Big data-based cost accounting method and device, and computer equipment

Abstract

The present application relates to the technical field of cost accounting, in particular to a cost accounting method and device based on big data, and a computer device, comprising the following steps: obtaining component number and drawing coordinates, comparing task field and operation type, extracting organization and floor information, matching time and space data, screening material and task conflict nodes, aligning construction and supply rhythm, supplementing field disconnection content, collecting component, material and price information, and obtaining cost collection list. In the present application, by constructing the association relationship of component and drawing information, operation type and organization field, the association integrity of task data in the space and responsibility dimension is enhanced, combined with the comparison mechanism of material and task time field, the construction and material rhythm misplacement situation is identified, the time difference node is extracted and the field disconnection content is supplemented, the data through cost collection structure is established, and the refinement extraction, complete collection and responsibility range demarcation of component level cost data are promoted.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of cost accounting, in particular to a cost accounting method and device based on big data and a computer device. BACKGROUND

[0002] The technical field of cost accounting relates to the calculation and management of the cost of each link in the whole process of a construction project. The core matters include the preparation of a bill of quantities, the acquisition of material prices, the estimation of labor costs, the calculation of mechanical use costs, the dynamic cost monitoring in the construction phase, and the completion settlement checking, etc. Through the fixed price method or the list price method, the project cost is estimated by using budget quota, cost quota and fee standard, etc. based on the basic data such as design drawings, bill of quantities, market price information and construction organization design, and the project investment control and cost management goals are achieved. The traditional cost accounting method refers to the way of manually inputting the quantity data by budget personnel, selecting the corresponding consumption of materials, labor and machines and price parameters by referring to the quota manual and the static database built in the cost software, and combining with the manual experience, and performing the project total price and sub-item cost accounting by using tabular manual calculation or calling the fixed operation template of the cost software, which relies on the budget quota clauses, the manually collected material market prices and the construction dimensions marked in the project drawings for cost estimation and accounting.

[0003] The existing technology based on manual input and static data calling method lacks a data checking mechanism based on the linkage of spatial coordinates, task content and time nodes under the conditions of dynamic changes in the actual construction phase task state, frequent adjustment of drawings or change of organizational structure division, and cannot support the dynamic tracing and real-time collection of component-level cost information in process data. Especially when the fields between components and materials are not connected or there is a time difference between material supply rhythm and task execution, it is difficult to find and locate the structural deviation of resource use, which easily leads to problems such as omission of component cost information, deviation of material cost statistics and ambiguity of cost responsibility allocation, and reduces the data consistency and collection efficiency of construction management. SUMMARY

[0004] In order to solve the technical problems existing in the prior art, the embodiments of the present application provide a cost accounting method based on big data.

[0005] In order to achieve the above-mentioned purpose, the present application adopts the following technical scheme, the cost accounting method based on big data comprises the following steps:

[0006] S1: Obtain the structure component number and drawing coordinate data, compare the component field of the task list, analyze the operation item type, extract the floor and organization field, correspond the drawing field and operation field, and obtain the task binding path table;

[0007] S2: Based on the task binding path table, extract the material number and delivery time period fields, extract the task time field, compare the time coverage relationship, and obtain the corresponding material conflict distribution list by matching the spatial field and the time field.

[0008] S3: Based on the corresponding material conflict distribution list, extract the warehousing field and the sign-in time field, compare the time order, split the cross-cycle nodes, align the construction time and the supply time, extract the component numbers with inconsistent time order, and obtain the resource misalignment pointing sequence set;

[0009] S4: Based on the resource misalignment pointing sequence set, compare with the cost list field, extract the unconnected component number, associate the space field and organization field, and the unconnected content of the corresponding component field and material field to obtain the uncollected material item form;

[0010] S5: Based on the uncollected material item form, extract the organization field and price field, compare with the task status field, extract the correspondence between the component number and the task field, and obtain the corresponding field content to obtain the cost collection list.

[0011] As a further embodiment of the present invention, the task binding path table includes component number, operation type, organization information, and drawing coordinate fields; the corresponding material conflict distribution list includes discontinuous component numbers, time coverage differences, and spatial and time fields arranged in sequence; the resource misalignment pointing sequence set includes component number, inbound / outbound and check-in time differences, and cross-cycle node fields; the uncollected material item form includes unconnected component numbers, unconnected material numbers, spatial segment fields, and organizational unit fields; and the cost collection list includes component number, material price fields, organization fields, and task execution status fields.

[0012] As a further aspect of the present invention, the organization field refers to a data field associated with the target organization and task allocation, mapping the person in charge, participating department and division of labor unit for each task and activity;

[0013] The cross-cycle node refers to the node where the time and task arrangements are inconsistent and overlapping between different cycles in a project.

[0014] As a further aspect of the present invention, the specific steps of S1 are as follows:

[0015] S101: Obtain the component number from the structural component database and the coordinate field in the construction drawings, retrieve the corresponding item of the component number in the coordinate of the drawing, compare the coordinate axis segment with the component number, and obtain the field set corresponding to the component coordinate;

[0016] S102: Based on the component coordinate corresponding field set, compare the component number field in the task list, filter the component numbers whose operation items are binding, erection and pouring, and extract the corresponding floor field and action field to obtain the component task field mapping set;

[0017] S103: Based on the component task field mapping set, associate the drawing field and the operation item field, expand the pairing content of the component number and the floor field, link the action field and the organization field, and obtain the task binding path table.

[0018] As a further aspect of the present invention, the specific steps of S2 are as follows:

[0019] S201: Based on the component number in the task binding path table, extract the associated material number field and delivery time period field, extract the task start and end time field in the task list, compare the start and end nodes of the time field, remove component numbers with overlapping and discontinuous time, and obtain the set of numbers corresponding to the task delivery time.

[0020] S202: Based on the task delivery time corresponding number set, retrieve the spatial field and task time field corresponding to the component number, compare the continuous state of the time interval according to the order of the component number, filter the component data with discontinuities in the time series, and obtain the spatial task time corresponding field group.

[0021] S203: Based on the spatial task time corresponding field group, analyze the misalignment relationship between the delivery field and the task field time nodes, extract the component number of the time axis offset and match it with the material field to obtain the corresponding material conflict distribution list.

[0022] As a further aspect of the present invention, the specific steps of S3 are as follows:

[0023] S301: Based on the component number in the corresponding material conflict distribution list, extract the corresponding material entry / exit field and check-in time field, compare the time sequence, identify the interruption position of the time sequence, map the component number, and obtain the entry / exit record sequence distribution set;

[0024] S302: Based on the sequence distribution set of the entry and exit records, extract the task time field and delivery time field of the cross-cycle component, compare the time node interval, juxtapose the time fields and associate them with the component number to obtain the time node interleaved mapping table;

[0025] S303: Based on the time node interleaving mapping table, filter the component numbers where the construction and supply time sequences are interleaved, extract the offset sequence under the component number, and obtain the resource misalignment pointing sequence set.

[0026] As a further aspect of the present invention, the specific steps of S4 are as follows:

[0027] S401: Based on the component numbers in the resource misalignment pointing sequence set, compare the component fields and material fields in the cost list, retrieve the material field corresponding to each component number, filter out missing associated component numbers, match the missing items with the component numbers, and obtain the set of unconnected component numbers;

[0028] S402: Based on the set of unconnected component numbers, extract the spatial field and the organizational field. For each component number, associate the data items of the component number, spatial field and organizational field to obtain the spatial organizational field mapping group.

[0029] S403: Based on the spatial organization field mapping group, filter out the content with missing connections between the component field and the material field, analyze the unconnected data items by comparing the spatial field and the organization field, split the associated information data, and obtain the uncollected material item form.

[0030] As a further aspect of the present invention, the specific steps of S5 are as follows:

[0031] S501: Based on the material field and component field in the uncollected material item form, extract the organization field and material price field corresponding to each component field, classify the corresponding task status field, separate the status item of the component, and associate the organization field, price field, and task status field to obtain a set of organization and status fields.

[0032] S502: Based on the set of organization and status fields, retrieve the correspondence between component number and task field. For each group of component number and task field data items, match the number data with the status field and price field to obtain the component task status mapping table.

[0033] S503: Based on the component task status mapping table, call the organization field, component field, material field, material price field, task field, and status, match the corresponding field content, extract the association structure of the field items, and obtain the cost collection list.

[0034] The cost accounting device based on big data includes:

[0035] The task path generation module obtains structural component numbers and drawing coordinate data, compares them with the component fields in the task list, analyzes the operation item types, extracts floor and organization information, and obtains the task binding path table by matching the drawing fields and operation fields.

[0036] The time conflict identification module extracts the material number and delivery time period fields and the task time field based on the task binding path table, compares the time coverage relationship, and obtains the corresponding material conflict distribution list by corresponding spatial fields and time fields.

[0037] Based on the corresponding material conflict distribution list, the resource order screening module extracts the entry and exit time and check-in time, compares the order relationship, splits cross-cycle nodes, aligns the construction time and supply time, extracts the component numbers with inconsistent time order, and obtains the resource misalignment pointing sequence set.

[0038] The missing item field extraction module, based on the resource misalignment pointing sequence set, compares the cost list fields, extracts the unconnected component numbers, associates the space and organization fields, and the unconnected content of the corresponding component field and material field to obtain the uncollected material item form.

[0039] The list field output module extracts the organization and price fields from the material and component fields in the uncollected material item form, compares them with the task status field, extracts the correspondence between the component number and the task field, and obtains the corresponding field content to get the cost collection list.

[0040] The cost accounting computer device based on big data includes a memory and a processor, characterized in that the memory stores a computer program, and the processor executes the computer program to implement the aforementioned cost accounting device based on big data.

[0041] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0042] In this invention, by constructing the association relationship between components and drawing information, operation type and organization field, the integrity of task data in spatial and responsibility dimensions is enhanced. Combined with the comparison mechanism of material and task time fields, the misalignment of construction and material rhythm is identified, time difference nodes are extracted and field gaps are filled, and a cost collection structure with data connectivity is established to promote the detailed extraction, complete collection and delineation of responsibility scope of component-level cost data. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is a schematic diagram of the steps of the present invention;

[0045] Figure 2 This is a detailed schematic diagram of S1 of the present invention;

[0046] Figure 3 This is a detailed schematic diagram of S2 of the present invention;

[0047] Figure 4 This is a detailed schematic diagram of S3 of the present invention;

[0048] Figure 5 This is a detailed schematic diagram of S4 of the present invention;

[0049] Figure 6 This is a detailed schematic diagram of S5 of the present invention;

[0050] Figure 7 This is a schematic diagram of the device module of the present invention. Detailed Implementation

[0051] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0052] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0053] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0054] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0055] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0056] Please see Figure 1 This invention provides a cost accounting method based on big data, including the following steps:

[0057] S1: Obtain the component number and construction drawing coordinate data from the structural component database, compare the component number field in the task list, analyze whether the operation item field is binding, erection and pouring, extract the organization field by comparing the floor information, match the drawing field and operation field, and obtain the task binding path table.

[0058] S2: Based on the component number in the task binding path table, extract the material number and delivery time period fields, extract the task time field, compare the time coverage relationship, filter out discontinuous component numbers, and list the spatial field and time field in the order of component number to obtain the corresponding material conflict distribution list.

[0059] S3: Based on the component number in the corresponding material conflict distribution list, extract the warehousing field and check-in time field, compare the time sequence, split cross-cycle nodes, align construction and supply time, filter component numbers with misaligned time sequence, and obtain the resource misalignment pointing sequence set;

[0060] S4: Based on the component numbers in the resource misalignment pointing sequence set, compare the component fields and material fields in the cost list to extract the unconnected component numbers. Based on the unconnected content of the component fields and material fields corresponding to the space field and organization field, obtain the uncollected material item form.

[0061] S5: Based on the material and component fields in the uncollected material item form, extract the organization and material price fields, analyze the task status field, extract the correspondence between component number and task field, merge field information, and obtain the cost collection list.

[0062] The task binding path table includes component number, operation type, organization information, and drawing coordinate fields. The corresponding material conflict distribution list includes discontinuous component numbers, time coverage differences, and spatial and time fields arranged in sequence. The resource misalignment pointing sequence set includes component number, inbound / outbound and check-in time differences, and cross-cycle node fields. The uncollected material item form includes unconnected component numbers, unconnected material numbers, spatial segment fields, and organizational unit fields. The cost collection list includes component number, material price fields, organization fields, and task execution status fields.

[0063] Please see Figure 2 The specific steps of S1 are as follows:

[0064] S101: Obtain the component number from the structural component database and the coordinate field in the construction drawings, retrieve the corresponding item of the component number in the coordinate of the drawing, compare the coordinate axis segment with the component number, and obtain the field set corresponding to the component coordinate;

[0065] To retrieve the component number from the structural component database and its coordinate field from the construction drawings, it is necessary to first sequentially search each component number field. This field is a unique code describing the identity of a construction object, using a standard numbering format, such as "C1-01-A". A string search operation is then performed on this number to find the directly associated drawing index item in the construction drawing database. The coordinate field consists of two sets of axis numbers, such as "Axis A to Axis E" and "Axis 1 to Axis 5". Each component number is associated with a corresponding coordinate range. During the operation, it is necessary to determine whether the component number's position in the drawing index covers the corresponding coordinate segment. This can be limited by checking if the layer code in the component number field matches the layer field in the drawing index. For example, if the component number is "C1-01-A"... If the corresponding layer is "01", then the drawing range is limited to the index file of "01". Further filtering of coordinate fields is performed, and the start and end positions of the axis in the coordinate fields are extracted as the range boundary. The number item corresponding to the component number field is checked. If it exists, its index position is located and its corresponding coordinate field content is marked. The component number field is connected with the located coordinate field and fixed as a set of correspondence in subsequent processing. The above process is repeated for multiple component numbers. Each pair of component numbers and coordinate fields forms a set of two-field mapping relationship. At the same time, the mapping relationship is organized in sequence according to the actual arrangement order of the components in the drawing. In this way, field-level correspondence can be established without relying on specific drawing images to obtain the component coordinate corresponding field set.

[0066] S102: Based on the component coordinate corresponding field set, compare the component number field in the task list, filter the component numbers whose operation items are binding, erection and pouring, and extract the corresponding floor field and action field to obtain the component task field mapping set.

[0067] First, the component number field in the task list is retrieved, and each item is checked to see if it exists in the field set. If it exists, it means that the component corresponding to the task has locatable coordinate information in the drawing. Then, the operation item field content corresponding to each component number is extracted from the task list. By performing character content filtering, only component number items with operation item field values ​​equal to "tying", "erecting", or "pouring" are retained. For example, if the operation item corresponding to a component number C1-01-A is "erecting", then the component number is retained and marked as a valid action item. Based on this, the corresponding floor field is further extracted from the component number. The floor field is represented in the form of "XX floor" or "LXX". By recognizing the floor position value in the characters, its spatial hierarchical location is completed. Simultaneously, the action field, i.e. the task type field item marked in the operation item field, is extracted. The action type is associated with the spatial location through the field value. For example, if the component number C1-01-A corresponds to the floor "03" and the operation item is "binding", it means that the binding task occurs at the coordinate position corresponding to the number on the 03 floor. The same operation is continued for all component numbers that meet the conditions, extracting the floor field and action field item by item. Combined with the existing component number field and coordinate field content, a set of pairing relationships containing component number, coordinate field, action field and floor field is formed. Through this set, the task activities and floor information of all operable component numbers in the task list on the drawing coordinates are mapped, and the component task field mapping set is obtained.

[0068] S103: Based on the component task field mapping set, associate the drawing field and the operation item field, expand the pairing content of the component number and the floor field, link the action field and the organization field, and obtain the task binding path table;

[0069] First, identify the pairings between the component number and its corresponding coordinate, action, and floor fields in the field set. Using the component number as a reference, compare it with the component positioning information in the drawing fields. Through character matching, search whether the component number has a location description in the drawing data file. For example, if the component number is GZ-105, and the corresponding floor plan positioning information for GZ-105 exists in the drawing fields, then the component number is considered valid. Simultaneously, call the corresponding floor field value from the task field mapping set to expand the pairing content between the component number and the floor. Each pairing of component number and floor field items forms a matching comparison data set. In the comparison, the floor field is presented in numerical form; for example, "floor 03" maps to the value 3. The component number GZ-105 and the floor... 3. Binding: Further extract the action field. The action field content, such as "binding", "erecting", "pouring", etc., represents the type of task operation. At the same time, extract the organization name field associated with the corresponding component number from the organization field. The organization field is the team number or task assignment identifier. For example, if the action field is "binding" and the organization field is Group B, then this action under the component number is the responsibility of Group B. Sequentially perform the association retrieval and pairing of the action field and organization field for all component numbers to complete the four-element correspondence relationship of component number - floor field - action field - organization field. Finally, using the component number as the key value, concatenate all its related field pairing data to expand into a set of task path data entries with the component number as the basic index, and obtain the task binding path table.

[0070] Please see Figure 3 The specific steps of S2 are as follows:

[0071] S201: Based on the component number in the task binding path table, extract the associated material number field and delivery time period field, extract the task start and end time field in the task list, compare the start and end nodes of the time field, remove component numbers with overlapping and discontinuous time, and obtain the set of numbers corresponding to the task delivery time.

[0072] First, locate the task entry corresponding to each component number in the dataset. Retrieve the material number field and delivery time period field for that entry. The material number field is a parameter used to identify the material type in the material supply process, and the delivery time period field represents the start and end points in the material transportation plan. For example, when the component number is GZ-203, its material number is M-45, and the delivery time period is "09:00-11:00". Then, extract the task start and end time fields from the task list and compare the start and end points of the tasks corresponding to the component numbers. If the end point of the delivery time period is later than or earlier than the task start point, it is considered a component number item with overlapping and discontinuous time, and a removal operation needs to be performed. To ensure consistent judgment criteria, a time node matching benchmark is set when performing the comparison operation. Using the task start and end time periods as the main axis, the overlap range of the delivery time periods is judged item by item. If the delivery time period is not overlapping... If the start or end point of a time period exceeds the main axis of the task time, it is defined as a discontinuous state. In this state, the component number is marked as an anomaly and removed from subsequent comparisons. For example, if the task start and end time is "08:00-12:00" and the delivery time is "13:00-15:00", the component number is judged as a discontinuous time component. If the task start and end time and the delivery time period partially overlap, such as the task time "08:00-12:00" and the delivery time "10:00-11:00", the component number is retained to continue participating in the subsequent verification process. Time interval comparison and filtering are performed on all component numbers in turn. The time matching status is determined by the correspondence between the start and end nodes in the data. After removing all overlapping and discontinuous records, the valid items are gathered according to the component number order and organized into a set of number sequences to obtain the set of numbers corresponding to the task delivery time.

[0073] S202: Based on the task delivery time corresponding number set, retrieve the spatial field and task time field corresponding to the component number, compare the continuous state of the time interval according to the order of the component number, filter the component data with discontinuities in the time series, and obtain the spatial task time corresponding field group.

[0074] First, for each component number in the set, the corresponding spatial field parameters in the spatial database are retrieved sequentially. These parameters include area labels or coordinate descriptions. Simultaneously, the task list data is linked to extract the task time field for the corresponding component, i.e., the start and end times of the construction task. Using the component number as the primary index, a pairing relationship is established between the component and the time and spatial fields to facilitate subsequent cross-field sequential checks. In this process, for example, component number GZ-045 has the spatial field X1 and the task time field 10:00-11:00. Next, based on the order of the component numbers, the task time periods of each component are compared side-by-side to obtain the time interval between every two consecutive components. The discontinuity between consecutive time periods is then calculated based on the time sequence. For example, GZ-045 and GZ-046 correspond to task times... Segments 10:00-11:00 and 11:00-12:00 are considered to be continuous in time. If a component, such as GZ-047, has a time period of 14:00-15:00, and there are more than two time periods that jump from the previous component, then there is a discontinuous time state. During the execution judgment process, a time discontinuity identification reference range needs to be set to determine whether the task time periods are continuous. In this process, the reference interval for task continuity judgment is defined as the state where the time periods do not overlap and are immediately adjacent. If the start time of a component number's time period is not adjacent to the end time of the previous component's time period, or the interval is more than one time period, then it is classified as a discontinuous state. Further filtering is performed to identify all component numbers with discontinuous states, and the corresponding component number, its spatial field, and the task time field form a triplet. These are then uniformly organized into a set of field items to obtain the spatial task time corresponding field group.

[0075] S203: Based on the spatial task time corresponding field group, analyze the misalignment relationship between the delivery field and the task field time nodes, extract the component number of the time axis offset and match it with the material field to obtain the corresponding material conflict distribution list;

[0076] First, the delivery and task fields associated with each component number in the field group are retrieved. The delivery field records the material transportation batches and scheduling time periods, while the task field records the start and end points of construction actions. Each of the two types of time points under the same component number is compared to determine if there is a misalignment on the timeline. During the analysis, the delivery field time point is used as the reference axis, and the task field time point as the comparison axis. When the end point of the delivery field is earlier than the start point of the task field, or when its start point is later than the end point of the task field, it is considered a time misalignment. This status information is recorded using the component number as an index. For example, if the delivery time period for component number GZ-058 is "08:00-09:00" and the task execution time period is "09:30-10:30", then a positive time misalignment exists. If the delivery time period is "09:30-10:30", then a positive time misalignment exists. If the task time period is "09:00-10:00", it is considered a reverse misalignment. For both types of misalignment, the component number is extracted and included in the offset dataset. At the same time, the material field corresponding to each component number is associated. The material number, name and batch number are retrieved from the material information and compared one-to-one with the component number to establish a mapping record between the time-misaligned component and the corresponding material. In the mapping process, if the component number GZ-058 corresponds to the material number M-23 and is a concrete pouring task, this data is marked as a material and task time sequence mismatch. The time offset matching and material field comparison of all components are completed in turn. Finally, the offset component and its corresponding material information are summarized and compiled. Using the time-misaligned component number as the primary key, the correspondence between four types of fields, namely component number, material number, delivery field and task field, is output to obtain the corresponding material conflict distribution list.

[0077] Please see Figure 4 The specific steps of S3 are as follows:

[0078] S301: Based on the component number in the corresponding material conflict distribution list, extract the corresponding material entry / exit field and sign-in time field, compare the time sequence, identify the interruption position of the time series, map the component number, and obtain the entry / exit record sequence distribution set;

[0079] First, the material entry / exit field corresponding to each component number is retrieved, and the outbound batch number and inbound batch number information recorded in this field are extracted. Then, the on-site check-in time field is extracted. The time sequence of the two types of fields is compared to determine the synchronicity between material flow and construction site operations. In implementation, each entry / exit record is compiled into a single sequence according to the component number and arranged in the order of outbound event first and inbound event second. By comparing the event sequence, time overlaps or breakpoints are identified. For example, if the outbound time of component number GZ-021 is earlier than the check-in time, it is considered a normal flow. If the outbound time is later than the check-in time, the operation of this component is out of sequence, and its time node position needs to be recorded. Subsequently, the continuity of the time sequence of all component numbers is checked, and the interval between the time nodes of each record is judged. If the interval between adjacent events exceeds the set baseline time interval, it is marked as a time breakpoint. The baseline time interval can be determined based on the logistics turnover rate at the construction site. For example, if the material turnover rate is 3 batches per hour, the upper limit of the time interval is set to within 20 minutes. If the actual interval exceeds this value, it is judged as an interruption. Taking component number GZ-034 as an example, if the material entry time is 09:00 and the check-in time is 09:25, it is considered a normal sequence. If the entry time is 10:10 and the check-in time is 09:25, then this number is marked as a breakpoint item. The time sequence of all component numbers is checked sequentially, the component number corresponding to the interruption position is extracted, and then it is mapped with the material number field to form a sequential distribution correspondence between the component number, the entry / exit field, and the check-in field, finally obtaining the sequential distribution set of entry / exit records.

[0080] S302: Based on the sequential distribution set of entry and exit records, extract the task time field and delivery time field of cross-cycle components, compare the time node intervals, juxtapose the time fields and associate them with the component number to obtain the time node interleaved mapping table;

[0081] First, the cross-cycle component numbers are retrieved from the dataset; these are component items that appear multiple times in the entry and exit records. These components often repeat across multiple construction phases or batches of tasks, and have multiple task and delivery time records. For each cross-cycle component, its task time and delivery time fields are extracted, and the two types of time fields are arranged in parallel according to the component number. Then, the node intervals of the two types of time fields are compared. The start node of each task and the start node of delivery are sequentially determined. If the task start node is earlier than the delivery start node, it is determined as forward interleaving; otherwise, it is reverse interleaving. This determines the offset state between the two types of time. Taking component number GZ-112 as an example, this component involves material supply in both the concrete pouring and formwork removal cycles. The first delivery time field is 08:00-09:00, and the task time field is 08:30-10:00. The second delivery time field is 13:00-14:00, and the task time field is 12:00-13:30. Therefore, this component exhibits a reverse staggered pattern in the second stage. For all components, the difference between the first and last nodes of the task and delivery time is recorded, and their chronological order on the timeline is determined. To standardize the time matching judgment, a time interval reference range can be set. For example, the distance between consecutive operation nodes should not exceed the average working time segment of the same task cycle. When the node distance deviates from this range, it is classified as an interleaved item. After performing this type of judgment on each component record, a cross relationship between the component number and the time field is formed. The task time node, delivery time node and component number are merged into the same mapping relationship. The time field is compared and matched. All component numbers with overlapping states and their corresponding fields are merged into field mapping content to obtain the time node overlapping mapping table.

[0082] S303: Based on the time node interleaving mapping table, filter the component numbers where the construction and supply time sequences are interleaved, extract the offset sequence under the component number, and obtain the resource misalignment pointing sequence set;

[0083] First, all component numbers and their corresponding construction time and supply time fields are extracted from the mapping table. For each component number, the time node information of both types of fields is read separately. The start and end nodes of the construction time are sequentially compared with the corresponding nodes of the supply time to identify the overlap between the two on the timeline. In practice, the construction time is used as the main sequence and the supply time as the comparison sequence. When the start node of the supply time is earlier than the start node of the construction time and the end node is later than the end node of the construction time, it is determined to be a forward overlap. When the start node of the construction time is earlier than the start node of the supply time and the end node of the supply time is earlier than the end node of the construction time, it is determined to be a reverse overlap. In the field example, the supply period of component number GZ-210 is from 08:00 to 09:00 and the construction period is from 08:30 to 09:30, so there is a forward overlap; the supply period of component number GZ-211 is from 09:00 to 09:30 and the construction period is from 08:00 to 09:30, so there is a reverse overlap. After performing the same judgment on all components, component numbers with overlapping states are selected and listed separately in the dataset. Then, for the selected component numbers, the differences in their corresponding time nodes are extracted, and the intervals between these time nodes are converted into offset data sequences to reflect the degree of deviation of each component on the time axis. The offset sequence uses the component number as an index to record the time difference between construction and supply, the offset direction, and the sequence order. For example, component number GZ-210 has an offset of -0.5 hours and a positive direction, while GZ-211 has an offset of +0.3 hours and a negative direction. After processing, all offset sequences are mapped to component numbers, forming a one-to-one mapping set between component numbers and time offset sequences, ultimately resulting in a resource misalignment pointing sequence set.

[0084] Please see Figure 5 The specific steps of S4 are as follows:

[0085] S401: Based on the component numbers in the resource misalignment pointing sequence set, compare the component fields and material fields in the cost list, retrieve the material field corresponding to each component number, filter out missing associated component numbers, match the missing items with the component numbers, and obtain the set of unconnected component numbers;

[0086] First, all component number index items are extracted from the dataset, and the corresponding component and material fields are retrieved from the cost list. These two types of fields are then compared according to the component number. During execution, for each component number, its component field value in the cost list is read first to confirm whether the number has a corresponding record in the material field. If a component number is found to exist during the comparison, but its corresponding material field is empty or undefined, it is marked as a missing item. To ensure consistency, a field integrity benchmark is set during implementation. When the material field missing rate exceeds the benchmark by 5%, the entire batch of component numbers is determined to be a set of missing items. For example, if the material field corresponding to component number GZ-052 in the cost list is empty, while components GZ-053 and GZ-054 in the same batch both have material fields, then GZ-052 is identified as a single missing item. Next, all component numbers identified as missing are extracted and compared one by one with the component fields in the original cost list to prevent interference from duplicate registrations of the same number. Through item-by-item retrieval and cross-verification, a list of component numbers containing only missing associations is generated. Subsequently, to verify the uniqueness of the missing components, the extracted component numbers need to be matched with the component numbers recorded in the misaligned sequence set, eliminating duplicate or corrected entries. For example, if the number GZ-052 in the misaligned sequence set has been adjusted to the material matching group, then this number will not be counted again in the missing set. All filtered and confirmed missing component numbers will be re-correlated with the cost list index, ultimately resulting in a set of unconnected component numbers.

[0087] S402: Based on the set of unconnected component numbers, extract the spatial field and the organizational field. For each component number, associate the data items of the component number, spatial field and organizational field to obtain the spatial organizational field mapping group.

[0088] First, all component numbers recorded in the set are read. For each number, an index search is performed, and the corresponding spatial and organizational fields are extracted from the project database. The spatial field represents the component's location coordinates or area division on the construction site, while the organizational field represents the construction unit or work group to which the component belongs. During execution, component numbers are scanned sequentially. For each component number read, the device automatically retrieves the spatial partition data with the same number from the spatial field table and searches for the corresponding organizational unit code in the organizational field table, forming a matching relationship between the two types of fields. For example, if the spatial field of component number GZ-086 is "Floor A-3 Zone" and the organizational field is "Concrete Work Group C1", the matching relationship can be represented as (GZ-086, A-3 Zone, C1). After performing the same operation on all component numbers, the component number, spatial field, and organizational field are arranged sequentially according to their numbers to ensure the uniqueness and completeness of the field correspondence. During this process, it is also necessary to detect overlaps in spatial fields, i.e., whether multiple component numbers share the same coordinates in the same area. When such cases are found, their location is distinguished by comparing component size information or material category to prevent spatial conflicts. Extracting the organizational field requires further checking whether the work group number is duplicated in the project personnel list. If duplicates are found, the one with the shorter construction period is prioritized. After this series of retrieval and correspondence processes, the spatial location and organizational affiliation of all component numbers are extracted and associated, ultimately forming a data set containing paired component numbers, spatial fields, and organizational fields, resulting in a spatial-organizational field mapping group.

[0089] S403: Based on the spatial organization field mapping group, filter out the content with missing connections between the component field and the material field, analyze the unconnected data items by comparing the spatial field and the organization field, split the related information data, and obtain the form of uncollected material items;

[0090] First, all component numbers and their corresponding spatial and organizational field information in the mapping group are read. This data is then matched and retrieved against the component and material fields in the cost list. During execution, the component field list is read sequentially, and each component number is checked for a corresponding record in its material field. When a component number is found to exist in a component field but a corresponding item is missing in the material field, the component number is marked as a missing connection item. To ensure the accuracy of the filtering, a data integrity benchmark is set during the comparison. For example, if the proportion of missing fields reaches 3%, a secondary confirmation process is initiated, and the reasonableness of the omissions is verified by cross-comparing the spatial and organizational fields. For example, if the spatial field of component number GZ-135 corresponds to "Floor B-2 Zone" and the organizational field is "Reinforcing Steel Team R1", but no record with the same number is found in the material field, the device identifies the component as an unconnected item and extracts it synchronously with the corresponding spatial and organizational information. Subsequently, for all component numbers marked as missing, an inter-field correlation analysis is performed. By matching the area code of the spatial field with the construction responsibility zoning of the organizational field, it is determined whether the data connection is caused by zoning differences. During the analysis, each group of component numbers was cross-checked with its corresponding spatial segment and organizational affiliation. Duplicate or missing data entries within the same segment were removed, and missing items from different organizational zones were retained separately to prevent data cross-contamination. Next, the processed missing component data was split, with the association information for the component field, spatial field, and organizational field arranged in separate rows to maintain independent traceability. For example, the split data for number GZ-135 consisted of the component field "GZ-135", the spatial field "B-2 zone", and the organizational field "R1". Finally, all the split records were merged into a unified form, reordered according to component number, and compiled into a set containing all disconnected data items, ultimately resulting in the form of uncollected material items.

[0091] Please see Figure 6 The specific steps of S5 are as follows:

[0092] S501: Based on the material field and component field in the uncollected material item form, extract the organization field and material price field corresponding to each component field, classify the corresponding task status field, separate the status item of the component, and associate the organization field, price field, and task status field to obtain the organization and status field set.

[0093] First, the index of the number for all component fields is extracted, and the corresponding material field content is retrieved sequentially to confirm whether a complete material record exists under each component number. Then, for the matched component numbers, the associated organization field and material price field are extracted and processed side-by-side using the component number as the primary key, forming a preliminary field mapping set. During execution, the reading of the organization field must ensure that it has a unique identifier in the construction task database. If duplicates are found, they are distinguished by project partition code. For example, when component number GZ-211 appears in two different construction units, it is filtered by comparing its organization number prefix, retaining the first number as the currently valid record. Next, the task status field associated with each component number is categorized into three types: "In Progress," "Paused," and "Completed." The material price field of the corresponding component is then grouped into different data groups according to its status for subsequent processing. This process is implemented by logically judging the status fields in the task list, based on the numerical range of the task status flag bit. For example, a status flag value of 1 is defined as "In Progress," 2 as "Paused," and 3 as "Completed." When a component number corresponds to multiple status records, the latest status value is taken as the valid item. After completing the status classification, the organization field, material price field, and task status field are sequentially associated and merged using the component number as the index. For example, the organization field for component number GZ-211 is "Template Team A2", the material price field is "480 yuan", and the task status field is "In Progress". The merged record is (GZ-211, A2, 480 yuan, In Progress). After all data items are associated, the merged result is structurally validated to check for null values ​​or duplicates, and incomplete records are removed. Finally, all processed component numbers, organization fields, price fields, and status fields are combined into a single set of organization and status fields.

[0094] S502: Based on the set of organization and status fields, retrieve the correspondence between component number and task field. For each group of component number and task field data items, match the number data with the status field and price field to obtain the component task status mapping table.

[0095] First, the component number and its corresponding organization, task status, and material price fields for each record in the collection are read. Then, the corresponding item for each component number in the task field is retrieved by comparing it with the task fields in the task list database. During execution, matching is performed sequentially by component number. For each component number, its task code and operation item in the task list are retrieved. When multiple task types exist in a task field, the uniqueness of the task identifier is used to ensure a one-to-one correspondence between component numbers and task fields. For example, component number GZ-312 corresponds to "tying operation" in the task field, so this is taken as the main task item for the component, and its corresponding task status and price information are further associated. Next, the task field and status field under each component number are compared synchronously. If the status field shows "in progress," it is directly matched with the corresponding material price field; if the status field is "completed," a numerical validation is performed on the price field to eliminate abnormal values. If an item has a price of zero or significantly deviates from the average, manual verification is performed. Subsequently, all successfully matched records are integrated, and the component number, task field, task status field, and material price field are arranged sequentially to form a mapping structure with a two-way correspondence. During this process, to prevent incorrect matching due to duplicate numbers, a uniqueness check is performed on the component number, and conflicts are detected between records in the task and status fields. If multiple statuses correspond to the same task item, the record with the latest time is retained as the valid record. Through the above comparison and data filtering, the relationship between the component number and the task field is stably established, achieving a complete correspondence with the status and price fields. Finally, all retrieved, matched, and organized field relationships are arranged in the order of the component number to obtain the component task status mapping table.

[0096] S503: Based on the component task status mapping table, call the organization field, component field, material field, material price field, task field and status, match the corresponding field content, extract the association structure of the field items, and obtain the cost collection list;

[0097] First, the organization field, component field, material field, material price field, task field, and status field corresponding to each component number in the mapping table are read, and the content of these fields is matched. During execution, the component number is used as an index to perform a one-to-one search on each field in each record to confirm whether the content of each field has a related item under the same number. For example, when the component number GZ-406 corresponds to the task field "template installation", the status field "in progress", the organization field "template team B3", the material field "wooden template", and the price field "650 yuan", it is considered a complete match and enters the subsequent association processing stage. If any field content is missing for a component number, that item is temporarily skipped and processed after the data is supplemented. Next, a field parallel operation is performed on all valid records, and the organization field, task field, and status field under the same component number are cross-matched to ensure that the status information corresponds to the task execution stage. Then, the corresponding material field and price field are associated to form a multi-field association structure with the component number as the primary key. During this process, the matching order of each field is logically validated. First, the matching of the task field and status field is checked for consistency. Then, the matching of the organization field and price field is extended to prevent data misalignment. For example, if the task field is "tying operation" and the status field is "completed," the price field data for that component should be in the settlement status. Subsequently, all matched component numbers have their field items extracted, null values ​​and duplicate records are removed, and the data is rearranged in ascending order by component number for later aggregation. During data extraction, the consistency of field value types is also checked to ensure that material price fields are all in numeric format and task status fields are all in text format, preventing data mismatches from causing field parsing errors. Finally, all validated and matched field items are compiled uniformly by component number, outputting a complete data set containing component number, organization field, task field, status field, material field, and price field, resulting in a cost aggregation list.

[0098] Please see Figure 7 The cost accounting device based on big data includes:

[0099] The task path generation module obtains structural component numbers and drawing coordinate data, compares them with the component fields in the task list, analyzes the operation item types, extracts floor and organization information, and obtains the task binding path table by matching the drawing fields and operation fields.

[0100] The time conflict identification module extracts the material number and delivery time period fields from the task binding path table, extracts the task time field, compares the time coverage relationship, and obtains the corresponding material conflict distribution list by matching the spatial field and the time field.

[0101] The resource order screening module extracts the entry and exit time and sign-in time based on the corresponding material conflict distribution list, compares the order relationship, splits cross-cycle nodes, aligns the construction time and supply time, extracts the component numbers with inconsistent time order, and obtains the resource misalignment pointing sequence set.

[0102] The missing field extraction module is based on the resource misalignment pointing sequence set. By comparing the cost list fields, it extracts the unconnected component numbers, associates the space and organization fields, and identifies the unconnected content between the corresponding component field and material field to obtain the form of uncollected material items.

[0103] The list field output module extracts the organization and price fields from the material and component fields in the uncollected material item form, compares them with the task status field, extracts the correspondence between the component number and the task field, and obtains the corresponding field content to get the cost collection list.

[0104] The cost accounting computer equipment based on big data includes a memory and a processor, characterized in that the memory stores a computer program, and the processor executes the computer program to realize the above-mentioned cost accounting device based on big data.

[0105] 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 cost accounting method based on big data, characterized in that, Includes the following steps: S1: Obtain structural component numbers and drawing coordinate data, compare with the component fields in the task list, analyze the operation item types, extract the floor and organization fields, correspond to the drawing fields and operation fields, and obtain the task binding path table; S201: Based on the component number in the task binding path table, extract the associated material number field and delivery time field, extract the task start and end time field in the task list, compare the start and end nodes of the time field, remove component numbers with overlapping and discontinuous times, and obtain the set of numbers corresponding to the task delivery time. S202: Based on the task delivery time corresponding number set, retrieve the spatial field and task time field corresponding to the component number, compare the continuous state of the time interval according to the order of the component number, filter the component data with discontinuities in the time series, and obtain the spatial task time corresponding field group. S203: Based on the spatial task time corresponding field group, analyze the misalignment relationship between the delivery field and the task field time nodes, extract the component number of the time axis offset and match it with the material field to obtain the corresponding material conflict distribution list; S301: Based on the component number in the corresponding material conflict distribution list, extract the corresponding material entry / exit field and check-in time field, compare the time sequence, identify the interruption position of the time sequence, map the component number, and obtain the entry / exit record sequence distribution set; S302: Based on the sequence distribution set of the entry and exit records, extract the task time field and delivery time field of the cross-cycle component, compare the time node interval, juxtapose the time fields and associate them with the component number to obtain the time node interleaved mapping table; S303: Based on the time node interleaving mapping table, filter the component numbers whose construction and supply time sequences are interleaved, extract the offset sequence under the component number, and obtain the resource misalignment pointing sequence set; The resource misalignment pointing sequence set includes component number, difference between entry / exit and check-in time, and cross-period node field; The cross-cycle node refers to the node in the project where the time and task arrangements are inconsistent and overlapping between different cycles; S401: Based on the component numbers in the resource misalignment pointing sequence set, compare the component fields and material fields in the cost list, retrieve the material field corresponding to each component number, filter out missing associated component numbers, match the missing items with the component numbers, and obtain the set of unconnected component numbers; S402: Based on the set of unconnected component numbers, extract the spatial field and the organizational field. For each component number, associate the data items of the component number, spatial field and organizational field to obtain the spatial organizational field mapping group. S403: Based on the spatial organization field mapping group, filter out the content with missing connections between the component field and the material field, analyze the unconnected data items by comparing the spatial field and the organization field, split the associated information data, and obtain the uncollected material item form; S5: Based on the uncollected material item form, extract the organization field and price field, compare with the task status field, extract the correspondence between the component number and the task field, and obtain the corresponding field content to obtain the cost collection list.

2. The cost accounting method based on big data according to claim 1, characterized in that, The task binding path table includes component number, operation type, organization information, and drawing coordinate fields. The corresponding material conflict distribution list includes discontinuous component numbers, time coverage differences, and spatial and time fields arranged in sequence. The uncollected material item form includes unconnected component numbers, unconnected material numbers, spatial segment fields, and organizational unit fields. The cost collection list includes component number, material price fields, organization fields, and task execution status fields.

3. The cost accounting method based on big data according to claim 1, characterized in that, The organization field refers to the data field associated with the target organization and task allocation, mapping the person in charge, participating departments, and division of labor units for each task and activity.

4. The cost accounting method based on big data according to claim 1, characterized in that, The specific steps of S1 are as follows: S101: Obtain the component number from the structural component database and the coordinate field in the construction drawings, retrieve the corresponding item of the component number in the coordinate of the drawing, compare the coordinate axis segment with the component number, and obtain the field set corresponding to the component coordinate; S102: Based on the component coordinate corresponding field set, compare the component number field in the task list, filter the component numbers whose operation items are binding, erection and pouring, and extract the corresponding floor field and action field to obtain the component task field mapping set; S103: Based on the component task field mapping set, associate the drawing field and the operation item field, expand the pairing content of the component number and the floor field, link the action field and the organization field, and obtain the task binding path table.

5. The cost accounting method based on big data according to claim 1, characterized in that, The specific steps of S5 are as follows: S501: Based on the material field and component field in the uncollected material item form, extract the organization field and material price field corresponding to each component field, classify the corresponding task status field, separate the status item of the component, and associate the organization field, price field, and task status field to obtain a set of organization and status fields. S502: Based on the set of organization and status fields, retrieve the correspondence between component number and task field. For each group of component number and task field data items, match the number data with the status field and price field to obtain the component task status mapping table. S503: Based on the component task status mapping table, call the organization field, component field, material field, material price field, task field and status, match the corresponding field content, extract the association structure of the field items, and obtain the cost collection list.

6. A cost accounting device based on big data, characterized in that, The apparatus is used to implement the cost calculation method based on big data as described in any one of claims 1-5, and the apparatus comprises: The task path generation module obtains structural component numbers and drawing coordinate data, compares them with the component fields in the task list, analyzes the operation item types, extracts floor and organization information, and obtains the task binding path table by matching the drawing fields and operation fields. The time conflict identification module extracts the material number and delivery time fields and the task time field based on the task binding path table, compares the time coverage relationship, and obtains the corresponding material conflict distribution list by matching the spatial field and the time field. Based on the corresponding material conflict distribution list, the resource order screening module extracts the entry and exit time and check-in time, compares the order relationship, splits cross-cycle nodes, aligns the construction time and supply time, extracts the component numbers with inconsistent time order, and obtains the resource misalignment pointing sequence set. The missing item field extraction module, based on the resource misalignment pointing sequence set, compares the cost list fields, extracts the unconnected component numbers, associates the space and organization fields, and the unconnected content of the corresponding component field and material field to obtain the uncollected material item form. The list field output module extracts the organization and price fields from the material and component fields in the uncollected material item form, compares them with the task status field, extracts the correspondence between the component number and the task field, and obtains the corresponding field content to get the cost collection list.

7. A computer device for cost accounting based on big data, including a memory and a processor, characterized in that, The memory stores a computer program, and when the processor executes the computer program, it implements the cost accounting method based on big data as described in any one of claims 1-5.

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