CN113205248A - Regulating valve fault early warning system and method based on big data medium parameter diagnosis - Google Patents
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Abstract
A fault early warning system and method for a regulating valve based on big data medium parameter diagnosis are disclosed, step 1, according to the fluid mechanics characteristics of a flowing medium, a contrast area in direct proportion to the valve flow area is obtained through medium density, medium flow and front and back differential pressure of the valve, step 2, historical big data information of long-term normal operation parameters of the system is obtained, and the opening theta of the regulating valve is used as an X axis and A is used as an axisdThe value is Y axis, and the normal operation condition theta-A of the regulating valve is drawndA drawing; step 3, obtaining an upper boundary curve and a lower boundary curve of the normal operation working condition point of the regulating valve through fitting of a polynomial fitting method, and obtaining the upper boundary curve and the lower boundary curve at the theta-A according to the curvesdDrawing an early warning area and an alarm area on the graph; step 4, when the operating condition point is in the early warning area, the system sends out a fault early warning to remind an operator to check the state of the valve; when the operating condition point is in the alarm area, the system sends a fault alarm to remind the operator to operateAnd (4) treating the fault according to the operation condition by the staff. The invention can effectively avoid safety accidents.
Description
Technical Field
The invention relates to the technical field of safety production of thermal power plants, in particular to a fault early warning system and method for a regulating valve based on large data medium parameter diagnosis.
Background
The adjusting valve is a common and indispensable important device in a thermal power plant, and is often used for directly controlling the flow of a system working medium. In the normal operation of the unit, the adjusting valve needs to frequently act to meet the requirement of working medium flow under various working conditions. As the number of the adjusting valves of the thermal power plant is large and the actions are frequent, the fault defect of the adjusting valves in the operation process is common. If the fault cannot be found in time, parameters such as medium flow, pressure, temperature and the like controlled by the fault are very easy to be abnormal, if the fault is not found in time, the system deviates from the designed value to operate, and if the fault is not found, the unit is in a trip or even a safety accident.
At present, an operator can find part of adjusting valve faults on a DCS picture through valve instructions, feedback or fault signals and timely process the faults, such as: valve jam, communication failure, etc. However, some mechanical failure operators are difficult to find in time at the early stage of the failure of the regulating valve, such as: the valve rod is broken, the actuating mechanism falls off and the like, and the valve rod is found only when the parameters of the medium controlled by the valve rod are seriously deviated from normal values, so that the optimal time for fault treatment is often missed, and the safe operation of a unit is seriously influenced.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a fault early warning system and a fault early warning method for a regulating valve based on big data medium parameter diagnosis.
In order to achieve the purpose, the invention adopts the technical scheme that:
a fault early warning method of a regulating valve based on big data medium parameter diagnosis is disclosed, wherein the regulating valve is used as a throttling orifice plate with adjustable flow area, and the flow of a medium can be regulated by regulating the flow area according to the fluid mechanics characteristics of a flowing medium, and the early warning method comprises the following steps;
step 1, obtaining a comparison area in a direct proportion relation with a valve flow area through a medium density, a medium flow and a front-back differential pressure of the valve, wherein the comparison area corresponds to each opening of the regulating valve one by one;
step 1.1, obtaining the density of a medium:
for compressible media (such as air):
wherein: p is the medium pressure at the regulating valve and has the unit of Pa; t is the temperature of the medium at the position of the regulating valve and the unit is K; rho is the density of the medium at the position of the regulating valve and has the unit of kg/m3;P1In Pa for regulating the inlet pressure of the valve; p2In Pa for regulating the outlet pressure of the valve; t is1In order to regulate the inlet temperature of the valve, the unit is K; t is2In order to regulate the outlet temperature of the valve, the unit is K; p0、T0、ρ0The pressure, temperature and density of the medium in any determined state are known quantities;
the following can be derived from formula (1) to formula (3):
for incompressible media: according to a comparison table of the medium density along with the change of temperature and pressure, a module for calculating the medium density is compiled, and the module can directly output the medium density value after acquiring the temperature and the pressure of the medium;
step 1.2, deducing a contrast area by using medium flow and front-back differential pressure of a valve:
Qm=Qv×ρ (6)
ΔP=P2-P1 (7)
q in formula (5) -formula (7)vIs the volume flow of the medium, and has the unit of m3S; n is a comprehensive constant of the regulating valve under a certain opening degree; a is the flow area of the regulating valve in m2(ii) a The delta P is the pressure difference between the inlet and the outlet of the regulating valve and has the unit of Pa; qmThe mass flow rate of the medium is expressed in kg/s.
Obtained by the formula (5) to the formula (7):
wherein: a. thedFor comparison of the areas, since N is constant at a certain opening of the regulating valve, AdProportional to the flow area of the valve, A in the absence of a fault in the regulating valvedThe valve opening degree theta is always in one-to-one correspondence;
step 2, obtaining historical big data information of long-term normal operation parameters of the system, and calculating according to formula (8) to obtain AdData, using opening theta of regulating valve as X-axis and AdThe value is Y axis, and the normal operation condition theta-A of the regulating valve is drawndA drawing;
step 3, obtaining an upper boundary curve and a lower boundary curve of the normal operation working condition point of the regulating valve through fitting of a polynomial fitting method, and obtaining the upper boundary curve and the lower boundary curve at the theta-A according to the curvesdDrawing an early warning area and an alarm area on the graph;
adjusting the upper boundary curve of the normal operation working condition point of the valve:
Ad=fu(θ) (9)
adjusting the upper boundary curve of the normal operation working condition point of the valve:
Ad=fd(θ) (10)
step 4, obtaining real-time operation condition data of the regulating valve, and calculating A according to the formula (8)dWhen the operating condition point is in the early warning area, the system sends out fault early warning to remind operators to check the state of the valve; when the operating condition point is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operating condition.
Said step 3, at theta-Ad1.05f in the figureu(θ)<Ad<1.1fu(theta) and 0.9fd(θ)<Ad<0.95fd(θ) the area belongs to an early warning zone; a. thed>1.1fu(theta) and Ad<0.9fdThe (theta) region belongs to the warning region.
A regulating valve fault early warning system based on big data medium parameter diagnosis comprises a measuring and collecting module, a data processing module and a judging and early warning module;
the measurement and acquisition module, the data processing module and the judgment and early warning module are sequentially connected;
the measurement and acquisition module measures, acquires and transmits all parameters in the system to the data processing module, and the data processing module firstly processes historical big data information of long-term normal work of the valve and draws theta-AdGraph according to theta-AdThe module fits the normal operation working condition points of the valve to obtain an upper boundary curve and a lower boundary curve, and then draws an early warning area and an alarm area;
after the early warning area and the warning area are determined, the data processing module is based on the factThe time-measuring parameters calculate the operating condition point AdValue, and judging this AdValue in theta-AdThe region of the figure is the operating condition point AdIf the value is in the early warning area, the system sends out fault early warning to remind operating personnel to check the state of the valve; if the operating condition point AdAnd if the value is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operation condition.
The parameters measured and collected by the measurement and collection module include: regulating valve inlet pressure P1Regulating valve inlet pressure P2Regulating valve inlet temperature T1Regulating the temperature T of the outlet of the valve2Medium mass flow rate QmAdjusting the opening theta of the valve;
the data processing module calculates historical big data information of long-term normal work of the system valve through an equation (8) to obtain the valve opening theta and A under various working conditionsdThe history data of (A) is obtained by taking the valve opening theta as an X axisdThe value is Y axis, and the normal operation condition theta-A of the valve is drawndThe upper boundary curve and the lower boundary curve of the normal operation working condition point of the valve are obtained by a data fitting method and are positioned according to the curves at theta-AdDrawing an early warning area and an alarm area on the graph; calculating A according to the real-time operation condition data collected by the measurement and collection moduledA real-time value of (c);
the judging and early warning module is used for judging theta-A drawn by the data processing moduledFIG. A and BdReal-time value, judging that the operating condition point is theta-AdIn the area where the graph is located, if the operation working condition point is in the early warning area, the system sends out fault early warning to remind an operator to check the state of the valve; and if the operating condition point is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operating condition.
The invention has the beneficial effects that:
in the operation process of the thermal power plant, when the control or mechanical fault which can not be reflected by a DCS system picture occurs in the regulating valve, the invention can carry out comprehensive judgment according to the through-flow medium parameter and the valve opening degree, and further send out early warning or alarm to the operator in time to remind the operator to check and process the system with abnormal operation as early as possible, thereby effectively avoiding the occurrence of safety accidents.
Description of the drawings:
FIG. 1 shows the normal operating condition θ -A of the regulating valve of the present inventiondFigure (a).
FIG. 2 is a schematic flow chart of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings. Example (b):
taking a regulating valve of a 350MW coal-fired boiler installed on a pipeline from cold primary air to dilution air of a denitration pyrolysis furnace as an example, a fault early warning method of the regulating valve based on large data medium parameter diagnosis comprises the following steps;
step 1, according to the mechanical characteristics of air flow, the air flow through an adjusting valve has a calculation formula shown in formula (5), and the contrast area in direct proportion to the flow area of the valve is deduced through air density, air flow and front-back differential pressure of the adjusting valve;
step 1.1, obtaining air density:
wherein: p is the air pressure at the regulating valve and has the unit of Pa; t is the air temperature at the regulating valve and the unit is K; rho is the air density at the regulating valve and has the unit of kg/m3;P1Regulating the inlet air pressure of the valve in Pa; p2Regulating the air pressure at the outlet of the valve in Pa; t is1In order to regulate the inlet air temperature of the valve, the unit is K; t is2For regulating valve outletMouth air temperature, in K; p0、T0、ρ0Is air pressure, temperature, density, P in the standard state0=101325Pa,T0=273K、ρ0=1.293kg/m3;
The following can be derived from formula (1) to formula (3):
step 1.2, deducing a contrast area by utilizing air flow and front-back differential pressure of an adjusting valve:
Qm=Qv×ρ (6)
ΔP=P2-P1 (7)
q in formula (5) -formula (7)vIs the air volume flow rate, in m3S; n is a comprehensive constant of the regulating valve under a certain opening degree; a is the flow area of the regulating valve in m2(ii) a The delta P is the pressure difference between the inlet and the outlet of the regulating valve and has the unit of Pa; qmThe air mass flow is expressed in kg/s.
A is derived from the formula (5) to the formula (7)d:
Step 2, obtaining historical big data information of long-term normal operation of the system, and calculating according to formula (8) to obtain AdHistorical data, using opening theta of regulating valve as X-axis and AdThe value is Y axis, and the normal operation condition theta-A of the regulating valve is drawndFIG. 1;
step 3, obtaining an upper boundary curve and a lower boundary curve of the normal operation working condition point of the regulating valve through fitting of a polynomial fitting method, and obtaining the upper boundary curve and the lower boundary curve at the theta-A according to the curvesdDrawing the early warning area and the alarm on the graphAn area;
adjusting the upper boundary curve of the normal operation working condition point of the valve:
Ad=fu(θ) (9)
adjusting the upper boundary curve of the normal operation working condition point of the valve:
Ad=fd(θ) (10)
step 4, obtaining real-time operation condition data of the regulating valve, and calculating A according to the formula (8)dWhen the operating condition point is in the early warning area, the system sends out fault early warning to remind operators to check the state of the valve; when the operating condition point is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operating condition.
In the step 3, theta-Ad1.05f in the figureu(θ)<Ad<1.1fu(theta) and 0.9fd(θ)<Ad<0.95fd(θ) the area belongs to an early warning zone; a. thed>1.1fu(theta) and Ad<0.9fdThe (θ) region belongs to the warning region, as shown in fig. 1.
A regulating valve fault early warning system based on big data medium parameter diagnosis comprises a measuring and collecting module, a data processing module and a judging and early warning module;
the measurement and acquisition module, the data processing module and the judgment and early warning module are sequentially connected; adjusting valve inlet air pressure P by measuring and collecting module1Regulating valve inlet air pressure P2Regulating valve inlet air temperature T1Regulating the temperature T of the air at the outlet of the valve2Air mass flow rate QmThe opening degree theta of the regulating valve and other parameters are measured, collected and transmitted to the data processing module, and the data processing module firstly processes historical big data information of long-term normal work of the valve and draws theta-AdGraph according to theta-AdThe module fits the normal operation working condition points of the valve to obtain an upper boundary curve and a lower boundary curve, and then draws an early warning area and an alarm area;
after the early warning area and the warning area are determined, the data processing module is based on the factThe time-measuring parameters calculate the operating condition point AdValue, and judging this AdValue in theta-AdThe region of the figure is the operating condition point AdIf the value is in the early warning area, the system sends out fault early warning to remind operating personnel to check the state of the valve; if the operating condition point AdAnd if the value is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operation condition.
The parameters measured and collected by the measurement and collection module include: regulating valve inlet pressure P1Regulating valve inlet pressure P2Regulating valve inlet temperature T1Regulating the temperature T of the outlet of the valve2Medium mass flow rate QmAdjusting the opening theta of the valve;
the data processing module calculates historical big data information of long-term normal work of the system valve through an equation (8) to obtain the valve opening theta and A under various working conditionsdThe history data of (A) is obtained by taking the valve opening theta as an X axisdThe value is Y axis, and the normal operation condition theta-A of the valve is drawndThe upper boundary curve and the lower boundary curve of the normal operation working condition point of the valve are obtained by a data fitting method and are positioned according to the curves at theta-AdDrawing an early warning area and an alarm area on the graph; calculating A according to the real-time operation condition data collected by the measurement and collection moduledA real-time value of (c);
the judging and early warning module is used for judging theta-A drawn by the data processing moduledFIG. A and BdReal-time value, judging that the operating condition point is theta-AdIn the area where the graph is located, if the operation working condition point is in the early warning area, the system sends out fault early warning to remind an operator to check the state of the valve; and if the operating condition point is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operating condition.
Claims (4)
1. A fault early warning method of a regulating valve based on big data medium parameter diagnosis is characterized in that the regulating valve is used as a throttling orifice plate with an adjustable flow area, the regulating valve can regulate the medium flow by changing the flow area according to the fluid mechanics characteristics of a flowing medium, and the early warning method comprises the following steps;
step 1, obtaining a comparison area in a direct proportion relation with a valve flow area through a medium density, a medium flow and a front-back differential pressure of the valve, wherein the comparison area corresponds to each opening of the regulating valve one by one;
step 1.1, obtaining the density of a medium:
for compressible media:
wherein: p is the medium pressure at the regulating valve and has the unit of Pa; t is the temperature of the medium at the position of the regulating valve and the unit is K; rho is the density of the medium at the position of the regulating valve and has the unit of kg/m3;P1In Pa for regulating the inlet pressure of the valve; p2In Pa for regulating the outlet pressure of the valve; t is1In order to regulate the inlet temperature of the valve, the unit is K; t is2In order to regulate the outlet temperature of the valve, the unit is K; p0、T0、ρ0The pressure, temperature and density of the medium in any determined state are known quantities;
the following can be derived from formula (1) to formula (3):
for incompressible media: according to a comparison table of the medium density along with the change of temperature and pressure, a module for calculating the medium density is compiled, and the module directly outputs the medium density value after acquiring the temperature and the pressure of the medium;
step 1.2, deducing a contrast area by using medium flow and front-back differential pressure of a valve:
Qm=Qv×ρ (6)
ΔP=P2-P1 (7)
q in formula (5) -formula (7)vIs the volume flow of the medium, and has the unit of m3S; n is a comprehensive constant of the regulating valve under a certain opening degree; a is the flow area of the regulating valve in m2(ii) a The delta P is the pressure difference between the inlet and the outlet of the regulating valve and has the unit of Pa; qmThe mass flow rate of the medium is expressed in kg/s.
Obtained by the formula (5) to the formula (7):
wherein: a. thedFor comparison of the areas, since N is constant at a certain opening of the regulating valve, AdProportional to the flow area of the valve, A in the absence of a fault in the regulating valvedThe valve opening degree theta is always in one-to-one correspondence;
step 2, obtaining historical big data information of long-term normal operation parameters of the system, and calculating according to formula (8) to obtain AdData, using opening theta of regulating valve as X-axis and AdThe value is Y axis, and the normal operation condition theta-A of the regulating valve is drawndA drawing;
step 3, obtaining an upper boundary curve and a lower boundary curve of the normal operation working condition point of the regulating valve through fitting of a polynomial fitting method, and obtaining the upper boundary curve and the lower boundary curve at the theta-A according to the curvesdDrawing an early warning area and an alarm area on the graph;
adjusting the upper boundary curve of the normal operation working condition point of the valve:
Ad=fu(θ) (9)
adjusting the upper boundary curve of the normal operation working condition point of the valve:
Ad=fd(θ) (10)
step 4, obtaining real-time operation condition data of the regulating valve, and calculating A according to the formula (8)dWhen the operating condition point is in the early warning area, the system sends out fault early warning to remind operators to check the state of the valve; when the operating condition point is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operating condition.
2. The regulating valve fault early warning method based on big data medium parameter diagnosis as claimed in claim 1, wherein in step 3, theta-A is adoptedd1.05f in the figureu(θ)<Ad<1.1fu(theta) and 0.9fd(θ)<Ad<0.95fd(θ) the area belongs to an early warning zone; a. thed>1.1fu(theta) and Ad<0.9fdThe (theta) region belongs to the warning region.
3. The regulating valve fault early warning system based on the big data medium parameter diagnosis of the method of claim 1 or 2, which is characterized by comprising a measuring and collecting module, a data processing module and a judging and early warning module;
the measurement and acquisition module, the data processing module and the judgment and early warning module are sequentially connected; the measurement and acquisition module measures, acquires and transmits all parameters in the system to the data processing module, and the data processing module firstly processes historical big data information of long-term normal work of the valve and draws theta-AdGraph according to theta-AdThe module fits the normal operation working condition points of the valve to obtain an upper boundary curve and a lower boundary curve, and then draws an early warning area and an alarm area;
after the early warning area and the warning area are determined, the data processing module calculates an operation working condition point A according to the real-time measurement parametersdValue and judgeThis A is adValue in theta-AdThe region of the figure is the operating condition point AdIf the value is in the early warning area, the system sends out fault early warning to remind operating personnel to check the state of the valve; if the operating condition point AdAnd if the value is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operation condition.
4. The big data medium parameter diagnosis-based fault early warning system for the regulating valve, as claimed in claim 3, wherein the parameters measured and collected by the measurement and collection module include: regulating valve inlet pressure P1Regulating valve inlet pressure P2Regulating valve inlet temperature T1Regulating the temperature T of the outlet of the valve2Medium mass flow rate QmAdjusting the opening theta of the valve;
the data processing module calculates historical big data information of long-term normal work of the system valve through an equation (8) to obtain the valve opening theta and A under various working conditionsdThe history data of (A) is obtained by taking the valve opening theta as an X axisdThe value is Y axis, and the normal operation condition theta-A of the valve is drawndThe upper boundary curve and the lower boundary curve of the normal operation working condition point of the valve are obtained by a data fitting method and are positioned according to the curves at theta-AdDrawing an early warning area and an alarm area on the graph; calculating A according to the real-time operation condition data collected by the measurement and collection moduledA real-time value of (c);
the judging and early warning module is used for judging theta-A drawn by the data processing moduledFIG. A and BdReal-time value, judging that the operating condition point is theta-AdIn the area where the graph is located, if the operation working condition point is in the early warning area, the system sends out fault early warning to remind an operator to check the state of the valve; and if the operating condition point is in the alarm area, the system sends a fault alarm to remind an operator to process the fault according to the operating condition.
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