CN116861613B - Construction method of axial flow fan simulation model of thermal power plant air-smoke system - Google Patents

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

Construction method of axial flow fan simulation model of air and smoke system in thermal power plant

Technical field

This application relates to the technical field of fan equipment simulation modeling, and in particular to a method of constructing a simulation model of an axial flow fan in a thermal power plant air and smoke system.

Background technique

An axial flow fan is a fluid conveying device that allows gas to flow in the axial direction. At present, axial flow fans are widely used in induced draft fans, blowers, and primary fans of large-capacity thermal power units. They are an important component of the air and smoke systems of thermal power plants. Studying the dynamic characteristics of axial flow fans will contribute to the development, design, and optimization of the air and smoke systems of thermal power plants. Provide important technical support.

In the process of establishing a simulation model of the air and smoke system of a thermal power plant, it is necessary to accurately simulate the operating conditions of the axial flow fan, and the dynamic and static characteristics of the axial flow fan simulation model are required to be consistent with the actual equipment. The operation process of the axial flow fan involves many fields such as fluid mechanics, thermodynamics, heat transfer, and electromechanics. There are physical phenomena such as flow, heat transfer, and vibration inside. These phenomena interact with each other, making the model equations highly nonlinear. Therefore, the traditional axial flow fan simulation calculation method has the problem of being unable to simultaneously handle severe nonlinear coupling and take into account ease of use and versatility.

Contents of the invention

In view of the shortcomings of the existing technology, embodiments of the present application provide a method for constructing a simulation model of an axial flow fan in the air and smoke system of a thermal power plant.

According to the first aspect of the embodiment of the present application, a method for constructing an axial flow fan simulation model of the air and smoke system of a thermal power plant is provided, including:

According to the working principle of the axial flow fan, a total pressure algorithm block is constructed based on Modelica, and the input and output are determined. The total pressure algorithm block is used to calculate the total fan pressure of the axial flow fan;

According to the working principle of the axial flow fan, a flow network algorithm block is constructed based on Modelica, and the input and output are determined. The flow network algorithm block is used to calculate the flow resistance of the axial flow fan and the fan mass flow rate;

According to the working principle of the axial flow fan, a power algorithm block is constructed based on Modelica and the input and output are determined. The power algorithm block is used to calculate the motor power of the axial flow fan;

According to the working principle of the axial flow fan, a heat exchange algorithm block is constructed based on Modelica and the input and output are determined. The heat exchange algorithm block is used to calculate the bearing temperature of the axial flow fan;

According to the working principle of the axial flow fan, a safety monitoring algorithm block is constructed based on Modelica and the input and output are determined. The safety monitoring algorithm block is used to calculate the bearing vibration of the axial flow fan;

According to the physical topology of the axial flow fan, the full pressure algorithm block and the flow network algorithm block are called to construct the flow network module, and the input and output are determined;

According to the functional topology of the axial flow fan, the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block are called to construct the sequential module, and the input and output are determined;

The flow net module and the sequential module are called to set the inlet and outlet parameters according to the actual operating conditions to build an axial flow fan simulation model.

Optionally, according to the working principle of the axial flow fan, build a full pressure algorithm block based on Modelica, and determine the input and output, including:

According to the axial flow fan characteristic curve fitting, the fan total pressure-fan mass flow function relationship for different fan stator vane guide vane angles is obtained;

According to the functional relationship between the fan total pressure and the fan mass flow rate at different fan stator vane angles, the fan torque-fan speed at different fan stator vane angles is obtained;

According to the physical topology and the functional relationship in the algorithm block, the input and output are determined. The input of the total pressure algorithm block is the fan mass flow rate, fan speed and stator vane angle, and the output is the fan total pressure and fan torque.

Optionally, according to the working principle of the axial flow fan, build a flow network algorithm block based on Modelica, and determine the input and output, including:

According to the design parameters provided by the manufacturer, the relationship between the fan resistance and the fan design parameters is obtained;

According to Poiseuille's law, the relationship between the fan mass flow rate and the fan inlet and outlet pressure is obtained;

According to the physical topology and the functional relationship in the algorithm block, the input and output are determined. The input of the flow network algorithm block is the inlet static pressure and the total pressure of the fan, and the output is the fan mass flow rate.

Optionally, according to the working principle of the axial flow fan, build a power algorithm block based on Modelica, and determine the input and output, including:

According to the design parameters provided by the manufacturer, obtain the relationship between motor power, motor current and motor voltage;

According to the design parameters provided by the manufacturer, obtain the relationship between the fan shaft power and the fan mass flow rate;

According to the physical topology and the functional relationship in the algorithm block, the input and output are determined. The inputs of the power algorithm block are 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, build a heat exchange algorithm block based on Modelica, and determine the input and output, including:

According to the design parameters provided by the manufacturer, obtain the relationship between the bearing heat generation and the cooling lubricating oil outlet temperature;

According to the physical topology and the functional relationship in the algorithm block, the input and output are determined. The inputs of the heat exchange algorithm block are 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. output temperature.

Optionally, according to the working principle of the axial flow fan, build a safety monitoring algorithm block based on Modelica, and determine the input and output, including:

According to the actual operation history data of the fan, the relationship between the radial vibration of the fan bearing and the fan speed is obtained.

According to the physical topology and the functional relationship in the algorithm block, the input and output are determined. The input of the safety monitoring algorithm block is the fan speed, and the output is the fan bearing radial displacement.

Optionally, the flow net module is used to describe the flow process of fluid medium through the axial flow fan. Its inputs are inlet static pressure, fan speed and stator vane angle, and the output is fan mass flow, fan total pressure and fan speed. moment.

Optionally, the sequential module is used to describe the physical characteristics and behavioral characteristics of the fluid passing through the axial flow fan, and its inputs are fan 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, the output is motor power, motor current, bearing temperature, cooling lubricating oil outlet temperature and fan bearing radial displacement.

According to the second aspect of the embodiment of the present application, a device for constructing an axial flow fan simulation model of the air and smoke system of a thermal power plant is provided, including:

The first construction and determination module is used to construct a total pressure algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The total pressure algorithm block is used to calculate the total fan pressure of the axial flow fan;

The second construction and determination module is used to construct a flow network algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The flow network algorithm block is used to determine the flow resistance of the axial flow fan and the fan mass flow rate. calculate;

The third construction determination module is used to construct a power algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The power algorithm block is used to calculate the motor power of the axial flow fan;

The fourth construction determination module is used to construct a heat exchange algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The heat exchange algorithm block is used to calculate the bearing temperature of the axial flow fan;

The fifth construction and determination module is used to construct a safety monitoring algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The safety monitoring algorithm block is used to calculate the bearing vibration of the axial flow fan;

The sixth construction determination module is used to call the full pressure algorithm block and the flow network algorithm block to build the flow network module according to the physical topology of the axial flow fan, and determine the input and output;

The seventh construction determination module is used to call the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block to build a sequential module according to the functional topology of the axial flow fan, and determine the input and output;

The building module is used to call the flow network module and the sequential module to set the inlet and outlet parameters according to the actual operating conditions to build the axial flow fan simulation model.

According to a third aspect of the embodiment of the present application, an electronic device is provided, including:

one or more processors;

Memory, used to store one or more programs;

When the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method described in the first aspect.

The technical solutions provided by the embodiments of this application may include the following beneficial effects:

As can be seen from the above embodiments, this application constructs a full pressure algorithm block, a flow network solution algorithm block, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block based on Modelica based on the working principle of the axial flow fan, and determines the algorithm The input and output of the block; according to the physical topology and functional topology of the axial flow fan, the full pressure algorithm block and the flow net algorithm block are called to construct the flow net module, and the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block are called Construct a sequential module and determine the input and output of the module; call the flow network module and the sequential module, set the import and export parameters according to the actual operating conditions to build an axial flow fan simulation model. Modeling based on Modelica overcomes the technical problems of traditional modeling methods that are not comprehensive, consider causality, and are not easy to modify and reuse, thereby improving the accuracy and reusability of the axial flow fan simulation model. Applying Modelica to the modeling and simulation of axial flow fans can easily analyze the comprehensive performance of axial flow fans, shorten the research and development cycle, and reduce research and development costs.

It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and do not limit the present application.

Description of the 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.

Figure 1 is a flow chart of a Modelica-based method for building an axial flow fan simulation model of the air and smoke system of a thermal power plant according to an exemplary embodiment.

Figure 2 is a schematic diagram of a heat exchange algorithm block according to an exemplary embodiment.

Figure 3 is a schematic diagram of sequential modules according to an exemplary embodiment.

Figure 4 is a schematic diagram of an axial flow fan simulation model according to an exemplary embodiment.

Figure 5 is a block diagram of a device for building a simulation model of an axial flow fan of a thermal power plant air and smoke system based on Modelica according to an exemplary embodiment.

Detailed ways

Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this application. Rather, they are merely examples of apparatus and methods consistent with aspects of the application as detailed in the appended claims.

The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a," "the" and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It will also be understood that the term "and/or" as used herein refers to and includes any and 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 in this application to describe various information, the information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of the present application, the first information may also be called second information, and similarly, the second information may also be called first information. Depending on the context, the word "if" as used herein may be interpreted as "when" or "when" or "in response to determining."

Figure 1 is a flow chart of a method for constructing an axial flow fan simulation model of a thermal power plant air and smoke system according to an exemplary embodiment. As shown in Figure 1, this method is applied to a terminal and may include the following steps:

S1: According to the working principle of the axial flow fan, build a total pressure algorithm block based on Modelica, and determine the input and output. The total pressure algorithm block is used to calculate the total fan pressure of the axial flow fan;

S2: According to the working principle of the axial flow fan, build a flow network algorithm block based on Modelica, and determine the input and output. The flow network algorithm block is used to calculate the flow resistance of the axial flow fan and the fan mass flow rate;

S3: According to the working principle of the axial flow fan, build a power algorithm block based on Modelica, and determine the input and output. The power algorithm block is used to calculate the motor power of the axial flow fan;

S4: According to the working principle of the axial flow fan, build a heat exchange algorithm block based on Modelica, and determine the input and output. The heat exchange algorithm block is used to calculate the bearing temperature of the axial flow fan;

S5: According to the working principle of the axial flow fan, build a safety monitoring algorithm block based on Modelica, and determine the input and output. The safety monitoring algorithm block is used to calculate the bearing vibration of the axial flow fan;

S6: According to the physical topology of the axial flow fan, call the full pressure algorithm block and the flow network algorithm block to construct the flow network module, and determine the input and output;

S7: According to the functional topology of the axial flow fan, call the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block to build a sequential module, and determine the input and output;

S8: Call the flow net module and sequential module to set the inlet and outlet parameters according to the actual operating conditions to build an axial flow fan simulation model.

As can be seen from the above embodiments, this application constructs a full pressure algorithm block, a flow network solution algorithm block, a power algorithm block, a heat exchange algorithm block and a safety monitoring algorithm block based on Modelica based on the working principle of the axial flow fan, and determines the algorithm The input and output of the block; according to the physical topology and functional topology of the axial flow fan, the full pressure algorithm block and the flow net algorithm block are called to construct the flow net module, and the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block are called Construct a sequential module and determine the input and output of the module; call the flow network module and the sequential module, set the import and export parameters according to the actual operating conditions to build an axial flow fan simulation model. Modeling based on Modelica overcomes the technical problems of traditional modeling methods that are not comprehensive, consider causality, and are not easy to modify and reuse, thereby improving the accuracy and reusability of the axial flow fan simulation model. Applying Modelica to the modeling and simulation of axial flow fans can easily analyze the comprehensive performance of axial flow fans, shorten the research and development cycle, and reduce research and development costs.

In the specific implementation of S1: According to the working principle of the axial flow fan, a total pressure algorithm block is constructed based on Modelica, and the input and output are determined. The total pressure algorithm block is used to calculate the total fan pressure of the axial flow fan. This step can include the following sub-steps:

S11: According to the axial flow fan characteristic curve fitting, the fan total pressure-fan mass flow function relationship for different fan stator blade guide vane angles is obtained;

Specifically, according to the axial flow fan characteristic curve provided by the manufacturer, the data corresponding to the fan total pressure, the fan mass flow rate and the fan stator blade and guide vane angle are obtained, and the fan total pressure-fan with different fan stator vane and guide vane angles are obtained by fitting. Mass flow function relationship.

In the formula, β _i is the different fan stator blade guide vane angle, It is the total pressure of the fan corresponding to different fan stator vane and guide vane angles,/> is the fan mass flow corresponding to different fan stator vane angles, a _i , b _i , c _i , di _, e _i , f _i are the fitting coefficients corresponding to different fan stator vane angles.

S12: Based on the functional relationship between the fan total pressure and the fan mass flow rate at different fan stator vane and guide vane angles, obtain the fan torque-fan speed at different fan stator vane and guide vane angles;

Specifically, according to the similarity rate of the fan and the above fitting function relationship, the fan torque-fan rotation speed functional relationship for different fan stator vane and guide vane angles can be obtained.

In the formula, P is the total pressure of the fan, q _m is the mass flow rate of the fan, N is the fan speed, W is the fan torque, is the fan torque corresponding to different fan stator blade guide vane angles,/> It is the fan speed corresponding to different fan stator blade guide vane angles.

S13: Determine the input and output based on the physical topology and the functional relationship in the algorithm block.

Specifically, according to the physical topology, the fan mass flow rate, fan speed and stator vane angle are determined as the input of the algorithm block, and the fan total pressure and fan torque are the output of the algorithm block.

The total pressure algorithm block is constructed from the above steps. The total pressure algorithm block is used to calculate the total fan pressure of the axial flow fan. It can describe the characteristic curve of the axial flow fan in different working scenarios, increasing the ease of use and versatility of the algorithm block. sex.

In the specific implementation of S2: According to the working principle of the axial flow fan, a flow network algorithm block is constructed based on Modelica, and the input and output are determined. The flow network algorithm block is used to calculate the flow resistance of the axial flow fan and the fan mass flow rate. . This step can include the following sub-steps:

S21: According to the design parameters provided by the manufacturer, obtain the relationship between the fan resistance and the fan design parameters;

Specifically, according to the pipe diameter provided by the manufacturer and the collected actual operating data fluid velocity and fluid density, and according to the resistance formula along the way, the relationship between the fan resistance and the fan design parameters can be obtained.

In the formula, Bsm _i is the flow resistance of the i-th node and the i+1-th node, λ _i is the resistance coefficient of the i-th node and the i+1-th node, D _i is the i-th node and the i+-th node Pipe diameter of 1 node, υ _i fluid flow velocity at the i-th node and i+1-th node, ρ _i is the fluid density at the i-th node and i+1-th node, g is the gravity acceleration.

S22: According to Poiseuille's law, obtain the relationship between the fan mass flow rate and the fan inlet and outlet pressure;

Specifically, according to the collected actual operating conditions, the fan inlet and outlet pressure corresponding to the actual fan mass flow rate, and according to the fluid network formula, the relationship between the fan mass flow rate and the fan inlet and outlet pressure can be obtained

The flow net algorithm block is used to calculate the flow resistance of the axial flow fan and the fan mass flow rate, and describes the relationship between the fan inlet and outlet pressure difference and the fan mass flow rate for different fluids under different working conditions, thereby increasing versatility.

S23: Determine the input and output based on the physical topology and the functional relationship in the algorithm block.

Specifically, according to the physical topology, the inlet static pressure and the total fan pressure are determined as the input of the algorithm block, and the fan mass flow rate is the output of the algorithm block.

The flow network algorithm block is constructed from the above steps. The flow network algorithm block is used to calculate the flow resistance of the axial flow fan and the fan mass flow rate, and describes the relationship between the fan inlet and outlet pressure difference and the fan mass flow rate for different fluids under different working conditions. relationships, increasing versatility.

In the specific implementation of S3: According to the working principle of the axial flow fan, a power algorithm block is constructed based on Modelica, and the input and output are determined. The power algorithm block is used to calculate the motor power of the axial flow fan. This step can include the following sub-steps:

S31: According to the design parameters provided by the manufacturer, obtain the relationship between motor power, motor current and motor voltage;

Specifically, according to the design parameters provided by the manufacturer, such as motor power, motor voltage, and motor rated current, etc., and based on electric power calculations, the relationship between motor power, motor current, and motor voltage can be obtained.

_PE =U·I

In the formula, P _E is the motor power, U is the motor voltage, and I is the motor current.

S32: According to the design parameters provided by the manufacturer, obtain the relationship between the fan shaft power and the fan mass flow rate;

Specifically, according to the design parameters provided by the manufacturer, fan efficiency, shaft efficiency and motor efficiency, and based on the power calculation formula, the relationship between fan shaft power and fan mass flow rate is obtained.

P _E =q _m *P/(3600*n ₁ *n ₂ )

P _E =P _E,N /n ₃

In the formula, P _E,N is the fan shaft power, eta ₁ is the fan efficiency, eta ₂ is the shaft efficiency, and eta ₃ is the motor efficiency.

S33: Determine the input and output based on the physical topology and the functional relationship in the algorithm block.

Specifically, according to the physical topology, the fan mass flow, fan total voltage, motor voltage, fan efficiency, shaft efficiency and motor efficiency are determined as the input of the algorithm block, and the motor power and motor current are the output of the algorithm block.

The power algorithm block is constructed from the above steps, and the power algorithm block is used to calculate the motor power of the axial flow fan and describe the work capability of the axial flow fan motor per unit time.

In the specific implementation of S4: According to the working principle of the axial flow fan, a heat exchange algorithm block is constructed based on Modelica, and the input and output are determined. The heat exchange algorithm block is used to calculate the bearing temperature of the axial flow fan. This step can include the following sub-steps:

S41: According to the design parameters provided by the manufacturer, obtain the relationship between the bearing heat generation and the cooling lubricating oil outlet temperature;

Specifically, according to the design parameters provided by the manufacturer, the motor power, motor efficiency and heat dissipation loss determine the bearing heat, and the heat is transferred to the cooling lubricating oil through metal heat storage. According to the design parameters provided by the manufacturer, the cooling lubricating oil mass flow rate and the cooling lubricating oil inlet temperature. Based on energy conservation, the relationship between the bearing heat generation and the cooling lubricating oil outlet temperature is determined.

Q ₁ =P _E *(1-n ₃ )*n ₄

Q ₂ =q _m *(h _out - h _in )

In the formula, Q ₁ is the heat generated by the fan bearing, η ₄ is the heat dissipation loss, Q ₂ is the heat absorption of the cooling lubricating oil, h _in is the cooling lubricating oil inlet specific enthalpy, h _out is the cooling lubricating oil inlet specific enthalpy, and k is the transmission Thermal coefficient, t _in is the cooling lubricating oil inlet temperature, t _out is the cooling lubricating oil outlet temperature, t _m is the actual metal temperature, n is the correction index under different flow conditions, M is the effective metal mass of the fan bearing, and C _m is Specific heat capacity of metal materials.

S42: Determine the input and output based on the physical topology and the functional relationship in the algorithm block.

Specifically, according to the physical topology, the motor power, motor efficiency, cooling lubricating oil mass flow rate and cooling lubricating oil inlet temperature are determined as the input of the algorithm block, and the bearing temperature and cooling lubricating oil outlet temperature are the output of the algorithm block.

The heat exchange algorithm block is constructed from the above steps, as shown in Figure 2. The heat exchange algorithm block is used to calculate the bearing temperature of the axial flow fan and describe the heat exchange effects of fan bearings of different materials and different types of lubricating oil.

In the specific implementation of S5: According to the working principle of the axial flow fan, a safety monitoring algorithm block is constructed based on Modelica, and the input and output are determined. The safety monitoring algorithm block is used to calculate the bearing vibration of the axial flow fan. This step can include the following sub-steps:

S51: Based on the actual operation history data of the fan, extract the radial vibration of the fan bearing and the fan speed value under different working conditions, and obtain the relationship between the radial vibration of the fan bearing and the fan speed;

Specifically, it is assumed that the wind turbine bearing is constrained and only vibrates in the radial direction, and the wind turbine bearing is simplified into a mechanical model system composed of a series of concentrated masses, springs and dampers with certain motion constraints. According to the design parameters provided by the manufacturer, the quality of the fan bearing and the stiffness coefficient of the fan bearing, as well as the actual operating conditions collected, the radial vibration of the fan bearing and the fan speed, and based on the dynamic laws, the relationship between the fan bearing vibration and the fan speed is established.

ω=2πN

In the formula, y is the radial displacement of the fan bearing, c is the damping coefficient, k is the stiffness coefficient of the fan bearing, ω is the circular frequency, and F ₀ is the interference force.

S52: Determine the input and output based on the physical topology and the functional relationship in the algorithm block.

Specifically, according to the physical topology, the fan speed is determined as the input of the algorithm block, and the radial displacement of the fan bearing is the output of the algorithm block.

A safety monitoring algorithm block is constructed from the above steps. The safety monitoring algorithm block is used to calculate the bearing vibration of the axial flow fan and describe the vibration effect of the bearing under different working conditions.

In the specific implementation of S6: According to the physical topology of the axial flow fan, the full pressure algorithm block and the flow network algorithm block are called to construct the flow network module, and the input and output are determined;

Specifically, according to the physical topology of the axial flow fan, the full pressure algorithm block and the flow network algorithm block are instantiated to construct a flow network module. The flow network module is used to describe the flow process of the fluid medium through the axial flow fan. , where the flow net algorithm block receives the fan total pressure output from the full pressure algorithm block, and the full pressure algorithm block receives the fan mass flow output from the flow net algorithm block. The flow net module describes the flow relationship of different fluids in the axial flow fan, increasing reuse. sex and easy to expand. Determine the input and output. The module input is the inlet static pressure, fan speed and stator vane angle, and the module output is the fan mass flow rate, fan total pressure and fan torque.

In the specific implementation of S7: According to the functional topology of the axial flow fan, the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block are called to construct the sequential module, and the input and output are determined;

Specifically, according to the functional topology of the axial flow fan, the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block are instantiated and used to build a sequential module, as shown in Figure 3. The sequential module is used to describe the physical characteristics and behavioral characteristics of the fluid passing through the axial flow fan. The heat exchange algorithm block receives the motor power output from the power algorithm block, and the safety monitoring algorithm block receives the fan speed in the model input. The sequential module The module describes the internal operating characteristics of the axial flow fan, which is closer to the actual operation. Determine the input and output. The module inputs are fan 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. The module output is motor power and motor current. , bearing temperature, cooling lubricating oil outlet temperature and fan bearing radial displacement.

In the specific implementation of S8: the flow network module and the sequential module are called, and the inlet and outlet parameters are set according to the actual operating conditions to build an axial flow fan simulation model.

Specifically, the flow net module and the sequential module are instantiated, the geometric parameters, design parameters, operation influence parameters, and import and export parameters of the flow net module and the sequential module are set according to the actual operating conditions, and the flow net module and the sequential module are connected. Construct an axial flow fan simulation model, as shown in Figure 4, in which the sequential module receives the fan speed, fan total pressure and fan mass flow rate from the flow network module. The axial flow fan simulation model is used to describe the geometric characteristics, physical characteristics and behavioral characteristics of the axial flow fan, and can better simulate the operation process of the axial flow fan.

Corresponding to the foregoing Modelica-based embodiment of a method for constructing an axial flow fan simulation model of a thermal power plant air and smoke system, this application also provides an embodiment of a Modelica-based device for constructing an axial flow fan simulation model of a thermal power plant air and smoke system.

FIG. 5 is a block diagram of a device for constructing an axial flow fan simulation model of the air and smoke system of a thermal power plant according to an exemplary embodiment. Referring to Figure 5, the device includes:

The first construction determination module 1 is used to construct a total pressure algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The total pressure algorithm block is used to calculate the total fan pressure of the axial flow fan;

The second construction and determination module 2 is used to construct a flow network algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The flow network algorithm block is used to determine the flow resistance of the axial flow fan and the fan mass flow rate. Calculation;

The third construction determination module 3 is used to construct a power algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The power algorithm block is used to calculate the motor power of the axial flow fan;

The fourth construction determination module 4 is used to construct a heat exchange algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The heat exchange algorithm block is used to calculate the bearing temperature of the axial flow fan;

The fifth construction determination module 5 is used to construct a safety monitoring algorithm block based on Modelica according to the working principle of the axial flow fan, and determine the input and output. The safety monitoring algorithm block is used to calculate the bearing vibration of the axial flow fan;

The sixth construction determination module 6 is used to call the full pressure algorithm block and the flow network algorithm block to construct the flow network module according to the physical topology of the axial flow fan, and determine the input and output;

The seventh construction determination module 7 is used to call the power algorithm block, heat exchange algorithm block and safety monitoring algorithm block to build a sequential module according to the functional topology of the axial flow fan, and determine the input and output;

Building module 8 is used to call the flow network module and the sequential module to set the inlet and outlet parameters according to the actual operating conditions to build the axial flow fan simulation model.

Regarding the devices in the above embodiments, the specific manner in which each module performs operations has been described in detail in the embodiments related to the method, and will not be described in detail here.

As for the device embodiment, since it basically corresponds to the method embodiment, please refer to the partial description of the method embodiment for relevant details. The device embodiments described above are only illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in One location, or it can be distributed across multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application. Persons of ordinary skill in the art can understand and implement the method without any creative effort.

Correspondingly, this application also provides an electronic device, including: 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 , so that the one or more processors implement the above-mentioned Modelica-based construction method of the axial flow fan simulation model of the air and smoke system of the thermal power plant.

Correspondingly, this application also provides a computer-readable storage medium on which computer instructions are stored. When the instructions are executed by the processor, the above-mentioned Modelica-based method for constructing an axial flow fan simulation model of the air and smoke system of a thermal power plant is implemented.

Other embodiments of the present application will be readily 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 this application that follow the general principles of this application and include common knowledge or customary technical means in the technical field that are not disclosed in this application. . 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 structures described above and illustrated in the accompanying drawings, and that various modifications and changes may be made 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.