CN116861613B - Construction method of axial flow fan simulation model of thermal power plant air-smoke system - Google Patents
Construction method of axial flow fan simulation model of thermal power plant air-smoke system Download PDFInfo
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- 238000010276 construction Methods 0.000 title claims description 24
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- 230000017525 heat dissipation Effects 0.000 description 2
- 239000000314 lubricant Substances 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 description 1
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- 239000003546 flue gas Substances 0.000 description 1
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Abstract
The invention discloses a method for constructing an axial flow fan simulation model of a thermal power plant wind and smoke system, which comprises the following steps: according to the working principle of the axial flow fan, a full-pressure algorithm block, a flow network resolving algorithm block, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block are constructed based on Modelica, and the input and the output of the algorithm blocks are determined; according to the physical topology and the functional topology of the axial flow fan, the full-pressure algorithm block and the flow network algorithm block are called to construct a flow network module, the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block are called to construct a sequential module, and the input and the output of the module are determined; and calling a flow net module and a sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model. The modeling method based on Modelica solves the technical problems that a traditional modeling method is incomplete, causality is considered, modification and reuse are difficult, and accuracy and reusability of an axial flow fan simulation model are improved.
Description
Technical Field
The application relates to the technical field of fan equipment simulation modeling, in particular to a method for constructing an axial flow fan simulation model of a thermal power plant wind and smoke system.
Background
An axial flow fan is a fluid delivery device in which gas flows in an axial direction. At present, the axial flow fan is widely applied to a draught fan, a blower and a primary fan of a large-capacity thermal power generating unit, is important component equipment of a thermal power plant air and smoke system, and provides important technical support for development, design and optimization of the thermal power plant air and smoke system by researching the dynamic characteristics of the axial flow fan.
In the process of establishing a simulation model of a wind and smoke system of a thermal power plant, the operation working condition of an axial flow fan needs to be accurately simulated, and the dynamic and static characteristics of the simulation model of the axial flow fan are required to be very consistent with those of actual equipment. The axial flow fan operation process relates to a plurality of fields such as fluid mechanics, thermodynamics, heat transfer science, electromechanics and the like, and physical phenomena such as flow, heat exchange, vibration and the like exist inside the axial flow fan operation process, and the phenomena are mutually influenced, so that a model equation is highly nonlinear. Therefore, the traditional axial flow fan simulation calculation method has the problem that serious nonlinear coupling cannot be processed simultaneously and usability and universality are considered.
Disclosure of Invention
Aiming at the defects of the prior art, the embodiment of the application provides a method for constructing an axial flow fan simulation model of a thermal power plant wind and smoke system.
According to a first aspect of an embodiment of the present application, a method for constructing an axial flow fan simulation model of a thermal power plant flue gas system is provided, including:
according to the working principle of the axial flow fan, a full-pressure algorithm block is built based on Modelica, input and output are determined, and the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan;
according to the working principle of the axial flow fan, a flow net algorithm block is built based on Modelica, input and output are determined, and the flow net algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan;
according to the working principle of the axial flow fan, a power algorithm block is built based on Modelica, input and output are determined, and the power algorithm block is used for calculating the motor power of the axial flow fan;
according to the working principle of the axial flow fan, a heat exchange algorithm block is built based on Modelica, input and output are determined, and the heat exchange algorithm block is used for calculating the bearing temperature of the axial flow fan;
according to the working principle of the axial flow fan, a safety monitoring algorithm block is built based on Modelica, input and output are determined, and the safety monitoring algorithm block is used for calculating bearing vibration of the axial flow fan;
according to the physical topology of the axial flow fan, a full-pressure algorithm block and a flow network algorithm block are called to construct a flow network module, and input and output are determined;
according to the functional topology of the axial flow fan, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block are called to construct a sequential module, and input and output are determined;
and calling the flow net module and the sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model.
Optionally, according to the working principle of the axial flow fan, a full-pressure algorithm block is constructed based on Modelica, and input and output are determined, including:
obtaining fan total pressure-fan mass flow function relations of different fan stationary blade guide vane angles according to axial flow fan characteristic curve fitting;
obtaining fan torque-fan rotating speed of different fan stator vane angles according to fan total pressure-fan mass flow function relations of different fan stator vane angles;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the full-pressure algorithm block is fan mass flow, fan rotating speed and stator vane angle, and the output is fan full pressure and fan torque.
Optionally, according to the working principle of the axial flow fan, a flow network algorithm block is constructed based on Modelica, and input and output are determined, including:
obtaining the relation between the resistance of the fan and the design parameters of the fan according to the design parameters provided by a manufacturer;
obtaining the relation between the mass flow of the fan and the inlet and outlet pressure of the fan according to the poiseuille law;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the flow network algorithm block is inlet static pressure and total pressure of the fan, and the output is mass flow of the fan.
Optionally, according to the working principle of the axial flow fan, a power algorithm block is constructed based on Modelica, and input and output are determined, including:
obtaining the relation between the motor power and the motor current and motor voltage according to design parameters provided by a manufacturer;
obtaining the relation between the fan shaft power and the fan mass flow according to design parameters provided by manufacturers;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the power algorithm block is fan mass flow, fan full voltage, motor voltage, fan efficiency, shaft efficiency and motor efficiency, and the output is motor power and motor current.
Optionally, according to the working principle of the axial flow fan, the heat exchange algorithm block is constructed based on Modelica, and the input and the output are determined, including:
obtaining the relation between the heating value of the bearing and the outlet temperature of the cooling lubricating oil according to design parameters provided by manufacturers;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the heat exchange algorithm block is motor power, motor efficiency, cooling lubricating oil mass flow and cooling lubricating oil inlet temperature, and the output is bearing temperature and cooling lubricating oil outlet temperature.
Optionally, according to the working principle of the axial flow fan, the safety monitoring algorithm block is constructed based on Modelica, and the input and the output are determined, including:
obtaining the relation between radial vibration of a fan bearing and the rotating speed of the fan according to the actual operation history data of the fan
And determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the safety monitoring algorithm block is the rotating speed of the fan, and the output is the radial displacement of the fan bearing.
Optionally, the flow net module is used for describing the flow process of the fluid medium through the axial flow fan, and inputs are inlet static pressure, fan rotating speed and stator vane angle, and outputs are fan mass flow, fan total pressure and fan torque.
Optionally, the sequential module is used for describing physical characteristics and behavior characteristics of fluid passing through the axial flow fan, and inputs are fan rotating speed, fan mass flow, fan full pressure, motor voltage, fan efficiency, shaft efficiency, motor efficiency, cooling lubricating oil flow and cooling lubricating oil inlet temperature, and outputs are motor power, motor current, bearing temperature, cooling lubricating oil outlet temperature and radial displacement of the fan bearing.
According to a second aspect of the embodiments of the present application, there is provided a device for constructing an axial flow fan simulation model of a thermal power plant fan system, including:
the first construction determining module is used for constructing a full-pressure algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, wherein the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan;
the second construction determining module is used for constructing a flow network algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, and the flow network algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan;
the third construction determining module is used for constructing a power algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, and the power algorithm block is used for calculating the motor power of the axial flow fan;
a fourth construction determining module, configured to construct a heat exchange algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the heat exchange algorithm block is used to calculate a bearing temperature of the axial flow fan;
a fifth construction determining module, configured to construct a safety monitoring algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the safety monitoring algorithm block is used to calculate bearing vibration of the axial flow fan;
the sixth construction determining module is used for calling the full-pressure algorithm block and the flow network algorithm block to construct a flow network module according to the physical topology of the axial flow fan and determining input and output;
a seventh construction determining module for calling the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block to construct a sequential module according to the functional topology of the axial flow fan and determining input and output;
the building module is used for calling the flow net module and the sequential module, and setting inlet and outlet parameters according to actual operation conditions to build an axial flow fan simulation model.
According to a third aspect of embodiments of the present application, there is provided an electronic device, including:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of the first aspect.
The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:
as can be seen from the above embodiments, according to the working principle of the axial flow fan, the present application constructs a full-pressure algorithm block, a flow network resolving algorithm block, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block based on Modelica, and determines the input and output of the algorithm blocks; according to the physical topology and the functional topology of the axial flow fan, the full-pressure algorithm block and the flow network algorithm block are called to construct a flow network module, the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block are called to construct a sequential module, and the input and the output of the module are determined; and calling a flow net module and a sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model. Modeling is based on Modelica, so that the technical problems that a traditional modeling method is incomplete, causality is considered, modification and reuse are difficult are solved, and the accuracy and reusability of an axial flow fan simulation model are improved. The Modelica is applied to modeling and simulation of the axial flow fan, so that the comprehensive performance of the axial flow fan can be conveniently analyzed, the research and development period is shortened, and the research and development cost is reduced.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.
FIG. 1 is a flow chart illustrating a method of constructing a model based on Modelica for an axial flow fan simulation model of a thermal power plant fume system in accordance with an exemplary embodiment.
FIG. 2 is a block diagram of a heat exchange algorithm shown according to an exemplary embodiment.
FIG. 3 is a schematic diagram of sequential modules shown according to an exemplary embodiment.
Fig. 4 is a schematic diagram of an axial flow fan simulation model shown in accordance with an exemplary embodiment.
FIG. 5 is a block diagram illustrating an apparatus for constructing a model of an axial flow fan simulation of a thermal power plant fume system based on Modelica, according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the accompanying claims.
The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first message may also be referred to as a second message, and similarly, a second message may also be referred to as a first message, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
Fig. 1 is a flowchart of a method for constructing an axial flow fan simulation model of a smoke system of a thermal power plant according to an exemplary embodiment, and as shown in fig. 1, the method is applied to a terminal, and may include the following steps:
s1: according to the working principle of the axial flow fan, a full-pressure algorithm block is built based on Modelica, input and output are determined, and the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan;
s2: according to the working principle of the axial flow fan, a flow net algorithm block is built based on Modelica, input and output are determined, and the flow net algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan;
s3: according to the working principle of the axial flow fan, a power algorithm block is built based on Modelica, input and output are determined, and the power algorithm block is used for calculating the motor power of the axial flow fan;
s4: according to the working principle of the axial flow fan, a heat exchange algorithm block is built based on Modelica, input and output are determined, and the heat exchange algorithm block is used for calculating the bearing temperature of the axial flow fan;
s5: according to the working principle of the axial flow fan, a safety monitoring algorithm block is built based on Modelica, input and output are determined, and the safety monitoring algorithm block is used for calculating bearing vibration of the axial flow fan;
s6: according to the physical topology of the axial flow fan, a full-pressure algorithm block and a flow network algorithm block are called to construct a flow network module, and input and output are determined;
s7: according to the functional topology of the axial flow fan, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block are called to construct a sequential module, and input and output are determined;
s8: and calling a flow net module and a sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model.
As can be seen from the above embodiments, according to the working principle of the axial flow fan, the present application constructs a full-pressure algorithm block, a flow network resolving algorithm block, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block based on Modelica, and determines the input and output of the algorithm blocks; according to the physical topology and the functional topology of the axial flow fan, the full-pressure algorithm block and the flow network algorithm block are called to construct a flow network module, the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block are called to construct a sequential module, and the input and the output of the module are determined; and calling a flow net module and a sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model. Modeling is based on Modelica, so that the technical problems that a traditional modeling method is incomplete, causality is considered, modification and reuse are difficult are solved, and the accuracy and reusability of an axial flow fan simulation model are improved. The Modelica is applied to modeling and simulation of the axial flow fan, so that the comprehensive performance of the axial flow fan can be conveniently analyzed, the research and development period is shortened, and the research and development cost is reduced.
In the implementation of S1: according to the working principle of the axial flow fan, a full-pressure algorithm block is built based on Modelica, input and output are determined, and the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan. This step may comprise the sub-steps of:
s11: obtaining fan total pressure-fan mass flow function relations of different fan stationary blade guide vane angles according to axial flow fan characteristic curve fitting;
specifically, according to an axial flow fan characteristic curve provided by a manufacturer, obtaining data corresponding to the total pressure of a fan, the mass flow of the fan and the vane angle of a stator blade of the fan, and fitting to obtain the fan total pressure-mass flow function relationship of different vane angles of the stator blade of the fan.
Wherein beta is i For different angles of the stator vanes of the fan,for the corresponding fan full pressure of different fan stator blade angles, < ->For the fan mass flow corresponding to different fan stationary blade guide vane angles, a i ,b i ,c i ,d i ,e i ,f i Fitting coefficients corresponding to different stator blade angles of the fan are obtained.
S12: obtaining fan torque-fan rotating speed of different fan stator vane angles according to fan total pressure-fan mass flow function relations of different fan stator vane angles;
specifically, according to the similarity of the fans, fan torque-fan rotation speed functional relationships of different fan stator blade angles can be obtained according to the fitting functional relationship.
Wherein P is the total pressure of the fan, q m The mass flow of the fan, the rotating speed of the fan, the torque of the fan,for the corresponding fan torque of different fan stator blade angles, +.>The rotation speeds of the fans corresponding to different stator blade angles of the fans are obtained.
S13: and determining input and output according to the physical topology and the functional relation in the algorithm block.
Specifically, according to the physical topology, the mass flow of the fan, the rotating speed of the fan and the angle of the stator blade are determined to be input into an algorithm block, and the total pressure of the fan and the torque of the fan are determined to be output from the algorithm block.
The full-pressure algorithm block is constructed through the steps, and is used for calculating the full pressure of the fan of the axial fan, so that the characteristic curves of the axial fan in different working scenes can be described, and the usability and the universality of the algorithm block are improved.
In the implementation of S2: according to the working principle of the axial flow fan, a flow net algorithm block is built based on Modelica, input and output are determined, and the flow net algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan. This step may comprise the sub-steps of:
s21: obtaining the relation between the resistance of the fan and the design parameters of the fan according to the design parameters provided by a manufacturer;
specifically, according to the pipeline diameter provided by the manufacturer, the collected actual operation data fluid speed and fluid density, and the along-the-way resistance formula, the relation between the fan resistance and the fan design parameters can be obtained.
In the formula, bsm i Flow resistance, lambda, for the i-th node and i+1th node i Resistance coefficient for the i node and the i+1th node, D i Pipeline diameter, v for the i node and i+1th node i Fluid flow rates, ρ, of the i node and the i+1th node i For the ith nodeAnd fluid density at node i+1, g is gravitational acceleration.
S22: obtaining the relation between the mass flow of the fan and the inlet and outlet pressure of the fan according to the poiseuille law;
specifically, according to the collected actual operation conditions and the fan inlet and outlet pressures corresponding to the actual fan mass flow, the relationship between the fan mass flow and the fan inlet and outlet pressures can be obtained according to a fluid network formula
The flow network algorithm block is used for calculating the flow resistance of the axial fan and the mass flow of the fan, describing the relationship between the inlet and outlet pressure differences of the fan and the mass flow of the fan under different working conditions of different fluids, and increasing the universality.
S23: and determining input and output according to the physical topology and the functional relation in the algorithm block.
Specifically, according to the physical topology, the inlet static pressure and the total pressure of the fan are determined to be input into an algorithm block, and the mass flow of the fan is output from the algorithm block.
The flow network algorithm block is constructed through the steps, and is used for calculating the flow resistance and the fan mass flow of the axial fan, describing the relationship between the inlet and outlet pressure differences of the fan and the fan mass flow of different fluids under different working conditions, and increasing the universality.
In the implementation of S3: according to the working principle of the axial flow fan, a power algorithm block is built based on Modelica, and input and output are determined, wherein the power algorithm block is used for calculating the motor power of the axial flow fan. This step may comprise the sub-steps of:
s31: obtaining the relation between the motor power and the motor current and motor voltage according to design parameters provided by a manufacturer;
specifically, according to design parameters provided by a manufacturer, motor power, motor voltage, motor rated current and the like, and according to electric power calculation, the relationship between motor power and motor current and motor voltage can be obtained.
P E ＝U·I
Wherein P is E The motor power, U is motor voltage, and I is motor current.
S32: obtaining the relation between the fan shaft power and the fan mass flow according to design parameters provided by manufacturers;
specifically, according to design parameters provided by manufacturers, fan efficiency, shaft efficiency and motor efficiency, and according to a power calculation formula, the relationship between fan shaft power and fan mass flow is obtained.
P E ＝q m *P/(3600*η 1 *η 2 )
P E ＝P E,N /η 3
Wherein P is E,N For fan shaft power, eta 1 Fan efficiency, eta 2 For axis efficiency, eta 3 Is motor efficiency.
S33: and determining input and output according to the physical topology and the functional relation in the algorithm block.
Specifically, according to the physical topology, the fan mass flow, the fan full voltage, the motor voltage, the fan efficiency, the shaft efficiency and the motor efficiency are determined as algorithm block inputs, and the motor power and the motor current are determined as algorithm block outputs.
The power algorithm block is constructed by the steps, and is used for calculating the motor power of the axial flow fan and describing the working capacity of the motor of the axial flow fan in unit time.
In the implementation of S4: according to the working principle of the axial flow fan, a heat exchange algorithm block is built based on Modelica, input and output are determined, and the heat exchange algorithm block is used for calculating the bearing temperature of the axial flow fan. This step may comprise the sub-steps of:
s41: obtaining the relation between the heating value of the bearing and the outlet temperature of the cooling lubricating oil according to design parameters provided by manufacturers;
specifically, the bearing heating value is determined according to design parameters provided by a manufacturer, the motor power, the motor efficiency and the heat dissipation loss, heat is transferred to cooling lubricating oil through metal heat accumulation, the mass flow of the cooling lubricating oil and the inlet temperature of the cooling lubricating oil are determined according to design parameters provided by the manufacturer, and the relation between the bearing heating value and the outlet temperature of the cooling lubricating oil is determined according to energy conservation.
Q 1 ＝P E *(1-η 3 )*η 4
Q 2 ＝q m *(h out -h in )
In which Q 1 For generating heat, eta of fan bearing 4 For heat dissipation loss, Q 2 To cool the lubricating oil and absorb heat, h in To cool the specific enthalpy of the lubricating oil inlet, h out To cool the specific enthalpy of the lubricating oil inlet, k is the heat transfer coefficient, t in To cool the lubricant inlet temperature, t out To cool the lubricant outlet temperature, t m For the actual metal temperature, n is the correction index under different flowing states, M is the effective metal mass of the fan bearing, C m Is the specific heat capacity of the metal material.
S42: and determining input and output according to the physical topology and the functional relation in the algorithm block.
Specifically, according to the physical topology, the motor power, the motor efficiency, the cooling lubricant mass flow and the cooling lubricant inlet temperature are determined as algorithm block inputs, and the bearing temperature and the cooling lubricant outlet temperature are determined as algorithm block outputs.
The heat exchange algorithm block is constructed by the above steps, as shown in fig. 2. The heat exchange algorithm block is used for calculating the bearing temperature of the axial flow fan and describing the heat exchange effect of fan bearings made of different materials and lubricating oil of different types.
In the implementation of S5: according to the working principle of the axial flow fan, a safety monitoring algorithm block is built based on Modelica, and input and output are determined, wherein the safety monitoring algorithm block is used for calculating bearing vibration of the axial flow fan. This step may comprise the sub-steps of:
s51: according to actual operation history data of the fan, radial vibration of the fan bearing and the fan rotating speed value under different working conditions are extracted, and the relation between the radial vibration of the fan bearing and the fan rotating speed is obtained;
in particular, assuming that the fan bearing is constrained, only radial vibrations, the fan bearing is reduced to a mechanical model system consisting of a series of concentrated masses, springs and dampers with certain motion constraints. According to design parameters provided by manufacturers, the mass of the fan bearing, the rigidity coefficient of the fan bearing and the collected actual operation working conditions, the radial vibration of the fan bearing and the rotating speed of the fan, and according to the dynamics law, the relation between the vibration of the fan bearing and the rotating speed of the fan is established.
ω＝2πN
Wherein y is radial displacement of the fan bearing, c is damping coefficient, k is rigidity coefficient of the fan bearing, ω is circular frequency, F 0 Is a disturbance force.
S52: and determining input and output according to the physical topology and the functional relation in the algorithm block.
Specifically, according to the physical topology, the rotating speed of the fan is determined to be the input of an algorithm block, and the radial displacement of the fan bearing is determined to be the output of the algorithm block.
And constructing a safety monitoring algorithm block by the steps, wherein the safety monitoring algorithm block is used for calculating the vibration of the bearing of the axial fan and describing the vibration effect of the bearing under different working conditions.
In the implementation of S6: according to the physical topology of the axial flow fan, a full-pressure algorithm block and a flow network algorithm block are called to construct a flow network module, and input and output are determined;
specifically, the full-pressure algorithm block and the flow net algorithm block are instantiated according to the physical topology of the axial flow fan to construct a flow net module, wherein the flow net module is used for describing the flow process of fluid media through the axial flow fan, the flow net algorithm block receives the full pressure of the fan output by the full-pressure algorithm block, the full-pressure algorithm block receives the mass flow of the fan output by the flow net algorithm block, and the flow net module describes the flow relation of different fluids in the axial flow fan, so that reusability is increased and expansion is facilitated. And determining input and output, wherein the input of the module is inlet static pressure, fan rotating speed and stator vane angle, and the output of the module is fan mass flow, fan total pressure and fan torque.
In the implementation of S7: according to the functional topology of the axial flow fan, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block are called to construct a sequential module, and input and output are determined;
specifically, the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block are instantiated according to the functional topology of the axial flow fan and are used for constructing a sequential module, as shown in fig. 3. The sequential module is used for describing physical characteristics and behavior characteristics of fluid passing through the axial flow fan, wherein the heat exchange algorithm block receives motor power output by the power algorithm block, the safety monitoring algorithm block receives fan rotating speed in model input, and the sequential module describes internal operation characteristics of the axial flow fan and is closer to actual operation. The input and output are determined, the module input is fan rotating speed, fan mass flow, fan full pressure, motor voltage, fan efficiency, shaft efficiency, motor efficiency, cooling lubricating oil flow and cooling lubricating oil inlet temperature, and the module output is motor power, motor current, bearing temperature, cooling lubricating oil outlet temperature and fan bearing radial displacement.
In the implementation of S8: and calling a flow net module and a sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model.
Specifically, the flow net module and the sequential module are instantiated, geometric parameters, design parameters, operation influence parameters and inlet and outlet parameters of the flow net module and the sequential module are set according to actual operation conditions, the flow net module and the sequential module are connected to construct an axial flow fan simulation model, and as shown in fig. 4, the sequential module receives fan rotating speed, fan total pressure and fan mass flow of the flow net module. The axial flow fan simulation model is used for describing the geometric characteristics, physical characteristics and behavior characteristics of the axial flow fan, and can better simulate the running process of the axial flow fan.
Corresponding to the embodiment of the method for constructing the model of the axial flow fan of the thermal power plant fume system based on Modelica, the application also provides the embodiment of the device for constructing the model of the axial flow fan of the thermal power plant fume system based on Modelica.
FIG. 5 is a block diagram of a device for constructing a simulation model of an axial flow fan of a thermal power plant fume system according to an exemplary embodiment. Referring to fig. 5, the apparatus includes:
the first construction determining module 1 is used for constructing a full-pressure algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, wherein the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan;
the second construction determining module 2 is used for constructing a flow net algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, wherein the flow net algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan;
a third construction determining module 3, configured to construct a power algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the power algorithm block is used to calculate motor power of the axial flow fan;
a fourth construction determining module 4, configured to construct a heat exchange algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the heat exchange algorithm block is used to calculate a bearing temperature of the axial flow fan;
a fifth construction determination module 5, configured to construct a safety monitoring algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the safety monitoring algorithm block is used to calculate bearing vibration of the axial flow fan;
a sixth construction determining module 6, configured to invoke the full-pressure algorithm block and the flow network algorithm block to construct a flow network module according to the physical topology of the axial flow fan, and determine input and output;
a seventh construction determining module 7, configured to invoke the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block to construct a sequential module according to the functional topology of the axial flow fan, and determine input and output;
and the construction module 8 is used for calling the flow net module and the sequential module, setting inlet and outlet parameters according to actual operation conditions and constructing an axial flow fan simulation model.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
For the device embodiments, reference is made to the description of the method embodiments for the relevant points, since they essentially correspond to the method embodiments. The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purposes of the present application. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
Correspondingly, the application also provides electronic equipment, which comprises: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are enabled to realize the method for constructing the model based on the Modelica for constructing the axial flow fan simulation model of the thermal power plant smoke system.
Correspondingly, the application also provides a computer readable storage medium, wherein computer instructions are stored on the computer readable storage medium, and the instructions realize the method for constructing the model based on Modelica for the axial flow fan simulation model of the thermal power plant wind-smoke system when being executed by a processor.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the application following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the application pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It is to be understood that the present application is not limited to the precise arrangements and instrumentalities shown in the drawings, which have been described above, and that various modifications and changes may be effected without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (8)
1. The method for constructing the simulation model of the axial flow fan of the fume system of the thermal power plant is characterized by comprising the following steps of:
according to the working principle of the axial flow fan, a full-pressure algorithm block is built based on Modelica, input and output are determined, and the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan;
according to the working principle of the axial flow fan, a flow net algorithm block is built based on Modelica, input and output are determined, and the flow net algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan;
according to the working principle of the axial flow fan, a power algorithm block is built based on Modelica, input and output are determined, and the power algorithm block is used for calculating the motor power of the axial flow fan;
according to the working principle of the axial flow fan, a heat exchange algorithm block is built based on Modelica, input and output are determined, and the heat exchange algorithm block is used for calculating the bearing temperature of the axial flow fan;
according to the working principle of the axial flow fan, a safety monitoring algorithm block is built based on Modelica, input and output are determined, and the safety monitoring algorithm block is used for calculating bearing vibration of the axial flow fan;
according to the physical topology of the axial flow fan, a full-pressure algorithm block and a flow network algorithm block are called to construct a flow network module, and input and output are determined;
according to the functional topology of the axial flow fan, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block are called to construct a sequential module, and input and output are determined;
calling the flow net module and the sequential module, and setting inlet and outlet parameters according to actual operation conditions to construct an axial flow fan simulation model;
the flow net module is used for describing the flow process of a fluid medium passing through the axial flow fan, and is input into an inlet static pressure, a fan rotating speed and a stator vane angle, and output into a fan mass flow, a fan total pressure and a fan torque;
the sequential module is used for describing physical characteristics and behavior characteristics of fluid passing through the axial flow fan, and inputs are fan rotating speed, fan mass flow, fan total pressure, motor voltage, fan efficiency, shaft efficiency, motor efficiency, cooling lubricating oil flow and cooling lubricating oil inlet temperature, and outputs are motor power, motor current, bearing temperature, cooling lubricating oil outlet temperature and fan bearing radial displacement.
2. The method of claim 1, wherein constructing the full pressure algorithm block based on Modelica and determining the input and output according to the operating principle of the axial flow fan comprises:
obtaining fan total pressure-fan mass flow function relations of different fan stationary blade guide vane angles according to axial flow fan characteristic curve fitting;
obtaining fan torque-fan rotating speed of different fan stator vane angles according to fan total pressure-fan mass flow function relations of different fan stator vane angles;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the full-pressure algorithm block is fan mass flow, fan rotating speed and stator vane angle, and the output is fan full pressure and fan torque.
3. The method of claim 1, wherein constructing a flow network algorithm block based on Modelica according to the operating principle of the axial flow fan, and determining the input and the output, comprises:
obtaining the relation between the resistance of the fan and the design parameters of the fan according to the design parameters provided by a manufacturer;
obtaining the relation between the mass flow of the fan and the inlet and outlet pressure of the fan according to the poiseuille law;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the flow network algorithm block is inlet static pressure and total pressure of the fan, and the output is mass flow of the fan.
4. The method of claim 1, wherein constructing a power algorithm block based on Modelica according to the operating principle of the axial flow fan, and determining the input and the output, comprises:
obtaining the relation between the motor power and the motor current and motor voltage according to design parameters provided by a manufacturer;
obtaining the relation between the fan shaft power and the fan mass flow according to design parameters provided by manufacturers;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the power algorithm block is fan mass flow, fan full voltage, motor voltage, fan efficiency, shaft efficiency and motor efficiency, and the output is motor power and motor current.
5. The method of claim 1, wherein constructing a heat exchange algorithm block based on Modelica according to the operating principle of the axial flow fan, and determining the input and the output, comprises:
obtaining the relation between the heating value of the bearing and the outlet temperature of the cooling lubricating oil according to design parameters provided by manufacturers;
and determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the heat exchange algorithm block is motor power, motor efficiency, cooling lubricating oil mass flow and cooling lubricating oil inlet temperature, and the output is bearing temperature and cooling lubricating oil outlet temperature.
6. The method of claim 1, wherein constructing a safety monitoring algorithm block based on Modelica according to an operation principle of an axial flow fan, and determining an input and an output, comprises:
obtaining the relation between radial vibration of a fan bearing and the rotating speed of the fan according to the actual operation history data of the fan
And determining input and output according to the physical topology and the functional relation in the algorithm block, wherein the input of the safety monitoring algorithm block is the rotating speed of the fan, and the output is the radial displacement of the fan bearing.
7. The utility model provides a building device of thermal power plant's fan system axial fan simulation model which characterized in that includes:
the first construction determining module is used for constructing a full-pressure algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, wherein the full-pressure algorithm block is used for calculating the full pressure of the fan of the axial flow fan;
the second construction determining module is used for constructing a flow network algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, and the flow network algorithm block is used for calculating the flow resistance of the axial flow fan and the mass flow of the fan;
the third construction determining module is used for constructing a power algorithm block based on Modelica according to the working principle of the axial flow fan and determining input and output, and the power algorithm block is used for calculating the motor power of the axial flow fan;
a fourth construction determining module, configured to construct a heat exchange algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the heat exchange algorithm block is used to calculate a bearing temperature of the axial flow fan;
a fifth construction determining module, configured to construct a safety monitoring algorithm block based on Modelica according to an operating principle of the axial flow fan, and determine input and output, where the safety monitoring algorithm block is used to calculate bearing vibration of the axial flow fan;
the sixth construction determining module is used for calling the full-pressure algorithm block and the flow network algorithm block to construct a flow network module according to the physical topology of the axial flow fan and determining input and output;
a seventh construction determining module for calling the power algorithm block, the heat exchange algorithm block and the safety monitoring algorithm block to construct a sequential module according to the functional topology of the axial flow fan and determining input and output;
the building module is used for calling the flow net module and the sequential module, setting inlet and outlet parameters according to actual operation conditions and building an axial flow fan simulation model;
the flow net module is used for describing the flow process of a fluid medium passing through the axial flow fan, and is input into an inlet static pressure, a fan rotating speed and a stator vane angle, and output into a fan mass flow, a fan total pressure and a fan torque;
the sequential module is used for describing physical characteristics and behavior characteristics of fluid passing through the axial flow fan, and inputs are fan rotating speed, fan mass flow, fan total pressure, motor voltage, fan efficiency, shaft efficiency, motor efficiency, cooling lubricating oil flow and cooling lubricating oil inlet temperature, and outputs are motor power, motor current, bearing temperature, cooling lubricating oil outlet temperature and fan bearing radial displacement.
8. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-6.
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