A Fault Diagnosis Method and System Based on Rolling Bearing Vibration

Abstract

The present invention discloses a fault diagnosis method and system based on rolling bearing vibration, which relates to the technical field of rolling bearing diagnosis. When the vibration amplitude exceeds a first vibration threshold, the timer starts timing. When the timing duration is equal to the duration threshold, the diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates an equipment operation index according to the operation status, and then obtains the health data of the rolling bearing. After preprocessing the health data of the rolling bearing, the equipment operation index and the preprocessed health data are comprehensively analyzed through a diagnostic model, and the bearing coefficient of the rolling bearing is output. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold. The diagnostic system can effectively combine the equipment data and the rolling bearing data for analysis, and analyze whether the rolling bearing under the vibration condition has the possibility of failure, so that it can accurately warn and effectively reduce the probability of false alarms in the diagnostic system.

Description

Technical Field

[0001] The present invention relates to the technical field of rolling bearing diagnosis, and in particular to a rolling bearing vibration-based fault diagnosis method and system. Background Art

[0002] Rolling bearings are common and critical components in many mechanical systems. They support and guide rotating shafts. Vibration is one of the common indicators of rolling bearing failure because failure often leads to changes in bearing vibration levels.

[0003] The prior art has the following deficiencies:

[0004] Existing fault diagnosis systems usually monitor the vibration amplitude of rolling bearings in real time by installing vibration sensors near the rolling bearings, and issue an alarm when the real-time vibration amplitude exceeds the vibration threshold. However, in actual applications, due to the influence of equipment or the outside world, the rolling bearing may have intermittent vibration amplitude exceeding the vibration threshold, and the intermittent vibration may not cause rolling bearing failure. At this time, the fault diagnosis system will frequently give false alarms, increasing the system burden and manual burden (manual inspection is required when the alarm is issued). Summary of the invention

[0005] The purpose of the present invention is to provide a fault diagnosis method and system based on rolling bearing vibration to solve the shortcomings of the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a fault diagnosis method based on rolling bearing vibration, the diagnosis method comprising the following steps:

[0007] The diagnostic system monitors the vibration amplitude of the rolling bearing through a vibration sensor, and if the vibration amplitude exceeds a first vibration threshold, a timer starts timing;

[0008] When the timing duration is equal to the duration threshold, the diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates an equipment operation index according to the operation status;

[0009] Acquire the health data of the rolling bearing and pre-process the health data of the rolling bearing;

[0010] The equipment operation index and pre-processed health data are comprehensively analyzed through the diagnostic model to output the bearing coefficient of the rolling bearing. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result between the bearing coefficient and the warning threshold.

[0011] When the initially monitored vibration amplitude exceeds the second vibration threshold or the vibration amplitude exceeds the second vibration threshold during the timing process, the diagnostic system directly sends a warning signal and remotely transmits the warning signal to the management platform.

[0012] In a preferred embodiment, obtaining the health data of the rolling bearing and preprocessing the health data of the rolling bearing include the following steps:

[0013] The diagnostic system obtains the use data of the rolling bearing through the equipment system log, obtains the noise data through the decibel meter near the rolling bearing, obtains the temperature data through the temperature sensor near the rolling bearing, and obtains the displacement data through the displacement sensor on the rolling bearing;

[0014] The aging rate is obtained after preprocessing the usage data, the average noise decibel is obtained after preprocessing the noise data, the temperature deviation value is obtained after preprocessing the temperature data, and the coordinate similarity is obtained after preprocessing the displacement data.

[0015] In a preferred embodiment, the equipment operation index and the pre-processed health data are comprehensively analyzed by a diagnostic model, and the bearing coefficient of the rolling bearing is outputted, including the following steps:

[0016] The function expression of the diagnostic model is:

[0017] In the formula, zcx is the bearing coefficient, SYZ is the equipment operation index, LH is the aging rate, is the average noise decibel, WP is the temperature deviation value, JL is the coordinate similarity, ω1, ω2, ω3, and ω4 are the weight coefficients of aging rate, average noise decibel, temperature deviation value, and coordinate similarity, respectively, and ω1+ω2+ω3+ω4=1, ω4>ω2>ω1>ω3.

[0018] When the rolling bearing vibrates, the real-time aging rate, average noise decibel, temperature deviation value, and coordinate similarity are obtained and substituted into the diagnosis model to calculate the bearing coefficient.

[0019] In a preferred embodiment, the diagnostic system determines whether a warning signal needs to be issued based on the comparison result between the bearing coefficient and the warning threshold, including the following steps:

[0020] After obtaining the bearing coefficient, the bearing coefficient is compared with the preset warning threshold;

[0021] If the bearing coefficient is greater than the warning threshold, it is determined that a warning signal needs to be issued;

[0022] If the bearing coefficient is less than or equal to the warning threshold, it is determined that there is no need to issue a warning signal.

[0023] In a preferred embodiment, the coordinate similarity is obtained after preprocessing the displacement data. The calculation expression of the coordinate similarity is: Where JL is the coordinate similarity, (x2, y2) is the current x-axis and y-axis coordinates of the rolling bearing, and (x1, y1) is the standard x-axis and y-axis coordinates of the rolling bearing.

[0024] In a preferred embodiment, the temperature deviation value is obtained after preprocessing the temperature data, and the calculation expression of the temperature deviation value is: WP=|WS-WB|, where WP is the temperature deviation value, WS is the real-time temperature, and WB is the standard temperature.

[0025] In a preferred embodiment, the noise data is preprocessed to obtain the average noise decibel, and the calculation expression of the average noise decibel is: In the formula, is the average noise decibel, i=1, 2, 3, ..., n, n represents the number of sampling points in a period of time, and dbi represents the noise decibel at the i-th sampling point.

[0026] In a preferred embodiment, the aging rate is obtained after preprocessing the usage data. The calculation expression of the aging rate is:

[0027] Where C is the basic dynamic load, P is the actual working load, and LH is the aging rate.

[0028] In a preferred embodiment, the diagnostic system determines whether the equipment using the rolling bearing is in operation and generates the equipment operation index according to the operation status, including the following steps:

[0029] When it is determined that the equipment using rolling bearings is in operation and continues for a period of time, the equipment operation index SYZ=1.5 is generated based on the operation status; when it is determined that the equipment using rolling bearings is in a stopped state, the equipment operation index SYZ=1.0 is generated based on the operation status.

[0030] The present invention also provides a fault diagnosis system based on rolling bearing vibration, comprising an amplitude monitoring module, a timing module, an equipment status acquisition module, a data acquisition module, a comprehensive analysis module, a fault diagnosis module, an amplitude judgment module, and a communication module;

[0031] Amplitude monitoring module: monitors the vibration amplitude of rolling bearings through vibration sensors;

[0032] Timing module: when the vibration amplitude exceeds the first vibration threshold, the timer starts timing;

[0033] Equipment status acquisition module: when the timing duration is equal to the duration threshold, it determines whether the equipment using the rolling bearing is in operation, and generates the equipment operation index according to the operation status;

[0034] Data acquisition module: obtains the health data of rolling bearings and pre-processes the health data of rolling bearings;

[0035] Comprehensive analysis module: Comprehensively analyze the equipment operation index and pre-processed health data through the diagnostic model, and output the bearing coefficient of the rolling bearing;

[0036] Fault diagnosis module: determines whether a warning signal needs to be issued based on the comparison result between the bearing coefficient and the warning threshold;

[0037] Amplitude judgment module: when the vibration amplitude of the initial monitoring exceeds the second vibration threshold or the vibration amplitude exceeds the second vibration threshold during the timing process, a warning signal is directly issued;

[0038] Communication module: sends warning signals remotely to the management platform.

[0039] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0040] The present invention monitors the vibration amplitude of the rolling bearing through a vibration sensor. If the vibration amplitude exceeds the first vibration threshold, the timer starts timing. When the timing duration is equal to the duration threshold, the diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates an equipment operation index based on the operation status, and then obtains the health data of the rolling bearing. After preprocessing the health data of the rolling bearing, the equipment operation index and the preprocessed health data are comprehensively analyzed through a diagnostic model, and the bearing coefficient of the rolling bearing is output. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold. The diagnostic system can effectively combine the equipment data and the rolling bearing data for analysis, and analyze whether the rolling bearing under the vibration condition has the possibility of failure, so that it can accurately warn and effectively reduce the probability of false alarms in the diagnostic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0042] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Example 1: Please refer to Figure 1 As shown, the present embodiment provides a fault diagnosis method based on rolling bearing vibration, the diagnosis method comprising the following steps:

[0045] The diagnostic system monitors the vibration amplitude of the rolling bearing through a vibration sensor and includes the following steps:

[0046] Signal acquisition: Vibration sensors are used to collect vibration signals near rolling bearings. This can be an acceleration signal, usually in g (gravitational acceleration), or a velocity signal, usually in mm / s (millimeter per second).

[0047] Time domain analysis: Perform time domain analysis on the vibration signal to obtain the timing characteristics of the vibration. This includes information such as the amplitude, frequency, and period of the vibration signal. Time domain analysis can evaluate the intensity of the vibration by calculating indicators such as the root mean square value (RMS) of the signal.

[0048] Frequency domain analysis: Perform frequency domain analysis on the vibration signal to obtain the distribution of the vibration signal at different frequencies. This can be achieved by performing Fourier transform or using spectrum analysis tools. Frequency domain analysis helps to detect vibration components at specific frequencies and identify fault modes.

[0049] Real-time monitoring and recording: The vibration monitoring system is embedded in the real-time monitoring system to record and monitor the vibration data of the rolling bearing in real time. This helps to track the status of the bearing in real time and provide data for further analysis and diagnosis.

[0050] If the vibration amplitude exceeds the first vibration threshold, the timer starts timing, including the following steps:

[0051] Vibration Amplitude Monitoring: Continuously monitor the vibration amplitude of rolling bearings. This can be detected in real time using data collected by vibration sensors.

[0052] Set the first vibration threshold: Set the first vibration threshold, which is used to trigger the start of the timer. This threshold should be an empirical value or based on previous analysis results to determine whether an abnormal vibration situation has occurred.

[0053] Vibration amplitude detection: Continuously detect whether the vibration amplitude exceeds the set first vibration threshold.

[0054] Trigger timer: When the vibration amplitude is detected to exceed the first vibration threshold, the trigger timer starts timing. The timer unit can be seconds, minutes or other suitable time units, depending on the specific application requirements.

[0055] Record start time: When the timer starts, the timestamp of when the timer starts is recorded. This helps with subsequent analysis and recording.

[0056] Record: Record the timer running time, vibration amplitude and other information for subsequent maintenance records and analysis.

[0057] When the timing duration is equal to the duration threshold, the diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates an equipment operation index based on the operation status, then obtains the health data of the rolling bearing, pre-processes the health data of the rolling bearing, and comprehensively analyzes the equipment operation index and the pre-processed health data through the diagnostic model, and outputs the bearing coefficient of the rolling bearing. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold. The diagnostic system monitors the vibration amplitude of the rolling bearing through a vibration sensor. When the initially monitored vibration amplitude exceeds the second vibration threshold or the vibration amplitude exceeds the second vibration threshold during the timing process, the diagnostic system directly issues a warning signal, including the following steps:

[0058] Real-time vibration monitoring: Continuously monitor the vibration of rolling bearings in real time, including the vibration amplitude. This can be done in real time using data collected by vibration sensors.

[0059] Set the second vibration threshold: Set the second vibration threshold, which is used to determine whether the vibration amplitude reaches the alarm level. This threshold is usually set higher than the first vibration threshold to identify more severe vibration conditions.

[0060] Initial monitoring: In the initial monitoring stage, it is detected whether the vibration amplitude exceeds the set second vibration threshold.

[0061] Timing process monitoring: During the timing process, continuously monitor whether the vibration amplitude exceeds the set second vibration threshold.

[0062] Issue a warning signal: If the vibration amplitude detected during the initial monitoring phase or the timing process exceeds the second vibration threshold, the system should immediately issue a warning signal. This can be achieved through an audible alarm, a visual warning light, a system notification, etc.

[0063] Record relevant information: record the timestamp, vibration amplitude, specific location and other relevant information of the warning signal for subsequent analysis and maintenance.

[0064] Stop timer: If the timer is running, the alarm signal requires stopping the timer for further maintenance operations.

[0065] Notify relevant personnel: After a warning signal is issued, the system should notify relevant maintenance personnel or operators so that they can take appropriate actions quickly.

[0066] Detailed vibration analysis: A detailed vibration analysis is performed on situations that issue warning signals to determine the cause of the fault and develop further maintenance plans.

[0067] Maintenance measures: Based on the results of the vibration analysis, take appropriate maintenance measures, including bearing replacement, lubricant replenishment, equipment calibration, etc.

[0068] The warning signal is remotely sent to the management platform, which processes it accordingly, including the following steps:

[0069] Set up remote communication protocols: Ensure that there is an appropriate remote communication protocol between the system and the management platform, such as Internet Protocol (IP) or other communication standards. This helps ensure reliable data transmission.

[0070] Configure the remote communication interface: Configure the remote communication interface in the diagnostic system so that it can transmit the warning signal to the management platform. This includes setting network connection parameters, authentication information, etc.

[0071] Warning signal transmission: When the system detects that the conditions for sending a warning signal are met, the warning signal is transmitted to the management platform through the configured remote communication interface. This can be done through network transmission, API call or other suitable methods.

[0072] Data encryption and security: Ensure appropriate data encryption and security handling of alert signals during transmission to protect the confidentiality and integrity of the data.

[0073] Management platform reception: Set up a receiving terminal on the management platform to receive warning signals from the diagnostic system. Ensure that the management platform has the corresponding interface and protocol to receive, parse and process the transmitted data.

[0074] Real-time display and recording: The received warning signals are displayed in real time on the management platform and recorded. This helps operators understand the equipment status in real time and leave detailed records for subsequent analysis.

[0075] The present application monitors the vibration amplitude of the rolling bearing through a vibration sensor. If the vibration amplitude exceeds the first vibration threshold, the timer starts timing. When the timing duration is equal to the duration threshold, the diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates an equipment operation index based on the operation status, and then obtains the health data of the rolling bearing. After preprocessing the health data of the rolling bearing, the equipment operation index and the preprocessed health data are comprehensively analyzed through the diagnostic model, and the bearing coefficient of the rolling bearing is output. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold. The diagnostic system can effectively combine the equipment data and the rolling bearing data for analysis, and analyze whether the rolling bearing under vibration conditions has the possibility of failure, so that it can accurately warn and effectively reduce the probability of false alarms in the diagnostic system.

[0076] Embodiment 2: The diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates an equipment operation index according to the operation status, and then obtains the health data of the rolling bearing. After preprocessing the health data of the rolling bearing, the equipment operation index and the preprocessed health data are comprehensively analyzed by the diagnostic model, and the bearing coefficient of the rolling bearing is output. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold;

[0077] The diagnostic system determines whether the equipment using rolling bearings is in operation and generates the equipment operation index according to the operation status, including the following steps:

[0078] The diagnostic system determines whether the equipment using rolling bearings is in operation. The specific methods are as follows:

[0079] Power status monitoring: Monitor the power status of the device and detect whether the device is turned on. This can be achieved by detecting current, voltage or other power parameters.

[0080] Speed ​​monitoring: Monitor the speed of the equipment. When the machine is started, the speed usually increases gradually, while when it is stopped, the speed decreases gradually. This can be achieved by using a speed sensor or other motion monitoring equipment.

[0081] When it is determined that the equipment using rolling bearings is in operation and lasts for a period of time (e.g. 5 minutes), the equipment operation index SYZ=1.5 is generated according to the operation state. When it is determined that the equipment using rolling bearings is in a stopped state, the equipment operation index SYZ=1.0 is generated according to the operation state. When the rolling bearing vibrates, if the equipment is in operation, it is more likely to cause rolling bearing failure, specifically:

[0082] Increased friction: Vibration can be caused by increased friction inside the rolling bearing, which can be caused by insufficient lubrication, lubricant aging or failure, resulting in increased friction between bearing components. Such a situation can accelerate the wear of the bearing and eventually lead to failure.

[0083] Bearing imbalance: Unbalanced rotating parts can cause vibrations and place additional loads on rolling element bearings. This imbalance can be caused by uneven wear of bearing components, unbalanced wear or improper assembly. Continued vibrations can lead to bearing failure.

[0084] Bearing fatigue: Vibration can cause bearings to experience additional stress, accelerating the bearing fatigue process. Under the influence of vibration, the life of the bearing may be reduced, thereby increasing the risk of failure.

[0085] Noise caused by vibration: Abnormal vibration is often accompanied by noise. These noises may be caused by abnormal friction, impact or cracks inside the bearing. The presence of noise may indicate that the bearing is experiencing abnormal conditions that may lead to further failure.

[0086] Loose or misaligned bearings: Vibration can cause bearings to become loose or misaligned in their seats. This condition can cause the bearing to lose proper alignment, increase friction and vibration, and ultimately lead to failure.

[0087] Resonance effect: The vibration of the equipment in operation may match the natural frequency of the rolling bearing or other components, causing a resonance effect. The resonance effect may cause the amplitude to increase, increasing the load and wear of the bearing.

[0088] Obtaining the health data of the rolling bearing and preprocessing the health data of the rolling bearing include the following steps:

[0089] The diagnostic system obtains the use data of the rolling bearing through the equipment system log, obtains the noise data through the decibel meter near the rolling bearing, obtains the temperature data through the temperature sensor near the rolling bearing, and obtains the displacement data through the displacement sensor on the rolling bearing;

[0090] After preprocessing the usage data, the aging rate is obtained; after preprocessing the noise data, the average noise decibel is obtained; after preprocessing the temperature data, the temperature deviation value is obtained; after preprocessing the displacement data, the coordinate similarity is obtained;

[0091] After preprocessing the usage data, the aging rate is obtained. The calculation expression is:

[0092] In the formula, C is the basic dynamic load, P is the actual working load, and LH is the aging rate. When the rolling bearing vibrates, the greater the aging rate of the rolling bearing, the more likely it is to cause rolling bearing failure, specifically:

[0093] Increased friction and wear: A higher aging rate means that the bearing has experienced relatively more working cycles, which may lead to wear and damage of the friction surfaces. Vibration increases friction and accelerates the wear process of these damaged surfaces, eventually leading to bearing failure.

[0094] Fatigue crack growth: A high aging rate means that the bearing may have experienced a large number of load cycles, resulting in fatigue cracks inside the bearing. Under vibration, these cracks may be more likely to grow, leading to further breakage and failure of the bearing.

[0095] Deterioration of lubrication performance: As bearings age, the performance of the lubricant may decline, resulting in increased friction. Vibration can accelerate the consumption of lubricant, causing the bearing to operate in an under-lubricated state, increasing the risk of failure.

[0096] Imbalance and instability: Aging can cause uneven wear of bearing components, making the equipment more susceptible to imbalance. Imbalance problems can be exacerbated by vibration, causing more severe vibrations in the bearing and equipment.

[0097] Material deterioration: Long-term operation and aging may cause the deterioration of bearing materials, such as reduced hardness, increased brittleness, etc. The deterioration of these materials may cause the bearing to be more easily deformed or damaged under vibration.

[0098] After preprocessing the noise data, the average noise decibel is obtained. The calculation expression of the average noise decibel is: In the formula, is the average noise decibel, i = 1, 2, 3, ..., n, n represents the number of sampling points in a period of time, dbi represents the noise decibel at the i-th sampling point, when the rolling bearing vibrates, if the average noise decibel of the rolling bearing is larger, it is more likely to cause rolling bearing failure, specifically:

[0099] Friction and wear: Increased noise can be related to increased friction within the bearing. Increased friction causes wear of bearing components, and vibration can accelerate this process, ultimately leading to bearing failure.

[0100] Damage or cracks: Loud noises may indicate an abnormality inside the bearing, such as damage or cracks. These problems can lead to increased vibration and noise, which can accelerate bearing failure.

[0101] Abnormal lubrication condition: Abnormal noise may be related to abnormal lubricant condition. There may be problems such as insufficient lubrication, over-lubrication or lubricant contamination, which may lead to increased friction and vibration.

[0102] Failure of bearing components: Failure of certain components inside the bearing (such as balls, raceways) may lead to increased vibration and noise. The failure of these components may be caused by fatigue, damage or other reasons.

[0103] Imbalance and instability: Increased noise can be associated with imbalance or instability of the equipment. Imbalance can cause increased vibration in the bearings and equipment, which can exacerbate noise levels.

[0104] After preprocessing the temperature data, the temperature deviation value is obtained. The calculation expression of the temperature deviation value is: WP = |WS-WB|, where WP is the temperature deviation value, WS is the real-time temperature, and WB is the standard temperature. When the rolling bearing vibrates, the larger the temperature deviation value of the rolling bearing is, the higher or lower the actual temperature of the rolling bearing is, which is more likely to cause rolling bearing failure. Specifically:

[0105] Insufficient or failed lubrication: High temperatures may indicate insufficient or failed lubricants. Insufficient lubrication can increase friction and cause bearing overheating. Conversely, low temperatures may indicate that lubricants fail in low temperature environments, increasing friction and wear on the bearings.

[0106] Increased bearing friction: Increased temperatures can be associated with increased friction inside the bearing. Increased friction can cause the bearing to overheat, damage the lubricant and accelerate wear of the bearing components.

[0107] Material damage: High temperatures may cause the bearing material to degenerate, soften, or otherwise become damaged. This material damage may make the bearing more susceptible to cracks or failure.

[0108] Internal bearing fault: Temperature abnormalities may be an indicator of internal bearing faults, such as damaged balls, raceways or seals. These faults can cause additional friction and heat generation, increasing the temperature of the bearing.

[0109] After preprocessing the displacement data, the coordinate similarity is obtained. The calculation expression of the coordinate similarity is: Where JL is the coordinate similarity, (x2, y2) is the current x-axis and y-axis coordinates of the rolling bearing, and (x1, y1) is the standard x-axis and y-axis coordinates of the rolling bearing. The greater the coordinate similarity, the more the rolling bearing deviates from the initial position when the rolling bearing vibrates, and the more likely it is to cause a rolling bearing failure, specifically:

[0110] Unbalanced load: Deflection of the rolling bearing from its original position may result in an unbalanced load on the bearing. This may be caused by deformation, looseness or other problems with the bearing support structure. Unbalanced loads may cause additional friction and vibration, increasing the risk of bearing wear and failure.

[0111] Bearing eccentricity: A bearing that deviates from its initial position during operation may indicate a bearing eccentricity or misalignment. This may be caused by loose bearing housing components, improper bearing installation, or uneven equipment loading. Eccentricity may cause uneven loading of the bearing, increasing the likelihood of failure.

[0112] Increased vibration amplitude: The deviation of the bearing from the initial position may lead to an increase in the vibration amplitude. Excessive vibration amplitude may cause collision between the bearing and adjacent components, increasing the risk of wear and damage.

[0113] Self-excitation: Bearing deviation from the initial position may cause self-excited vibration, that is, the system vibrates at a specific frequency and is amplified. Self-excited vibration may cause system instability and increase the possibility of bearing fatigue and failure.

[0114] Additional loads: Deviation from the initial position may cause the bearing to bear additional loads, such as lateral force, axial force, etc. These additional loads may cause the bearing to bear forces beyond the design range, accelerating bearing wear and failure.

[0115] The equipment operation index and the pre-processed health data are comprehensively analyzed through the diagnostic model to output the bearing coefficient of the rolling bearing, including the following steps:

[0116] The function expression of the diagnostic model is:

[0117] In the formula, zcx is the bearing coefficient, SYZ is the equipment operation index, LH is the aging rate, is the average noise decibel, WP is the temperature deviation value, JL is the coordinate similarity, ω1, ω2, ω3, and ω4 are the weight coefficients of aging rate, average noise decibel, temperature deviation value, and coordinate similarity, respectively, and ω1+ω2+ω3+ω4=1, ω4>ω2>ω1>ω3.

[0118] When the rolling bearing vibrates, the real-time aging rate, average noise decibel, temperature deviation value, and coordinate similarity are obtained and substituted into the diagnosis model to calculate the bearing coefficient.

[0119] The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold, including the following steps:

[0120] From the calculation expression of the bearing coefficient, it can be seen that the larger the bearing coefficient is, the more likely the rolling bearing is to fail. Therefore, after obtaining the bearing coefficient, the bearing coefficient is compared with the preset warning threshold.

[0121] If the bearing coefficient is greater than the warning threshold, it is determined that a warning signal needs to be issued;

[0122] If the bearing coefficient is less than or equal to the warning threshold, it is determined that there is no need to issue a warning signal.

[0123] Embodiment 3: A rolling bearing vibration-based fault diagnosis system described in this embodiment includes an amplitude monitoring module, a timing module, an equipment status acquisition module, a data acquisition module, a comprehensive analysis module, a fault diagnosis module, an amplitude judgment module, and a communication module;

[0124] Amplitude monitoring module: monitors the vibration amplitude of the rolling bearing through a vibration sensor, and the vibration amplitude is sent to the timing module and the amplitude judgment module;

[0125] Timing module: When the vibration amplitude exceeds the first vibration threshold, the timer starts timing, and the timing duration is sent to the device status acquisition module;

[0126] Equipment status acquisition module: when the timing duration is equal to the duration threshold, it determines whether the equipment using the rolling bearing is in operation, and generates the equipment operation index according to the operation status, and the equipment operation index is sent to the comprehensive analysis module;

[0127] Data acquisition module: obtains the health data of rolling bearings, pre-processes the health data of rolling bearings, and sends the health data to the comprehensive analysis module;

[0128] Comprehensive analysis module: The equipment operation index and pre-processed health data are comprehensively analyzed through the diagnostic model, and the bearing coefficient of the rolling bearing is output. The bearing coefficient is sent to the fault diagnosis module;

[0129] Fault diagnosis module: determines whether a warning signal needs to be issued based on the comparison result between the bearing coefficient and the warning threshold. When a warning signal is issued, the warning signal is sent to the communication module;

[0130] Amplitude judgment module: when the vibration amplitude of the initial monitoring exceeds the second vibration threshold or the vibration amplitude exceeds the second vibration threshold during the timing process, a warning signal is directly issued, and the warning signal is sent to the communication module;

[0131] Communication module: The warning signal is sent remotely to the management platform, which will process it accordingly.

[0132] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0133] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0134] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A fault diagnosis method based on rolling bearing vibration, characterized in that: The diagnostic method comprises the following steps: The diagnostic system monitors the vibration amplitude of the rolling bearing through a vibration sensor, and if the vibration amplitude exceeds a first vibration threshold, a timer starts timing; When the timing duration is equal to the duration threshold, the diagnostic system determines whether the equipment using the rolling bearing is in operation, and generates different equipment operation indexes according to the operation status and the stop status; Acquire the health data of the rolling bearing and pre-process the health data of the rolling bearing; The equipment operation index and pre-processed health data are comprehensively analyzed through the diagnostic model to output the bearing coefficient of the rolling bearing. The diagnostic system determines whether a warning signal needs to be issued based on the comparison result between the bearing coefficient and the warning threshold. When the vibration amplitude of the initial monitoring exceeds the second vibration threshold or the vibration amplitude exceeds the second vibration threshold during the timing process, the diagnostic system directly sends a warning signal, and the warning signal is remotely sent to the management platform; Obtaining the health data of the rolling bearing and preprocessing the health data of the rolling bearing include the following steps: The diagnostic system obtains the use data of the rolling bearing through the equipment system log, obtains the noise data through the decibel meter near the rolling bearing, obtains the temperature data through the temperature sensor near the rolling bearing, and obtains the displacement data through the displacement sensor on the rolling bearing; After preprocessing the usage data, the aging rate is obtained; after preprocessing the noise data, the average noise decibel is obtained; after preprocessing the temperature data, the temperature deviation value is obtained; after preprocessing the displacement data, the coordinate similarity is obtained; The equipment operation index and the pre-processed health data are comprehensively analyzed through the diagnostic model to output the bearing coefficient of the rolling bearing, including the following steps: The function expression of the diagnostic model is: In the formula, zcx is the bearing coefficient, SYZ is the equipment operation index, LH is the aging rate, is the average noise decibel, WP is the temperature deviation value, JL is the coordinate similarity, ω1, ω2, ω3, ω4 are the weight coefficients of aging rate, average noise decibel, temperature deviation value, and coordinate similarity, respectively, and ω1+ω2+ω3+ω4=1, ω4>ω2>ω1>ω3; When the rolling bearing vibrates, the real-time aging rate, average noise decibel, temperature deviation value, and coordinate similarity are obtained and substituted into the diagnosis model to calculate the bearing coefficient.

2. A rolling bearing vibration-based fault diagnosis method according to claim 1, characterized in that: The diagnostic system determines whether a warning signal needs to be issued based on the comparison result of the bearing coefficient and the warning threshold, including the following steps: After obtaining the bearing coefficient, the bearing coefficient is compared with the preset warning threshold; If the bearing coefficient is greater than the warning threshold, it is determined that a warning signal needs to be issued; If the bearing coefficient is less than or equal to the warning threshold, it is determined that there is no need to issue a warning signal.

3. A rolling bearing vibration-based fault diagnosis method according to claim 2, characterized in that: After preprocessing the displacement data, the coordinate similarity is obtained. The calculation expression of the coordinate similarity is: Where JL is the coordinate similarity, (x2, y2) is the current x-axis and y-axis coordinates of the rolling bearing, and (x1, y1) is the standard x-axis and y-axis coordinates of the rolling bearing.

4. A rolling bearing vibration-based fault diagnosis method according to claim 3, characterized in that: After preprocessing the temperature data, the temperature deviation value is obtained. The calculation expression of the temperature deviation value is: WP=|WS-WB|, where WP is the temperature deviation value, WS is the real-time temperature, and WB is the standard temperature.

5. A rolling bearing vibration-based fault diagnosis method according to claim 4, characterized in that: After preprocessing the noise data, the average noise decibel is obtained. The calculation expression of the average noise decibel is: In the formula, is the average noise decibel, i = 1, 2, 3, ..., n, n represents the number of sampling points in a period of time, db i Represents the noise decibel at the i-th sampling point.

6. A rolling bearing vibration-based fault diagnosis method according to claim 5, characterized in that: After preprocessing the usage data, the aging rate is obtained. The calculation expression of the aging rate is: Where C is the basic dynamic load, P is the actual working load, and LH is the aging rate.

7. A rolling bearing vibration-based fault diagnosis method according to claim 6, characterized in that: The diagnostic system determines whether the equipment using rolling bearings is in operation and generates different equipment operation indexes according to the operation state and the stop state, including the following steps: When it is judged that the equipment using rolling bearings is in operation and continues for a period of time, different equipment operation indexes SYZ=1.5 are generated according to the operation state and the stop state. When it is judged that the equipment using rolling bearings is in the stop state, different equipment operation indexes SYZ=1.0 are generated according to the operation state and the stop state.

8. A rolling bearing vibration-based fault diagnosis system, used to implement the diagnosis method according to any one of claims 1 to 7, characterized in that: It includes amplitude monitoring module, timing module, equipment status acquisition module, data acquisition module, comprehensive analysis module, fault diagnosis module, amplitude judgment module and communication module; Amplitude monitoring module: monitors the vibration amplitude of rolling bearings through vibration sensors; Timing module: when the vibration amplitude exceeds the first vibration threshold, the timer starts timing; Equipment status acquisition module: When the timing duration is equal to the duration threshold, it determines whether the equipment using rolling bearings is in operation, and generates different equipment operation indexes according to the operation status and stop status; Data acquisition module: obtains the health data of rolling bearings and pre-processes the health data of rolling bearings; Comprehensive analysis module: Comprehensively analyze the equipment operation index and pre-processed health data through the diagnostic model, and output the bearing coefficient of the rolling bearing; Fault diagnosis module: determines whether a warning signal needs to be issued based on the comparison result between the bearing coefficient and the warning threshold; Amplitude judgment module: when the vibration amplitude of the initial monitoring exceeds the second vibration threshold or the vibration amplitude exceeds the second vibration threshold during the timing process, a warning signal is directly issued; Communication module: sends warning signals remotely to the management platform.

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