Unit sliding bearing fault identification method and system based on vibration and temperature cooperation

Abstract

The invention discloses a unit sliding bearing fault identification method and system based on vibration and temperature cooperation. At present, a traditional sliding bearing fault diagnosis method cannot accurately predict the working state of a sliding bearing, and is not beneficial to prevention of faults such as large vibration, bearing fragmentation and bearing metal shedding of large rotating equipment. The fault identification method comprises the following steps: acquiring vibration and temperature data of a sliding bearing of a unit by using a data acquisition system; performing trend and spectrum analysis on the collected vibration data to generate a vibration trend graph, a time domain graph and a spectrogram; performing trend analysis on the acquired temperature data to generate a temperature trend chart; performing collaborative analysis on the vibration and temperature data by using the vibration trend chart, the time domain chart, the spectrogram and the temperature trend chart to obtain an analysis result; and judging the fault of the sliding bearing according to the analysis result. Bearing vibration and temperature signals are fully utilized, and the accuracy degree of sliding bearing state detection is effectively improved.

Description

Technical Field

[0001] The invention belongs to the technical field of sliding bearing fault diagnosis, and relates to a method and system for identifying sliding bearing faults of a unit based on the coordination of vibration and temperature. Background Art

[0002] Sliding bearings have always been one of the key components of various types of large equipment, such as large steam turbine generator sets, large gas-steam combined cycle generator sets, large wind turbine sets, converter station phase regulators, etc. Its vibration, temperature and other parameters are important monitoring indicators of the sliding bearing status, and are also the main parameters for judging whether its working status is normal. Therefore, improving the working status of sliding bearings and increasing their service life are one of the main measures to ensure and enhance the safe and reliable operation of large equipment. At present, the traditional fault diagnosis method of sliding bearings fails to accurately predict the working status of sliding bearings, and fails to timely prevent large vibrations, bearing breakage, bearing black metal shedding and other faults of large rotating equipment, resulting in unplanned shutdown of large equipment and a significant reduction in overall safety and stability.

[0003] In recent years, with the continuous development and progress of sensor technology, multi-sensor joint analysis has gradually become a hot topic in the field of sliding bearing fault identification. By applying vibration sensors and temperature sensors, multi-dimensional information generated by sliding bearings at work can be obtained, including vibration signals, bearing temperature, oil return temperature and other data. The multi-sensor joint analysis method utilizes the advantages of different sensors. By comprehensively analyzing multi-dimensional information, the working status and health level of the unit sliding bearing can be comprehensively and accurately judged.

[0004] Therefore, it is particularly important to study an efficient and reliable method for fault identification of sliding bearings of units using multi-sensor joint analysis technology. Summary of the invention

[0005] In view of the problem of low accuracy in sliding bearing fault identification of existing units, the present invention provides a sliding bearing fault identification method and system based on vibration and temperature collaboration, which can make full use of bearing vibration and temperature signals to improve the accuracy of sliding bearing status detection.

[0006] To this end, the present invention adopts the following technical solution.

[0007] In a first aspect, the present invention provides a method for identifying a unit sliding bearing fault based on vibration and temperature coordination, which comprises:

[0008] Step 1: Use a data acquisition system to collect vibration and temperature data of the unit's sliding bearings;

[0009] Step 2: Perform trend and spectrum analysis on the collected vibration data to generate a vibration trend graph, a time domain graph, and a spectrum graph; perform trend analysis on the collected temperature data to generate a temperature trend graph;

[0010] Step 3, using the vibration trend graph, time domain graph, spectrum graph and temperature trend graph, collaboratively analyze the vibration and temperature data to obtain analysis results; the vibration trend graph is used to determine the change in vibration amplitude, the time domain graph is used to determine whether there is an impact phenomenon in the vibration, the spectrum graph is used to determine each multiplier component, and the temperature trend graph is used to determine whether there is a fault on the surface of the sliding bearing supporting the rotor;

[0011] Step 4: determine the fault of the sliding bearing according to the analysis results.

[0012] The present invention can not only improve the accuracy of fault identification, but also realize real-time monitoring of the unit sliding bearings, discover the initial characteristics of bearing failures, reasonably use downtime opportunities, and take maintenance measures in time, which not only reduces the maintenance cost of rotating equipment, but also improves the reliability and service life of the equipment.

[0013] Furthermore, the data acquisition system is a vibration acquisition system and a temperature acquisition system, the vibration acquisition system is the TDM system of the unit or a vibration acquisition system externally connected to the unit vibration detection system TSI, and the temperature acquisition system is the unit DCS system.

[0014] Furthermore, the step 3 comprises:

[0015] Step 31), using the vibration trend diagram, when the shaft amplitude change is ≥30μm or the bearing vibration velocity change is ≥1.2mm / s, the working state of the sliding bearing needs to be evaluated;

[0016] Step 32), using the bearing vibration velocity value, convert the bearing vibration velocity from mm / s to an amplitude of μm; determine what kind of fault the sliding bearing has through the ratio of the shaft amplitude value to the bearing amplitude value and the temperature change amount obtained by the temperature trend graph.

[0017] Furthermore, the conversion relationship between the vibration velocity of the shoe and the vibration amplitude of the shoe is:

[0018]

[0019] In the formula, V is the watt amplitude value, in μm; rms is the vibration speed of the motor, in mm / s; f is the operating speed frequency, in Hz.

[0020] Furthermore, in the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is less than 3, it is judged that the dynamic stiffness of the sliding bearing decreases, indicating a support failure of the sliding bearing bearing body. The temperature trend diagram is used for comparison under the same operating conditions of the unit. When the bearing temperature change is greater than 3°C, it indicates that there is still a bearing surface failure of the sliding bearing supporting the rotor. Otherwise, there is only a support failure of the sliding bearing bearing body.

[0021] Furthermore, in the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is ≥3, and the temperature trend diagram is used for comparison under the same operating conditions of the unit, when the bearing temperature change is >3°C, it indicates that there is a bearing surface fault of the sliding bearing supporting the rotor.

[0022] Furthermore, in the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is ≥3, and the temperature trend chart is used to compare under the same operating conditions of the unit, and the bearing temperature change is ≤3°C, then other faults exist and further judgment is made, including the following situations:

[0023] 1) Using the vibration spectrum diagram, if there is no half-frequency component or other non-half-frequency low-frequency component in the vibration spectrum diagram except the operating speed frequency, there is a mass imbalance fault; if there is still a half-frequency component or other non-half-frequency low-frequency component, there are other faults;

[0024] 2) Using the vibration time domain diagram, whether there are obvious impact waveform characteristics, if so, it indicates that there is an abnormal gap between the bearing pad and the bearing block;

[0025] Furthermore, in the case 1), if there are half-frequency components or other non-half-frequency low-frequency components in the vibration spectrum in addition to the operating speed frequency, there are other faults, and the following further judgment is made:

[0026] If the unit steam inlet is operated in the sequential valve mode and the full-circle steam inlet mode, the shaft vibration can be significantly reduced by adjusting the sequential valve sequence, and the vibration fault is steam flow excitation vibration; otherwise, it is a bearing surface fault and the state of the sliding bearing has changed seriously;

[0027] If the unit's lubricating oil temperature is changed, the vibration of the sliding bearing is reduced or the low-frequency component is reduced, it is an oil film failure, otherwise it is a bearing surface failure.

[0028] In a second aspect, the present invention provides a unit sliding bearing fault identification system based on vibration and temperature coordination, which is used to implement the unit sliding bearing fault identification system, and includes:

[0029] Data acquisition unit: Use the data acquisition system to collect vibration and temperature data of the unit's sliding bearings;

[0030] Graph generation unit: performs trend and spectrum analysis on the collected vibration data to generate vibration trend graph, time domain graph and spectrum graph; performs trend analysis on the collected temperature data to generate temperature trend graph;

[0031] Collaborative analysis unit: using a vibration trend graph, a time domain graph, a spectrum graph and a temperature trend graph to collaboratively analyze vibration and temperature data to obtain analysis results; the vibration trend graph is used to determine the change in vibration amplitude, the time domain graph is used to determine whether there is an impact phenomenon in vibration, the spectrum graph is used to determine each frequency multiplication component, and the temperature trend graph is used to determine whether there is a fault on the surface of the sliding bearing supporting the rotor;

[0032] Fault judgment unit: judges the fault of the sliding bearing according to the analysis result.

[0033] The invention has the following beneficial effects: the invention uses vibration and temperature to perform a joint collaborative analysis on the state of the unit sliding bearing, effectively improving the accuracy and reliability of the unit sliding bearing fault identification, reducing maintenance costs, and extending the service life of the equipment. The invention is mainly used for sliding bearing fault identification of large rotating equipment, including large steam turbine generator sets, gas steam combined cycle generator sets, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a flow chart of the unit sliding bearing fault identification method based on vibration and temperature coordination of the present invention;

[0035] Figure 2 It is a structural diagram of the unit sliding bearing fault identification system based on vibration and temperature coordination of the present invention;

[0036] Figure 3 It is a vibration trend diagram of the shaft vibration and shoe vibration of the sliding bearing of the present invention;

[0037] Figure 4 is a temperature trend diagram of the sliding bearing of the present invention;

[0038] Figure 5 This is a picture showing the bearing body surface crushing phenomenon when the No. 1 bearing in Application Example 1 of the present invention is being repaired.

[0039] Figure 6 is a spectrum diagram of shaft vibration of the sliding bearing of the present invention;

[0040] Figure 7 It is a time domain diagram of the shaft vibration of the sliding bearing of the present invention;

[0041] Figure 8 This is a picture showing the broken positioning bolt of the bearing during the overhaul of the No. 4 bearing in Application Example 2 of the present invention. DETAILED DESCRIPTION

[0042] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the technical scheme in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all 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.

[0043] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0044] Example 1

[0045] This embodiment provides a method for identifying unit sliding bearing faults based on vibration and temperature coordination. Figure 1 As shown, the steps are as follows:

[0046] Step 1: Use a data acquisition system to collect vibration and temperature data of the unit's sliding bearings;

[0047] Step 2: Perform trend and spectrum analysis on the collected vibration data to generate a vibration trend graph, a time domain graph, and a spectrum graph; perform trend analysis on the collected temperature data to generate a temperature trend graph;

[0048] Step 3, using the vibration trend graph, time domain graph, spectrum graph and temperature trend graph, collaboratively analyze the vibration and temperature data to obtain analysis results; the vibration trend graph is used to determine the change in vibration amplitude, the time domain graph is used to determine whether there is an impact phenomenon in the vibration, the spectrum graph is used to determine each multiplier component, and the temperature trend graph is used to determine whether there is a fault on the surface of the sliding bearing supporting the rotor;

[0049] Step 4: determine the fault of the sliding bearing according to the analysis results.

[0050] The data acquisition system is a vibration acquisition system and a temperature acquisition system. The vibration acquisition system is the TDM system of the unit or a vibration acquisition system externally connected to the vibration detection system TSI of the unit. The temperature acquisition system is the DCS system of the unit.

[0051] Specifically, the step 3 includes:

[0052] Step 31), using the vibration trend diagram, when the shaft amplitude change is ≥30μm or the bearing vibration velocity change is ≥1.2mm / s, the working state of the sliding bearing needs to be evaluated;

[0053] Step 32), using the bearing vibration velocity value, convert the bearing vibration velocity from mm / s to an amplitude of μm; determine what kind of fault the sliding bearing has through the ratio of the shaft amplitude value to the bearing amplitude value and the temperature change amount obtained by the temperature trend graph.

[0054] More specifically, the conversion relationship between the vibration velocity of the shoe and the vibration amplitude of the shoe is:

[0055]

[0056] In the formula, V is the watt amplitude value, in μm; rms is the vibration speed of the motor, in mm / s; f is the operating speed frequency, in Hz.

[0057] More specifically, in the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is less than 3, it is judged that the dynamic stiffness of the sliding bearing has decreased, indicating a support failure of the sliding bearing bearing body. The temperature trend graph is used for comparison under the same operating conditions of the unit. When the bearing temperature change is greater than 3°C, it indicates that there is still a bearing surface failure of the sliding bearing supporting the rotor. Otherwise, there is only a support failure of the sliding bearing bearing body.

[0058] More specifically, in the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is ≥3, and the temperature trend chart is used for comparison under the same operating conditions of the unit, when the bearing temperature change is >3°C, it indicates that there is a bearing surface fault of the sliding bearing supporting the rotor.

[0059] More specifically, in step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is ≥3, and the temperature trend chart is used to compare under the same operating conditions of the unit, and the bearing temperature change is ≤3°C, then other faults exist and further judgment is made, including the following situations:

[0060] 1) Using the vibration spectrum diagram, if there is no half-frequency component or other non-half-frequency low-frequency component in the vibration spectrum diagram except the operating speed frequency, there is a mass imbalance fault; if there is still a half-frequency component or other non-half-frequency low-frequency component, there are other faults;

[0061] 2) Using the vibration time domain diagram, whether there are obvious impact waveform characteristics, if so, it indicates that there is an abnormal gap between the bearing pad and the bearing block;

[0062] Using the vibration spectrum diagram, if the 50 Hz power frequency component is dominant, dynamic balance calculation is performed and the existence of dynamic balance is confirmed. A dynamic balance test should be performed to reduce vibration and eliminate sliding bearing faults.

[0063] In the case 1), if there are half-frequency components or other non-half-frequency low-frequency components in addition to the operating speed frequency of 50 Hz in the vibration spectrum, there are other faults, and further judgment is made as follows:

[0064] If the unit steam inlet is operated in the sequential valve mode and the full-circle steam inlet mode, the shaft vibration can be significantly reduced by adjusting the sequential valve sequence, and the vibration fault is steam flow excitation vibration; otherwise, it is a bearing surface fault and the state of the sliding bearing has changed seriously;

[0065] If the unit's lubricating oil temperature is changed, the vibration of the sliding bearing is reduced or the low-frequency component is reduced, it is an oil film failure, otherwise it is a bearing surface failure.

[0066] The present invention provides a vibration and temperature coordinated sliding bearing fault identification method, which can effectively monitor the current working state of the sliding bearing of a large steam turbine generator set, and if a fault exists, can determine what kind of fault it is.

[0067] Example 2

[0068] This embodiment provides a unit sliding bearing fault identification system based on vibration and temperature coordination, such as Figure 2 As shown, the system for realizing the unit sliding bearing fault identification described in Example 1 is composed of a data acquisition unit, a graph generation unit, a collaborative analysis unit and a fault judgment unit.

[0069] The data acquisition unit uses a data acquisition system to collect vibration and temperature data of the unit's sliding bearings.

[0070] The graph generating unit: performs trend and spectrum analysis on the collected vibration data to generate a vibration trend graph, a time domain graph and a spectrum graph; performs trend analysis on the collected temperature data to generate a temperature trend graph.

[0071] The collaborative analysis unit: uses a vibration trend graph, a time domain graph, a spectrum graph and a temperature trend graph to collaboratively analyze the vibration and temperature data to obtain an analysis result; the vibration trend graph is used to determine the change in vibration amplitude, the time domain graph is used to determine whether there is an impact phenomenon in the vibration, the spectrum graph is used to determine each harmonic component, and the temperature trend graph is used to determine whether there is a fault on the surface of the sliding bearing supporting the rotor.

[0072] The fault judgment unit judges the fault of the sliding bearing according to the analysis result.

[0073] The parts of the above units that are not described in detail are the same as those in Example 1 and will not be described again here.

[0074] Application Example 1

[0075] The model of the No. 6 steam turbine of a power plant is N1050-26.5 / 600 / 600 (TC4F), an ultra-supercritical, single-shaft, four-cylinder, four-exhaust, single-intermediate reheat, single back-pressure condensing steam turbine. The generator model is a THDF 125 / 67 water-hydrogen-hydrogen-cooled generator. The unit is equipped with a VM600 TSI monitoring system, which can be used to collect shaft vibration signals with a shaft vibration collector. There are eight supporting bearings, and each bearing is equipped with an eddy current sensor at 45° and 135° to measure shaft vibration. 1-2 watts are equipped with four temperature measuring points, 3-5 watts are equipped with two temperature measuring points, and 6-8 watts are equipped with one temperature measuring point. The operating speed is 3000r / min (50Hz).

[0076] The unit No. 1 bearing shaft vibration fluctuates, with the maximum vibration fluctuating to 153 μm. The method described in Example 1 of the present invention is applied to this unit.

[0077] From the shaft vibration and bearing vibration trend chart of the No. 1 bearing of the unit, it can be seen that the maximum vibration value of the shaft vibration is 153μm, the maximum shaft vibration change is 105μm, the maximum vibration value of the bearing vibration is 1.5mm / s, and the maximum bearing vibration change is 0.8mm / s, indicating that there is a fault in the No. 1 bearing.

[0078] The formula is used to convert the bearing vibration velocity into bearing amplitude value. The bearing amplitude value is 13.5μm, and the ratio of the bearing amplitude value to the shaft amplitude value is greater than 3, such as Figure 3 As shown in the figure, and from the temperature trend diagram, it can be concluded that when the unit load is about 950MW, the maximum bearing temperature change is 15°C, which is 3°C greater than the set value in the present invention, indicating that the bearing surface of the sliding bearing supporting the rotor is faulty, such as Figure 4 shown.

[0079] Based on the above analysis, it is judged that there is a fault on the surface of the No. 1 bearing supporting the rotor of the unit, and it is necessary to shut down for inspection. Later, during the maintenance of the unit, it was found that there was a grinding phenomenon on the surface of the No. 1 bearing. Figure 5 As shown, after the repair was completed, the vibration of tile No. 1 returned to normal.

[0080] Application Example 2

[0081] The No. 3 steam turbine of a certain power plant is a D11 condensing steam turbine produced by GE of the United States. It consists of high- and medium-pressure rotors and a low-pressure rotor. Each shaft has a double-support structure. No. 1-3 bearings are 6-tile tilting pads, and No. 4 bearings are 4-tile tilting pad bearings. Each bearing is equipped with an eddy current sensor at 45° and 135° to measure shaft vibration. Each of the bearings 1-4 is equipped with a temperature measuring point, and the operating speed is 3000r / min (50Hz).

[0082] During the operation of the unit, the vibration of bearing No. 4 suddenly increased and continued to fluctuate, with the maximum vibration fluctuating to 180μm. As the operation time increased, the overall vibration fluctuation trend gradually increased. The sensor installation of this unit is different from that of other units. Only the shaft vibration measurement point is installed, and there is no bearing vibration measurement point. In addition, the bearing temperature measurement point is damaged. In this case, the method described in Example 1 of the present invention is applied to this unit.

[0083] The trend chart of the shaft vibration of the No. 4 bearing of the unit shows that the maximum vibration value of the shaft vibration is about 180μm and the maximum shaft vibration change is about 130μm, indicating that there is a fault in the No. 4 bearing.

[0084] Since the bearing vibration signal and bearing temperature signal are missing, the 4 bearing shaft vibration spectrum shows that there is an obvious low-frequency component (lower than the operating frequency 50Hz), such as Figure 6 shown.

[0085] Since there are low-frequency components in the axial vibration spectrum of bearing No. 4, further analysis is carried out.

[0086] (1) The No. 4 bearing is located at the rear bearing of the low-pressure cylinder. The steam inlet parameters are small, which can eliminate steam flow vibration.

[0087] (2) The unit was subjected to a variable lubricating oil temperature test. When the lubricating oil temperature changed by 8°C, there was no significant change in the low-frequency components of the shaft vibration spectrum, thus ruling out oil film failure.

[0088] From the vibration time domain diagram of the No. 4 bearing shaft, it can be concluded that there is an impact phenomenon, which is an abnormal waveform, indicating that the sliding bearing has an abnormal installation clearance or other installation abnormalities, such as Figure 7 shown.

[0089] Based on the above analysis, it is judged that the No. 4 bearing block of the unit has a fault and needs to be shut down for inspection. Later, during the maintenance of the unit, it was found that the positioning bolts of the upper bearing block of the No. 4 bearing were broken. Figure 8 As shown, after the repair was completed, the vibration of tile No. 4 returned to normal.

[0090] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0091] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for identifying unit sliding bearing faults based on vibration and temperature coordination, characterized in that: include: Step 1: Use a data acquisition system to collect vibration and temperature data of the unit's sliding bearings; Step 2: Perform trend and spectrum analysis on the collected vibration data to generate a vibration trend graph, a time domain graph, and a spectrum graph; Perform trend analysis on the collected temperature data and generate a temperature trend graph; Step 3, using the vibration trend graph, time domain graph, spectrum graph and temperature trend graph, collaboratively analyze the vibration and temperature data to obtain the analysis results; the vibration trend graph is used to determine the change in vibration amplitude, the time domain graph is used to determine whether there is an impact phenomenon in the vibration, the spectrum graph is used to determine each frequency multiplication component, and the temperature trend graph is used to determine whether there is a deviation in the bearing and installation of the bearing bush; Step 4: determine the fault of the sliding bearing according to the analysis results.

2. The unit sliding bearing fault identification method according to claim 1 is characterized in that: The data acquisition system is a vibration acquisition system and a temperature acquisition system. The vibration acquisition system is the TDM system of the unit or a vibration acquisition system externally connected to the vibration detection system TSI of the unit. The temperature acquisition system is the DCS system of the unit.

3. The unit sliding bearing fault identification method according to claim 1, characterized in that: The step 3 comprises: Step 31), using the vibration trend diagram, when the shaft amplitude change is ≥30μm or the bearing vibration velocity change is ≥1.2mm / s, the working state of the sliding bearing needs to be evaluated; Step 32), using the bearing vibration velocity value, convert the bearing vibration velocity from mm / s to an amplitude of μm; determine what kind of fault the sliding bearing has through the ratio of the shaft amplitude value to the bearing amplitude value and the temperature change amount obtained by the temperature trend graph.

4. The unit sliding bearing fault identification method according to claim 3 is characterized in that: In the step 32), the conversion relationship between the vibration velocity of the shoe and the vibration amplitude of the shoe is: Where W 位移p-p V is the watt amplitude value, in μm; rms is the vibration speed of the motor, in mm / s; f is the operating speed frequency, in Hz.

5. The unit sliding bearing fault identification method according to claim 3 is characterized in that: In the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is less than 3, it is judged that the dynamic stiffness of the sliding bearing is reduced, indicating a support failure of the sliding bearing bearing body. The temperature trend diagram is used for comparison under the same operating conditions of the unit. When the bearing temperature change is greater than 3°C, it indicates that there is still a bearing surface failure of the sliding bearing supporting the rotor. Otherwise, there is only a support failure of the sliding bearing bearing body.

6. The unit sliding bearing fault identification method according to claim 3 is characterized in that: In the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is ≥3, and the temperature trend chart is used for comparison under the same operating conditions of the unit, when the bearing temperature change is greater than 3°C, it indicates that there is a bearing surface fault of the sliding bearing supporting the rotor.

7. The unit sliding bearing fault identification method according to claim 3 is characterized in that: In the step 32), if the ratio of the shaft amplitude value to the bearing amplitude value is ≥3, and the temperature trend chart is used to compare the bearing temperature change under the same operating conditions of the unit, and the bearing temperature change is ≤3°C, then there are other faults, and further judgment is made, including the following situations: 1) Using the vibration spectrum diagram, if there is no half-frequency component or other non-half-frequency low-frequency component in the vibration spectrum diagram except the operating speed frequency, there is a mass imbalance fault; if there is still a half-frequency component or other non-half-frequency low-frequency component, there are other faults; 2) Using the vibration time domain diagram, check whether there are obvious impact waveform features. If so, it indicates that there is an abnormal gap between the bearing and the bearing block.

8. The unit sliding bearing fault identification method according to claim 7, characterized in that: In the case 1), if there are half-frequency components or other non-half-frequency low-frequency components in the vibration spectrum in addition to the operating speed frequency, there are other faults, and further judgment is made as follows: If the unit steam inlet is operated in the sequential valve mode and the full-circle steam inlet mode, the shaft vibration can be significantly reduced by adjusting the sequential valve sequence, and the vibration fault is steam flow excitation vibration; otherwise, it is a bearing surface fault and the state of the sliding bearing has changed seriously; If the unit's lubricating oil temperature is changed, the vibration of the sliding bearing is reduced or the low-frequency component is reduced, it is an oil film failure, otherwise it is a bearing surface failure.

9. A unit sliding bearing fault identification system based on vibration and temperature coordination, used to implement the unit sliding bearing fault identification system according to any one of claims 1 to 8, characterized in that: include: Data acquisition unit: Use the data acquisition system to collect vibration and temperature data of the unit's sliding bearings; Graph generation unit: performs trend and spectrum analysis on the collected vibration data to generate vibration trend graphs, time domain graphs and spectrum graphs; Perform trend analysis on the collected temperature data and generate a temperature trend graph; Collaborative analysis unit: using a vibration trend graph, a time domain graph, a spectrum graph and a temperature trend graph to collaboratively analyze vibration and temperature data to obtain analysis results; the vibration trend graph is used to determine the change in vibration amplitude, the time domain graph is used to determine whether there is an impact phenomenon in vibration, the spectrum graph is used to determine each frequency multiplication component, and the temperature trend graph is used to determine whether there is a fault on the bearing surface of the sliding bearing supporting the rotor; Fault judgment unit: judges the fault of the sliding bearing according to the analysis result.

10. The unit sliding bearing fault identification system based on vibration and temperature coordination according to claim 1, characterized in that: The collaborative analysis unit is used to: use the vibration trend graph, when the shaft amplitude change is ≥30μm or the bearing vibration velocity change is ≥1.2mm / s, it is necessary to evaluate the working condition of the sliding bearing; use the bearing vibration velocity value to convert the bearing vibration velocity from mm / s to amplitude μm; and determine what kind of fault the sliding bearing has through the ratio of the shaft amplitude value to the bearing amplitude value and the temperature change obtained from the temperature trend graph.

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