Ice thickness tolerance randomness analysis method and device, terminal and medium

Abstract

The invention discloses an ice thickness tolerance randomness analysis method and device, a terminal and a medium, and the method comprises the steps: obtaining the mean coefficient and variation coefficient of the resistance, permanent load effect and wind load effect of a power transmission tower component based on the design data of the power transmission tower component; obtaining a wind load effect ratio, an ice load effect ratio, a structural importance coefficient, a permanent load subitem coefficient, a live load subitem coefficient and a resistance subitem coefficient; respectively calculating statistical parameters of the resistance, the permanent load effect and the wind load effect; determining a mean value, a variable coefficient and a distribution condition of the ice load tolerance; determining a physical relationship between the ice load tolerance and the ice thickness; and according to the mean value and the standard deviation of the ice load tolerance and the physical relationship between the ice load tolerance and the ice thickness, obtaining a probability model of the ice coating thickness tolerance under the designed ice thickness. On the premise of an existing tower design specification, the randomness of loads and resistance is comprehensively considered, and finally the icing thickness tolerance stochastic analysis method easy to implement is formed.

Description

Technical Field

[0001] The invention relates to the field of component reliability analysis, and in particular to a randomness analysis method, device, terminal and medium for tolerating ice thickness. Background Art

[0002] Reliability analysis plays an important role in evaluating the reliability level of the specification and the safety of the transmission tower design. However, the anti-icing ability of the transmission tower structure cannot be ignored and is even more concerned by the engineering community. However, the corresponding research is obviously less, and it mainly focuses on studying the ultimate bearing capacity of the transmission tower structure through experimental methods or finite element simulation methods. Compared with the reliability analysis of transmission towers, this type of research has the following shortcomings: on the one hand, the randomness of loads and resistance is not fully considered; on the other hand, although the design of each transmission tower is based on the current specifications, it also reflects the subjectivity of the designers. The bearing capacity analysis based on the design of the transmission tower must include the influence of subjectivity, which weakens the reference value of the research results.

[0003] The design specifications of transmission towers reflect the commonality in transmission tower design. Therefore, many scholars have conducted common research on the design specifications in the reliability analysis of transmission towers. However, in the study of the ice resistance of transmission towers, there is still a lack of random analysis of the ice thickness tolerance of transmission tower structures based on design specifications. Summary of the invention

[0004] The present invention provides a random analysis method, device, terminal and medium for tolerable ice thickness, which are applied to tolerable ice thickness analysis under specific circumstances. Carrying out relevant research is helpful to clarify the tolerable ice thickness of transmission towers designed according to current design specifications.

[0005] In order to achieve the above object, the present invention adopts the following technical scheme:

[0006] In a first aspect, the present invention provides a random analysis method for ice thickness tolerance, comprising the following steps:

[0007] Based on the design data of transmission tower components, the mean coefficient and coefficient of variation of the resistance, permanent load effect and wind load effect of transmission tower components are obtained, as well as the wind load effect ratio, ice load effect ratio, structural importance factor, permanent load partial factor, live load partial factor and resistance partial factor are obtained;

[0008] Assuming the standard value of ice load effect as a constant, the statistical parameters of resistance, permanent load effect and wind load effect are calculated separately;

[0009] According to the standard expression, the mean value, coefficient of variation and distribution of the ice load resistance are determined through the statistical parameters of resistance, permanent load effect and wind load effect;

[0010] Determine the physical relationship between ice load and ice thickness based on design specifications and design data;

[0011] According to the mean and standard deviation of the tolerable ice load and the physical relationship between the tolerable ice load and ice thickness, the probability model of the tolerable ice thickness under the designed ice thickness is obtained.

[0012] Furthermore, the statistical parameters of the resistance include the mean of the resistance and the standard deviation of the resistance, the statistical parameters of the permanent load effect include the mean of the permanent load effect and the standard deviation of the permanent load effect, and the statistical parameters of the wind load effect include the mean of the wind load effect and the standard deviation of the wind load effect.

[0013] Furthermore, the calculation formula of the mean value of the resistance is:

[0014]

[0015] Among them, μ R is the mean value of resistance, K R is the mean coefficient of resistance, γ R is the resistance partial coefficient, γ0 is the structural importance coefficient, γ G is the permanent load partial factor, γ Q is the live load partial factor, ρ W is the wind load effect ratio, S Ik =M·I k is the standard value of ice load effect, M is the ice load effect coefficient, I k is the standard value of ice load, ρ I is the ice load effect ratio;

[0016] The standard deviation of the resistance is calculated as:

[0017] σ R =δ R μ R ,

[0018] Among them, σ R is the standard deviation of resistance, δ R is the coefficient of variation of resistance;

[0019] The calculation formula for the mean value of the permanent load effect is:

[0020]

[0021] Among them, μ G is the mean value of the permanent load effect, K G is the mean coefficient of permanent load effect;

[0022] The standard deviation of the permanent load effect is calculated as:

[0023] σ G =δ G μ G ,

[0024] Among them, σ G is the standard deviation of the permanent load effect, δ G is the coefficient of variation of the permanent load effect;

[0025] The calculation formula for the mean value of the wind load effect is:

[0026]

[0027] Among them, μ W is the mean value of wind load effect, K W is the mean coefficient of wind load effect;

[0028] The calculation formula for the standard deviation of the wind load effect is:

[0029] σ W =δ W μ W ,

[0030] Among them, σ W is the standard deviation of wind load effect, K W is the coefficient of variation of wind load effect.

[0031] Furthermore, the mathematical expression of the mean value of the ice load resistance is:

[0032]

[0033] in, is the mean value of the ice load, M is the ice load effect coefficient, μ R is the mean value of resistance, μ G is the mean value of the permanent load effect, μ W is the mean value of wind load effect;

[0034] The mathematical expression of the coefficient of variation of the ice load resistance is:

[0035]

[0036] Among them, σ R is the standard deviation of resistance, σ G is the standard deviation of the permanent load effect, σ W is the standard deviation of wind load effect.

[0037] Furthermore, the distribution of the ice load resistance is obtained by simulating using a Monte Carlo simulation method.

[0038] Furthermore, the mathematical expression of the physical relationship between the ice load resistance and ice thickness is:

[0039] I kN =n s P I πc(c+d I )L V

[0040] Among them, I kN To withstand ice load, n s is the number of wire splits, g is the gravitational acceleration, P I is the ice density, c is the ice thickness, d I L is the outer diameter of the ground wire or single conductor. V It is the actual value of the vertical span of the tower under ice conditions.

[0041] Furthermore, the relationship between the tolerable ice thickness and the tolerable ice load is as follows:

[0042]

[0043] Among them, c N To withstand the ice thickness, I kN To withstand ice load, d I is the outer diameter of the ground wire or single conductor, n s is the number of wire splits, g is the gravitational acceleration, P I is the density of ice, L V It is the actual value of the vertical span of the tower under ice conditions.

[0044] In a second aspect, the present invention provides a random analysis device capable of withstanding ice thickness, the device comprising:

[0045] The parameter acquisition module is used to obtain the mean coefficient and variation coefficient of the resistance, permanent load effect and wind load effect of the transmission tower components according to the design data of the transmission tower components, and obtain the wind load effect ratio, ice load effect ratio, structural importance coefficient, permanent load sub-item coefficient, live load sub-item coefficient, and resistance sub-item coefficient;

[0046] The first calculation module is used to calculate the statistical parameters of resistance, permanent load effect and wind load effect;

[0047] The second calculation module is used to determine the mean value, coefficient of variation and distribution of the tolerable ice load through statistical parameters of resistance, permanent load effect and wind load effect according to the standard expression;

[0048] Model building module, used to determine the physical relationship model between ice load resistance and ice thickness according to design specifications and design data;

[0049] The analysis and calculation module is used to analyze and calculate the probability model of the tolerable ice thickness under the designed ice thickness according to the mean and standard deviation of the tolerable ice load and the physical relationship between the tolerable ice load and the ice thickness.

[0050] In a third aspect, the present invention provides a computer terminal, characterized in that the terminal includes a processor, a memory and a communication interface; the memory and the communication interface are coupled to the processor, the memory is used to store computer program code, and the computer program code includes computer instructions; wherein, when the processor executes the computer instructions, the terminal executes the method described in the first aspect above.

[0051] In a fourth aspect, the present invention provides a computer-readable storage medium, characterized in that the computer-readable storage medium includes computer instructions, and when the computer instructions are executed on a terminal, the terminal executes the method described in the first aspect.

[0052] Compared with the prior art, the present invention has the following beneficial technical effects:

[0053] The present invention is based on the existing pole tower design specifications, comprehensively considers the randomness of load and resistance, carries out random analysis of the ultimate bearing capacity of pole tower components under icing, and studies the probability model of the icing tolerance thickness of the pole tower design specifications in combination with the functional relationship between ice load and wind speed, and provides an approximate analytical expression for the mean and coefficient of variation of the icing tolerance thickness, thereby forming a random analysis method for the icing tolerance thickness that is simple in method steps and easy to implement, thereby accurately analyzing the icing tolerance thickness of the transmission tower structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The drawings in the specification are used to provide further understanding of the present invention and constitute a part of the present invention. The schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0055] Figure 1 is a flow chart of the method of the present invention;

[0056] Figure 2 is a principle block diagram of the device of the present invention;

[0057] Figure 3 is a principle block diagram of the terminal of the present invention;

[0058] Figure 4 The ice load effect S in the present invention is resistant to IN The distribution fitting results of ;

[0059] Figure 5 is the ice thickness c in the present invention N The distribution fitting results of . DETAILED DESCRIPTION

[0060] The present invention is further described below in conjunction with embodiments and drawings.

[0061] Embodiment 1:

[0062] like Figure 1 As shown, this embodiment provides a random analysis method for the ice thickness tolerance of a transmission tower, and analyzes the ice thickness tolerance under the designed ice thickness, including the following steps:

[0063] Step 1: Based on the design data of transmission tower components, obtain the transmission tower component resistance R and permanent load effect S G and wind load effect S W The mean coefficient and coefficient of variation of the wind load effect ratio ρ w , ice load effect ratio ρ I , structural importance factor γ0, permanent load partial factor γ G , live load partial factor γ Q , resistance partial coefficient γ R The specific acquisition process is as follows:

[0064] Based on the design specifications, the ultimate limit state of the transmission tower structure bearing capacity is:

[0065] γ0(γ Gk S Gk +ψγ Q S Qk )≤R k / γ R (1)

[0066] Among them, γ0 is the importance coefficient of the tower structure; γ G is the dead load partial factor; γ Q is the variable load partial factor; γ R is the resistance partial factor; ψ is the variable load combination factor; S Gk is the standard value of permanent load effect; S Qk is the standard value of variable load effect; R k It is the standard value of resistance under the limit state.

[0067] The limit state equation corresponding to the above bearing capacity limit state is:

[0068] RS=0 (2)

[0069] Among them, R is the resistance of the structure; S is the load effect acting on the structure.

[0070] In the reliability calibration and reliability analysis of the design code, usually only simple load combinations are considered, that is, the load effect is determined by the combination of the load effect of the permanent load and the load effect of one variable load. The embodiment of the present invention also adopts a similar processing method.

[0071] For the resistant ice thickness, the load effect S under the simple load combination is composed of the load effect S of the permanent load. G , Load effect of wind load S W and ice load effect S I To determine, that is, S = S G +S W +S I The ice load that a transmission tower can withstand can be expressed as:

[0072] S I =RS G -S W (3)

[0073] In the embodiment of the present invention, the ice load effect under this limit state is called the tolerable ice load effect, denoted by S IN The corresponding ice thickness is the tolerable ice thickness c of the transmission tower. N .

[0074] On the premise of meeting the requirements of the specification, the standard value of resistance under the limit state is:

[0075] R k =γ R γ0[γ G S Gk +γ Q (S Wk +S Ik )] (4)

[0076] Among them, S Wk , S Ik are the standard values ​​of wind load effect and ice load effect, respectively.

[0077] To determine the standard value of resistance, it is necessary to know the standard value of permanent load effect S Gk , Standard value of wind load effect S Wk , Standard value of ice load effect S Ik However, it is difficult to give the absolute values ​​of each standard value based on the standard expression. We can refer to the idea of ​​reliability analysis and give the relative value through the load effect ratio, that is:

[0078] ρ W =S Wk / S Gk (5)

[0079] ρ I =SIk / S Gk (6)

[0080] Therefore, assuming the standard value of ice load effect S Ik is a constant, and the statistical parameters of resistance, permanent load effect and wind load effect are calculated respectively. In this embodiment, the statistical parameters of resistance include the mean value of resistance and the standard deviation of resistance, the statistical parameters of permanent load effect include the mean value of permanent load effect and the standard deviation of permanent load effect, and the statistical parameters of wind load effect include the mean value of wind load effect and the standard deviation of wind load effect.

[0081] Therefore, the calculation formulas for the mean value of resistance, the standard deviation of resistance, the mean value of permanent load effect, the standard deviation of permanent load effect, the mean value of wind load effect, and the standard deviation of wind load effect are as follows:

[0082]

[0083] S Ik =M·I k (8)

[0084]

[0085] σ R =δ R μ R (10)

[0086]

[0087] σ G =δ G μ G (12)

[0088]

[0089] σ W =δ W μ W (14)

[0090] Where: μ R , σ R are the mean and standard deviation of resistance respectively; K R , δ R are the mean coefficient and coefficient of variation of resistance respectively; μ G , σ G are the mean and standard deviation of the permanent load effect; K G , δ G are the mean coefficient and coefficient of variation of permanent load effect respectively; μ W , σ W are the mean and standard deviation of wind load effect respectively; KW , K W are the mean coefficient and variation coefficient of wind load effect respectively. γ0 is the structural importance coefficient, γ G is the permanent load partial factor, γ Q is the live load partial factor, γ R is the resistance partial coefficient.

[0091] Step 2: According to the standard expression, the mean, coefficient of variation and distribution of the tolerable ice load are determined through the statistical parameters of resistance, permanent load effect and wind load effect;

[0092] It is usually assumed that the resistance R and the permanent load effect S G and wind load effect S W Independent of each other, substituting equations (9)-(14) into equation (3) yields the mean value μ of the ice load tolerance: IkN and the coefficient of variation is δ IkN :

[0093]

[0094] Although equations (15) and (16) can determine the statistical parameters of the ice load tolerance, their distribution type cannot be determined. The Monte Carlo method is a computational method based on probability statistics theory that solves mathematical problems by performing a large number of statistical random sampling on a computer. For any given standard value of ice load effect S Ik (such as S Ik =1,2) and the desirable load effect ratio ρ w , I (such as w =1,2;ρ I =1,2), both R and S can be determined Gk and S wk The statistical parameters and probability distribution of , and then combined with formula (3) to perform Monte Carlo simulation, the tolerable ice load effect S IN Based on this sample, we can count S IN On the other hand, the probability density function of the tolerable ice load effect, that is, the distribution type, can be directly obtained by calculating the mean and coefficient of variation of the tolerable ice load effect. Therefore, the distribution type of the tolerable ice load can be determined according to the relationship between the tolerable ice load effect and the tolerable ice load.

[0095] Step 3: Determine the ice load tolerance I according to the design specifications and design data kN The physical relationship between and ice thickness c;

[0096] According to the design specifications, the tower ice load I k The standard value is:

[0097] I k =nsk g k P Ik c0π(c0+d Ik )L Vk (17)

[0098] Among them, n sk , g k , P Ik d Ik , L Vk They are the number of conductor splits, gravitational acceleration, ice density, outer diameter of a single conductor and vertical spacing of towers under icing conditions determined according to specifications.

[0099] The analysis shows that formula (17) actually describes the tolerable ice load I kN The physical relationship between it and the ice thickness c is:

[0100] I kN =n s P I πc(c+d I )L V (18)

[0101] Among them, n s ,g,P I d I , L V It is the true value of the vertical span of the tower for the number of conductor splits, gravitational acceleration, ice density, outer diameter of the ground wire or single conductor and ice coverage conditions.

[0102] Step 4: According to the mean and standard deviation of the tolerable ice load and the physical relationship between the tolerable ice load and ice thickness, a probability model of the tolerable ice thickness under the designed ice thickness is obtained.

[0103] Based on the physical relationship described by formula (18), combined with the stochastic analysis results of the tolerable ice load effect, the stochastic analysis of the tolerable ice thickness can be realized. From formula (18), it can be seen that the tolerable ice thickness c N Withstand ice load I kN There are the following relationships:

[0104]

[0105] After the ice load resistance I is determined through design data kN In the physical relationship between n s ,g,P I d I , L V After the actual value of is obtained, it is substituted into formula (19), and the tolerable ice thickness c can be easily determined by Monte Carlo simulation method. N The statistical parameters and distribution type of , that is, its probability model.

[0106] Embodiment 2:

[0107] like Figure 2 As shown, this embodiment provides a randomness analysis device that can withstand ice thickness, and the device includes:

[0108] The parameter acquisition module is used to obtain the mean coefficient and variation coefficient of the resistance, permanent load effect and wind load effect of the transmission tower components according to the design data of the transmission tower components, and obtain the wind load effect ratio, ice load effect ratio, structural importance coefficient, permanent load sub-item coefficient, live load sub-item coefficient, and resistance sub-item coefficient;

[0109] The first calculation module is used to calculate the statistical parameters of resistance, permanent load effect and wind load effect;

[0110] The second calculation module is used to determine the mean value, coefficient of variation and distribution of the tolerable ice load through statistical parameters of resistance, permanent load effect and wind load effect according to the standard expression;

[0111] Model building module, used to determine the physical relationship model between ice load resistance and ice thickness according to design specifications and design data;

[0112] The analysis and calculation module is used to analyze and calculate the probability model of the tolerable ice thickness under the designed ice thickness according to the mean and standard deviation of the tolerable ice load and the physical relationship between the tolerable ice load and the ice thickness.

[0113] Embodiment three:

[0114] like Figure 3 As shown, this embodiment provides a terminal based on the above-mentioned overall reliability evaluation method, and the terminal includes:

[0115] One or more processors, one or more power supplies, one or more operating systems, one or more databases, memory, one or more network interfaces, and one or more input and output interfaces; wherein one or more programs are stored in the memory;

[0116] When the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the method described in Example 1.

[0117] It should be understood that in the embodiments of the present invention, the processor referred to may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0118] The general processor may be a microprocessor or any conventional processor. The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the type of device. The power supply may meet the power requirements of the computer device for normal operation or overclocking. The operating system may be, for example, Windows Server™, Mac OS X™, Unix™, Linux™, etc. When selecting an operating system, note that the version of the running code corresponds to the operating system.

[0119] Embodiment 4:

[0120] This embodiment provides a computer-readable storage medium, which includes computer instructions. When the computer instructions are executed on a terminal, the terminal executes the steps of the method described in Embodiment 1.

[0121] The computer-readable storage medium may be an internal storage unit of the controller, such as a hard disk or memory of the controller. The computer-readable storage medium may also be an external storage device of the controller, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the controller. The computer-readable storage medium may also include both the internal storage unit of the controller and the external storage device.

[0122] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0123] The present invention is described with reference to the flowcharts and / or block diagrams of the method, terminal device (system), and computer program product according to the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0124] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0125] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0126] Finally, according to the method of the present invention, a random analysis of the ice tolerance thickness of a transmission tower component in a certain place is carried out based on the load specification. The relevant statistical parameters in formula (3) are shown in Table 1.

[0127] Table 1 Statistical parameters of resistance, permanent load effect and wind load effect

[0128] random variable R <![CDATA[S G ]]> <![CDATA[S W ]]> Mean coefficient 1.092 1.000 0.544 Coefficient of variation 0.108 0.050 0.193 Distribution Type Lognormal distribution normal distribution Lognormal distribution

[0129] In formula (4), γ0 = 1.000, γ G =1.200,γ Q =1.400,γ R =1.111.

[0130] I can be calculated by equations (15) and (16): kN The means and coefficients of variation are shown in Tables 2 and 3.

[0131] Table 2 Ice load resistance I kN The calculation result of the mean

[0132]

[0133]

[0134] Table 3 Ice load resistance I kN Calculation results of coefficient of variation

[0135]

[0136] Then, through Monte Carlo simulation, the ice load effect S is obtained. IN The probability density function of , thus fitting its distribution, S Ik = 1, the fitting results are shown in Figure 4 (a) and Figure 4 (b). Among them, Figure 4 (a) ρ w =1,ρ I =1; Figure 4 (b) ρ w =1,ρ I = 2. Tolerance to ice load effect S IN They all approximately obey the log-normal distribution. Since the tolerable ice load effect is linearly related to the tolerable ice load, it is considered that the tolerable ice load obeys the log-normal distribution.

[0137] In formula (18): n s is the number of wire splits, and the ground wire is 1.0 (the present invention takes n s =2.0); g is the acceleration due to gravity, which is 9.80665m / s 2 ;P I is the density of ice, take 0.9g / cm 3 , c0 is the design ice thickness (m); d I The outer diameter of the ground wire or single conductor (the present invention takes d I =21.66mm); L V The vertical span of the tower under the design of icing conditions (the present invention takes L V =550m).

[0138] From formula (19), we can know that the tolerable ice thickness c N and ice load resistance I kN There are the following relationships:

[0139]

[0140] Based on the determined ice load resistance, c can be easily determined by Monte Carlo simulation. N probability information.

[0141] If the design ice thickness in the light ice area is 5 mm, the design ice thickness in the medium ice area is 15 mm, and the design ice thickness in the heavy ice area is 25 mm, the load effect ratio ρ w , I (such as w =0.5,1;ρ I =1, 2). The statistical parameters of the tolerable ice thickness under different design ice thicknesses calculated by formula (20) are shown in Tables 4 and 5. The distribution fitting results of the tolerable ice thickness are shown in Figure 5 ( Figure 5 (a) ρ w =0.5,ρ I =1; Figure 5 (b) ρ w =0.5,ρ I =2; Figure 5 (c) ρ w =1,ρ I =1; Figure 5 (d) ρ w =1,ρ I =2; the designed ice thickness is 5mm), which obeys the log-normal distribution.

[0142] Table 4 Calculation results of the average icing thickness tolerance

[0143]

[0144] Table 5 Calculation results of coefficient of variation of ice thickness tolerance

[0145]

[0146]

[0147] In summary, the present invention takes the existing pole tower design specifications as a premise, comprehensively considers the randomness of load and resistance, conducts random analysis of the ultimate bearing capacity of pole tower components under icing, and studies the probability model of the icing tolerance thickness of the pole tower design specifications in combination with the functional relationship between ice load and wind speed, and gives an approximate analytical expression of the mean and coefficient of variation of the icing tolerance thickness, forming an easy-to-implement random analysis method for the icing tolerance thickness. The method of the present invention is simple and easy to implement.

[0148] Finally, it should be noted that the above description is only a preferred embodiment of the present invention. Under the guidance of the present invention, ordinary technicians in this field can make various similar expressions without violating the purpose and claims of the present invention, and such changes all fall within the scope of protection of the present invention.

Claims

1. A random analysis method for tolerance to ice thickness, characterized in that: The steps include: Based on the design data of transmission tower components, the mean coefficient and coefficient of variation of the resistance, permanent load effect and wind load effect of transmission tower components are obtained, as well as the wind load effect ratio, ice load effect ratio, structural importance factor, permanent load partial factor, live load partial factor and resistance partial factor are obtained; Assuming the standard value of ice load effect as a constant, the statistical parameters of resistance, permanent load effect and wind load effect are calculated separately; According to the standard expression, the mean value, coefficient of variation and distribution of the ice load resistance are determined through the statistical parameters of resistance, permanent load effect and wind load effect; Determine the physical relationship between ice load and ice thickness based on design specifications and design data; According to the mean and standard deviation of the tolerable ice load and the physical relationship between the tolerable ice load and ice thickness, the probability model of the tolerable ice thickness under the designed ice thickness is obtained.

2. The randomness analysis method for ice tolerance according to claim 1, characterized in that: The statistical parameters of the resistance include the mean value of the resistance and the standard deviation of the resistance, the statistical parameters of the permanent load effect include the mean value of the permanent load effect and the standard deviation of the permanent load effect, and the statistical parameters of the wind load effect include the mean value of the wind load effect and the standard deviation of the wind load effect.

3. The randomness analysis method for ice thickness tolerance according to claim 2, characterized in that: The calculation formula for the mean value of the resistance is: Among them, μ R is the mean value of resistance, K R is the mean coefficient of resistance, γ R is the resistance partial coefficient, γ0 is the structural importance coefficient, γ G is the permanent load partial factor, γ Q is the live load partial factor, ρ W is the wind load effect ratio, S Ik =M·I k is the standard value of ice load effect, M is the ice load effect coefficient, I k is the standard value of ice load, ρ I is the ice load effect ratio; The standard deviation of the resistance is calculated as: s R =d R m R , Among them, σ R is the standard deviation of resistance, δ R is the coefficient of variation of resistance; The calculation formula for the mean value of the permanent load effect is: Among them, μ G is the mean value of the permanent load effect, K G is the mean coefficient of permanent load effect; The standard deviation of the permanent load effect is calculated as: s G =d G m G , Among them, σ G is the standard deviation of the permanent load effect, δ G is the coefficient of variation of the permanent load effect; The calculation formula for the mean value of the wind load effect is: Among them, μ W is the mean value of wind load effect, K W is the mean coefficient of wind load effect; The calculation formula for the standard deviation of the wind load effect is: s W =d W m W , Among them, σ W is the standard deviation of wind load effect, δ W is the coefficient of variation of wind load effect.

4. The method for analyzing the randomness of ice thickness tolerance according to claim 1, characterized in that: The mathematical expression of the mean value of the ice load resistance is: in, is the mean value of the ice load, M is the ice load effect coefficient, μ R is the mean value of resistance, μ G is the mean value of the permanent load effect, μ W is the mean value of wind load effect; The mathematical expression of the coefficient of variation of the ice load resistance is: Among them, σ R is the standard deviation of resistance, σ G is the standard deviation of the permanent load effect, σ W is the standard deviation of wind load effect.

5. The randomness analysis method for ice tolerance according to claim 1, characterized in that: The distribution of the ice load resistance is obtained by simulation using the Monte Carlo simulation method.

6. The method for analyzing the randomness of ice thickness tolerance according to claim 1, characterized in that: The mathematical expression of the physical relationship between the ice load resistance and ice thickness is: I kN =n s gP I πc(c+d I )L V Among them, I kN To withstand ice load, n s is the number of wire splits, g is the gravitational acceleration, P I is the ice density, c is the ice thickness, d I L is the outer diameter of the ground wire or single conductor. V It is the actual value of the vertical span of the tower under ice conditions.

7. The randomness analysis method for ice thickness tolerance according to claim 1, characterized in that: The relationship between the tolerable ice thickness and the tolerable ice load is as follows: Among them, c N To withstand the ice thickness, I kN To withstand ice load, d I is the outer diameter of the ground wire or single conductor, n s is the number of wire splits, g is the gravitational acceleration, P I is the density of ice, L V It is the actual value of the vertical span of the tower under ice conditions.

8. A random analysis device tolerant to ice thickness, characterized in that: The device comprises: The parameter acquisition module is used to obtain the mean coefficient and variation coefficient of the resistance, permanent load effect and wind load effect of the transmission tower components according to the design data of the transmission tower components, and obtain the wind load effect ratio, ice load effect ratio, structural importance coefficient, permanent load sub-item coefficient, live load sub-item coefficient, and resistance sub-item coefficient; The first calculation module is used to calculate the statistical parameters of resistance, permanent load effect and wind load effect; The second calculation module is used to determine the mean value, coefficient of variation and distribution of the tolerable ice load through statistical parameters of resistance, permanent load effect and wind load effect according to the standard expression; Model building module, used to determine the physical relationship model between ice load resistance and ice thickness according to design specifications and design data; The analysis and calculation module is used to analyze and calculate the probability model of the tolerable ice thickness under the designed ice thickness according to the mean and standard deviation of the tolerable ice load and the physical relationship between the tolerable ice load and the ice thickness.

9. A computer terminal, characterized in that: The terminal includes a processor, a memory and a communication interface; the memory and the communication interface are coupled to the processor, the memory is used to store computer program code, and the computer program code includes computer instructions; wherein, when the processor executes the computer instructions, the terminal executes the method as described in any one of claims 1 to 7 above.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium comprises computer instructions, and when the computer instructions are executed on a terminal, the terminal is caused to execute the method according to any one of claims 1 to 7.

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