CN115809577A - Method and system for assessing fatigue life of metal structures of overhead cranes - Google Patents

Abstract

The invention relates to equipment fatigue life evaluation technology, and provides a method and system for evaluating the fatigue life of a metal structure of a bridge crane. The method includes: determining the position of the dangerous point of the bridge crane, and the dangerous point is a measuring point; arranging a sensor network according to the number and position of the measuring point; obtaining measurement data of each sensor in the sensor network Obtain the stress-time history of the bridge crane according to the measurement data; Statistically analyze the stress-time history of the bridge crane to obtain the statistical characteristics of the load data; compile the bridge according to the statistical characteristics A real-time equivalent load spectrum of the crane; evaluating the remaining fatigue life of the bridge crane according to the real-time equivalent load spectrum. By adopting the embodiment of the present invention, the real-time monitoring of the remaining fatigue life of the bridge crane can be realized, so as to ensure the healthy and safe operation of the equipment.

Description

Method and system for evaluating fatigue life of metal structures of overhead cranes

technical field

The present invention relates to equipment fatigue life evaluation technology, more specifically, to a method and system for evaluating the fatigue life of a metal structure of a bridge crane.

Background technique

Bridge crane is an important material handling equipment, which is widely used in industrial enterprises. Due to the harsh working environment, frequent starting, and large lifting weight of bridge cranes, their failure rate is high, and the number of safety accidents caused by them is relatively high, which has brought great potential safety hazards to people's lives, property and enterprise production. However, the welded structure is one of the most important features of modern bridge cranes. The metal structure and welds are subjected to alternating loads for a long time, and the fatigue damage of the metal structure of the bridge crane gradually accumulates. When the damage limit is reached, macroscopic plastic deformation will occur, resulting in Structural failure, resulting in catastrophic accidents. Therefore, it is of great practical significance and engineering value to carry out the research on the fatigue failure law of the metal structure of the bridge crane and evaluate the remaining fatigue life and reliability of the metal structure to prevent and prevent the fatigue fracture accident of the bridge crane.

The existing technology often adopts the finite element method to study the static strength of the bridge crane structure, analyze the stress/strain value change of the metal structure of the bridge crane under different load levels, and invite experts to judge the bridge crane based on engineering experience and test data. remaining lifetime and safe state. The existing technology is to use the method of theoretical simulation under static load conditions to calculate the stress/strain change of the bridge crane under different load levels, without considering the time-varying nature of the bridge crane load, and it is impossible to quantitatively evaluate the bridge crane. The remaining life, therefore, the analysis results of the prior art have poor engineering practicability, and the evaluation accuracy and precision of the remaining life are low.

Contents of the invention

The invention provides a method and system for automatically evaluating the fatigue life of a metal structure of a bridge crane.

In one aspect, embodiments of the present invention provide a method for assessing fatigue life of a metal structure of an overhead traveling crane, the method comprising:

Determine the position of the dangerous point of the bridge crane, and the dangerous point is the measuring point;

Arranging the sensor network according to the number and position of the measuring points;

Obtain measurement data of each sensor in the sensor network;

Obtaining the stress-time history of the bridge crane according to the measurement data;

Statistical analysis is carried out to the stress-time history of the bridge crane to obtain the statistical characteristics of the load data;

Compiling a real-time equivalent load spectrum of the bridge crane according to the statistical characteristics;

The remaining fatigue life of the bridge crane is evaluated according to the real-time equivalent load spectrum.

In some embodiments, the determination of the location of the dangerous point of the bridge crane includes:

Establish a three-dimensional model of the bridge crane structure;

Generate a finite element model according to the three-dimensional model of the bridge crane structure;

Solving and calculating the finite element model to obtain stress contours, displacement contours and dangerous section positions of the bridge crane;

The position of the dangerous point of the bridge crane is determined according to the working principle and safety margin of the bridge crane, combined with the stress cloud map, the displacement cloud map and the position of the dangerous section.

In some embodiments, statistical analysis is performed on the stress-time history of the bridge crane by rainflow counting to obtain statistical characteristics of the load data.

In some embodiments, compiling the real-time equivalent load spectrum of the bridge crane according to the statistical characteristics includes:

Draw the frequency-amplitude histogram of the stress according to the statistical characteristics of the obtained load data;

The two-parameter Weibull distribution formula is used to fit the frequency-amplitude histogram of the stress to obtain the Weibull approximate expression of the load spectrum of the bridge crane; wherein, the two-parameter Weibull distribution formula is as follows:

In the formula, α is the scale parameter of the Weibull distribution, β is the shape parameter of the Weibull distribution, and SA is the variable range cycle value obtained by the rainflow counting method.

In some embodiments, the method also includes:

Judging that the evaluation value of the remaining life of the bridge crane is greater than the life threshold, an alarm message is sent and the machine is shut down,

If it is judged that the estimated value of the remaining life of the bridge crane is less than the life threshold, the process of acquiring measurement data and evaluating the remaining fatigue life of the bridge crane according to the measurement data is continued.

In another aspect, an embodiment of the present invention also provides a system for evaluating the fatigue life of a metal structure of a bridge crane, which includes:

A data acquisition module, configured to obtain the measurement data of each sensor arranged at each measuring point of the bridge crane;

The data processing module is used to perform the following operations: obtain the stress-time history of the bridge crane according to the measurement data; perform statistical analysis on the stress-time history of the bridge crane to obtain the statistical characteristics of the load data; Compiling a real-time equivalent load spectrum of the bridge crane according to the statistical characteristics; evaluating the remaining fatigue life of the bridge crane according to the real-time equivalent load spectrum.

In some embodiments, the system also includes a measuring point determination module, configured to determine the measuring point of the bridge crane according to the following method:

Establish a three-dimensional model of the bridge crane structure;

Generate a finite element model according to the three-dimensional model of the bridge crane structure;

Solving and calculating the finite element model to obtain stress contours, displacement contours and dangerous section positions of the bridge crane;

According to the working principle and safety margin of the bridge crane, combined with the stress cloud map, displacement cloud map and dangerous section position, determine the dangerous point position of the bridge crane, and the dangerous point is the measuring point.

In some embodiments, the data processing module performs statistical analysis on the stress-time history of the bridge crane by rainflow counting method, so as to obtain the statistical characteristics of the load data.

In some embodiments, the data processing module compiles the real-time equivalent load spectrum of the bridge crane according to the statistical characteristics, including:

Draw the frequency-amplitude histogram of the stress according to the statistical characteristics of the obtained load data;

The two-parameter Weibull distribution formula is used to fit the frequency-amplitude histogram of the stress to obtain the Weibull approximate expression of the load spectrum of the bridge crane; wherein, the two-parameter Weibull distribution formula is as follows:

In the formula, α is the scale parameter of the Weibull distribution, β is the shape parameter of the Weibull distribution, and SA is the variable range cycle value obtained by the rainflow counting method.

In some embodiments, the data processing module also performs the following operations:

Judging that the evaluation value of the remaining life of the bridge crane is greater than the life threshold, an alarm message is sent and the machine is shut down,

If it is judged that the evaluation value of the remaining life of the bridge crane is less than the life threshold, then continue to obtain measurement data through the data acquisition module, and evaluate the remaining fatigue life of the bridge crane according to the measurement data.

According to the embodiment of the present invention, the real-time monitoring of the remaining fatigue life of the bridge crane can be realized, and has the following advantages: ① the selection of dangerous points (measuring points) of the bridge crane is accurate, and the arrangement of the measuring points is accurate; ② real-time monitoring of the bridge crane can be realized. Online status monitoring and early warning; ③The life threshold can be adjusted by itself to ensure the safety of equipment and personnel to the greatest extent.

Various aspects, features, advantages, etc. of the embodiments of the present invention will be specifically described below with reference to the accompanying drawings. According to the following detailed description in conjunction with the accompanying drawings, the above-mentioned aspects, features, advantages, etc. of the present invention will become more clear.

Description of drawings

FIG. 1 is a flowchart of a method for evaluating the fatigue life of a metal structure of an overhead crane according to an embodiment of the present invention.

FIG. 2 is a flowchart illustrating an exemplary processing procedure of step S100 in FIG. 1 .

FIG. 3 is a histogram showing a real-time equivalent load spectrum of an overhead traveling crane according to an embodiment of the present invention.

Fig. 4 is a schematic diagram illustrating Miner's theory.

5 is a logic block diagram of a system for evaluating the fatigue life of a metal structure of an overhead crane according to an embodiment of the present invention.

FIG. 6 is an example of the hardware configuration of the system for evaluating the fatigue life of the metal structure of the bridge crane according to the embodiment of the present invention.

Figure 7 shows an example of a sensor arrangement of an embodiment of the invention.

Detailed ways

Hereinafter, exemplary embodiments will be described in more detail with reference to the accompanying drawings. This invention may, however, be embodied in various different forms and should not be construed as limited to only the embodiments set forth herein. Rather, these embodiments are provided as examples so that this disclosure will be thorough and complete, and will fully convey the aspects and features of the invention to those skilled in the art. Accordingly, procedures, elements and techniques not necessary for a person of ordinary skill in the art to fully understand the aspects and features of the invention may not be described. Throughout the drawings and written description, unless otherwise noted, like reference numerals denote like elements, and therefore descriptions thereof may not be repeated. In addition, features or aspects within each example embodiment should typically be considered as available for other similar features or aspects in other example embodiments.

Certain terms may be used in the following description for informational purposes only and as such are not intended to be limiting. For example, terms such as "top", "bottom", "upper", "lower", "above" and "below" may be used to refer to directions in the drawings to which reference is made. Terms such as "front," "rear," "rear," "side," "outside," and "inside" may be used to describe the orientation and/or position of parts of a component within a consistent but arbitrary frame of reference, described by reference to The orientation and/or position may be clearly understood from the text and associated figures of the components in question. Such terms may include the words specifically mentioned above, their derivatives and words of similar import. Similarly, the terms "first," "second," and other such numerical terms referring to structures do not imply a sequence or order unless clearly indicated by the context.

It will be understood that when an element or feature is referred to as being "on," "connected to," or "coupled to" another element or layer, it can be directly on, connected to, or is coupled to another element or feature, or one or more intervening elements or features may be present. In addition, it will also be understood that when an element or feature is referred to as being "between" two elements or features, it can be the only element or feature between the two elements or features, or one or more elements or features may also be present. Intermediate components or features.

The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting of the invention. As used herein, the singular forms "a" and "an" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the terms "comprising", "comprising" and "having" when used in this specification specify the presence of stated features, integers, steps, operations, elements and/or parts, but do not exclude one or more other Presence or addition of features, integers, steps, operations, elements, parts and/or collections thereof. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. An expression such as "at least one of" when preceding a list of elements modifies the entire list of elements and does not modify the individual elements of the list.

As used herein, the terms "substantially," "about," and similar terms are used as terms of approximation rather than degrees, and are intended to take into account inherent variations in measured or calculated values that one of ordinary skill in the art would recognize. Furthermore, the use of "may" in describing embodiments of the invention means "one or more embodiments of the invention". As used herein, the terms "use," "using," and "used" may be considered synonymous with the terms "utilizing," "utilizing," and "utilized," respectively.

Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It should also be understood that unless expressly so defined herein, terms (such as those defined in commonly used dictionaries) should be interpreted to have a meaning consistent with their meaning in the relevant art and/or in the context of this specification, And it should not be interpreted in an idealized or overly formal sense.

The present invention provides a solution for evaluating the fatigue life of metal structures of overhead cranes. According to the finite element force analysis results of the bridge crane, determine the dangerous points of the bridge crane structure, arrange the measuring points according to the dangerous points of the bridge crane structure, and then arrange the sensor network; use intelligent data online acquisition and processing equipment to collect bridge cranes in real time Structural stress data in the operating state; using the equivalent stress method and the fatigue damage accumulation criterion, combined with the real-time operating data of the equipment, to evaluate the remaining fatigue life of the bridge crane.

FIG. 1 shows a flowchart of a method for evaluating the fatigue life of a metal structure of an overhead crane according to an embodiment of the present invention. In an embodiment, the method for evaluating the fatigue life of a metal structure of an overhead traveling crane comprises:

S100, determining the location of the dangerous point of the bridge crane, where the dangerous point is the measuring point;

S200, arranging a sensor network according to the number and location of the measuring points;

S300. Obtain measurement data of each sensor in the sensor network;

S400, obtaining the stress-time history of the bridge crane according to the measurement data;

S500, performing statistical analysis on the stress-time history of the bridge crane to obtain statistical characteristics of the load data;

S600. Compiling a real-time equivalent load spectrum of the bridge crane according to the statistical characteristics;

S700. Evaluate the remaining fatigue life of the bridge crane according to the real-time equivalent load spectrum.

In some implementation manners, in S100, the determining the location of the dangerous point of the bridge crane includes:

S101, establishing a three-dimensional model of the bridge crane structure. In some embodiments, geometric shapes that have no influence on analysis results (such as chamfers, geometric designs that are not related to functions, etc.) in the three-dimensional model are deleted.

S102. Generate a finite element model according to the three-dimensional model of the bridge crane structure. In some embodiments, the 3D model of the bridge crane is imported into the finite element pre-processing software ANSA for geometric repair, mesh division (surface/body), material property setting, constraint condition setting, boundary condition loading (displacement, force, etc.) ) and analysis step settings to obtain the finite element model. The ANSA (Automatic Net-generation for Structural Analysis) is a finite element pre-processing software, which is mainly used in the modeling process of finite element analysis in collision, fatigue and other fields.

S103. Solve and calculate the finite element model to obtain a stress contour, a displacement contour, and a position of a dangerous section of the bridge crane. In some embodiments, the finite element model (pre-processing file) generated by ANSA is imported into the finite element analysis software (ANSYS/ABAQUS), and the solution calculation is performed to obtain the stress nephogram, displacement nephogram and dangerous section position of the bridge crane.

S104. According to the working principle and safety margin of the bridge crane, and in combination with the stress cloud map, displacement cloud map and dangerous section position, determine the dangerous point position of the bridge crane. In some embodiments, according to the working principle and safety margin of the bridge crane, fatigue analysis software (FE-SAFE: software for fatigue durability analysis and signal processing) is used to determine the location of the dangerous point of the bridge crane.

In some implementations, in S200, the sensor network is arranged according to the number and position of the measuring points, for example, as shown in Figure 7, the strain gauges 3, 4, 5, 8, 9, 10 are respectively installed Crane on cart metal structure. Then, check the working conditions and accuracy of the installed related data acquisition and processing equipment, and correct the signal. In S300-S400, run the equipment, and perform real-time data acquisition and processing to obtain the stress-time history of bridge cranes.

In some embodiments, in S500, statistical analysis is performed on the stress-time history of the bridge crane by rainflow counting method, so as to obtain statistical characteristics such as amplitude and frequency of the data.

In some embodiments, the specific implementation process of the statistical processing of the rainflow counting method is as follows:

(1) Initialize and preprocess the initial data of the stress-time history of the bridge crane, and calculate the extreme values X _max and X _min of the data and the group spacing;

(2) Hierarchical treatment. The stress-time history is graded as follows:

In the formula, C is the group distance, L is the graded series, X _max and X _min are the maximum and minimum values of the measured data, that is, the stress value, respectively.

(3) Statistics of variable range cycle value SA. Perform statistical processing on the variable range cycle value SA, and the median value of the group is processed according to the following formula:

In the formula, SA _J is the median value of the variable-range cycle group of the J-th group, SA _i is the i-th variable-range cycle value of the J-th group, and N is the cycle number of all the variable-range cycles of the J-th group.

(4) Statistics of variable range mean value SM. When dealing with the variable range cycle mean value, its group median value is taken as follows:

In the formula, SM _J is the average value of all variable range cycles of group J, and SM _i is the average value of the ith variable range cycle of group J.

(5) Statistics of total mean SU

In the formula, SU is the average value of all variable range cycles, SM _I is the average value of the first variable range cycle, and Z is the cycle number of all variable range cycles.

Through the above processing, the statistical features such as the amplitude, mean value and frequency of the data are extracted from the initial stress-time history data of the bridge crane, where SM is the mean value of the variable-range cycle data, and SA is the amplitude of the variable-range cycle data , N as the frequency of the variable range cycle.

In some implementations, at S600, compiling the real-time equivalent load spectrum of the bridge crane according to the statistical features, including:

According to the statistical processing results of the aforementioned initial data, draw the frequency-amplitude histogram of the stress. The two-parameter Weibull distribution formula is used to fit the frequency-amplitude histogram of the stress, and the correlation test is carried out to obtain the Weibull approximate expression of the load spectrum of the bridge crane, that is, the two-dimensional load spectrum of the bridge crane. Wherein, the two-parameter Weibull distribution formula is as follows:

In the formula, α is the scale parameter of the Weibull distribution, β is the shape parameter of the Weibull distribution, and SA is the variable range cycle value obtained by the rainflow counting method.

The real-time equivalent load spectrum of the bridge crane obtained through the above processing is shown in Figure 3.

In some embodiments, in S700, the fatigue damage accumulation law (such as Miner's law, etc.) is adopted, combined with the fatigue S-N curve or P-S-N curve of the metal structure, to calculate the fatigue life of the bridge crane at different stress levels, so as to calculate the fatigue life of the bridge crane The remaining fatigue life is evaluated. Among them, the S-N curve takes the fatigue strength (i.e. stress) of the material standard specimen as the ordinate, and takes the logarithmic value lgN of the fatigue life (i.e. the number of cycles) as the abscissa, indicating the fatigue strength and fatigue life of the standard specimen under certain cycle characteristics. The curve of the relationship between them is also called the stress-life curve. The P-S-N curve refers to the S-N curve corresponding to different survival rates P drawn considering the dispersion of fatigue life.

The schematic diagram of Miner theory is shown in Figure 4. In Miner theory, after n _i cycles, the fatigue damage is:

In the formula: n _i is the number of cycles of the i-th stress level in each operation, and N _i is the fatigue life under the i-th stress level.

When the damage of the stress σ _i to the metal structure reaches the critical value D, the material is destroyed, that is

Simplified to get:

In the formula: r is the number of cycle types.

In some embodiments, the method for evaluating the fatigue life of the metal structure of the bridge crane further includes:

Judging that the evaluation value of the remaining life of the bridge crane is greater than the life threshold, an alarm message (for example, text message, sound prompt, light prompt, etc.) is sent and the machine is shut down,

If it is judged that the estimated value of the remaining life of the bridge crane is less than the life threshold, the process of acquiring measurement data and evaluating the remaining fatigue life of the bridge crane according to the measurement data is continued.

The method for evaluating the fatigue life of the metal structure of the bridge crane according to the present invention has been described above. Correspondingly, the embodiment of the present invention also provides a system for evaluating the fatigue life of the metal structure of the bridge crane, as shown in FIG. 5 , the system includes:

A data acquisition module 1100, configured to acquire measurement data of each sensor arranged at each measurement point of the bridge crane;

The data processing module 2100 is configured to perform the following operations: obtain the stress-time history of the bridge crane according to the measurement data; perform statistical analysis on the stress-time history of the bridge crane to obtain the statistical characteristics of the load data ; compiling a real-time equivalent load spectrum of the bridge crane according to the statistical characteristics; evaluating the remaining fatigue life of the bridge crane according to the real-time equivalent load spectrum.

In some embodiments, the system further includes a measuring point determination module (not shown), which is used to determine the measuring points of the bridge crane according to the following method: establish a three-dimensional model of the bridge crane structure; Generate a finite element model according to the three-dimensional model of the bridge crane structure; solve and calculate the finite element model to obtain the stress cloud diagram, displacement cloud diagram and dangerous section position of the bridge crane; according to the working principle of the bridge crane and safety margin, combined with the stress cloud map, displacement cloud map and dangerous section position, determine the location of the bridge crane dangerous point, the dangerous point is the measuring point.

In some implementations, the data processing module 2100 performs statistical analysis on the stress-time history of the bridge crane by rainflow counting method, so as to obtain the statistical characteristics of the load data (data amplitude, frequency, etc.).

In some implementations, the data processing module 2100 compiles the real-time equivalent load spectrum of the bridge crane according to the statistical characteristics, including:

Draw the frequency-amplitude histogram of the stress according to the statistical characteristics of the obtained load data;

The two-parameter Weibull distribution formula is used to fit the frequency-amplitude histogram of the stress to obtain the Weibull approximate expression of the load spectrum of the bridge crane; wherein, the two-parameter Weibull distribution formula is as follows:

In the formula, α is the scale parameter of the Weibull distribution, β is the shape parameter of the Weibull distribution, and SA is the variable range cycle value obtained by the rainflow counting method.

In some implementations, the data processing module 2100 also performs the following operations:

Judging that the evaluation value of the remaining life of the bridge crane is greater than the life threshold, an alarm message is sent and the machine is shut down,

If it is judged that the evaluation value of the remaining life of the bridge crane is less than the life threshold, then continue to obtain measurement data through the data acquisition module, and evaluate the remaining fatigue life of the bridge crane according to the measurement data.

In some embodiments, the system for assessing the fatigue life of a metal structure of an overhead crane may be a computer device comprising a memory and a processor, wherein the memory has computer readable instructions or programs stored thereon, the The processor executes the computer-readable instructions or programs to perform the operations performed by the data acquisition module, data processing module or measurement point determination module. In some embodiments, as shown in FIG. 6, the computer equipment includes an industrial computer 1, which communicates with various sensors through an industrial control board 2, and the sensors include strain gauges 3, 4, 5, 8, 9, 10 and Vibration sensors 6, 7, 11, 12. As shown in Figure 7, the strain gauges 3, 4, 5, 8, 9, and 10 are respectively installed on the metal structure of the cart. Vibration sensors 6, 7, 11, 12 (not shown in Fig. 7) are respectively installed at the four pulley bearing seats of the cart. The measurement data of each sensor is transmitted to the industrial computer 1 through the industrial control board 2, and the industrial computer 1 processes the obtained measurement data according to the method described in each embodiment of the present invention, thereby completing the remaining fatigue life of the bridge crane. estimate. The equipment and device of the present invention are installed on the bridge crane, and as a health status monitoring system of the bridge crane, the health status of the bridge crane can be monitored in real time to ensure the healthy and safe operation of the equipment.

In some embodiments, through the state monitoring system installed on the bridge crane, data such as displacement, stress, and strain of key positions are obtained; a virtual model of the bridge crane is established, and a twin model of the bridge crane is established in combination with real-time operation data , drive the operation of the twin model through the real-time data of the physical model, monitor the operating status of the bridge crane from the twin model, and ensure the safe operation of the equipment.

It should be understood by those skilled in the art that what is disclosed above is only the embodiment of the present invention, and of course it cannot be used to limit the scope of rights for patent protection of the present invention. The equivalent changes made according to the embodiment of the present invention still belong to the rights of the present invention. The scope covered by the request.

Claims (10)

1. A method for evaluating the fatigue life of a metal structure of an overhead crane, characterized in that the method comprises: Determine the position of the dangerous point of the bridge crane, and the dangerous point is the measuring point; Arranging the sensor network according to the number and position of the measuring points; Obtain measurement data of each sensor in the sensor network; Obtaining the stress-time history of the bridge crane according to the measurement data; Statistical analysis is carried out to the stress-time history of the bridge crane to obtain the statistical characteristics of the load data; Compiling a real-time equivalent load spectrum of the bridge crane according to the statistical characteristics; The remaining fatigue life of the bridge crane is evaluated according to the real-time equivalent load spectrum. 2. The method according to claim 1, wherein said determining the position of the dangerous point of said bridge crane comprises: Establish a three-dimensional model of the bridge crane structure; Generate a finite element model according to the three-dimensional model of the bridge crane structure; Solving and calculating the finite element model to obtain stress contours, displacement contours and dangerous section positions of the bridge crane; The position of the dangerous point of the bridge crane is determined according to the working principle and safety margin of the bridge crane, combined with the stress cloud map, the displacement cloud map and the position of the dangerous section. 3. The method according to claim 1, characterized in that statistical analysis is performed on the stress-time history of the bridge crane by rainflow counting method to obtain the statistical characteristics of the load data. 4. The method according to claim 3, characterized in that, the real-time equivalent load spectrum of the bridge crane is compiled according to the statistical characteristics, comprising: Draw the frequency-amplitude histogram of the stress according to the statistical characteristics of the obtained load data; The two-parameter Weibull distribution formula is used to fit the frequency-amplitude histogram of the stress to obtain the Weibull approximate expression of the load spectrum of the bridge crane; wherein, the two-parameter Weibull distribution formula is as follows:

In the formula, α is the scale parameter of the Weibull distribution, β is the shape parameter of the Weibull distribution, and SA is the variable range cycle value obtained by the rainflow counting method. 5. The method according to claim 1, wherein the method further comprises: Judging that the evaluation value of the remaining life of the bridge crane is greater than the life threshold, an alarm message is sent and the machine is shut down, If it is judged that the estimated value of the remaining life of the bridge crane is less than the life threshold, the process of acquiring measurement data and evaluating the remaining fatigue life of the bridge crane according to the measurement data is continued. 6. A system for evaluating the fatigue life of a metal structure of an overhead crane, comprising: A data acquisition module, configured to obtain the measurement data of each sensor arranged at each measuring point of the bridge crane; The data processing module is used to perform the following operations: Obtaining the stress-time history of the bridge crane according to the measurement data; Statistical analysis is carried out to the stress-time history of the bridge crane to obtain the statistical characteristics of the load data; Compiling a real-time equivalent load spectrum of the bridge crane according to the statistical characteristics; The remaining fatigue life of the bridge crane is evaluated according to the real-time equivalent load spectrum. 7. system according to claim 6, is characterized in that, also comprises measuring point determining module, is used for determining the measuring point of described overhead traveling crane according to following method: Establish a three-dimensional model of the bridge crane structure; Generate a finite element model according to the three-dimensional model of the bridge crane structure; Solving and calculating the finite element model to obtain stress contours, displacement contours and dangerous section positions of the bridge crane; According to the working principle and safety margin of the bridge crane, combined with the stress cloud map, displacement cloud map and dangerous section position, determine the dangerous point position of the bridge crane, and the dangerous point is the measuring point. 8 . The system according to claim 6 , wherein the data processing module performs statistical analysis on the stress-time history of the bridge crane by rainflow counting method, so as to obtain the statistical characteristics of the load data. 9. The system according to claim 8, wherein the data processing module compiles the real-time equivalent load spectrum of the bridge crane according to the statistical characteristics, comprising: Draw the frequency-amplitude histogram of the stress according to the statistical characteristics of the obtained load data; The two-parameter Weibull distribution formula is used to fit the frequency-amplitude histogram of the stress to obtain the Weibull approximate expression of the load spectrum of the bridge crane; wherein, the two-parameter Weibull distribution formula is as follows:

In the formula, α is the scale parameter of the Weibull distribution, β is the shape parameter of the Weibull distribution, and SA is the variable range cycle value obtained by the rainflow counting method. 10. The system according to claim 6, wherein the data processing module also performs the following operations: Judging that the evaluation value of the remaining life of the bridge crane is greater than the life threshold, an alarm message is sent and the machine is shut down, If it is judged that the evaluation value of the remaining life of the bridge crane is less than the life threshold, then continue to obtain measurement data through the data acquisition module, and evaluate the remaining fatigue life of the bridge crane according to the measurement data.

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