CN114186704A - Method and system for early warning of operation state of rotary auxiliary engine cluster of thermal power plant - Google Patents
Method and system for early warning of operation state of rotary auxiliary engine cluster of thermal power plant Download PDFInfo
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Abstract
The invention relates to a method and a system for early warning the running state of a rotary auxiliary machine cluster of a thermal power plant, wherein the method comprises the following steps: s1, coding the equipment, the components and the faults respectively; s2, determining the measuring points of the equipment, wherein the positions and the number of the measuring points of the similar equipment are the same; s3, establishing a remote platform and monitoring the cluster state of the similar equipment; s4, classifying the faults, and formulating different early warning levels according to different influences of different faults on the equipment; and S5, comparing the monitoring result of the remote platform with the early warning grade, and giving out early warning information. After equipment diagnosis knowledge, data sources are unified and fault samples are rapidly obtained, pertinence early warning is carried out according to different damage degrees of the equipment by different faults, and therefore accuracy of early warning is improved.
Description
Technical Field
The invention relates to the technical field of thermal power equipment running state evaluation, in particular to a thermal power plant rotary auxiliary machine cluster running state early warning method and system.
Background
In a thermal power plant, a plurality of rotary auxiliary equipment are provided, and various rotary equipment such as a fan, a water pump, a motor and the like are important components in a thermal power generation system. The vibration fault of the rotating equipment has the characteristics of burstiness, persistence, serious harm and the like. All rotating equipment all belong to a certain subsystem in the power plant, therefore rotating equipment in case develops the operation that vibration trouble directly influences the subsystem, influences the safe operation of whole power plant even. In order to ensure the safe operation of the rotating equipment of the thermal power plant, how to accurately know the operation state of the current rotating mechanical equipment and how to early warn risks existing in the equipment are the key for realizing the health management.
The existing early warning system or method has low accuracy and mainly has the following problems: (1) when cluster early warning is carried out on the same equipment running in different regions, unified coding is not needed to be carried out on the equipment, components and structural characteristics, so that the computer can be read; however, the vibration characteristics of the similar equipment are different due to different models, structural characteristics and the like, so that targeted early warning cannot be performed according to the structural characteristics of the equipment; (2) the source of the obtained vibration data is lack of uniform regulation, so that the vibration difference caused by different measuring point positions cannot be identified, and the data is not comparable; (3) various fault risks of equipment are not treated differently, particularly for a rotary auxiliary machine of a thermal power plant, vibration deletion is serious due to the fact that a measuring point is far away from a bearing and due to the influence of lubricating oil, and a smaller fault characteristic frequency amplitude value usually means serious bearing fault; (4) the early warning level assignment is relatively fixed and is not integrated with a power plant overhaul system, so that the early warning level assignment cannot be updated according to the overhaul disassembly state of the equipment.
Chinese patent CN105809255B discloses a thermal power plant rotating machinery health management method and system based on internet of things, including: acquiring basic information and state information of rotary mechanical equipment; monitoring the running state of the rotating mechanical equipment according to the acquired basic information and state information, diagnosing potential faults of the rotating mechanical equipment, evaluating the health state of the rotating mechanical equipment, and predicting the remaining life of the rotating mechanical equipment; and generating a maintenance plan of the rotary mechanical equipment according to the potential fault diagnosis result of the rotary mechanical equipment. But the data sources are not uniformly specified, and the different damage degrees of different fault types to the equipment are not considered.
The invention discloses a Chinese patent CN 109186748A, which relates to an auxiliary machine vibration early warning method and a system based on a big data mining technology, wherein the method comprises the following steps: comparing historical vibration data A and a vibration standard value B of each measuring point of the auxiliary machine of the power plant with real-time vibration data C to obtain a comparison result; if the comparison result is: and (5) sending a fault alarm prompt when the real-time vibration data C is larger than the vibration standard value B. The system comprises: the comparison module is used for comparing historical vibration data A and a vibration standard value B of each measuring point of the auxiliary machine of the power plant with real-time vibration data C to obtain a comparison result; and the early warning module is used for sending a fault alarm prompt when the comparison result shows that the real-time vibration data C is larger than the vibration standard value B, so that the purposes of early warning the vibration fault of the auxiliary machine of the power plant and quickly eliminating the vibration fault of the auxiliary machine can be achieved, and the safe and stable operation of the auxiliary machine system of the power plant is ensured. However, the vibration standard value is relatively fixed, and is not integrated with equipment maintenance information, and the different damage degrees of different fault types to the equipment are not considered.
Disclosure of Invention
The invention aims to provide a method for early warning the running state of a rotary auxiliary machine cluster of a thermal power plant, which has the characteristics of uniform coding of equipment fault information, uniform measuring point positions, remote similar equipment clusters, targeted early warning according to fault types and the like and has better applicability.
In order to achieve the purpose, the invention adopts the following technical scheme:
a thermal power plant rotary auxiliary machine cluster operation state early warning method comprises the following steps: s1, coding the equipment, the components and the faults respectively;
s2, determining the measuring points of the equipment, wherein the positions and the number of the measuring points of the similar equipment are the same;
s3, establishing a remote platform and monitoring the cluster state of the similar equipment;
s4, classifying the faults, and formulating different early warning levels according to different influences of different faults on the equipment;
s5, comparing the monitoring result of the remote platform with the early warning grade, and giving out early warning information;
in S4, the faults include rolling bearing faults and non-rolling bearing faults, the non-rolling bearing faults carry out early warning according to vibration pass frequency values and changes of the vibration pass frequency values, the rolling bearing faults carry out early warning according to frequency spectrum characteristics, and different early warnings are carried out according to different hazards of different faults to the equipment.
Preferably, the rolling bearing faults comprise inner ring faults, outer ring faults, rolling body faults and retainer faults, and the specific frequency of the faults of the inner ring faults, the outer ring faults, the rolling body faults and the retainer faults is uniquely determined according to the model of the rolling bearing; the spectral characteristics include the variation trend of the frequency and the magnitude of the characteristic frequency amplitude.
Preferably, in S4, the method for warning the non-rolling bearing fault includes: when the vibration value is greater than the standard boundary value, early warning is carried out according to the vibration pass frequency value; and when the vibration value is smaller than the standard boundary value, early warning is carried out according to the change rate of the vibration pass frequency value.
Preferably, in S1, the devices are encoded to form device codes, and the device codes of the same type of devices are the same; the equipment codes comprise part codes and fault codes, the part codes and the fault codes respectively represent the parts and the faults, and targeted early warning is achieved.
Preferably, in S2, station positioning means indicating the driving direction and the rotating direction are installed at the same position of the same kind of the apparatus.
Preferably, the equipment code comprises an equipment structure type, an operation speed, the number of parts and a part sequence; the part code includes a structural feature of the part; the fault code includes a fault signature frequency of the device code.
Preferably, the components are sequentially ordered according to the driving device, the intermediate connection device and the driven device, and the structural characteristics include structural patterns of the driving device, the intermediate link device and the driven device.
Preferably, the remote platform is integrated with an enterprise maintenance management system, and the early warning level assignment value is updated through maintenance disintegration records, so that the early warning level corresponds to the actual operation condition of the equipment.
Preferably, a rotatory auxiliary engine cluster running state early warning system of thermal power plant, the system includes:
the coding module is used for coding equipment, components and faults respectively;
the measuring point module is used for determining measuring points of the equipment, and the positions and the number of the measuring points of the similar equipment are the same;
the monitoring module is used for establishing a remote platform and monitoring the cluster state of the similar equipment;
the classification module is used for classifying the faults and formulating different early warning levels according to different influences of different faults on the equipment;
the early warning module compares the monitoring result of the remote platform with the early warning grade and gives out early warning information;
in the classification module, the faults comprise rolling bearing faults and non-rolling bearing faults, the non-rolling bearing faults carry out early warning according to vibration pass frequency values and changes of the vibration pass frequency values, the rolling bearing faults carry out early warning according to frequency spectrum characteristics, and different early warnings are carried out according to different hazards of different faults to the equipment.
Preferably, the rolling bearing faults comprise inner ring faults, outer ring faults, rolling body faults and retainer faults, and the specific frequency of the faults of the inner ring faults, the outer ring faults, the rolling body faults and the retainer faults is uniquely determined according to the model of the rolling bearing; the spectral characteristics include the variation trend of the frequency and the magnitude of the characteristic frequency amplitude.
Compared with the prior art, the invention has the beneficial effects that:
the method for early warning the running state of the rotary auxiliary machine cluster of the thermal power plant has the following advantages and effects: 1. Fault diagnosis knowledge of equipment, components, structural characteristics and the like is uniformly coded, so that double consideration of test data and structural characteristics of the equipment is realized, and early warning information is more comprehensive; 2. The data source is standardized, and the measuring points of the same type of equipment are in the same position, so that the test data of the same type of equipment has comparability; 3. The cluster early warning of the similar equipment is realized through a remote platform, and the cluster early warning is integrated with a power plant maintenance management system, so that the fault sample of the similar equipment is quickly obtained, and the early warning level corresponds to the actual state of the equipment; 4. After the equipment diagnosis knowledge, the data source are unified and the fault sample is rapidly obtained, the pertinence early warning is carried out according to different damage degrees of different faults to the equipment, so that the accuracy of the early warning is improved.
Drawings
Fig. 1 is a flowchart of an early warning method for an operating state of a rotating auxiliary machine cluster of a thermal power plant according to an embodiment of the present invention.
Detailed Description
The present invention will now be described in more detail with reference to the accompanying drawings, in which the description of the invention is given by way of illustration and not of limitation. The various embodiments may be combined with each other to form other embodiments not shown in the following description.
The important rotary auxiliary engine of thermal power plant mainly includes: the method comprises the steps of an induced draft fan, a blower, a primary fan, a water feeding pump, a condensate pump and a circulating water pump, and other rotary auxiliary machines can also be used for early warning after diagnosis knowledge is uniformly expressed.
As shown in fig. 1, the method for early warning the operating state of the rotary auxiliary cluster of the thermal power plant disclosed by the invention comprises five steps:
s1, the device, the component, and the failure are encoded.
The knowledge representation is descriptive or otherwise conventional of the contents of concepts, events, data, signals, and processes, as represented in a structured or formal manner to form a computer-recognizable data structure.
The remote system must know the structure of the device to correctly apply the pre-warning rules. The object-oriented method is selected to express the diagnosis knowledge, so that the difficulty in realizing a huge knowledge base system can be reduced, and the universality and the normalization of system management are improved. According to the Fault diagnosis knowledge and the characteristics of the object-oriented representation method, the device Code (Machine ID), the Part Code (Part Code) and the Fault Code (Fault Code) are adopted to carry out unified data representation on the Fault diagnosis knowledge.
The device code (MID) is used for knowing a knowledge base of the device structure, each group of similar devices has one MID, and the MID contains the following device information:
(1) the speed of operation of the device and the speed of other transport devices.
(2) The number of components, the order of the components and the individual component attributes, e.g., motor, flexible coupling, fan, etc.
(3) Component characteristics, e.g., pump and fan type: centrifugal, axial, rotary, etc.; bearing type: cylindrical roller bearings, deep groove ball bearings, angular contact ball bearings, and the like.
(4) Rotating part detail information: the number of fan blades, the number of pump impellers, etc.
(5) Vibration sensor orientation, i.e. on which bearing the sensor is mounted, rotor rotation direction, etc.
The Part Code (Part Code) defines the exact structure of each Part in the device group, for example: whether the motor is direct current or alternating current, whether the motor is a rolling bearing or a sliding bearing; the shaft of the fan is double-supported or cantilever, and the pump has one or more measuring points.
Fault Code (Fault Code): each MID has a "finite number" of disturbance frequencies, the number of the disturbance frequencies depends on each element constituting the device rotor, such as the number of pump blades, the number of fan rotor blades, the number of motors, the number of motor rotors, and the like, and common fault codes of important rotary auxiliary machines of the thermal power plant are shown in table 1.
TABLE 1 common Fault code Table
| Serial number | Code | Description of English | Chinese reference paraphrase |
| 1 | BSF | Ball spin frequency | Rolling body |
| 2 | BPI | Ball pass freqency inner race | Bearing inner ring |
| 3 | BPO | Ball pass freqency outer race | Bearing outer ring |
| 4 | FTF | Fundamental train freqency | Bearing retainer |
| 5 | CG | Coupling elements | Coupling part |
| 6 | FB | Fan rotor blades | Number of blades of fan rotor |
| 7 | FV | Fan stator vanes | Number of static blades of fan |
| 8 | MB | Motor rotor bars | Number of motor rotors |
| 9 | MFB | Motor fan blades | Number of blades of motor fan |
| 10 | PB | Pump rotor blades | Number of moving vanes of pump rotor |
| 11 | PV | Pump rotor vanes | Number of pump rotor blades |
| 12 | X | Shaft | Shaft |
| 13 | XF | Fan shaft | Fan frequency conversion |
| 14 | XM | Motor shaft | Frequency conversion of motor |
| 15 | XN | Spindle shaft | Spindle frequency conversion |
| 16 | XP | Pump shaft | Frequency conversion of pump shaft |
| 17 | XR | Idler shaft | Speed of rotation of driven shaft |
The knowledge representation is carried out by using an object-oriented method, so that large-scale coding of a knowledge body is avoided, writing and modification of knowledge are limited in an object, the hierarchical division of multidisciplinary professional knowledge can be realized, a corresponding detection technology is determined according to the characteristics of equipment, and early-stage preparation work is carried out.
And S2, determining the measuring points of the equipment, wherein the positions and the number of the measuring points of the same kind of equipment are the same.
For the important rotary auxiliary machine of the thermal power plant, even if the equipment is in the same running state, the difference of measured values can be larger due to the difference of the positions of the measured points, in order to enhance the comparability of test data and improve the accuracy of early warning, the important rotary auxiliary machine of the thermal power plant generally adopts a three-way sensor, the sensor marks the driving direction and the rotating direction, the pasting surface of the sensor is completely attached to the measured point position of the equipment, and the mounting position of the measured point is determined according to the principle that the transmission path is shortest and the rigidity along the path is the greatest. For horizontally-mounted equipment, the measuring point positioning device is mounted at a position which is 10 degrees lower than the horizontal direction of the bearing seat, and preferably the first channel is in the horizontal direction; for the equipment which is vertically installed, the measuring point positioning device is installed on the axial end face of the bearing seat.
The number of the measuring points is determined according to the '800 mm criterion', namely when the bearing span on the same shaft is larger than 800mm, two measuring point positioning devices are installed; when the bearing span is less than 800mm, a measuring point positioning device is installed. No matter the equipment is horizontally or vertically installed, a measuring point is arranged at the position of the thrust bearing, and a measuring point positioning device is installed.
On the premise of following the principle, the same installation positions and quantity of the measuring points of the same type of equipment are ensured, so that the comparability of the measurement historical data of the same type of equipment is improved.
And S3, establishing a remote platform and monitoring the cluster state of the similar equipment.
By establishing the remote platform, the centralized monitoring of the similar equipment running in different regions is realized, and the remote platform is effectively integrated with the maintenance management system of the thermal power plant, so that the comparison and update of the early warning grade value and the maintenance disintegration condition of the equipment are realized. The method comprises the steps that state early warning thresholds are defined according to operation parameters, fault symptoms and fault mode levels of each type of equipment, when equipment monitoring data exceed the thresholds, the equipment automatically gives an alarm, the early warning is updated through overhaul disassembly records, and when the damage degree of the disassembled equipment is larger than the early warning level, the early warning threshold is reduced; when the damage degree of the disassembled equipment is smaller than the early warning level, increasing an early warning threshold value; so that the early warning level corresponds to the actual operation condition of the equipment.
For example: the running vibration values of 223 condensate pumps distributed in each power plant under the same boundary condition are obtained through the remote platform, the average vibration value running below the alarm value can be used as a reference value of normal early warning level, the vibration value is larger than the alarm value, the initial value of the alarm value and the initial value of the crisis value are determined according to the damage degree of the repaired equipment, and therefore the initial value determination of the early warning level is completed through a large number of similar equipment. And then, acquiring the damage state of the equipment after each disassembly and maintenance from a maintenance management system of the thermal power plant, comparing the damage state with the early warning grade value, and adjusting the initial value of the early warning grade value when the early warning grade value does not accord with the damage state of the equipment, so that the early warning grade value is consistent with the actual running state of the equipment. Other similar devices may determine the warning value by the same method, which is not described herein again.
And S4, classifying the faults, and formulating different early warning levels according to different influences of different faults on the equipment.
Specifically, the same vibration value and different fault types have different damage degrees to equipment, particularly the fault of a rolling bearing of rotating equipment of a thermal power plant, because the position of the bearing far away from a measuring point is away, lubricating oil seeps out, the vibration attenuation is fast, and sometimes a small vibration value pass-frequency value can possibly cause the damage of a bearing part, therefore, the early warning is needed according to the classification of the equipment fault.
The fault of the rotary auxiliary machine of the thermal power plant is divided into a rolling bearing fault and a non-rolling bearing fault, the non-rolling bearing fault is pre-warned according to the vibration pass frequency value and the change of the vibration pass frequency value, and the rolling bearing fault is pre-warned according to the frequency spectrum characteristics, so that targeted pre-warning is performed on the difference of the equipment hazard degree according to different fault types. The rolling bearing faults are divided into inner ring faults, outer ring faults, rolling body faults and retainer faults, the specific frequency of the faults of all the parts of the rolling bearing is uniquely determined according to the type of the bearing and is non-integer frequency multiplication, and the frequency spectrum characteristics of the rolling bearing comprise the change trend of the frequency and the amplitude of the characteristic frequency. As can be seen from the above analysis, the rolling bearing failure characteristics are uniquely determined according to the model thereof, and therefore a failure without the rolling bearing failure characteristics is a non-rolling bearing failure.
For non-rolling bearing failures, the state in which the rotating equipment is located is divided into four zones, according to the standard ISO10816, where the vibrations of the newly delivered equipment generally fall; the vibration of the equipment in the area is generally considered to be capable of running for an unlimited long time; the equipment vibration is in the area, which is generally not suitable for long-time continuous operation, and the equipment can normally operate for a limited time in the state until a proper time for taking remedial measures is available; the vibration of the equipment in this area is generally considered to be of sufficient intensity to cause damage to the equipment. The standard boundary value refers to a boundary value of the region C.
The boundary value of A, B, C, D area is shown in Table 2 for large equipment with rated power more than 300 kW and less than 50MW and the height H of the rotating shaft more than or equal to 315 mm.
TABLE 2 vibration value region classification
Generally, when the equipment vibration is above the C region boundary value specified by the ISO10816 standard, an alarm is given. As shown in Table 2, for rigid support, the boundary value of the C area is 4.5 mm/s, namely for the equipment, when the vibration value is greater than or equal to 4.5 mm/s, an alarm is given, and machine selection and maintenance are recommended; for flexible supports, the boundary of the C area is 7.1mm/s, namely for the equipment, when the vibration value is greater than or equal to 7.1mm/s, an alarm is given, and machine selection and maintenance are recommended. Other types of devices the standards are also specified and are not listed here.
However, the thermal power plant often has a fault that the vibration value does not exceed the standard, that is, the vibration value does not reach the boundary value of the region C, and the equipment is damaged, and the embodiment provides an early warning method based on the variation trend of the vibration value.
When significant changes in the vibration values occur, even if the zone C boundary specified by the standard ISO10816 is not reached, measures should be taken which can be produced instantaneously or which develop gradually over time and which may indicate early damage or some other problem.
The vibration tests to be compared should be conducted at the same sensor location and orientation and under substantially the same operating conditions of the equipment. By studying the obvious change (no matter what the pass frequency vibration value is) from the normal vibration value, the dangerous condition can be avoided. These changes are preferably considered significant when they exceed 25% of the upper limit of the region B as specified by the standard ISO10816, in particular if they occur suddenly, at which point diagnostic studies should be undertaken to ascertain the cause of the change and to determine appropriate measures for the next step. It should be noted that the 25% value is merely a general guideline for significant variations in vibration magnitude, and that other values may be used empirically for a particular device.
Further, for some specific faults, when the vibration value and the variation trend of the vibration value are small, the equipment may be damaged, for example: the rolling bearing retainer characteristic frequency with a small vibration value can cause serious bearing damage faults, so the rolling bearing faults should be comprehensively considered in combination with the frequency spectrum characteristics.
For the evaluation of the detection result of the rolling bearing, the evaluation is carried out according to the frequency spectrum characteristics, and the fault development of the rolling bearing can be divided into four stages: an initial stage, a second stage, a third stage, and a fourth stage. The corresponding fault degrees are respectively slight, moderate, severe and critical, the characteristics of each stage are different, and the fault severity degrees are different.
In the initial stage (slight) of the fault of the rolling bearing, the vibration amplitude is small, noise is generated, the demodulation waveform can show very short impact, and the frequency range is 5kHz-40 kHz; the second stage (moderate) of the rolling bearing fault, friction and smaller impact, the envelope demodulation frequency spectrum can show the characteristic frequency of the fault, and the frequency range is 1kHz-5 kHz; in the third stage (serious) of the fault of the rolling bearing, the ultrahigh frequency amplitude is continuously increased, harmonic waves generated by impact and side frequency components formed by load periodic variation modulation appear, and the characteristic frequency of the fault of the bearing is seen to have a peak value; in the fourth stage (emergency) of the rolling bearing fault, the ultrahigh frequency amplitude is reduced, the periodic vibration is reduced, the background noise is obviously increased, a hay pile is formed and continues to develop, the characteristic frequency of the hay pile disappears completely, and the frequency spectrum is more like a rotary loosening mode.
And S5, comparing the monitoring result of the remote platform with the early warning grade, and giving out early warning information.
Specifically, for the non-rolling bearing fault, the test result is compared with the early warning level of the running state of the equipment in the step S4, and the early warning level is determined. For a non-rolling bearing fault, when the vibration value of the equipment is below the limit in the area C and the vibration value is not more than 25% or the vibration value is less than the limit in the area B, the early warning level is normal; when the vibration value of the equipment is above the upper limit value of the area C or the vibration value exceeds the upper limit value of the area B and the change exceeds 25%, the early warning grade is alarm; and when the vibration value of the equipment is in the D area and above, the early warning level is crisis.
For the rolling bearing fault, when the frequency spectrum characteristic is in the initial stage and within, the early warning level is normal; when the frequency spectrum characteristic is in the second stage, the early warning level is warning; when the spectrum features are at the third stage and above, the early warning level is crisis.
In addition, it should be noted that the threshold or the characteristic corresponding to the early warning level is dynamically changed, the established remote platform is effectively integrated with the thermal power plant maintenance management system through S3, the original early warning value or characteristic is compared with the condition after the equipment is overhauled and disassembled, and when the early warning level does not match the condition of the equipment damage, the early warning threshold is updated, so that the early warning level corresponds to the actual operation condition of the equipment.
The invention also provides a system for early warning the running state of the rotary auxiliary machine cluster in the thermal power plant, which comprises the following components:
the coding module is used for coding equipment, components and faults respectively;
the measuring point module is used for determining measuring points of the equipment, and the positions and the number of the measuring points of the similar equipment are the same;
the monitoring module is used for establishing a remote platform and monitoring the cluster state of the similar equipment;
the classification module is used for classifying the faults and formulating different early warning levels according to different influences of different faults on the equipment;
the early warning module compares the monitoring result of the remote platform with the early warning grade and gives out early warning information;
in the classification module, the faults comprise rolling bearing faults and non-rolling bearing faults, the non-rolling bearing faults carry out early warning according to vibration pass frequency values and changes of the vibration pass frequency values, the rolling bearing faults carry out early warning according to frequency spectrum characteristics, and different early warnings are carried out according to different hazards of different faults to the equipment.
The rolling bearing faults comprise inner ring faults, outer ring faults, rolling body faults and retainer faults, and the specific frequency of the faults of the inner ring faults, the outer ring faults, the rolling body faults and the retainer faults is uniquely determined according to the model of the rolling bearing; the spectral characteristics include the variation trend of the frequency and the magnitude of the characteristic frequency amplitude.
The above embodiments are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby, and any insubstantial changes and substitutions made by those skilled in the art based on the present invention are within the protection scope of the present invention.
Claims (10)
1. A method for early warning of the operation state of a rotary auxiliary engine cluster of a thermal power plant is characterized by comprising the following steps:
s1, coding the equipment, the components and the faults respectively;
s2, determining the measuring points of the equipment, wherein the positions and the number of the measuring points of the similar equipment are the same;
s3, establishing a remote platform and monitoring the cluster state of the similar equipment;
s4, classifying the faults, and formulating different early warning levels according to different influences of different faults on the equipment;
s5, comparing the monitoring result of the remote platform with the early warning grade, and giving out early warning information;
in S4, the faults include rolling bearing faults and non-rolling bearing faults, the non-rolling bearing faults carry out early warning according to vibration pass frequency values and changes of the vibration pass frequency values, the rolling bearing faults carry out early warning according to frequency spectrum characteristics, and different early warnings are carried out according to different hazards of different faults to the equipment.
2. The thermal power plant rotary auxiliary machine cluster operation state early warning method as claimed in claim 1, wherein the rolling bearing faults include an inner ring fault, an outer ring fault, a rolling element fault and a cage fault, and the fault specific frequencies of the inner ring fault, the outer ring fault, the rolling element fault and the cage fault are uniquely determined according to the model of the rolling bearing; the spectral characteristics include the variation trend of the frequency and the magnitude of the characteristic frequency amplitude.
3. The method for early warning of the operating state of the rotary auxiliary machine cluster in the thermal power plant as claimed in claim 1, wherein in S4, the method for early warning of the fault of the non-rolling bearing is as follows: when the vibration value is greater than the standard boundary value, early warning is carried out according to the vibration pass frequency value; and when the vibration value is smaller than the standard boundary value, early warning is carried out according to the change rate of the vibration pass frequency value.
4. The method for early warning of the operating state of the thermal power plant rotary auxiliary machine cluster as claimed in claim 1, wherein in S1, the devices are encoded to form device codes, and the device codes of the devices of the same type are the same; the equipment codes comprise part codes and fault codes, the part codes and the fault codes respectively represent the parts and the faults, and targeted early warning is achieved.
5. The method for early warning of the operating state of the rotary auxiliary machine cluster in the thermal power plant as claimed in claim 1, wherein in S2, measuring point positioning devices are installed at the same positions of the similar devices, and the measuring point positioning devices indicate the driving direction and the rotating direction.
6. The thermal power plant rotary auxiliary machine cluster operation state early warning method as claimed in claim 4, wherein the device code includes a device configuration type, an operation speed, a number of components, and a component order; the part code includes a structural feature of the part; the fault code includes a fault signature frequency of the device code.
7. The thermal power plant rotary auxiliary machine cluster operation state early warning method as claimed in claim 6, wherein the components are sequentially ordered according to driving devices, intermediate connection devices and driven devices, and the structural characteristics include structural types of the driving devices, the intermediate connection devices and the driven devices.
8. The thermal power plant rotary auxiliary machine cluster operation state early warning method as claimed in claim 1, wherein the remote platform is integrated with an enterprise overhaul management system, and the early warning level assignment is updated through overhaul disassembly records so that the early warning level corresponds to an actual operation condition of the equipment.
9. The utility model provides a rotatory auxiliary engine cluster running state early warning system of thermal power plant, its characterized in that, the system includes:
the coding module is used for coding equipment, components and faults respectively;
the measuring point module is used for determining measuring points of the equipment, and the positions and the number of the measuring points of the similar equipment are the same;
the monitoring module is used for establishing a remote platform and monitoring the cluster state of the similar equipment;
the classification module is used for classifying the faults and formulating different early warning levels according to different influences of different faults on the equipment;
the early warning module compares the monitoring result of the remote platform with the early warning grade and gives out early warning information;
in the classification module, the faults comprise rolling bearing faults and non-rolling bearing faults, the non-rolling bearing faults carry out early warning according to vibration pass frequency values and changes of the vibration pass frequency values, the rolling bearing faults carry out early warning according to frequency spectrum characteristics, and different early warnings are carried out according to different hazards of different faults to the equipment.
10. The thermal power plant rotary auxiliary machine cluster operation state early warning system according to claim 9, wherein the rolling bearing faults include an inner ring fault, an outer ring fault, a rolling element fault and a cage fault, and the fault specific frequencies of the inner ring fault, the outer ring fault, the rolling element fault and the cage fault are uniquely determined according to the model of the rolling bearing; the spectral characteristics include the variation trend of the frequency and the magnitude of the characteristic frequency amplitude.
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