensor away from the oil filling hole.

8. The bearing monitoring system according to claim 7, characterized in that: The magnetic sensor comprises a magnetic probe and a collector, wherein the magnetic probe is located in the oil filling hole, the collector is arranged on the magnetic probe, the collector is electrically connected to the magnetic probe, and the collector is electrically connected to the controller through the signal circuit.

9. The bearing monitoring system according to claim 7, characterized in that: The vibration acceleration sensor comprises an elastic member, a mass block, a piezoelectric element, a base and a connecting member, wherein one end of the mass block away from the base is connected to the elastic member, and the piezoelectric element is located between the base and the mass block; The connecting member connects the elastic member, the mass block, the piezoelectric element and the base in sequence, one end of the connecting member away from the base is connected to the magnetic probe, and the piezoelectric element is electrically connected to the controller.

10. The bearing monitoring system according to claim 7, characterized in that: The sensing component also has a cavity for accommodating the controller and the wireless communicator, and the cavity is arranged on the base of the vibration acceleration sensor.

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