Non-excavation repair cost measuring and calculating method for grouting pipeline after wall combination of stainless steel lining

Abstract

The invention discloses a non-excavation repair cost measuring and calculating method for a grouting pipeline after wall combination of a stainless steel lining. The method comprises the following steps: 1, establishing a cost subject division standard; the method specifically comprises the following steps: importing a file in which the expense subject division standard is stored into an expense standard, and reading listed information in the file; 2, analyzing the historical project file; the method specifically comprises the following steps: importing historical project files of various existing projects, and analyzing the historical project files including GUID codes, compiling time, project cost names, project cost unit prices, quantities, amounts and cost structural composition of project feature information; 3, optimizing standard data; the method specifically comprises the following steps of: de-duplicating and combining all item feature information with similar or same feature values; 4, converting the standard data; and 5, further applying the converted standard data to obtain the total cost. According to actual engineering characteristics and process characteristics, comparative analysis and characteristic matching with historical projects are carried out, and economic and technical indexes are effectively measured and calculated.

Description

Technical Field

[0001] The invention relates to the technical field of computer-aided design, and in particular to a method for calculating the cost of trenchless repair of a pipeline with stainless steel lining and wall grouting. Background Art

[0002] "Thin-wall stainless steel lining + back-grouting" is an advanced trenchless pipe repair process. The repair cost will vary according to different working conditions, such as the thickness and material of the stainless steel lining, the thickness and material selection of the back-grouting. For example, the thickness of the stainless steel lining, the type of stainless steel, the thickness of the back-grouting and the selection of grouting materials, the thickness of the grouting around the pipe and the selection of grouting materials, the material selection of the water stop at the pipe joint, whether it is a water-carrying repair, etc. Obviously, the cost composition is different for different subdivided working conditions.

[0003] At present, only a few regions, such as Guangdong, have quotas for trenchless repair that include this technology, and most regions do not have relevant standards.

[0004] Traditional cost estimation methods, such as manual experience judgment and reference cases, are inefficient and highly subjective, and are unable to meet the needs of modern project management.

[0005] Therefore, how to reduce human errors, improve work efficiency, provide more solid data support for the formulation of construction plans, make costs more transparent, avoid excessive investment, and make the construction process and measurement work more reasonable and based on evidence has become a technical problem that technical personnel in this field urgently need to solve. Summary of the invention

[0006] In view of the above-mentioned defects of the prior art, the present invention provides a cost calculation method for trenchless repair of pipelines with stainless steel lining and wall grouting. The purpose of the present invention is to achieve a cost estimation method based on big data and artificial intelligence technology. Through automated data processing and analysis, human errors are reduced, work efficiency is improved, and more solid data support is provided for the formulation of construction plans, making costs more transparent and avoiding excessive investment, thereby making the construction process and measurement work more reasonable and based on evidence.

[0007] To achieve the above object, the present invention discloses a method for calculating the cost of trenchless repair of a pipeline with stainless steel lining and wall grouting, comprising the following steps:

[0008] Step 1: Establish the cost account classification standard; specifically: import the file storing the cost account classification standard into the cost standard, and read the information listed in the file;

[0009] The information includes hierarchical structure, code, standard name, engineering cost name, characteristic classification, weight ratio W, unit and calculation formula;

[0010] Each of the engineering cost names is associated with a plurality of the characteristic classifications, including thickness T, material M, thickness P of back-wall grouting, and material selection N;

[0011] Each of the feature categories includes a corresponding weight ratio;

[0012] Develop calculation formulas to relate these characteristic categories to cost factors.

[0013] Step 2, parsing historical engineering files; specifically: importing the historical engineering files of various existing projects, parsing the cost structure of the historical engineering files to obtain GUID code, compilation time, engineering cost name, engineering cost unit price, quantity, amount and project feature information, extracting pipeline damage degree D, pipeline thickness T, strength S, corrosion resistance C, material type N, fluidity L, strength I, curing time H, and water stop material selection SW and water repair W;

[0014] Step 3, optimizing standard data; specifically: de-duplication and merging the feature information of all items with similar or identical feature values, where similarity refers to the range of feature values, for example: the thickness of the stainless steel lining is within the range of ±0.5 mm, and the thickness of the back wall grouting is within the range of ±10 mm;

[0015] Step 4: converting the standard data;

[0016] Step 5: further apply the converted standard data to obtain the total cost; specifically: use the characteristic values ​​of all the project characteristic information of the project to be measured as screening conditions, calculate the price index that meets the screening conditions; then calculate the price fluctuation rate according to the time of price fluctuation, multiply it by the price index obtained by the preliminary calculation, and make adaptive adjustments;

[0017] Stainless steel lining SC=T*M*C*W1

[0018] Back wall grouting PC = P*N*L*I*W2

[0019] Waterstop SWC=SW*W6

[0020] Repair with water WC=W*W7

[0021] Artificial LC = D*S*W3

[0022] Equipment EC = H * W4

[0023] Transport TC = C*W5

[0024] Material MC=SC+PC+SWC+WC

[0025] Total TC of single item = MC + LC + EC + TC

[0026] Among them, W1, W2, W3, W4, W5, W6, and W7 are the weight proportions of different cost factors;

[0027] Finally, multiply the adjusted unit price by the current amount of project costs, calculate the amount of each project cost, add up all the project cost amounts, and finally get the total cost.

[0028] Preferably, the file is an Excel file.

[0029] Preferably, step 4 is as follows:

[0030] Step 4.1, matching engineering costs; specifically, the GUID code and the engineering cost name obtained by parsing the cost structure of the historical engineering file are matched with the code and the engineering cost name in the cost subject classification standard in sequence;

[0031] Step 4.2, matching feature parameters; specifically: extracting the project features of the matched engineering cost name, matching the feature classification name with the feature classification, and associating feature value information, so that the historical engineering file is reorganized with the cost subject classification standard, and converted into a set of standard model data;

[0032] Step 4.3, merge multiple groups of standard model data into a complete classification standard tree, use feature classification and feature value as screening conditions, filter out standardized data that meets the conditions by adding different screening conditions, and then recalculate the price index of each classification standard according to the feature classification and weight ratio.

[0033] Beneficial effects of the present invention:

[0034] The present invention compares and analyzes actual engineering characteristics and process features with historical projects and performs characteristic matching, thereby effectively calculating economic and technical indicators.

[0035] The present invention is applicable to the rapid cost estimation of the trenchless repair process of pipelines with thin-walled stainless steel lining and post-grouting by utilizing cost data and data analysis technology through information-based cost modeling. It is also applicable to various maintenance projects such as municipal roads, drainage projects, and underground pipeline maintenance and renewal projects.

[0036] The concept, specific structure and technical effects of the present invention will be further described below in conjunction with the accompanying drawings to fully understand the purpose, characteristics and effects of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A flow chart showing an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0038] Example

[0039] like Figure 1 As shown in the figure, the cost calculation method for trenchless repair of pipelines with stainless steel lining and wall grouting includes the following steps:

[0040] Step 1: Establish the cost account classification standard; specifically: import the file containing the cost account classification standard into the cost standard, and read the information listed in the file;

[0041] The information includes hierarchical structure, code, standard name, engineering cost name, and feature classification, with special attention paid to the thickness and material of the stainless steel lining, the thickness of the wall grouting, and the material selection, and the material selection of the water stop strip at the pipeline joint SW and whether it is a water-bearing repair W, and the corresponding weight ratio, unit, and calculation formula;

[0042] Among them, each engineering cost name is associated with multiple feature classifications;

[0043] Each feature classification includes a corresponding weight ratio;

[0044] For example, the weight ratios of the characteristics of geological conditions, pipeline size, pipeline length and materials that have a greater impact on the cost of the repair project will be relatively high, and the impact on the cost will also be greater.

[0045] Step 2, parsing historical project files; specifically: importing historical project files of various existing projects, parsing the cost structure of the historical project files to obtain GUID code, compilation time, project cost name, project cost unit price, quantity, amount and project feature information;

[0046] Step 3: Optimize standard data; specifically: remove duplicates and merge all project feature information with similar or identical feature values, for example: the thickness of the stainless steel lining is within the range of ±0.5mm, and the thickness of the back wall grouting is within the range of ±10mm;

[0047] Deduplication and merging of all project feature information with similar or identical feature values ​​can ensure that when the corresponding feature classification or the corresponding feature value is used as a screening condition, more historical engineering files that meet the conditions can be screened out.

[0048] Step 4: Convert standard data;

[0049] Step 5: Further apply the converted standard data to obtain the total cost; specifically: use the characteristic values ​​of all project characteristic information of the project to be measured as screening conditions, and calculate the price index that meets the screening conditions; for example, if the pipe length is 10m, use the algorithm to classify the characteristics and weight ratio.

[0050] Then, according to the time of price fluctuation, calculate the price fluctuation rate, multiply it by the price index calculated initially, and make adaptive adjustments;

[0051] Stainless steel lining SC=T*M*C*W1

[0052] Back wall grouting PC = P*N*L*I*W2

[0053] Waterstop SWC=SW*W6

[0054] Repair with water WC=W*W7

[0055] Artificial LC = D*S*W3

[0056] Equipment EC = H * W4

[0057] Transport TC = C*W5

[0058] Material MC=SC+PC+SWC+WC

[0059] Total TC of single item = MC + LC + EC + TC

[0060] Among them, W1, W2, W3, W4, W5, W6, and W7 are the weight proportions of different cost factors;

[0061] Finally, multiply the adjusted price by the current amount of project costs, calculate the amount of each project cost, add up all the project cost amounts, and finally get the total cost.

[0062] In some embodiments, the file is an excel file.

[0063] In some embodiments, step 4 is as follows:

[0064] Step 4.1, match the project costs; specifically: parse the cost structure of the historical project files to obtain the GUID code and project cost name, and match them with the code and project cost name in the cost account classification standard; for example: lining material fee, grouting material fee, labor hour fee, equipment rental fee, etc.

[0065] Step 4.2, matching feature parameters; specifically: extracting the project features of the matched engineering cost names, matching the feature classification names with the feature classifications, and associating the feature value information, so as to reorganize the historical engineering files and the cost account classification standards and convert them into a set of standard model data;

[0066] Step 4.3: Merge multiple sets of standard model data into a complete classification standard tree, use feature classification and feature value as screening conditions, filter out qualified standardized data by adding different screening conditions, and then recalculate the price index of each classification standard according to feature classification and weight ratio.

[0067] The preferred specific embodiments of the present invention are described in detail above. It should be understood that a person skilled in the art can make many modifications and changes based on the concept of the present invention without creative work. Therefore, any technical solution that can be obtained by a person skilled in the art through logical analysis, reasoning or limited experiments based on the concept of the present invention on the basis of the prior art should be within the scope of protection determined by the claims.

Claims

1. A method for calculating the cost of trenchless repair of pipelines with stainless steel lining and wall grouting; it is characterized by: The steps include: Step 1: Establish the cost account classification standard; specifically: import the file storing the cost account classification standard into the cost standard, and read the information listed in the file; The information includes hierarchical structure, code, standard name, engineering cost name, characteristic classification, weight ratio W, unit and calculation formula; Each of the engineering cost names is associated with a plurality of the characteristic classifications, including thickness T, material M, thickness P of back-wall grouting, and material selection N; Each of the feature categories includes a corresponding weight ratio; Develop calculation formulas to relate these characteristic categories to cost factors. Step 2, parsing historical engineering files; specifically: importing the historical engineering files of various existing projects, parsing the cost structure of the historical engineering files to obtain GUID code, compilation time, engineering cost name, engineering cost unit price, quantity, amount and project feature information, extracting pipeline damage degree D, pipeline thickness T, strength S, corrosion resistance C, material type N, fluidity L, strength I, curing time H, and water stop material selection SW and water repair W; Step 3, optimizing standard data; specifically: de-duplication and merging the feature information of all items with similar or identical feature values, where similarity refers to the range of feature values, for example: the thickness of the stainless steel lining is within the range of ±0.5 mm, and the thickness of the back wall grouting is within the range of ±10 mm; Step 4: converting the standard data; Step 5: further apply the converted standard data to obtain the total cost; specifically: use the characteristic values ​​of all the project characteristic information of the project to be measured as screening conditions, calculate the price index that meets the screening conditions; then calculate the price fluctuation rate according to the time of price fluctuation, multiply it by the price index obtained by the preliminary calculation, and make adaptive adjustments; Stainless steel lining SC=T*M*C*W1 Back wall grouting PC = P*N*L*I*W2 Waterstop SWC=SW*W6 Repair with water WC=W*W7 Artificial LC = D*S*W3 Equipment EC = H * W4 Transport TC = C*W5 Material MC=SC+PC+SWC+WC Total TC of single item = MC + LC + EC + TC Among them, W1, W2, W3, W4, W5, W6, and W7 are the weight proportions of different cost factors; Finally, multiply the adjusted unit price by the current amount of project costs, calculate the amount of each project cost, add up all the project cost amounts, and finally get the total cost.

2. The method for calculating the cost of trenchless repair of a pipeline with stainless steel lining and wall grouting according to claim 1 is characterized in that: The file is an Excel file.

3. The method for calculating the cost of trenchless repair of a pipeline with stainless steel lining and wall grouting according to claim 1 is characterized in that: Step 4 is as follows: Step 4.1, matching engineering costs; specifically, the GUID code and the engineering cost name obtained by parsing the cost structure of the historical engineering file are matched with the code and the engineering cost name in the cost subject classification standard in sequence; Step 4.2, matching feature parameters; specifically: extracting the project features of the matched engineering cost name, matching the feature classification name with the feature classification, and associating feature value information, so that the historical engineering file is reorganized with the cost subject classification standard, and converted into a set of standard model data; Step 4.3, merge multiple groups of standard model data into a complete classification standard tree, use feature classification and feature value as screening conditions, filter out standardized data that meets the conditions by adding different screening conditions, and then recalculate the price index of each classification standard according to the feature classification and weight ratio.

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