Crane load spectrum compiling method, computing device and computer readable storage medium

Abstract

The application discloses a crane load spectrum compiling method, a computing device and a readable storage medium. The method comprises the following steps: acquiring hoisting data of a preset number of target cranes in at least one working condition within a preset time length; analyzing the hoisting data to obtain the number of each type of work cycle contained in each working condition; the work cycle refers to the process from starting to hoist an article to starting to hoist the next article; screening each type of work cycle according to the number, and determining the occurrence probability of at least one target type of work cycle obtained after the screening; determining the occurrence number of each target type of work cycle in the life cycle of the target crane according to the total work cycle number of the target crane in the life cycle and the occurrence probability; and determining the load spectrum of the target crane based on the occurrence number. In this way, the crane load spectrum can be conveniently compiled, and the compiling efficiency and applicability of the crane load spectrum are improved.

Description

Technical Field

[0001] This invention relates to the field of crane technology, and in particular to a method for compiling crane load spectra, a computing device, and a computer-readable storage medium. Background Technology

[0002] Current crane design specifications do not provide a load spectrum for calculating crane fatigue. However, a crane typically has a lifespan of over ten years, making it impractical to collect data throughout its entire lifespan to calculate the corresponding load spectrum. Furthermore, existing methods for compiling crane load spectra suffer from being cumbersome, costly, and lacking in applicability. Summary of the Invention

[0003] The purpose of this application is to provide a method, computing device and readable storage medium for compiling crane load spectra, which enables convenient compilation of crane load spectra and improves the efficiency and applicability of crane load spectra compilation.

[0004] To achieve the above objectives:

[0005] In a first aspect, embodiments of this application provide a method for compiling a crane load spectrum, including:

[0006] Acquire lifting data of a preset number of target cranes under at least one working condition within a preset time period;

[0007] Analyze the hoisting data to obtain the number of each type of work cycle under each working condition; the work cycle refers to the process from the start of hoisting one item to the start of hoisting the next item.

[0008] Based on the quantity, the work cycles of each type are filtered, and the probability of occurrence of at least one target type of work cycle obtained after filtering is determined.

[0009] Based on the total number of working cycles of the target crane during its life cycle and the probability of occurrence, determine the number of times each target type of working cycle occurs during the life cycle of the target crane.

[0010] Based on the number of occurrences, the load spectrum of the target crane is determined.

[0011] Optionally, the analysis of the hoisting data to obtain the number of each type of work cycle included in each of the aforementioned working conditions includes:

[0012] The hoisting data is identified to obtain parameters for at least one work cycle under each of the aforementioned working conditions; the parameters include the load weight, the luffing angle at the starting point, and the luffing angle at the ending point.

[0013] The hoisting load range is divided according to the load weight of at least one work cycle included in the target working condition to obtain at least one hoisting load range under the target working condition; the target working condition is any working condition.

[0014] Based on at least one preset amplitude angle range and at least one hoisting load range under the target working condition, the at least one work cycle included under the target working condition is classified into types to obtain the number of work cycles corresponding to each type under the target working condition.

[0015] Optionally, the step of dividing the lifting load range according to the load weight of the work cycle included in the target working condition to obtain at least one lifting load range under the target working condition includes:

[0016] Based on the load weight of at least one work cycle contained in the target working condition, obtain the maximum load weight and the minimum load weight in the at least one work cycle contained in the target working condition.

[0017] Based on the maximum load weight, the minimum load weight, and the preset maximum load value and preset minimum load value under the target working condition, the hoisting load range is divided according to a preset method to obtain at least one hoisting load range under the target working condition.

[0018] Optionally, before classifying at least one work cycle included in the target working condition according to at least one preset amplitude angle range and at least one hoisting load range under the target working condition, and obtaining the number of work cycles corresponding to each type included in the target working condition, the process includes:

[0019] The luffing angle range of the target crane boom is divided at preset angle intervals to obtain at least one luffing angle interval.

[0020] Optionally, the step of filtering each type of work cycle according to the quantity and determining the occurrence probability of at least one target type of work cycle obtained after filtering includes:

[0021] Sort the work cycles of each type according to the stated quantity, and obtain the sorting results;

[0022] Based on the sorting results, the corresponding types of work cycles are selected as target type work cycles in descending order of quantity, until the ratio between the sum of the quantities of the selected target type work cycles and the total quantity of all types of work cycles is greater than or equal to a preset threshold.

[0023] The probability of occurrence of each target type's work cycle is determined based on the number of work cycles corresponding to each target type and the preset number.

[0024] Optionally, determining the probability of occurrence of each target type's work cycle based on the number of work cycles corresponding to each target type and the preset number includes:

[0025] The frequency of the work cycle corresponding to the target type is determined by the quotient of the number of work cycles corresponding to the target type and the target value; the target value is the sum of the preset threshold and the preset number.

[0026] The probability of occurrence of each target type's work cycle is determined by the ratio of the frequency of each target type's work cycle to the sum of the frequencies of all target types' work cycles.

[0027] Optionally, determining the occurrence count of each target type's work cycle within the target crane's lifecycle based on the total number of work cycles and the occurrence probability within the target crane's lifecycle includes:

[0028] Based on the usage level of the target crane, determine the total number of working cycles of the target crane during its life cycle;

[0029] The product of the total number of working cycles of the target crane during its life cycle and the probability of occurrence of the working cycle corresponding to the target type is determined as the number of times the working cycle of the target type occurs during the life cycle of the target crane.

[0030] Optionally, determining the load spectrum of the target crane based on the number of occurrences includes:

[0031] The work cycles of each target type are sorted according to the load weight, and the corresponding occurrence counts are added to generate the load spectrum of the target crane.

[0032] Secondly, embodiments of this application provide a computing device, including: a processor and a memory storing a computer program, wherein when the processor runs the computer program, the above-described crane load spectrum compilation method is implemented.

[0033] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-described crane load spectrum compilation method.

[0034] The crane load spectrum compilation method, computing device, and computer-readable storage medium provided in this application embodiment include: acquiring hoisting data of a preset number of target cranes under at least one working condition within a preset time period; analyzing the hoisting data to obtain the quantity of each type of work cycle included in each working condition; the work cycle refers to the process from the start of hoisting one item to the start of hoisting the next item; filtering each type of work cycle according to the quantity, and determining the occurrence probability of at least one target type of work cycle obtained after filtering; determining the occurrence frequency of each target type of work cycle in the life cycle of the target crane according to the total number of work cycles in the life cycle of the target crane and the occurrence probability; and determining the load spectrum of the target crane based on the occurrence frequency. Thus, based on the lifting data of a preset number of target cranes under at least one working condition within a preset time period, the number of work cycles of each type included in each working condition is determined, and the work cycles of each type are filtered according to the number. Then, based on the occurrence probability of the work cycle of at least one target type obtained by the filtering and the total number of work cycles of the target crane in its life cycle, the load spectrum of the target crane is generated. This makes the compiled crane load spectrum more reflective of the actual use of the crane, and at the same time, it enables convenient compilation of crane load spectrum, improves the compilation efficiency and applicability of crane load spectrum, and lays the foundation for calculating fatigue life. Attached Figure Description

[0035] Figure 1 A schematic flowchart of the crane load spectrum compilation method provided in an embodiment of the present invention;

[0036] Figure 2 This is a schematic diagram illustrating the identification of the working cycle in an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram of the structure of a computing device provided in an embodiment of the present invention. Detailed Implementation

[0038] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0039] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, components, features, and elements with the same names in different embodiments of this application may have the same meaning or different meanings, the specific meaning of which must be determined by its interpretation in that specific embodiment or further in conjunction with the context of that specific embodiment.

[0040] It should be understood that although the terms first, second, third, etc., may be used herein to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this document, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if," as used herein, can be interpreted as "when," "when," or "in response to determination." Furthermore, as used herein, the singular forms "a," "an," and "the" are intended to also include the plural forms unless the context indicates otherwise. It should be further understood that the terms "comprising," "including," indicate the presence of the stated feature, step, operation, element, component, item, kind, and / or group, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" as used herein are to be interpreted as inclusive, or mean any one or any combination thereof. Therefore, "A, B, or C" or "A, B, and / or C" means "any one of the following: A; B; C; A and B; A and C; B and C; A, B, and C". Exceptions to this definition will only occur if the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0041] It should be understood that although the steps in the flowcharts of this application's embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0042] It should be noted that step designations such as S101 and S102 are used in this document for the purpose of more clearly and concisely describing the corresponding content, and do not constitute a substantial limitation on the order. In specific implementation, those skilled in the art may execute S102 first and then S101, etc., but these should all be within the protection scope of this application.

[0043] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0044] In the following description, the use of suffixes such as "module," "part," or "unit" to denote elements is solely for the purpose of illustrative purposes and has no specific meaning in itself. Therefore, "module," "part," or "unit" may be used interchangeably.

[0045] See Figure 1 This application provides a method for compiling a crane load spectrum, which can be executed by a crane load spectrum compilation device provided in this application. The crane load spectrum compilation device can be implemented using software and / or hardware, such as a computer or server. In this embodiment, a computer is used as the executing entity for the crane load spectrum compilation method. The crane load spectrum compilation method provided in this embodiment includes:

[0046] Step S101: Obtain lifting data of a preset number of target cranes under at least one working condition within a preset time period.

[0047] The target crane is the crane for which load spectrum compilation is required, and its specific model can be set based on actual needs. The preset quantity can also be set based on actual needs, such as 50 or 100 units. The preset duration can also be set based on actual needs, such as one month or one year, without specific limitations. When the target crane performs lifting operations under different working conditions, it can collect corresponding lifting data through set data acquisition devices such as sensors. This lifting data can include at least the correspondence between time and load data under different working conditions, as well as data such as slewing angle, luffing angle, and lifting angle.

[0048] One working condition can be determined by combining characteristic parameters of the crane, such as outrigger extension type, counterweight, boom combination method, main boom length, jib length, and jib installation angle. For example, a working condition can be defined by combining fully extended outriggers, a 5-ton counterweight, and a 5-meter main boom.

[0049] Step S102: Analyze the hoisting data to obtain the quantity of each type of work cycle under each working condition; a work cycle refers to the process from the start of hoisting one item to the start of hoisting the next item.

[0050] Here, by analyzing hoisting data and determining the effective operating time range for each working condition based on the time points of change for each condition, the time range for each work cycle is obtained by identifying the time points of significant load changes within the effective operating time range. This allows for the determination of parameters for each work cycle, including load weight, the slewing angle, luffing angle, and hoisting angle corresponding to the starting point, and the slewing angle, luffing angle, and hoisting angle corresponding to the ending point. Each working condition may contain multiple work cycles, and the load weight of a work cycle can be the average load weight within the time range of that work cycle.

[0051] It is understandable that after the crane enters the work-ready state according to the set working conditions, it controls the movement of the hook to achieve lifting through three operations: slewing, luffing, and hoisting. That is, a crane lifting operation process is to first move the hook to the lifting point above the object to be lifted and hook it, then move the object to the target position and unhook it, and finally move the hook away from the target position where the object is located. In the lifting operation process, there are usually three movement processes: slewing, luffing, and hoisting. Considering that the slewing and hoisting movements do not change the torque, for the sake of simplicity, this embodiment only considers the change of luffing angle in the lifting operation process and ignores the movement change process from the start to the end of the lifting operation. That is, each work cycle is simplified as the start and end of the luffing angle.

[0052] The type of work cycle can be determined based on the parameters of the work cycle. The types of work cycles under the same working condition may be the same or different.

[0053] In one embodiment, the hoisting data is analyzed to obtain the quantity of each type of work cycle included in each working condition, including:

[0054] The hoisting data is identified to obtain parameters for at least one work cycle under each working condition; the parameters include the load weight and the luffing angle at the starting point and the luffing angle at the ending point.

[0055] The hoisting load range is divided according to the load weight of at least one work cycle included in the target working condition to obtain at least one hoisting load range under the target working condition; the target working condition is any working condition.

[0056] Based on at least one preset amplitude angle range and at least one lifting load range under the target working condition, the at least one working cycle included under the target working condition is classified into types to obtain the number of working cycles corresponding to each type under the target working condition.

[0057] First, by identifying the lifting data of a preset number of target cranes under at least one working condition, parameters of at least one work cycle contained in each working condition can be obtained. Each working condition may contain multiple work cycles. Next, for any working condition, i.e., the target working condition, the lifting load range is divided based on the load weight of the at least one work cycle contained in the target working condition, thus obtaining at least one lifting load range for the target working condition. Then, based on the preset at least one luffing angle range and the at least one lifting load range for the target working condition, the at least one work cycle contained in the target working condition is classified by type. Work cycles with load weights belonging to the same lifting load range and luffing angles belonging to the same luffing angle range are classified as work cycles of the same type, thereby obtaining the type of at least one work cycle contained in the target working condition, and subsequently determining the number of work cycles corresponding to each type.

[0058] Here, the luffing angle of the target crane's main boom can be pre-divided into several equal luffing angle intervals, with each interval being the same size. The load weight of any work cycle can be considered as the average load weight over the time range of that work cycle. It should be noted that luffing angles belonging to the same interval mean that the luffing angle at the starting point and the luffing angle at the ending point both belong to the same interval. For example, taking the load weights of work cycles a, b, and c as belonging to the same lifting load range, assuming that the amplitude angle at the start of work cycle a belongs to amplitude angle range B1 and the amplitude angle at the end of work cycle a belongs to amplitude angle range C1, if the amplitude angle at the start of work cycle b belongs to amplitude angle range B1 and the amplitude angle at the end of work cycle b belongs to amplitude angle range C1, then it can be determined that work cycles a and b are of the same type; if the amplitude angle at the start of work cycle c belongs to amplitude angle range B1 and the amplitude angle at the end of work cycle c belongs to amplitude angle range C2, then it can be determined that work cycles a and c are of different types.

[0059] In one embodiment, the hoisting load range is divided according to the load weight of the work cycle included in the target working condition to obtain at least one hoisting load range under the target working condition, including:

[0060] Based on the load weight of at least one working cycle contained in the target working condition, obtain the maximum load weight and the minimum load weight in at least one working cycle contained in the target working condition.

[0061] Based on the maximum and minimum load weights, as well as the preset maximum and minimum load values ​​under the target working conditions, the hoisting load range is divided according to a preset method to obtain at least one hoisting load range under the target working conditions.

[0062] It is understood that by comparing the load weights of at least one work cycle within the target working condition, the maximum and minimum load weights within that work cycle can be determined. The preset maximum and minimum load values ​​for the target working condition can be obtained by consulting a preset lifting capacity table, as detailed in existing technical specifications. After obtaining the maximum and minimum load weights, as well as the preset maximum and minimum load values ​​for the target working condition, the lifting load range can be divided according to a preset method based on the relationship between the maximum load weight and the preset maximum load value, and the relationship between the minimum load weight and the preset minimum load value, thus obtaining at least one lifting load range for the target working condition. The preset method can be set according to actual needs. For example, when the minimum load weight is greater than or equal to the preset minimum load value and the maximum load weight is less than or equal to the preset maximum load value, the load range between the preset minimum load value and the preset maximum load value can be divided into n lifting load intervals by preset load intervals. The preset load interval is the difference between the preset maximum load value and the preset minimum load value divided by n, where n is a preset positive integer. Alternatively, when the minimum load weight is less than the preset minimum load value and the maximum load weight is less than or equal to the preset maximum load value, the load range between the first load weight and the preset maximum load value can be divided into multiple lifting load intervals by preset load intervals. The first load weight is the difference between the preset minimum load value and the second load weight, the second load weight is the product of the preset load interval and the first target quantity, and the first target quantity is the smallest integer greater than the first target value. The target value is obtained by dividing the difference between the preset minimum load value and the minimum load weight by the preset load interval. For example, when the minimum load weight is greater than or equal to the preset minimum load value and the maximum load weight is greater than the preset maximum load value, the load range from the preset minimum load value to the third load weight can be divided into multiple lifting load intervals using preset load intervals. The third load weight is the sum of the preset maximum load value and the fourth load weight, and the fourth load weight is the product of the preset load interval and the second target quantity. The second target quantity is the smallest integer greater than the second target value, and the second target value is obtained by dividing the difference between the maximum load weight and the preset maximum load value by the preset load interval. Similarly, when the minimum load weight is less than the preset minimum load value and the maximum load weight is greater than the preset maximum load value, the load range from the first load weight to the third load weight can be divided into multiple lifting load intervals using preset load intervals. This allows for precise and rapid division of lifting load intervals, improving the accuracy of work cycle type division and further enhancing the efficiency of crane load spectrum compilation.

[0063] Specifically, for any work cycle included in the target working condition, the amplitude angle intervals of the starting and ending points of the work cycle can be determined based on at least one preset amplitude angle interval. Furthermore, the load weight interval of the work cycle can be determined based on at least one hoisting load interval under the target working condition. Then, using the hoisting load interval, the amplitude angle interval of the starting point, and the amplitude angle interval of the ending point as classification indicators, work cycles with the same hoisting load interval, the same amplitude angle interval of the starting point, and the same amplitude angle interval of the ending point are considered to be of the same type. For example, if the load weight of a work cycle falls within the first load range, the luffing angle range at the starting point is the first luffing angle range, and the luffing angle range at the end point is the first luffing angle range, then the work cycle can be classified as type one. Similarly, if the load weight of a work cycle falls within the first load range, the luffing angle range at the starting point is the first luffing angle range, and the luffing angle range at the end point is the second luffing angle range, then the work cycle can be classified as type two, and so on. Here, after determining the type of each work cycle included in the target working condition, the number of work cycles of each type can be statistically obtained. This allows for rapid and accurate classification of work cycles, facilitating the subsequent generation of crane load spectra and further improving the efficiency and applicability of crane load spectra compilation.

[0064] In one embodiment, before classifying at least one work cycle included in the target working condition into types based on at least one preset amplitude angle range and at least one lifting load range under the target working condition, and obtaining the type and corresponding quantity of at least one work cycle included in the target working condition, the process includes:

[0065] The luffing angle range of the target crane boom is divided by a preset angle interval to obtain the at least one luffing angle interval.

[0066] The luffing angle range of the target crane's main boom can be obtained based on the lifting height curve of the target crane's main boom. After determining the luffing angle range of the target crane's main boom, the luffing angle variation range can be divided according to preset angle intervals such as 5 degrees, 10 degrees, etc., to obtain at least one luffing angle interval. Here, the luffing angle at the beginning and end of a work cycle may be in the same luffing angle interval or in different luffing angle intervals.

[0067] Step S103: Filter the work cycles of each type according to the quantity, and determine the probability of occurrence of at least one target type of work cycle obtained after filtering.

[0068] It is understandable that the number of different types of work cycles varies, with some types having a larger number of work cycles and others having a smaller number. Considering that the fewer types of work cycles are not very meaningful for the load spectrum, and in order to speed up the generation of the load spectrum, the work cycles of each type can be screened according to their number to select the more typical types of work cycles for load spectrum generation.

[0069] In one embodiment, the process involves filtering work cycles of various types based on quantity and determining the probability of occurrence of at least one target type of work cycle obtained after filtering, including:

[0070] Sort the work cycles of each type according to quantity, and obtain the sorting results;

[0071] Based on the sorting results, the corresponding types of work cycles are selected as the target type work cycles in descending order of quantity, until the ratio between the sum of the quantities of the selected target type work cycles and the total quantity of all types of work cycles is greater than or equal to a preset threshold.

[0072] Based on the number of work cycles corresponding to each target type and the preset number, determine the probability of occurrence of work cycles corresponding to each target type.

[0073] It should be noted that sorting the work cycles of different types by quantity can be done either in descending order of quantity or in ascending order of quantity; no specific limitation is made here. Based on the sorting results, the quantity ranking of different types of work cycles can be obtained. At this point, work cycles of the corresponding types can be selected sequentially in descending order of quantity as target type work cycles until the ratio between the sum of the quantities of the selected target type work cycles and the total quantity of all types of work cycles is greater than or equal to a preset threshold. For example, suppose the sorting results of the work cycles of each type, in descending order of quantity, are work cycles A1, A2, A3, A4, and A5, and the corresponding quantities of work cycles of each type are n1, n2, n3, n4, and n5, respectively. Let n be the total quantity of work cycles of all types. Then, A1 is first selected as the target type work cycle. If the ratio of n1 to n is less than a preset threshold, A2 is selected as the target type work cycle. If the ratio of (n1+n2) to n is less than the preset threshold, A3 is selected as the target type work cycle, and the ratio of (n1+n2+n3) to n is checked to see if it is less than the preset threshold. This process is repeated. If the ratio of (n1+n2) to n is greater than the preset threshold, the selection operation stops, and the selected target type work cycles include A1 and A2. The preset threshold can be set according to actual needs, such as 0.8 or 0.85, etc., without specific limitations here.

[0074] Here, one approach is to first categorize at least one working condition to obtain at least one working condition type. For example, based on the outrigger extension type and the usage of the main and auxiliary booms, the working condition types can be divided into four categories: outriggers fully extended and using the main boom, outriggers partially extended and using the main boom, outriggers fully extended and using the auxiliary boom, and outriggers partially extended and using the auxiliary boom. Then, for each working condition type, i.e., the target working condition type, the work cycles of each type contained in the working condition under the target working condition type can be sorted in descending order of quantity to obtain the sorting result of the work cycles of each type contained in the working condition under the target working condition type. Next, based on the sorting result corresponding to the target working condition type, the corresponding type of work cycle can be selected sequentially in descending order of quantity as the target type of work cycle under the target working condition type, until the ratio between the sum of the quantities of the selected target type of work cycles and the total quantity of the various types of work cycles contained in the working condition under the target working condition type is greater than or equal to a preset threshold.

[0075] In one embodiment, the probability of occurrence of each target type's work cycle is determined based on the number of work cycles corresponding to each target type and a preset number, including:

[0076] The frequency of the work cycle corresponding to the target type is determined by the quotient of the quantity corresponding to the target type and the target value; the target value is the product of a preset threshold and a preset quantity.

[0077] The probability of occurrence of each target type's work cycle is determined by the ratio of the frequency of each target type's work cycle to the sum of the frequencies of all target types' work cycles.

[0078] It is understandable that, since the preset quantity represents the number of target cranes, and the quantity corresponding to the work cycle of the target type is generated based on the lifting data of the preset quantity of target cranes under at least one working condition, in order to obtain the frequency of the work cycle corresponding to the target type for a single target crane, the quotient of the quantity corresponding to the work cycle of the target type and the target value can be determined as the frequency of the work cycle corresponding to the target type, where the target value is the product of the preset threshold and the preset quantity. After obtaining the frequency of the work cycle corresponding to each target type, the ratio of the frequency of the work cycle corresponding to each target type to the sum of the frequencies of the work cycles corresponding to all target types can be determined as the probability of occurrence of the work cycle corresponding to each target type. In this way, the probability of occurrence of the work cycle corresponding to each target type can be quickly evaluated, improving the efficiency of load spectrum acquisition.

[0079] Step S104: Based on the total number of work cycles and the probability of occurrence of the target crane within its life cycle, determine the number of occurrences of each target type of work cycle within the life cycle of the target crane.

[0080] The total number of working cycles of the target crane during its life cycle can be obtained from a pre-defined "Crane Design Specification" based on the target crane's usage level; specific details can be found in existing technologies. It can be understood that after determining the total number of working cycles of the target crane during its life cycle and the probability of occurrence of working cycles for each target type, the frequency of occurrence of working cycles for each target type during the target crane's life cycle can be determined.

[0081] In one embodiment, the number of occurrences of each target type's work cycle within the target crane's lifecycle is determined based on the total number of work cycles and the probability of occurrence of the target crane over its lifecycle, including:

[0082] Determine the total number of work cycles of the target crane throughout its life cycle based on the target crane's usage level;

[0083] The product of the total number of work cycles of the target crane within its life cycle and the probability of occurrence of the work cycle corresponding to the target type is determined as the number of occurrences of the work cycle of the target type within the life cycle of the target crane.

[0084] The pre-defined "Crane Design Specification" classifies crane usage levels based on the total number of working cycles within a crane's lifespan, with each usage level corresponding to a different total number of working cycles. The usage level of the target crane can be obtained through its design data. After obtaining the target crane's usage level, the total number of working cycles within its lifespan can be determined based on the pre-defined correspondence between the crane's usage level and the total number of working cycles within its lifespan. After determining the total number of working cycles within the target crane's lifespan, the product of this total number of working cycles and the probability of occurrence of the corresponding working cycle for each target type can be used to determine the frequency of occurrence of each target type of working cycle within the target crane's lifespan. This allows for the rapid and accurate determination of the frequency of occurrence of each target type of working cycle within the target crane's lifespan, improving the efficiency and accuracy of load spectrum acquisition.

[0085] Step S105: Determine the load spectrum of the target crane based on the number of occurrences.

[0086] Specifically, the work cycles of each target type are sorted according to the load weight and the corresponding occurrence counts are added to generate the load spectrum of the target crane.

[0087] The load spectrum refers to the set of loads that list the actual working loads (or the ratio of actual working load to rated load) experienced by the crane during its life cycle (also known as the design reference period), categorized by magnitude and frequency of occurrence. In this embodiment, the load spectrum of the target crane can be generated by sorting the work cycles of each target type according to their load weight and adding the corresponding frequency of occurrence. It should be noted that since there may be multiple work cycles of the same target type, and the load weight of each work cycle may be different, sorting the work cycles of each target type according to their load weight can be done by sorting the work cycles of each target type according to the average load weight of the work cycles it contains.

[0088] In summary, the crane load spectrum compilation method provided in the above embodiments determines the number of work cycles of each type under each work condition based on the hoisting data of a preset number of target cranes under at least one working condition within a preset time period. The method then filters the work cycles of each type based on the number of cycles. Finally, based on the occurrence probability of the work cycle of at least one target type obtained from the filtering and the total number of work cycles of the target crane within its lifespan, a load spectrum of the target crane is generated. This makes the compiled crane load spectrum more reflective of the actual use of the crane, while also enabling convenient compilation of the crane load spectrum, improving the compilation efficiency and applicability of the crane load spectrum, and laying the foundation for calculating fatigue life.

[0089] Based on the same inventive concept as the foregoing embodiments, the foregoing embodiments will be described in detail below through a specific example. In this embodiment, a truck crane is used as an example. The crane load spectrum compilation method provided in this embodiment mainly includes the following parts:

[0090] (I) Typical Operating Conditions Analysis of Truck Cranes

[0091] When compiling a load spectrum for a specific model of truck crane, the first step is to determine the typical operating conditions of the crane based on its specific characteristics. Here, based on the rated lifting capacity table, the total number of operating conditions is determined to be n under various combinations such as outrigger extension / retraction, counterweight, boom configuration, main boom length, jib length, and jib installation angle. w .

[0092] (II) Definition of Crane Working Cycle

[0093] After the truck crane enters the work-ready state according to the working conditions, the movement of the hook is controlled through three operations: slewing, luffing, and hoisting. One work cycle (lifting operation) of a truck crane includes:

[0094] 1) Move the hook to the lifting point above the object being lifted and hook it onto the object;

[0095] 2) Move the hoisted object to the target location, and then unhook it;

[0096] 3) Move the hook away from the target location where the object being lifted is located.

[0097] 1. Work cycle identification

[0098] The process of identifying the work cycle from the recorded data transmitted back from the truck crane is as follows:

[0099] 1) By identifying the time points of change in operating conditions, the effective operating time range [t] can be determined. wstart ,t wend Here, if there are multiple operating conditions, then there are multiple time ranges corresponding to each operating condition.

[0100] 2) In [t wstart ,t wend Within [t], by identifying the time points where the load changes significantly, the time range of each work cycle is determined. cstart ,t cend ],like Figure 2 As shown (horizontal axis represents time, vertical axis represents load weight). It should be noted that the process of the hook being unloaded is ignored here; only the process of the hook lifting the load is taken as one work cycle.

[0101] 3) Because the load data transmitted back by the truck crane is not an accurate measurement but an estimated value calculated based on hydraulic pressure, the load weight varies during the lifting process, with a variation range of up to 10%. Therefore, this will... Average load weight inside This serves as the load weight for this work cycle.

[0102] 4) Record The parameter values ​​for the corresponding work cycles are shown in Table 1 below:

[0103] Table 1

[0104]

[0105] 2. Work Cycle Description

[0106] During hoisting operations, there are typically three motion processes: slewing, luffing, and lifting. Considering that slewing and lifting do not change the torque, for simplicity, this embodiment only considers the change in luffing. Furthermore, the motion changes from the starting point to the ending point during hoisting are ignored. In summary, this embodiment simplifies each work cycle by describing the starting and ending points of luffing.

[0107] 3. Discretization of the working cycle description

[0108] To facilitate statistical analysis, the boom luffing angle of the crane is divided into several reasonable intervals. Specifically, based on the boom lifting height curve of the crane model, the range of boom luffing angle variation is [β]. min ,β max Then, with Δβ = 5° as the interval, the amplitude angle range is divided into the following amplitude angle intervals:

[0109] [β min ,β min +Δβ),[β min +Δβ,β min +2Δβ),...,[β min +(m-1)Δβ,β max )

[0110] in,

[0111] As can be seen from the above, since a work cycle is defined by the start and end points of the amplitude change, and there are m intervals to choose from for the amplitude angle change range, under the same working condition, there can be a maximum of m... 2 Work cycles with different start and end points.

[0112] 4. Number of work cycle types

[0113] The number of possible work cycle types w for a certain type of crane n Equal to the number of working conditions n w The number m of work cycles with different start and end points under each working condition 2 The product of: w n =n w ×m 2 .

[0114] (III) Division of Crane Lifting Load Range

[0115] The load lifted by the crane is different each time. In order to facilitate statistical data, the load lifted by the crane under each working condition is divided into several reasonable load ranges.

[0116] Table 2

[0117]

[0118] Suppose that within a year, there are n c The cranes are in an active state (i.e., they are in operation most of the time). For these n... w For any of the operating conditions, the following operation shall be performed:

[0119] 1) Statistically, under this working condition, these n c The maximum value Q of the lifting load of the crane max and minimum value Q min ;

[0120] 2) If under this operating condition, this n c If no data is recorded for any of the cranes, then record that there is no data for that working condition and decrement the total number of working conditions by 1, i.e., n. w -1;

[0121] 3) Find the maximum value P of the lifting load under this working condition in the lifting capacity table. max and minimum value P min ;

[0122] 4) According to Q max and Q min The load range for this working condition is defined as shown in Table 2.

[0123] (iv) Data Statistical Processing

[0124] For a crane, its design life is generally over ten years, and its expected number of working cycles is over ten thousand. Collecting data on the working cycles throughout its entire lifespan is clearly impractical. Therefore, based on one year's worth of data, we can infer the overall situation using principles of probability theory and mathematical statistics.

[0125] 1. Reduce the number of work cycle types

[0126] In practice, some work cycles may be used infrequently. Therefore, it is necessary to select a large number of typical work cycle types for analysis and generate load spectra in order to make the analysis meaningful.

[0127] Suppose that within a year, there are n c A crane of model xx.1 is in an active state. Data from these cranes over a year was compiled to obtain the number of work cycles for each type, as shown in Table 3 below (xxx represents the statistical count of that work cycle).

[0128] Table 3

[0129]

[0130]

[0131] Here, based on the outrigger extension type and the usage of the main and auxiliary booms, the work cycle can be divided into four main types, as shown in the first column of Table 3 above.

[0132] When the outriggers are fully extended and only the boom is used, the number of work cycle types, n, is: n = 168 × 11 × 11 × 5 = 101640. Assuming we use variable i to represent the work cycle type, i = 1, 2, 3, ..., n, the corresponding statistical quantity is C. i Arrange sequence C in descending order. i Sort the sequences, resulting in sequence C. i Let j represent the position index from largest to smallest. Then j and i have a one-to-one mapping relationship, which is represented by the function i = f(j). The position index J that satisfies the following relationship is found through calculation:

[0133]

[0134] Here, we ignore the work cycle types corresponding to i = J+1 to j = n, and record the work cycle types corresponding to i = f(j), j = 1, 2, ..., J.

[0135] Similarly, in the same way, only the work cycle types corresponding to 80% of the total number of working condition types such as "outrigger half-extended + main boom", "outrigger fully extended + auxiliary boom", and "outrigger half-extended + auxiliary boom" are retained.

[0136] After the above simplification process, the number of effective work cycle types will be significantly reduced, and the set of these work cycle types is denoted as Z.

[0137] 2. Statistical analysis of the probability of a work cycle

[0138] Any element z in set Z represents a work cycle type, n c The frequency of this work cycle used by the crane has been statistically analyzed in the above steps. Here, the frequency of this work cycle is denoted as c. z For a single crane, the frequency of this work cycle is calculated using the following formula:

[0139]

[0140] For a single crane, the probability p of any work cycle z occurring in the work cycle set Z is... z Estimate using the corresponding proportions:

[0141]

[0142] The sum of the probabilities of all work cycles in the work cycle set Z is 1, that is...

[0143]

[0144] (v) Determining the total number of work cycles

[0145] According to the "Crane Design Specification", the use level of a crane is divided into 10 levels based on the total number of work cycles that the crane can complete, as shown in Table 4 below.

[0146] Table 4

[0147]

[0148] Meanwhile, the "Crane Design Specification" provides an example of the overall classification of mobile cranes, as shown in Table 5.

[0149] Table 5

[0150]

[0151] If the usage class of the truck crane is defined as U2 during the design phase, then the total number of work cycles C during its lifespan is... T The option is 63,000 times.

[0152] (vi) Formation of the load spectrum

[0153] Based on the work cycle set Z and the probability p of each element z And the total number of work cycles C within the lifecycle. T The number of times any working cycle z in set Z appears within its lifetime is:

[0154] c z =C T ×p z

[0155] After obtaining the number of times each work cycle occurs within the life cycle using the method described above, these results can be summarized to finally compile the crane load spectrum.

[0156] In summary, the crane load spectrum compilation method provided in this embodiment generates the crane load spectrum based on the crane's usage data over a period of time, thus better reflecting the actual usage of the crane. At the same time, the load data obtained by this method can macroscopically display the lifting load data of the research object, laying the foundation for calculating fatigue life.

[0157] Based on the same inventive concept as the foregoing embodiments, this embodiment of the invention provides a computing device, such as... Figure 3 As shown, the computing device includes: a processor 310 and a memory 311 storing computer programs; wherein, Figure 3 The processor 310 shown in the diagram does not indicate that there is only one processor 310, but only indicates the positional relationship of the processor 310 relative to other devices. In practical applications, there can be one or more processors 310; similarly, Figure 3 The memory 311 shown in the diagram has the same meaning, that is, it is only used to indicate the positional relationship of memory 311 relative to other devices. In practical applications, there can be one or more memories 311. When the processor 310 runs the computer program, the crane load spectrum compilation method described above is implemented.

[0158] The computing device may also include at least one network interface 312. The various components of the computing device are coupled together via a bus system 313. It is understood that the bus system 313 is used to implement communication between these components. In addition to a data bus, the bus system 313 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 3 The general designated all buses as Bus System 313.

[0159] The memory 311 can be volatile memory or non-volatile memory, or both. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); the magnetic surface memory can be disk storage or magnetic tape storage. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 311 described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0160] The memory 311 in this embodiment of the invention is used to store various types of data to support the operation of the computing device. Examples of this data include: any computer programs used to operate on the computing device, such as operating systems and applications; contact data; phonebook data; messages; pictures; videos, etc. The operating system includes various system programs, such as the framework layer, core library layer, driver layer, etc., used to implement various basic services and handle hardware-based tasks. Applications can include various applications, such as media players, browsers, etc., used to implement various application services. Here, the program implementing the method of this embodiment of the invention can be included in the application.

[0161] Based on the same inventive concept as the foregoing embodiments, this embodiment also provides a computer storage medium storing a computer program. The computer storage medium can be a magnetic random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM), etc.; it can also be various devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc. When the computer program stored in the computer storage medium is run by a processor, it implements the crane load spectrum compilation method described above. For the specific steps implemented when the computer program is executed by the processor, please refer to [link to relevant documentation]. Figure 1 The description of the illustrated embodiments will not be repeated here.

[0162] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0163] In this document, the terms “comprising,” “including,” or any other variations thereof are intended to cover non-exclusive inclusion, which includes not only the elements listed but also other elements not expressly listed.

[0164] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for compiling a crane load spectrum, characterized in that, include: Acquire lifting data of a preset number of target cranes under at least one working condition within a preset time period; Analyze the hoisting data to obtain the number of each type of work cycle under each working condition; the work cycle refers to the process from the start of hoisting one item to the start of hoisting the next item. Based on the quantity, the work cycles of each type are filtered, and the probability of occurrence of at least one target type of work cycle obtained after filtering is determined. Based on the total number of working cycles of the target crane during its life cycle and the probability of occurrence, determine the number of times each target type of working cycle occurs during the life cycle of the target crane. Based on the number of occurrences, the load spectrum of the target crane is determined.

2. The method according to claim 1, characterized in that, The analysis of the hoisting data yields the quantity of each type of work cycle under each of the aforementioned working conditions, including: The hoisting data is identified to obtain parameters for at least one work cycle under each of the aforementioned working conditions; the parameters include the load weight, the luffing angle at the starting point, and the luffing angle at the ending point. The hoisting load range is divided according to the load weight of at least one work cycle included in the target working condition to obtain at least one hoisting load range under the target working condition; the target working condition is any working condition. Based on at least one preset amplitude angle range and at least one hoisting load range under the target working condition, the at least one work cycle included under the target working condition is classified into types to obtain the number of work cycles corresponding to each type under the target working condition.

3. The method according to claim 2, characterized in that, The step of dividing the lifting load range according to the load weight of the work cycle included in the target working condition to obtain at least one lifting load range under the target working condition includes: Based on the load weight of at least one work cycle contained in the target working condition, obtain the maximum load weight and the minimum load weight in the at least one work cycle contained in the target working condition. Based on the maximum load weight, the minimum load weight, and the preset maximum load value and preset minimum load value under the target working condition, the hoisting load range is divided according to a preset method to obtain at least one hoisting load range under the target working condition.

4. The method according to claim 2, characterized in that, Before classifying at least one work cycle included in the target working condition according to at least one preset amplitude angle range and at least one hoisting load range under the target working condition, and obtaining the number of work cycles corresponding to each type included in the target working condition, the following steps are included: The luffing angle range of the target crane boom is divided at preset angle intervals to obtain at least one luffing angle interval.

5. The method according to any one of claims 1 to 4, characterized in that, The step of filtering work cycles of each type based on the quantity and determining the probability of occurrence of at least one target type of work cycle obtained after filtering includes: Sort the work cycles of each type according to the stated quantity, and obtain the sorting results; Based on the sorting results, the corresponding types of work cycles are selected as target type work cycles in descending order of quantity, until the ratio between the sum of the quantities of the selected target type work cycles and the total quantity of all types of work cycles is greater than or equal to a preset threshold. The probability of occurrence of each target type's work cycle is determined based on the number of work cycles corresponding to each target type and the preset number.

6. The method according to claim 5, characterized in that, The step of determining the probability of occurrence of each target type's work cycle based on the number of work cycles corresponding to each target type and the preset number includes: The frequency of the work cycle corresponding to the target type is determined by the quotient of the number of work cycles corresponding to the target type and the target value; the target value is the product of the preset threshold and the preset number. The probability of occurrence of each target type's work cycle is determined by the ratio of the frequency of each target type's work cycle to the sum of the frequencies of all target types' work cycles.

7. The method according to any one of claims 1 to 4, characterized in that, The step of determining the occurrence count of each target type's work cycle within the target crane's lifecycle based on the total number of work cycles and the occurrence probability within the target crane's lifecycle includes: Based on the usage level of the target crane, determine the total number of working cycles of the target crane during its life cycle; The product of the total number of working cycles of the target crane during its life cycle and the probability of occurrence of the working cycle corresponding to the target type is determined as the number of times the working cycle of the target type occurs during the life cycle of the target crane.

8. The method according to any one of claims 2 to 4, characterized in that, Determining the load spectrum of the target crane based on the number of occurrences includes: The work cycles of each target type are sorted according to the load weight, and the corresponding occurrence counts are added to generate the load spectrum of the target crane.

9. A computing device, characterized in that, include: The processor and the memory storing the computer program implement the crane load spectrum compilation method according to any one of claims 1 to 8 when the processor runs the computer program.

10. A computer-readable storage medium, characterized in that, The system contains a computer program that, when executed by a processor, implements the crane load spectrum compilation method according to any one of claims 1 to 8.

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