CN102213116B - Device and method for monitoring and controlling security risk of turbine bearing in on-line manner - Google Patents

Abstract

The invention relates to a device and method for monitoring and controlling the security risk of a turbine bearing in an on-line manner. The method comprises steps of: calculating a fault probability FPi of the turbine bearing; on-line monitoring a rotor vibration signal, a rotor axial displacement signal of the turbine, a bearing bush metal temperature signal and a bearing oil back signal as well as a bearing lubricating oil pressure signal of the turbine; calculating a mean time to repair MTTRi of the bearing, determining a weight coefficient Wi of bearing fault result; calculating a risk priority number RPNi of the turbine bearing; evaluating the turbine bearing security rank; determining the max risk priority number RPNmax of the turbine bearing; and recommending risk control measures of the turbine bearing. The invention provides the on-line monitoring and control method of the security risk of the turbine bearing, and realizes the on-line calculation and control of the security risk of the turbine bearing.

Description

Steam turbine bearing security risk in-service monitoring and control device and method

Technical field

The present invention relates to steam turbine bearing security risk in-service monitoring and control device and method, belong to steam turbine technology field.

Background technology

Steam turbine bearing has transverse bearing and thrust bearing two class, and bearing is used for bearing the weight of rotor and determines rotor tram in the cylinder.Transverse bearing is used for bearing the out-of-balance force of rotor weight and rotation and determines the radial position of rotor, thus ensures radial play correct between the stationary parts such as rotor and cylinder, packing, dividing plate or stator blade.Thrust bearing bears vapor action in epitrochanterian axial thrust, and determines the axial location of rotor, to ensure end play correct between flow passage component sound.The fault mode that bearing generation bearing shell scaling loss, bearing bush abrasion, bearing leakage of oil and bearing bush temperature are higher, consequence is serious.The security risk of steam turbine bearing is relevant with bearing fault consequence with bearing likelihood of failure; Steam turbine bearing likelihood of failure is relevant with fault characteristic signals with probability of malfunction, the failure effect of steam turbine bearing with repair time length and fault harm relevant.Existing steam turbine protection system in heat power engineering, has the online defencive function of rotor oscillation, rotor axial displacement, bearing shell metal temperature, bearing return oil temperature and bearing lubrication oil pressure, does not also have in-service monitoring and the controlling functions of steam turbine bearing security risk.

Summary of the invention

The object of this invention is to provide steam turbine bearing security risk in-service monitoring and control device and method, realize in-service monitoring and the control of steam turbine bearing security risk.

In order to realize above object, the invention provides a kind of security risk in-service monitoring and control method of steam turbine bearing, use a kind of in-service monitoring and control device of steam turbine bearing security risk, the in-service monitoring of described steam turbine bearing security risk and control device involving vibrations sensor, shaft position sensor, bearing shell metallic temperature sensor, bearing return oil temperature sensor and bearing oil pressure transducer, the thrust bearing of High inter case speed regulator side is provided with a shaft position sensor, a bearing shell metallic temperature sensor and a bearing return oil temperature sensor, the transverse bearing of High inter case speed regulator side, the transverse bearing of High inter case generator side, the transverse bearing of low pressure rotor speed regulator side and the transverse bearing of low pressure rotor generator side are respectively provided with two vibration transducers, a bearing shell metallic temperature sensor, a bearing return oil temperature sensor and a bearing oil pressure transducer, vibration transducer, shaft position sensor, bearing shell metallic temperature sensor, bearing return oil temperature sensor and bearing oil pressure transducer are all connected with steam turbine protection system in heat power engineering interface, steam turbine protection system in heat power engineering interface connects calculation server, calculation server connects web page server, web page server connects user side browser, it is characterized in that, C language is adopted to write the software for calculation of steam turbine bearing security risk, operate on calculation server, be applied to steam turbine bearing security risk in-service monitoring and control, its concrete steps are:

The first step: the probability of malfunction F calculating steam turbine bearing _pi: using computer software, there is the probability F of i-th kind of fault mode in the transverse bearing respectively in line computation High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides _pi

In formula, n _ifor the number of times of i-th kind of fault mode has occurred this TV station steam turbine each bearing, i=1, the 2,3 or 4,1st kind of fault mode is bearing shell scaling loss, and the 2nd kind of fault mode is bearing bush abrasion, and the 3rd kind of fault mode is bearing leakage of oil, and the 4th kind of fault mode is that bearing bush temperature is higher, n _0ifor in software data file, the historical data statistical value of the total degree of i-th kind of fault mode occurs existing same model steam turbine corresponding bearing, t _ifor this TV station steam turbine is from putting into operation to current calendar hourage, t _0ifor the statistical value of the historical data of total calendar hourage of same model steam turbine use existing in software data file;

Second step: in-service monitoring Vibration Signal of Steam Turbine Rotor: adopt vibration transducer, in-service monitoring turbine rotor vibration double-amplitude, according to the size of rotor oscillation double-amplitude supervision value, define the 1st FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₁represent at table 1;

Table 1:

3rd step: in-service monitoring rotor axial displacement signal: adopt rotor axial displacement sensor, the axial displacement of in-service monitoring turbine rotor, according to the size of turbine rotor axial displacement supervision value, define the 2nd FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₂represent at table 2;

Table 2:

4th step: in-service monitoring turbine bearing pad metal temperature signal: adopt bearing shell metallic temperature sensor, in-service monitoring turbine bearing pad metal temperature, according to the size of turbine bearing pad metal temperature supervision value, define the 3rd FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₃represent at table 3;

Table 3:

5th step: in-service monitoring bearing return oil temperature signal: adopt bearing return oil temperature sensor, in-service monitoring steam turbine bearing returning-oil temperature, according to the size of steam turbine bearing returning-oil temperature supervision value, define the 4th FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₄represent at table 4;

Table 4:

6th step: in-service monitoring bearing oil pressure signal: adopt bearing oil pressure transducer (5), in-service monitoring steam turbine bearing lubrication oil pressure, according to the size of steam turbine bearing lubrication oil pressure monitoring value, define the 5th FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₅represent at table 5;

Table 5:

7th step: the mean time to overhaul MTTR of calculation bearing _i: using existing historical data in computer software, there is the mean time to overhaul MTTR of i-th kind of fault mode in the transverse bearing respectively in line computation High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides _i

In formula, τ _0ifor total unplanned outage time of the steam turbine that fault mode causes in i-th occurs the corresponding bearing of software data file existing same model steam turbine;

8th step: the weight coefficient W determining bearing fault consequence _i: there is the weight coefficient W of the failure effect of following four kinds of fault modes in definition steam turbine bearing _irepresent at table 6;

Table 6:

9th step: the security risk sequence number RPN calculating steam turbine bearing _i: use software for calculation, calculate the security risk sequence number RPN that i-th kind of fault mode occurs for the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides respectively _i

RPN _i=F _Pi×P ₁×P ₂×P ₃×P ₄×P ₅×MTTR _i×W _i

Tenth step: evaluation steam turbine bearing security risk grade: according to the RPN of steam turbine bearing security risk sequence number _isize, is divided into 5 grades the security risk of steam turbine bearing respectively, represents table 7;

Table 7:

11 step: the maximum security risk sequence number RPN determining steam turbine bearing _max: adopt following formula, calculate the maximum security risk sequence number RPN in the security risk sequence number of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides _max

RPN _max=max{RPN _i}

12 step: recommend the risk control measure of steam turbine bearing: according to the maximum security risk sequence number RPN of steam turbine bearing _maxcalculated value, recommend following risk control measure countermeasure:

(1) if RPN _max<8, has Pyatyi risk, slight risk, acceptable risk, advises that the maintenance interval specified by " electricity power enterprise's overhaul of the equipments directive/guide " (DL/T838) overhauls (plan light maintenance) with maintenance content arrangement C level, checks comprehensively;

(2) if 8≤RPN _max<24, has level Four risk, ordinary risk, acceptable risk, and suggestion arranges in C level maintenance (plan light maintenance) within this month, checks comprehensively;

(3) if 24≤RPN _max<72, has tertiary risk, important risk, unacceptable risk, advises arranging ad hoc inspection and repair within this week, checks comprehensively;

(4) if 72≤RPN _max168, there is secondary risk, serious risk, unacceptable risk, advise arranging ad hoc inspection and repair in three days, check comprehensively;

(5) if RPN _max>=168, have primary risk, material risk, unacceptable risk, suggestion hard stop arranges ad hoc inspection and repair, checks comprehensively.

Preferably, the angle between described vibration transducer and surface level is 45 °.

Advantage of the present invention is the in-service monitoring and the control device that give steam turbine bearing security risk, achieves the online calculation and control of steam turbine bearing security risk.If when steam turbine bearing security risk sequence number increases, the security risk of steam turbine bearing is made to be in slave mode by reasonably arranging ad hoc inspection and repair or the maintenance of C level.

Accompanying drawing explanation

Fig. 1 is the block scheme of steam turbine bearing security risk in-service monitoring of the present invention and control device;

Fig. 2 is the process flow diagram of steam turbine bearing security risk in-service monitoring of the present invention and control method;

Fig. 3 is the computer software block diagram that calculation server of the present invention adopts;

Fig. 4 is the schematic diagram of steam turbine bearing security risk sequence number result of calculation.

Embodiment

The present invention is illustrated below in conjunction with embodiment.

Embodiment

As shown in Figure 1, the block scheme of steam turbine bearing security risk in-service monitoring of the present invention and control method, steam turbine bearing security risk in-service monitoring of the present invention and control device are by vibration transducer 1, shaft position sensor 2, bearing shell metallic temperature sensor 3, bearing return oil temperature sensor 4, bearing oil pressure transducer 5, steam turbine protection system in heat power engineering interface, calculation server, web page server and user side browser composition, the thrust bearing of High inter case speed regulator side is provided with a shaft position sensor 2, a bearing shell metallic temperature sensor 3 and a bearing return oil temperature sensor 4, the transverse bearing of High inter case speed regulator side, the transverse bearing of High inter case generator side, the transverse bearing of low pressure rotor speed regulator side and the transverse bearing of low pressure rotor generator side are respectively provided with two with the vibration transducer 1 of the mutual installation at 45 ° of surface level, a bearing shell metallic temperature sensor 3, a bearing return oil temperature sensor 4 and a bearing oil pressure transducer 5, vibration transducer 1, shaft position sensor 2, bearing shell metallic temperature sensor 3, bearing return oil temperature sensor 4 and bearing oil pressure transducer 5 are all connected with steam turbine protection system in heat power engineering interface, steam turbine protection system in heat power engineering interface connects calculation server, calculation server connects web page server, and web page server connects user side browser.

As shown in Figure 2, the process flow diagram of steam turbine bearing security risk in-service monitoring and control method, as shown in Figure 3, the computer software block diagram that calculation server of the present invention adopts, this software be arranged on steam turbine bearing security risk sequence number calculation server on, be applied to steam turbine bearing security risk in line computation and control.

For the subcritical 300MW steam turbine that certain model throttle (steam) temperature is 538 DEG C, HP-IP combined casing, also has a low pressure (LP) cylinder, this 300MW steam turbine is provided with 1 thrust bearing and 4 transverse bearings, thrust bearing is arranged in the bearing seat of High inter case high pressure exhaust steam end, No. 1 transverse bearing is arranged on High inter case speed regulator side, No. 2 transverse bearings are arranged on High inter case generator side, No. 3 transverse bearings are arranged on low pressure rotor speed regulator side, and No. 4 transverse bearings are arranged on low pressure rotor generating project side.The alarming value of bear vibration double-amplitude is for being greater than 0.125mm, the alarming value of rotor axial displacement is for being less than 1.64mm or being greater than 3.44mm, the alarming value of thrust bearing bearing shell metal temperature is 99 DEG C, the alarming value of transverse bearing bearing shell metal temperature is 107 DEG C, the alarming value of thrust bearing and transverse bearing returning-oil temperature is 77 DEG C, and the alarming value of bearing lubrication oil pressure is 0.082MPa.The thrust bearing of this 300MW steam turbine and transverse bearing adopt the computer software shown in the process flow diagram shown in the device shown in Fig. 1, Fig. 2 and Fig. 3, and Fig. 4 is the schematic diagram of this 300MW steam turbine bearing security risk result of calculation at a time.The supervisory and control result of the thrust bearing of this 300MW steam turbine and transverse bearing security risk is at a time as follows:

The first step: Steam Turbine Thrust Bearing and transverse bearing probability of malfunction F _pionline result of calculation list in table 8;

[table 8]

Second step and the 3rd step: use computer software, the FACTOR P being worth going out by 300MW steam turbine bearing vibration signal in-service monitoring ₁the FACTOR P being worth going out is monitored with rotor axial displacement ₂calculated value list in table 9;

Table 9:

4th step and the 5th step: the FACTOR P being worth going out by 300MW turbine bearing pad metal temperature in-service monitoring ₃with the FACTOR P being worth going out by 300MW steam turbine bearing returning-oil temperature in-service monitoring ₄calculated value list in table 10;

Table 10:

6th step: the FACTOR P being worth going out by 300MW steam turbine bearing lubrication oil pressure in-service monitoring ₅calculated value list in table 11;

Table 11:

7th step: the mean time to overhaul MTTR of 300MW Steam Turbine Thrust Bearing and transverse bearing _ithe result of calculation of historical data list in table 12;

Table 12:

8th step: the weight coefficient W of the failure effect of 300MW Steam Turbine Thrust Bearing and transverse bearing _ivalue list in table 13;

Table 13:

9th step and the tenth step: this 300MW steam turbine bearing security risk sequence number RPN _icalculated value and the evaluation result of risk class list in table 14;

Table 14:

11 step and the 12 step: this 300MW steam turbine bearing is RPN in the maximal value of the security risk sequence number in this moment _max=79.34>72, has secondary risk, serious risk, and fault mode is No. 4 transverse bearing bearing shell scaling loss, and the security risk control measure of recommendation are arrange ad hoc inspection and repair in three days, check No. 4 transverse bearings comprehensively.

Adopt in-service monitoring and the control device of steam turbine bearing security risk provided by the invention, achieve the online security risk sequence number quantitatively calculating 300MW steam turbine bearing, maximum security risk sequence number according to steam turbine bearing arranges ad hoc inspection and repair or the maintenance of C level, makes the security risk of this 300MW steam turbine bearing be in slave mode.

Claims (2)

1. the security risk in-service monitoring of a steam turbine bearing and control method, use a kind of in-service monitoring and control device of steam turbine bearing security risk, the in-service monitoring of described steam turbine bearing security risk and control device involving vibrations sensor (1), shaft position sensor (2), bearing shell metallic temperature sensor (3), bearing return oil temperature sensor (4) and bearing oil pressure transducer (5), the thrust bearing of High inter case speed regulator side is provided with a shaft position sensor (2), a bearing shell metallic temperature sensor (3) and a bearing return oil temperature sensor (4), the transverse bearing of High inter case speed regulator side, the transverse bearing of High inter case generator side, the transverse bearing of low pressure rotor speed regulator side and the transverse bearing of low pressure rotor generator side are respectively provided with two vibration transducers (1), a bearing shell metallic temperature sensor (3), a bearing return oil temperature sensor (4) and a bearing oil pressure transducer (5), vibration transducer (1), shaft position sensor (2), bearing shell metallic temperature sensor (3), bearing return oil temperature sensor (4) is all connected with steam turbine protection system in heat power engineering interface with bearing oil pressure transducer (5), steam turbine protection system in heat power engineering interface connects calculation server, calculation server connects web page server, web page server connects user side browser, it is characterized in that, C language is adopted to write the software for calculation of steam turbine bearing security risk, operate on calculation server, be applied to steam turbine bearing security risk in-service monitoring and control, its concrete steps are:

The first step: the probability of malfunction F calculating steam turbine bearing _pi: using computer software, there is the probability F of i-th kind of fault mode in the transverse bearing respectively in line computation High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides _pi

$F_{\mathrm{Pi}}=\frac{8760(n_i+n_{0i})}{(t_i+t_{0i})}$

In formula, n _ifor the number of times of i-th kind of fault mode has occurred this TV station steam turbine each bearing, i=1, the 2,3 or 4,1st kind of fault mode is bearing shell scaling loss, and the 2nd kind of fault mode is bearing bush abrasion, and the 3rd kind of fault mode is bearing leakage of oil, and the 4th kind of fault mode is that bearing bush temperature is higher, n _0ifor in software data file, the historical data statistical value of the total degree of i-th kind of fault mode occurs existing same model steam turbine corresponding bearing, t _ifor this TV station steam turbine is from putting into operation to current calendar hourage, t _0ifor the statistical value of the historical data of total calendar hourage of same model steam turbine use existing in software data file;

Second step: in-service monitoring Vibration Signal of Steam Turbine Rotor: adopt vibration transducer (1), in-service monitoring turbine rotor vibration double-amplitude, according to the size of rotor oscillation double-amplitude supervision value, define the 1st FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₁represent at table 1;

Table 1:

3rd step: in-service monitoring rotor axial displacement signal: adopt rotor axial displacement sensor (2), the axial displacement of in-service monitoring turbine rotor, according to the size of turbine rotor axial displacement supervision value, define the 2nd FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₂represent at table 2;

Table 2:

4th step: in-service monitoring turbine bearing pad metal temperature signal: adopt bearing shell metallic temperature sensor (3), in-service monitoring turbine bearing pad metal temperature, according to the size of turbine bearing pad metal temperature supervision value, define the 3rd FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₃represent at table 3;

Table 3:

5th step: in-service monitoring bearing return oil temperature signal: adopt bearing return oil temperature sensor (4), in-service monitoring steam turbine bearing returning-oil temperature, according to the size of steam turbine bearing returning-oil temperature supervision value, define the 4th FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₄represent at table 4;

Table 4:

6th step: in-service monitoring bearing oil pressure signal: adopt bearing oil pressure transducer (5), in-service monitoring steam turbine bearing lubrication oil pressure, according to the size of steam turbine bearing lubrication oil pressure monitoring value, define the 5th FACTOR P of transverse bearing fault possibility occurrence of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and low pressure rotor both sides respectively ₅represent at table 5;

Table 5:

7th step: the mean time to overhaul MTTR of calculation bearing _i: using existing historical data in computer software, there is the mean time to overhaul MTTR of i-th kind of fault mode in the transverse bearing respectively in line computation High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides _i

${\mathrm{MTTR}}_i=\frac{{\mathrm{\&tau;}}_{0i}}{n_{0i}}$

In formula, τ _0ifor total unplanned outage time of the steam turbine that fault mode causes in i-th occurs the corresponding bearing of software data file existing same model steam turbine;

8th step: the weight coefficient W determining bearing fault consequence _i: there is the weight coefficient W of the failure effect of following four kinds of fault modes in definition steam turbine bearing _irepresent at table 6;

Table 6:

Fault mode W _i Bearing shell scaling loss 4 Bearing bush abrasion 3

Bearing leakage of oil 2 Bearing bush temperature is higher 1

9th step: the security risk sequence number RPN calculating steam turbine bearing _i: use software for calculation, calculate the security risk sequence number RPN that i-th kind of fault mode occurs for the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides respectively _i

RPN _i=F _Pi×P ₁×P ₂×P ₃×P ₄×P ₅×MTTR _i×W _i

Tenth step: evaluation steam turbine bearing security risk grade: according to the RPNi size of steam turbine bearing security risk sequence number, respectively the security risk of steam turbine bearing is divided into 5 grades, represents table 7;

Table 7:

11 step: the maximum security risk sequence number RPN determining steam turbine bearing _max: adopt following formula, calculate the maximum security risk sequence number RPN in the security risk sequence number of the transverse bearing of High inter case both sides, the thrust bearing of High inter case speed regulator side and the transverse bearing of low pressure rotor both sides _max

RPN _max=max{RPN _i}

12 step: recommend the risk control measure of steam turbine bearing: according to the maximum security risk sequence number RPN of steam turbine bearing _maxcalculated value, recommend following risk control measure countermeasure:

(1) if RPN _max<8, has Pyatyi risk, slight risk, acceptable risk, advises that the maintenance interval specified by " electricity power enterprise's overhaul of the equipments directive/guide " overhauls with maintenance content arrangement C level, checks comprehensively;

(2) if 8≤RPN _max<24, has level Four risk, ordinary risk, acceptable risk, and suggestion arranges, in the maintenance of C level, to check within this month comprehensively;

(3) if 24≤RPN _max<72, has tertiary risk, important risk, unacceptable risk, advises arranging ad hoc inspection and repair within this week, checks comprehensively;

(4) if 72≤RPN _max<168, has secondary risk, serious risk, unacceptable risk, advises arranging ad hoc inspection and repair in three days, checks comprehensively;

(5) if RPN _max>=168, have primary risk, material risk, unacceptable risk, suggestion hard stop arranges ad hoc inspection and repair, checks comprehensively.

2. the security risk in-service monitoring of steam turbine bearing as claimed in claim 1 and control method, it is characterized in that, the angle between described vibration transducer (1) and surface level is 45 °.