A stall warning method for axial flow power station fans based on stall safety margin assessment

Abstract

The present invention discloses a stall warning method for axial-flow power station fans based on stall safety margin assessment. The method evaluates and corrects the fan performance curve through on-site axial-flow fan performance tests and fan stall line calibration tests. Real-time aerodynamic performance parameters of the fan are acquired based on the fan data acquisition system. Stall critical points under each equal-opening line are calculated based on the corrected axial-flow power station fan performance curve. The stall critical points of the equal-opening line at the measured fan operating point are calculated based on the distribution of the fan's actual operating points on its performance curve. Whether the fan is nearing stall is determined by calculating indicators such as the stall pressure margin coefficient, stall flow margin coefficient, and stall safety factor at the measured fan operating point. The method has clear physical meaning, strong robustness, and high reliability. It is suitable for stall warning of axial-flow fans in large coal-fired units and provides a reliable basis for safe operation and control of axial-flow power station fans.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind power generation, and in particular relates to a stall warning method for an axial flow power station fan based on stall safety margin assessment. Background Art

[0002] Currently, axial-flow fans are widely used in power plant wind turbines. These fans exhibit stall characteristics and are highly sensitive to changes in the resistance parameters of the smoke and air system. Axial-flow fans are particularly susceptible to stalling when improperly selected or when the smoke and air system resistance increases due to various factors after unit modification. Once a fan enters a stalled state, it will operate in an unstable state, with reduced output and a sharp increase in vibration. Without timely intervention, this can damage the fan equipment, impacting the normal operation of the thermal power unit. Currently, power plant wind turbines typically use stall differential pressure switches for stall alarms. However, because these stall alarms utilize changes in the fan's internal flow field during stall, they are only post-failure warnings, requiring operators to respond promptly and intervene; otherwise, the fan will trip. Therefore, reliable and efficient pre-emptive warnings of axial-flow fan stalls remain a pressing technical challenge for the safe operation of power plant wind turbines.

[0003] Currently, many researchers have extracted the changing patterns of various state parameters (such as current, opening, inlet and outlet pressures, and vibration) under normal and abnormal wind turbine operating conditions. Using extensive historical data, they construct monitoring models and compare real-time state parameters with the monitoring models to determine and predict wind turbine stall. However, this approach is limited by the number of samples of abnormal operating conditions, making it difficult to guarantee the accuracy of the monitoring model and prone to false alarms and missed alarms. By monitoring the operating performance parameters of power plant wind turbines in real time, the distance between the actual operating point and the theoretical stall line is assessed, and the stall safety margin coefficient of the wind turbine is obtained in real time. This method, with its clear physical meaning and high accuracy, can provide stall warnings based on the stall safety margin coefficient. This method has significant application value, with its clear physical meaning and high accuracy. In practical applications, due to the varying operating characteristics of the pipe network systems in which wind turbines are located and the varying patterns of the equal-opening pressure curves at the wind turbine operating point, false alarms and missed alarms can still occur when evaluating solely based on the stall safety factor and the limits specified in relevant standards. Summary of the Invention

[0004] In order to realize stall warning of axial flow power station fans, the present invention provides a stall warning method for axial flow power station fans based on stall safety margin assessment.

[0005] The present invention is achieved by adopting the following technical solutions:

[0006] A stall warning method for an axial flow power station fan based on stall safety margin assessment includes the following steps:

[0007] 1) Based on the axial flow fan field performance test and fan stall line calibration test, the fan performance curve is evaluated and corrected to obtain the actual fan performance curve and its actual stall line;

[0008] 2) Build a data acquisition system for power plant fans to obtain real-time aerodynamic performance parameters of power plant fans, calculate the real-time operating point parameters of the fans, and mark them on the corrected performance curve;

[0009] 3) Discretize the performance curve of the modified axial-flow power station fan and construct a cluster of pressure-flow curves and actual stall lines at various openings, and calculate the stall critical point at each opening;

[0010] 4) Based on the measured operating parameters of the fan and their distribution on its performance curve, the adjacent equal-opening pressure-flow curves of the operating point are obtained, and the minimum distance from the measured operating point of the fan to the two adjacent equal-opening pressure-flow curves is calculated, and then the stall critical point of the equal-opening line where the measured operating point of the fan is located is calculated;

[0011] 5) By calculating the relative relationship between the fan's measured operating point and the stall critical point of its equal opening line, it is determined whether the fan is close to stalling, and a stall warning is issued by setting a threshold.

[0012] A further improvement of the present invention is that the specific implementation method of step 1) is as follows:

[0013] 101) According to the normal operating range of the boiler, select N typical load conditions for fan performance test, where N ≥ 3, including the maximum load and maximum load conditions of normal operation, and obtain the main performance parameters of the fan, including fan inlet volume flow Q, fan total pressure P, fan blade opening β and fan efficiency η;

[0014] 102) Based on the deviations between the measured performance parameters of the fan and the design parameters corresponding to the design performance curve, including the opening deviation Δβ and the efficiency deviation Δη, assess whether the actual fan performance curve deviates from its design performance curve; if Δβ>3° or Δη>5%, the fan performance curve is corrected based on the opening and efficiency deviation values ​​under multiple operating conditions;

[0015] 103) According to the structural characteristics of the axial flow fan, the fan flow rate is measured by using the static pressure difference between the collector outlet and the fan inlet. The fan stall line approximation test is carried out under multiple fan openings to obtain the fan stall critical point under each opening. The actual fan stall line P is obtained by cubic spline curve fitting. s =f s (Q), and supplement and verify based on the historical monitoring parameters of the wind turbine.

[0016] A further improvement of the present invention is that in step 2), the fan operating parameters (Q, P) are obtained as follows:

[0017] The average dynamic pressure P of a certain section of the fan inlet pipe is measured in real time by a multi-point matrix flow meter installed at the fan inlet. d , and then calculate the fan inlet volume flow Q according to the Bernoulli equation;

[0018] Based on the static pressure measurement points, temperature measurement points and atmospheric pressure measurement device of the fan inlet and outlet, the fan inlet static pressure P is obtained. in , fan outlet static pressure P out , fan inlet temperature T in , fan outlet temperature T out , and atmospheric pressure P e ;

[0019] Based on the above fan aerodynamic parameters, data processing and calculation are performed according to relevant fan field performance test standards to obtain the main fan operating parameters, namely the fan inlet volume flow rate Q and the fan total pressure P.

[0020] A further improvement of the present invention is that, in step 3), the actual stall critical point set {(Q s ,P s ) β}, as follows:

[0021] 301) Discretize the corrected axial flow fan performance curve to obtain the coordinate point set {(Q i ,P i ) β}, where β∈[βmin,βmax], i=1,2,3,…,n;

[0022] 302) Based on the coordinate point set of each equal opening pressure-flow curve {(Q i ,P i )}, the least square method is used for approximate fitting to obtain the fitting relationship P of the pressure-flow curve of each opening β =f β (Q); the algorithm is as follows:

[0023] Given a data point {(Q j , P j )} and a set of functions g k (Q), j = 1, 2, ..., m, k = 1, 2, ..., n, find the numbers a1, a2, ..., a n , and m>n, so that the function

[0024] f(Q)=a1g1(Q)+a2g2(Q)+...+a n g n (Q)

[0025] satisfy

[0026]

[0027] The form of the approximate function is the polynomial f(Q) = a0+a1Q+a2Q 2 +...+a n Q n ;

[0028] 303) Based on the fitting model P of the pressure-flow curve of each equal opening β =f β (Q) and the actual stall line P of the fan s =f s (Q), construct equation P β -P s =f β (Q)-f s (Q) = 0, the intersection point set of the equal opening line and the actual stall line of the fan is obtained by using the bisection method {(Q s ,P s ) β}, that is, the actual stall critical point set at each opening.

[0029] A further improvement of the present invention is that, in step 4), the specific implementation method is as follows:

[0030] 401) According to the fan operating parameters (Q, P), the fitting model P of the pressure-flow curve of each opening β =f β (Q) and the actual stall line P of the fan s =f s (Q), calculate the intersection of the equal opening line where the fan is operating and the actual stall line of the fan (Q s , P s ), namely the stall critical point;

[0031] 402) Based on the fan operating point (Q, P) and its stall critical point (Q s , P s ), calculate the fan pressure stall margin coefficient k p , flow stall margin coefficient k q and stall safety factor k;

[0032] 403) Different stall warning judgment conditions are set according to different fan types.

[0033] A further improvement of the present invention is that, in step 401), a distance function between the fan operating parameters and each equal opening pressure-flow curve is constructed, and the minimum distance D from the fan operating point to each equal opening curve is calculated by the golden section one-dimensional optimization algorithm. β , β∈[βmin,βmax];

[0034]

[0035] The bubble sorting method is used to find the minimum distance D between the fan operating point and each equal opening curve. β Sort and obtain the two equal opening curves P closest to the fan operating point β =f1(Q) and P β =f2(Q) and its opening values ​​β1 and β2, the minimum distances D1 and D2 from the fan operating point to the two opening curves, and D1 < D2;

[0036] In the discrete degree set of equal opening lines {(Q s ,P s ) β}, find the two stall critical points (Q s,β1 ,P s,β1 ) and (Q s,β2 ,P s,β2 );

[0037] When D1=0, Q s =Q s,β1 , P s =P s,β1 Otherwise, according to the law of equal proportional changes between equal opening lines, the solution equation is constructed as follows:

[0038]

[0039] Where P = f s (Q), Q∈[Q s,β1 ,β s,β2 ];

[0040] The equation is solved by bisection method to obtain the intersection point (Q s , P s ).

[0041] A further improvement of the present invention is that, in step 402), k p =P s / P,k q =Q / Q s ,

[0042] A further improvement of the present invention is that, in step 403), for a primary fan, any of the following conditions is met and an early warning signal is issued:

[0043] 1) k≤1.4;

[0044] 2)k p ≤1.15;

[0045] 3)k q ≤1.1 or QQ s ≤1.1×flow rate change ΔQ when a single mill fails to exit;

[0046] For the blower, any of the following conditions is met and an early warning signal is issued:

[0047] 1) k≤1.4;

[0048] 2)k p ≤1.15;

[0049] 3)k q ≤1.1;

[0050] For induced draft fans, any of the following conditions is met and an early warning signal is issued:

[0051] 1)k≤1.4

[0052] 2)k p ≤1.15 or P s -P≤ΔP, ΔP is obtained based on field tests and historical data analysis;

[0053] 3)k q ≤1.1.

[0054] The present invention has at least the following beneficial technical effects:

[0055] The present invention provides a stall warning method for axial-flow power station fans based on stall safety margin assessment. The method evaluates and corrects the fan performance curve through on-site axial-flow fan performance tests and fan stall line calibration tests. Real-time aerodynamic performance parameters of the fan are acquired based on the fan data acquisition system. Stall critical points under each equal-opening line are calculated based on the corrected axial-flow power station fan performance curve. The stall critical points of the equal-opening line at the measured fan operating point are calculated based on the distribution of the fan's actual operating points on its performance curve. Whether the fan is nearing stall is determined by calculating indicators such as the stall pressure margin coefficient, stall flow margin coefficient, and stall safety factor at the measured fan operating point, and stall warning is issued by setting a threshold. Therefore, the present invention has clear physical meaning, strong robustness, and high reliability. It is suitable for stall warning of axial-flow fans in large coal-fired units and provides a reliable basis for safe operation and regulation of axial-flow power station fans. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 It is a schematic diagram of the principle of the present invention.

[0057] Figure 2 It is a schematic diagram of the distribution of the fan operating points and the stall critical points adjacent to the equal opening line on the fan performance curve of the present invention.

[0058] Figure 3 This is a schematic diagram of the distribution of typical operating points of a fan on its performance curve.

[0059] in, Figure 1 Where Q is the fan inlet volume flow rate, unit is m 3 / s, P is the total pressure of the fan, unit is Pa, β is the opening value of the fan performance curve, unit is °, D1 is the minimum distance between the actual operating point of the fan and the equal opening line 1, D2 is the minimum distance between the actual operating point of the fan and the equal opening line 2, Q s，β1 The flow rate near the stall point of the fan opening line 1, unit: m 3 / s,P s，β1 The total pressure of the fan near the stall point of the opening line 1, unit Pa, Q s，β2 The flow rate near the stall point of the fan equal opening line 2, unit: m 3 / s,P s，β2 The total pressure of the fan near the stall point of the opening line 2, unit Pa, Q s The flow rate near the stall point of the equal opening line where the fan operating point is located, unit: m 3 / s,P s is the total pressure of the stall point near the equal opening line, in Pa, k is the stall safety factor, k p is the stall pressure margin coefficient, k q is the stall flow margin coefficient. DETAILED DESCRIPTION

[0060] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0061] like Figure 1 and Figure 2As shown, the present invention provides a stall warning method for axial flow power station fans based on stall safety margin assessment, including: based on the axial flow fan field performance test and the fan stall line calibration test, evaluating and correcting the fan performance curve; constructing a power station fan data acquisition system to obtain the real-time aerodynamic performance parameters of the power station fan; discretizing the performance curve of the corrected axial flow power station fan and constructing a pressure-flow curve cluster under each opening, and calculating the stall critical point under each opening; according to the distribution of the fan's measured operating point on its performance curve, obtaining the adjacent equal opening pressure-flow curves where the operating point is located, and calculating the minimum distance from the fan's measured operating point to the two adjacent equal opening pressure-flow curves, and then calculating the stall critical point of the equal opening line where the fan's measured operating point is located; by calculating the relative relationship between the fan's measured operating point and the stall critical point of its equal opening line, it is judged whether the fan is close to stalling, and a stall warning is performed by setting a threshold. The specific implementation method is as follows:

[0062] 1. Carry out on-site hot performance tests of axial flow fans and fan stall line calibration tests, and evaluate and correct fan performance curves.

[0063] ① According to the normal operating range of the boiler, N typical load conditions are selected for fan performance test, where N ≥ 3, including the maximum load and maximum load conditions of normal operation, to obtain the main performance parameters of the fan, including fan inlet volume flow Q, fan total pressure P, fan blade opening β, fan efficiency η, etc.

[0064] ② Based on the deviation between the measured performance parameters of the fan and the design parameters corresponding to the design performance curve, including the opening deviation Δβ and the efficiency deviation Δη, evaluate whether the actual fan performance curve deviates from its design performance curve. If Δβ>3° or Δη>5%, the fan performance curve is corrected according to the opening and efficiency deviation values ​​under multiple operating conditions.

[0065] ③ According to the structural characteristics of the axial flow fan, the fan flow rate is measured by using the static pressure difference between the collector outlet and the fan inlet. The fan stall line approximation test is carried out under multiple fan openings to obtain the fan stall critical point under each opening. The actual fan stall line P is obtained by cubic spline curve fitting. s =f s (Q). And supplement and verify based on the historical monitoring parameters of the wind turbine.

[0066] 2. Obtain wind turbine operating parameters (Q, P) in real time through the power station wind turbine online monitoring system.

[0067] ① The average dynamic pressure P of a certain section of the fan inlet pipe is measured in real time by a multi-point matrix flow meter installed at the fan inlet. d , and then the fan inlet volume flow Q is calculated according to the Bernoulli equation.

[0068] ② Based on the static pressure measurement points, temperature measurement points and atmospheric pressure measurement device of the fan inlet and outlet, the fan inlet static pressure P is obtained. in , fan outlet static pressure P out , fan inlet temperature T in , fan outlet temperature T out , atmospheric pressure P e wait.

[0069] ③ According to the relevant fan field performance test standards, data processing and calculation are performed to obtain the main operating parameters of the fan, namely the fan inlet volume flow rate Q and the fan total pressure P.

[0070] 3. Discretize the corrected axial flow fan performance curve {(Q i ,P i ) β}, where β∈[βmin,βmax], i=1,2,3,…,n, obtain the set of stall critical points under each opening {(Q s ,P s ) β}.

[0071] ① Based on the coordinate point set of each equal opening pressure-flow curve {(Q i ,P i )}, the least square method is used for approximate fitting to obtain the fitting relationship P of the pressure-flow curve of each opening β =f β (Q). Its main algorithm is as follows:

[0072] Given a data point {(Q j , P j )}(j=1,2,...,m) and a set of functions g k (Q)(k=1,2,...,n), find the numbers a1,a2,...,a n (assuming m>n), so that the function

[0073] f(Q)=a1g1(Q)+a2g2(Q)+...+a n g n (Q)

[0074] satisfy

[0075]

[0076] The form of the approximate function is the polynomial f(Q) = a0+a1Q+a2Q 2 +...+a n Q n .

[0077] ② Fitting model P based on pressure-flow curves of various openings β =f β (Q) and the actual stall line P of the fan s =f s (Q), construct equation P β -P s =f β (Q)-f s (Q) = 0, the intersection point set of the equal opening line and the actual stall line of the fan is obtained by using the bisection method {(Q s ,P s ) β}.

[0078] 4. According to the fan operating parameters (Q, P), the fitting model P of the pressure-flow curve of each opening β =f β (Q) and the actual stall line P of the fan s =f s (Q), calculate the intersection of the equal opening line where the fan is operating and the actual stall line of the fan (Q s , P s ).

[0079] ① Construct the distance function between the fan operating parameters and the pressure-flow curves of each equal opening, and calculate the minimum distance D from the fan operating point to each equal opening curve through the golden section one-dimensional optimization algorithm. β , β∈[βmin,βmax].

[0080]

[0081] ②Use bubble sorting method to find the minimum distance D between the fan operating point and each equal opening curve β Sort and obtain the two equal opening curves P closest to the fan operating point β =f1(Q) and P β =f2(Q) and its opening values ​​β1 and β2, the minimum distance values ​​D1 and D2 from the fan operating point to the two opening curves, and D1<D2.

[0082] ③ In the discrete degree set of equal opening lines {(Q s ,P s ) β}, find the two stall critical points (Q s,β1 ,P s,β1 ) and (Q s,β2 ,P s,β2 ).

[0083] ④When D1=0, Q s =Q s,β1 , P s=P s,β1 Otherwise, according to the law of equal-proportional change between equal-opening lines, the solution equation is constructed as follows:

[0084]

[0085] Where P = f s (Q), Q∈[Q s,β1 ,β s,β2 ].

[0086] The equation is solved by bisection method to obtain the intersection point (Q s , P s ).

[0087] 5. Stall critical point (Q s , P s ), calculate the fan pressure stall margin coefficient k p , flow stall margin coefficient k q And the stall safety factor k.

[0088] k p =P s / P

[0089] k q =Q / Q s

[0090]

[0091] 6. Set different stall warning judgment conditions according to different fan types.

[0092] For a primary fan, any of the following conditions is met and an early warning signal is issued:

[0093] 1) k≤1.4;

[0094] 2)k p ≤1.15;

[0095] 3)k q ≤1.1 or QQ s ≤1.1×flow rate change ΔQ when a single mill fails to exit.

[0096] For the blower, any of the following conditions is met and an early warning signal is issued:

[0097] 1) k≤1.4;

[0098] 2)k p ≤1.15;

[0099] 3)k q ≤1.1.

[0100] For induced draft fans, any of the following conditions is met and an early warning signal is issued:

[0101] 1) k≤1.4;

[0102] 2)k p ≤1.15 or P s -P≤ΔP, ΔP is obtained based on field tests and historical data analysis;

[0103] 3)k q ≤1.1.

[0104] 7. The present invention has the characteristics of clear physical meaning, strong robustness and high reliability. It is suitable for stall warning of axial flow fans in large coal-fired units and provides a reliable basis for the safe operation and control of axial flow power station fans.

[0105] Example

[0106] A 300MW unit is equipped with two dynamically regulated axial flow primary fans, which are driven by motors and operate under variable load by adjusting the blades. The distribution of the fan operating points on its performance curve under typical operating conditions is shown in the following figure: Figure 3 The stall margin parameters for the operating points of each operating condition are shown in Table 1. During the operation of the unit, the fan experienced a stall phenomenon. To improve the operational safety of the fan, an online monitoring system for the power station fan was added to monitor the fan's aerodynamic performance in real time. The algorithm was compiled using an object-oriented programming language, and the present invention was implemented and embedded in the fan online monitoring system (see Table 1 for the specific calculation process). This achieved advance warning of the fan, allowing power plant operators to make timely adjustments based on the warning situation, thereby improving the operational safety of the fan and preventing the occurrence of fan stall.

[0107] Table 1 Stall warning calculation of fan at typical operating point

[0108]

[0109]

[0110] Although the present invention has been described in detail above using general descriptions and specific embodiments, it will be apparent to those skilled in the art that modifications and improvements may be made based on the present invention. Therefore, such modifications and improvements, which do not depart from the spirit of the present invention, are intended to be within the scope of protection claimed herein.

Claims

1. A stall warning method for axial flow power station fans based on stall safety margin assessment, characterized in that: The following steps are involved: 1) Based on the axial fan field performance test and fan stall line calibration test, the fan performance curve is evaluated and corrected to obtain the actual fan performance curve and its actual stall line. The specific implementation method is as follows: 101) According to the normal operating range of the boiler, select N typical load conditions for fan performance test, where N ≥ 3, including the maximum load and maximum load conditions of normal operation, and obtain the main performance parameters of the fan, including fan inlet volume flow Q, fan total pressure P, fan blade opening β and fan efficiency η; 102) Based on the deviations between the measured performance parameters of the fan and the design parameters corresponding to the design performance curve, including the opening deviation Δβ and the efficiency deviation Δη, assess whether the actual fan performance curve deviates from its design performance curve; if Δβ>3° or Δη>5%, the fan performance curve is corrected based on the opening and efficiency deviation values ​​under multiple operating conditions; 103) According to the structural characteristics of the axial flow fan, the fan flow rate is measured by using the static pressure difference between the collector outlet and the fan inlet. The fan stall line approximation test is carried out under multiple fan openings to obtain the fan stall critical point under each opening. The actual fan stall line P is obtained by cubic spline curve fitting. s =f s (Q), and supplement and verify based on historical monitoring parameters of the wind turbine; 2) Build a data acquisition system for power plant fans to obtain real-time aerodynamic performance parameters of power plant fans, calculate the real-time operating point parameters of the fans, and mark them on the corrected performance curve; 3) Discretize the performance curve of the modified axial-flow power station fan and construct a cluster of pressure-flow curves and actual stall lines at various openings, and calculate the stall critical point at each opening; 4) Based on the measured operating parameters of the fan and their distribution on its performance curve, the adjacent equal-opening pressure-flow curves of the operating point are obtained, and the minimum distance from the measured operating point of the fan to the two adjacent equal-opening pressure-flow curves is calculated. Then, the stall critical point of the equal-opening line where the measured operating point of the fan is located is calculated; 5) By calculating the relative relationship between the fan's measured operating point and the stall critical point of its equal opening line, it is determined whether the fan is close to stalling, and a stall warning is issued by setting a threshold.

2. The stall warning method for an axial flow power station fan based on stall safety margin assessment according to claim 1, characterized in that: In step 2), the fan operating parameters (Q, P) are obtained as follows: The average dynamic pressure P of a certain section of the fan inlet pipe is measured in real time by a multi-point matrix flow meter installed at the fan inlet. d , and then calculate the fan inlet volume flow Q according to the Bernoulli equation; Based on the static pressure measurement points, temperature measurement points and atmospheric pressure measurement device of the fan inlet and outlet, the fan inlet static pressure P is obtained. in , fan outlet static pressure P out , fan inlet temperature T in , fan outlet temperature T out , and atmospheric pressure P e ; Based on the above fan aerodynamic parameters, data processing and calculation are performed according to relevant fan field performance test standards to obtain the main fan operating parameters, namely the fan inlet volume flow rate Q and the fan total pressure P.

3. The stall warning method for axial flow power station wind turbine based on stall safety margin assessment according to claim 2, characterized in that: In step 3), the actual stall critical point set {(Q s ,P s ) β }, as follows: 301) Discretize the corrected axial flow fan performance curve to obtain the coordinate point set {(Q i ,P i ) β }, where β∈[βmin,βmax], i=1,2,3,…,n; 302) Based on the coordinate point set of each equal opening pressure-flow curve {(Q i ,P i )}, the least square method is used for approximate fitting to obtain the fitting relationship P of the pressure-flow curve of each opening β =f β (Q); the algorithm is as follows: Given a data point {(Q j , P j )} and a set of functions g k (Q), j=1,2,...,m, k=1,2,...,n, find the numbers a1, a2,...,a n , and m>n, so that the function f(Q)=a1g1(Q)+a2g2(Q)+...+a n g n (Q) satisfy The form of the approximate function is the polynomial f(Q) = a0+a1Q+a2Q 2 +...+a n Q n ; 303) Based on the fitting model P of the pressure-flow curve of each equal opening β =f β (Q) and the actual stall line P of the fan s =f s (Q), construct equation P β -P s =f β (Q)-f s (Q) = 0, the intersection set of the equal opening line and the actual stall line of the fan is obtained by using the bisection method {(Q s ,P s ) β }, that is, the actual stall critical point set at each opening.

4. The stall warning method for axial flow power station wind turbine based on stall safety margin assessment according to claim 3, characterized in that: In step 4), the specific implementation method is as follows: 401) According to the fan operating parameters (Q, P), the fitting model P of the pressure-flow curve of each opening β =f β (Q) and the actual stall line P of the fan s =f s (Q), calculate the intersection of the equal opening line where the fan is operating and the actual stall line of the fan (Q s , P s ), namely the stall critical point; 402) Based on the fan operating point (Q, P) and its stall critical point (Q s , P s ), calculate the fan pressure stall margin coefficient k p , flow stall margin coefficient k q and stall safety factor k; 403) Different stall warning judgment conditions are set according to different fan types.

5. The stall warning method for axial flow power station wind turbine based on stall safety margin assessment according to claim 4, characterized in that: In step 401), a distance function between the fan operating parameters and each equal opening pressure-flow curve is constructed, and the minimum distance D between the fan operating point and each equal opening curve is calculated by the golden section one-dimensional optimization algorithm. β , β∈[βmin,βmax]; The bubble sorting method is used to find the minimum distance D between the fan operating point and each equal opening curve. β Sort and obtain the two equal opening curves P closest to the fan operating point β =f1(Q) and P β = f2(Q) and its opening values ​​β1 and β2, the minimum distances D1 and D2 from the fan operating point to the two opening curves, and D1 < D2; In the discrete degree set of equal opening lines {(Q s ,P s ) β }, find the two stall critical points (Q s,β1 ,P s,β1 ) and (Q s,β2 ,P s,β2 ); When D1=0, Q s =Q s,β1 , P s =P s,β1 Otherwise, according to the law of equal proportional changes between equal opening lines, the solution equation is constructed as follows: Where P = f s (Q), Q∈[Q s,β1 ,β s,β2 ]; The equation is solved by bisection method to obtain the intersection point (Q s , P s ).

6. The stall warning method for axial flow power station wind turbine based on stall safety margin assessment according to claim 5, characterized in that: In step 402), k p =P s / P,k q =Q / Q s , 7. The stall warning method for axial flow power station wind turbine based on stall safety margin assessment according to claim 6, characterized in that: In step 403), for a primary fan, any of the following conditions is met and an early warning signal is issued: 1)k≤1.4； 2)k p ≤1.15； 3)k q ≤1.1 or QQ s ≤1.1×flow rate change ΔQ when a single mill fails to exit; For the blower, any of the following conditions is met and an early warning signal is issued: 1)k≤1.4； 2)k p ≤1.15； 3)k q ≤1.1； For induced draft fans, any of the following conditions is met and an early warning signal is issued: 1)k≤1.4 2)k p ≤1.15 or P s -P≤ΔP, ΔP is obtained based on field tests and historical data analysis; 3)k q ≤1.1。

Images