Insulated concrete composite pole and big data-based power product quality traceability tracking management method

Abstract

The invention discloses an insulating concrete composite electric pole, and belongs to the technical field of power transmission equipment. The cable is composed of a main body part and an insulating part, and the main body part is wrapped by the insulating part. Wherein the main body is prepared from a composite concrete material, a plurality of insulating glass fiber reinforced plastic main reinforcements and a plurality of layers of insulating grid glass fiber cloth winding the main reinforcements; an electric power product quality traceability tracking management method based on big data is adopted in the preparation process of the insulated concrete composite electric pole; according to the electric power product quality traceability tracking management method based on big data, each insulation concrete composite electric pole is provided with a unique code, and the quality is tracked according to the unique code. The insulation portion wraps the main body portion to achieve the technical effects of electric pole insulation, electric shock prevention, product quality guarantee and traceability of the product quality.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission equipment, and particularly to an insulated concrete composite electric pole, and more particularly to an insulated concrete composite electric pole and a method for tracing and managing the quality of power products based on big data. Background Art

[0002] As the name implies, an electric pole is a pole for supporting electric wires. It appears in various rural areas, fields, roads, and streets, and was one of the important infrastructure in early China. All early electric poles started from wooden poles, even including high-voltage electric poles with relatively low voltage levels. Later, due to the development of steel and reinforced concrete and technical requirements, these two materials replaced most of the wooden poles, and the applicable wood gradually became scarce, so it is basically difficult to see wooden poles in cities.

[0003] However, during the process of implementing the technical solutions in the prior art, the applicant found that the following technical problems exist in the technical solutions of the prior art:

[0004] If an electric pole encounters a thunderstorm, lightning may directly strike the ground along the electric pole, affecting the safety of personnel near the electric pole. In addition, the vast majority of production scales are small, the equipment is simple, and the technology is imperfect. Quality problems in the produced power products are often visible, and the quality problems are not limited to those caused during the production process. There may also be product failures caused during transportation or application, but they are all attributed to production quality. There is inaccurate analysis of quality abnormalities caused by production, resulting in a serious decline in the efficiency of problem-solving, and it is not easy to guarantee the production quality of electric poles. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an insulated concrete composite electric pole, which solves the technical problems that the electric pole in the prior art is not lightning-proof and the product quality cannot be guaranteed, and at least achieves one of the technical effects that the electric pole is lightning-proof and the product quality is traced and guaranteed.

[0006] To solve the above technical problems, the technical solution of the present invention is as follows:

[0007] An insulated concrete composite electric pole is composed of a main body part and an insulating part, and the main body part is surrounded by the insulating part; wherein, the main body is prepared from composite concrete materials, multiple insulating fiberglass main bars, and multiple layers of insulating grid fiberglass cloth wound around the main bars; the insulated concrete composite electric pole adopts a method for tracing and managing the quality of power products based on big data during at least one of the preparation process, transportation process, or construction process; wherein, through the method for tracing and managing the quality of power products based on big data, each insulated concrete composite electric pole is set with a unique code, and the quality is traced according to the unique code.

[0008] Preferably, the composite concrete material includes graphene oxide; the insulating part is a polymer insulating material, which includes rubber, nano-zinc oxide, nano-silica and fillers, and the rubber and fillers are prepared from municipal solid waste; the main body part includes at least one whole section;

[0009] The quality includes at least one of the quality in the production process, the quality in the transportation process and the quality in the application process.

[0010] Preferably, the main body part is formed by splicing multiple sections or integrally formed;

[0011] The big data-based power product quality traceability and tracking management method includes:

[0012] Step 1: Obtain the preset manufacturer, preset transporter and preset user of the target power product, and combine the production serial number of the target power product to set a unique code for the matching target power product;

[0013] Step 2: Conduct the first quality tracking on the production process of the preset manufacturer of the target power product, the second quality tracking on the transportation process of the preset transporter, and the third quality tracking on the application process of the preset user;

[0014] Step 3: Based on the quality tracking results, conduct a comprehensive quality analysis on the target power product, and lock the abnormal stage of the target power product and the abnormal factor corresponding to the abnormal stage;

[0015] Step 4: Based on the unique code of the corresponding power product and the abnormal factor, construct an abnormal storage block and conduct abnormal management on the target power product;

[0016] Among them, conducting the third quality tracking on the application process of the preset user includes:

[0017] According to the monitoring results of each application stage in the application process of the preset user, construct a placement matrix of the stage placement result and the standard placement result of each application stage;

[0018] Set a placement label for each placement matrix and construct an application label vector corresponding to the target power product to achieve the third quality tracking;

[0019] Among them, obtaining the preset manufacturer, preset transporter and preset user of the target power product, and combining the production serial number of the target power product to set a unique code for the matching target power product includes:

[0020] Obtain the manufacturer number of the preset manufacturer of the target power product;

[0021] Obtain the carrier number of the preset carrier of the target power product;

[0022] Obtain the applicant number of the preset applicant of the target power product;

[0023] Based on the manufacturer number, carrier number, applicant number, and production serial number, obtain a unique code.

[0024] More preferably, the first quality tracking of the production process of the preset manufacturer of the target power product includes:

[0025] Obtain the standard production results and actual production results of the production molds in each production stage during the production process, and construct a regular comparison matrix and a special comparison matrix according to the regular production factors and special production factors of each production process;

[0026] Perform a first analysis on the regular comparison matrix, a second analysis on the special comparison matrix, and factor fusion of the regular production factors and special production factors according to the production nature of the corresponding production stage to obtain a final comparison matrix, and perform a third analysis on the final comparison matrix;

[0027] Extract the first feature based on the first analysis result, the second feature based on the second analysis result, and the third feature based on the third analysis result;

[0028] Perform a mutual feature analysis on the first feature and the second feature with the third feature to obtain a mutual exclusion value;

[0029]

[0030] Among them, T1 represents the first feature; T2 represents the second feature; T3 represents the third feature; ∪ represents the union symbol; ∩ represents the intersection symbol; ln represents the natural logarithm function symbol with base e; lg represents the common logarithm function symbol with base 10; n1 represents the number of intersection features corresponding to (T1∪T2)∩T3; p i represents the historical intersection probability of the i-th intersection feature; represents the fine-tuning function of; H1 represents the corresponding mutual exclusion value;

[0031] When the mutual exclusion value is less than the first preset value, set a first quality label for the corresponding production stage according to the third analysis result;

[0032] Otherwise, obtain the information volume x1 of the first abnormal information of the first analysis result and the second analysis result, and the information volume x2 of the second abnormal information of the third analysis result. According to max{x1, x2}, use the analysis result with the larger information volume as the main analysis result, and the analysis result with the smaller information volume as the secondary analysis result. Extract the non-intersecting abnormal results with a weight ratio greater than the preset ratio in the secondary analysis result, and perform result fusion with the main analysis result, and set the second quality label for the corresponding production stage;

[0033] Obtain the production label vector of the corresponding target power product according to the quality label of each production stage in the production process, and realize the first quality tracking.

[0034] More preferably, the second quality tracking of the transportation process of the preset transportation party includes:

[0035] Extract the transportation path in the transportation log generated by the preset transportation party during the transportation process and the stage transportation impact factor of each transportation stage in the transportation path;

[0036] Obtain the transportation constraint conditions of each transportation stage, and set an effective transportation label for the corresponding transportation stage;

[0037] Extract the constraint factors in the transportation constraint conditions and the constraint range of each constraint factor, and perform consistency analysis on the constraint factors and the stage transportation impact factors;

[0038] When there is a constraint factor consistent with the stage transportation impact factor and the influence value of the corresponding stage transportation impact factor is within the constraint range, set a factor consistency value of 1 for the corresponding stage transportation impact factor;

[0039] When there is a constraint factor consistent with the stage transportation impact factor and the influence value of the corresponding stage transportation impact factor is not within the constraint range, if then set a factor consistency value of 0 for the corresponding stage transportation impact factor, where maxy1 represents the maximum value y1 based on the constraint range, miny2 represents the minimum value y2 based on the constraint range; y0 represents the influence value of the corresponding stage transportation impact factor, where the values of y0, miny2, and maxy1 are greater than or equal to 0, and maxy1 is greater than miny2;

[0040] If then set a factor consistency value of a1 for the corresponding stage transportation impact factor, where the value range of a1 is (0, 1);

[0041] When there is a constraint factor inconsistent with the stage transportation impact factor, determine whether the existing constraint factors cover all stage transportation impact factors;

[0042] If included, determine the factor consistency value of the transportation impact factor for the corresponding stage according to the corresponding setting result.

[0043] If not included, determine the occurrence frequency of the stage transportation impact factor based on the entire transportation path.

[0044] When Set the factor consistency value to -1 for the transportation impact factor of the corresponding stage, where p1 represents the individual occurrence frequency of the transportation impact factor of the corresponding stage based on the entire transportation path; p2 represents the non - individual occurrence frequency of the transportation impact factor of the corresponding stage based on the entire transportation path.

[0045] When Set the factor consistency value to a2 for the transportation impact factor of the corresponding stage, where the value range of a2 is (-1, 0).

[0046] Calculate the stage consistency value for the corresponding transportation stage according to the factor consistency value.

[0047] Match and obtain the effective transportation label related to the stage consistency value from the value - label mapping table.

[0048] Based on the effective transportation label, obtain the transportation label vector of the corresponding target power product to achieve the second quality tracking.

[0049] Specifically preferred, the comprehensive quality analysis of the target power product based on the quality tracking result includes:

[0050] Perform a first comparative analysis of the production label vector of the first quality tracking result with the standard production vector, a second comparative analysis of the transportation label vector of the second quality tracking result with the standard transportation vector, and a third comparative analysis of the application label vector of the third quality tracking result with the standard application label.

[0051] According to the comparison results, determine the quality problems corresponding to each process and the problem - related information of the production process, transportation process, and application process; lock the abnormal stage of the target power product and the abnormal factors corresponding to the abnormal stage, including:

[0052] Lock the abnormal stage and the initial factors existing in the abnormal stage according to the quality problems of each process.

[0053] Optimize the initial factors according to the problem - related information of the production process, transportation process, and application process to obtain the abnormal factors corresponding to the abnormal stage.

[0054] The present invention also provides a method for quality traceability and tracking management of power products based on big data, which is applied to the production of any of the insulating concrete composite electric poles described above.

[0055] Preferably, an abnormal storage block is constructed based on the unique code of the corresponding power product and the abnormal factor, including:

[0056] Process chains for each process are respectively constructed, where each process chain includes several process stages;

[0057] The abnormal factors involved in each process and the abnormal stages corresponding to the corresponding abnormal factors are set at the matching process stages to obtain the corresponding storage chains;

[0058] An abnormal storage block larger than the total chain space is constructed according to the chain space of each storage chain of the target power product with a unique code;

[0059] An abnormal storage block is constructed, and abnormal management is performed on the target power product, including:

[0060] The abnormal storage blocks of the power products of the same type are associated with each other, and a corresponding association framework is constructed based on the block positions of the abnormal storage blocks of the power products of the same type;

[0061] The most prominent abnormality of each storage block on the association framework is displayed with a first annotation, and the high-frequency abnormality is displayed with a second annotation, and the same abnormality management and prominent abnormality management are performed on the power products of the same type.

[0062] More preferably, the power product quality traceability and tracking management method based on big data further includes a system, and the system includes:

[0063] A coding setting module, configured to obtain the preset manufacturer, preset transporter, and preset application party of the target power product, and combine the production serial number of the target power product to set a unique code for the matching target power product;

[0064] A quality tracking module, configured to perform first quality tracking on the production process of the preset manufacturer of the target power product, second quality tracking on the transportation process of the preset transporter, and third quality tracking on the application process of the preset application party;

[0065] An abnormality locking module, configured to perform comprehensive quality analysis on the target power product based on the quality tracking results, and lock the abnormal stage of the target power product and the abnormal factor corresponding to the abnormal stage;

[0066] An abnormality management module, configured to construct an abnormal storage block based on the unique code of the corresponding power product and the abnormal factor, and perform abnormality management on the target power product.

[0067] One or more technical solutions provided by this application have at least the following technical effects or advantages:

[0068] In the above technical solution, since it is composed of a main body part and an insulating part, and the main body part is surrounded by the insulating part; among them, the main body is prepared from composite concrete material, multiple insulating glass fiber reinforced plastic main bars, and insulating grid glass fiber cloth wound around the main bars in multiple layers; a series of technical means such as a power product quality traceability and tracking management method based on big data are adopted in the preparation process of the insulating concrete composite electric pole. The combination of the insulating part surrounding the main body part and the main body part being prepared from composite concrete material, multiple insulating glass fiber reinforced plastic main bars, and insulating grid glass fiber cloth wound around the main bars in multiple layers enables the outside of the electric pole to be insulated and the support structure of the main body part to be insulated to a certain extent, which can prevent lightning from flowing through easily; through the power product quality traceability and tracking management method based on big data, each insulating concrete composite electric pole is set with a unique code, and the quality is tracked according to the unique code. It effectively solves the technical problems that the electric poles in the prior art are not lightning-proof and the production quality cannot be guaranteed, and further realizes the technical effect that the electric poles are lightning-proof and the production quality is guaranteed by traceability and tracking. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 is a schematic structural diagram of the present invention;

[0070] Figure 2 is a sectional view of the present invention;

[0071] Figure 3 is a flowchart of a power product quality traceability and tracking management method based on big data in an embodiment of the present invention;

[0072] Figure 4 is a structural diagram of a power product quality traceability and tracking management system based on big data in an embodiment of the present invention;

[0073] Figure 5 is a structural diagram of an associated framework in an embodiment of the present invention.

[0074] In the figure, 100, main body part; 110, composite concrete material; 120, insulating glass fiber reinforced plastic main bar; 130, insulating grid glass fiber cloth; 200, insulating part; 300, unique code. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0075] The following further describes the specific embodiments of the present invention with reference to the drawings. It should be noted here that the description of these embodiments is for helping to understand the present invention, but does not constitute a limitation to the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0076] High-voltage transmission networks or urban lighting devices cannot do without poles. For example, the existing 1,000-volt high-voltage line transmission network cannot do without concrete poles, and street lights cannot do without concrete poles. Concrete poles stand on the ground, which is equivalent to grounding. During thunderstorms, lightning may enter the ground through the poles. In addition, if high-voltage line poles or street light poles are used as grounding parts, there may be certain safety hazards during construction. In addition, from raw materials to applications, poles go through the production, transportation and construction processes. Improper operation in each process will affect the product quality of the poles.

[0077] The technical solution of the implementation mode of the present application solves the problem that the poles in the prior art are not protected against lightning and the product quality cannot be guaranteed by providing an insulating concrete composite pole. When the main part 100 is surrounded by the insulating part 200 and combined with the insulating concrete composite pole, a power product quality traceability and tracking management method based on big data is adopted in at least one of the preparation process, transportation process or construction process to achieve the beneficial effect of lightning protection of the pole and traceability guarantee of product quality.

[0078] The overall idea of the implementation solution of the present invention to solve the above technical problems is as follows:

[0079] An insulated concrete composite electric pole consisting of a main body part 100 and an insulated part 200, such as Figure 1 As shown, the main body portion 100 is surrounded by the insulating portion 200 . The main body portion 100 includes concrete.

[0080] The insulating concrete composite pole adopts a power product quality traceability and tracking management method based on big data in at least one of the preparation process, transportation process or construction process; wherein, through the power product quality traceability and tracking management method based on big data, each insulating concrete composite pole is set with a unique code 300, and the quality is tracked according to the unique code 300.

[0081] When lightning strikes the surface of the pole, since the main body 100 of the pole is surrounded by the insulating part 200 to form an insulating concrete composite pole with an insulating layer on the outside and a main body layer on the inside, the lightning cannot easily fall to the ground from the pole surface.

[0082] When a pole has a quality problem, it can be traced back through its unique code 300 to understand its production process (including batches), its transportation process, or its application process in the actual use site. This will clearly understand the experience of the product in various environments and identify the specific link where the problem occurs, so as to avoid the same problem from happening again.

[0083] To further improve the insulation level of the utility pole, the main body is prepared from a composite concrete material 110, multiple insulating fiberglass main bars 120, and multiple layers of insulating grid fiberglass cloth 130 wound around the main bars. By adopting an insulating support structure combining the insulating fiberglass main bars 120 and the insulating grid fiberglass cloth 130, the insulation level of the utility pole is further improved to enhance its resistance to lightning strikes and also improve the safety of operation and construction.

[0084] To better understand the above technical solution, the above technical solution will be described in detail below in combination with the specification drawings and specific implementation manners.

[0085] An insulating concrete composite utility pole, as Figure 1 and Figure 2 shown, is composed of a main body part 100 and an insulating part 200, and the main body part 100 is surrounded by the insulating part 200. Among them, the main body is prepared from a composite concrete material 110, multiple insulating fiberglass main bars 120, and multiple layers of insulating grid fiberglass cloth 130 wound around the main bars. The insulating concrete composite utility pole adopts a big data-based power product quality traceability and tracking management method at least in one of the preparation process, transportation process, or construction process. Among them, through the big data-based power product quality traceability and tracking management method, each insulating concrete composite utility pole is set with a unique code 300, and the quality is tracked according to the unique code 300.

[0086] Among them, the composite concrete material 110 includes graphene oxide; the insulating part 200 is a polymer insulating material, and the polymer insulating material includes rubber, nano-zinc oxide, nano-silica, and fillers, and the rubber and fillers are prepared from municipal solid waste; the main body part 100 includes at least one whole section (that is, the main body part 100 can be composed of multiple sections spliced together or integrally formed).

[0087] Among them, the quality includes at least one of the production process quality, transportation process quality, and application process quality, preferably the production process quality, transportation process quality, and application process quality.

[0088] The embodiment of the present invention also provides a big data-based power product quality traceability and tracking management method, as Figure 5 shown, including:

[0089] Step 1: Obtain the preset manufacturer, preset transporter, and preset user of the target power product, and combine the production serial number of the target power product to set a unique code 300 for the matching target power product;

[0090] Step 2: Conduct the first quality tracking on the production process of the preset manufacturer of the target power product, the second quality tracking on the transportation process of the preset transporter, and the third quality tracking on the application process of the preset user;

[0091] Step 3: Based on the quality tracking results, conduct a comprehensive quality analysis on the target power product, and lock the abnormal stage of the target power product and the abnormal factors corresponding to the abnormal stage;

[0092] Step 4: Based on the unique code 300 of the corresponding power product and the abnormal factors, construct an abnormal storage block, and conduct abnormal management on the target power product.

[0093] In this embodiment, the target power products refer to concrete poles and cable trench covers.

[0094] In this embodiment, the preset manufacturer refers to the manufacturing enterprise that produces concrete poles and cable trench covers. The preset transporter refers to the transportation vehicles, transportation personnel, etc. that need to transport the products from the production factory of the enterprise to the destination where the power products are to be used after the production of concrete poles and cable trench covers. The preset user refers to the user of the power product when the power product is transported to the destination, and this user can be a person or a device.

[0095] In this embodiment, the unique code 300: preset manufacturer serial number + preset transporter serial number + preset user serial number + production serial number, where the preset manufacturer serial number, preset transporter serial number, and preset user serial number all have corresponding codes, and the production serial number is composed of the production time and production batch.

[0096] For example, the unique code 300 is: @@1##1￥￥11001&1, where @@1 represents the preset manufacturer serial number, ##1 represents the preset transporter serial number, ￥￥1 represents the preset user serial number, 1001 represents the production time, and &1 represents the production batch.

[0097] In this embodiment, the production process of concrete poles includes: the production of steel bar skeletons, concrete mixing, mold cleaning and mold installation, prestressed steel bar tensioning, centrifugal forming, curing, and demolding, etc. That is, the production stages involved in different power products are different, and the production stages corresponding to each power product are the manufacturing processes set by the enterprise during the product manufacturing process. That is, the production process of each power product is public and the automatic control parameters corresponding to each stage of the production product are set in advance, and there are standard parameters consistent with the automatic control parameters, which all belong to the prior art.

[0098] In this embodiment, by monitoring each stage in the production process of the power product, the quality of the produced power product is determined.

[0099] In this embodiment, the transportation process of the power product includes: monitoring each operating logistics section and the product damage problem of the power product on the logistics transportation section, so as to determine the quality of the power product obtained by transportation. Since each power product has a corresponding transportation starting point and transportation ending point, it is necessary to monitor the transportation processes of different power products.

[0100] In this embodiment, the application process of the power product refers to the usage of the product. For example, an electric pole is used to support the wire, and each stage in the support process needs to be monitored, such as the stages of burying the electric pole into the soil, filling the soil, and installing guy wires based on the buried electric pole.

[0101] In this embodiment, the quality monitoring based on the production process is for determining whether there are production quality problems with the electric poles in each production stage, and then conducting the first quality tracking.

[0102] The quality monitoring based on the transportation process is for determining whether there are quality problems with the products due to external reasons, such as product collisions caused by difficult road driving, product dropping, or human factors, on different transportation sections during transportation, and then conducting the second quality tracking.

[0103] The quality monitoring based on the application process is for determining the application situation of the product in each application stage. Since application operation errors will inevitably occur during the application process, such as the pole falling during the pole erection process, and then conducting the third quality tracking.

[0104] In this embodiment, the comprehensive quality analysis means that each quality tracking result will have a corresponding quality tracking vector. Therefore, after comparing the standard vector corresponding to each process with the corresponding quality tracking vector, the abnormal stages and abnormal factors will be obtained. Among them, the abnormal factor is the element parameter that is inconsistent during the comparison process between the corresponding standard vector and the quality tracking vector.

[0105] For example, in the production process: stage 1, stage 2, and stage 3, the corresponding production quality vectors are: [r1 r2 r3], where r1 is the quality result of stage 1, r2 is the quality result of stage 2, and r3 is the quality result of stage 3. The standard vector is [r01 r02 r03], where r01 is the standard result of stage 1, r02 is the standard result of stage 2, and r03 is the standard result of stage 3. At this time, in stage 1: r1 is compared with r01, in stage 2: r2 is compared with r02, and in stage 3: r3 is compared with r03. Finally, the abnormal stage and the corresponding abnormal factors in the abnormal stage will be locked. For example, the abnormality between r1 and r01 occurs because in the actual process of manufacturing according to the steel bar skeleton, there is a lack of automated manufacturing according to the skeleton. That is, originally it was a complete manufacturing according to the skeleton, but in the actual process, a certain part of the skeleton cannot be manufactured, and the remaining parts can be manufactured. Therefore, there is a manufacturing deficiency.

[0106] In this embodiment, each power product includes three processes: production, transportation, and application, and there are corresponding quality monitoring results for each process. Furthermore, the stages and abnormal factors that may cause quality problems are locked and obtained to obtain the storage block for this power product. When subsequent impacts are caused by this power product, it is convenient to quickly trace back according to the unique code 300, timely determine the existing problems, and facilitate solution.

[0107] In this embodiment, the abnormal storage block is the corresponding storage unit, mainly for storing the existing abnormal stages and the corresponding abnormal factors in this stage, which is convenient for subsequent direct tracing.

[0108] In this embodiment, the abnormal storage block includes: process - abnormal stage - abnormal factor. For example, production process - skeleton manufacturing - skeleton deficiency.

[0109] In this embodiment, the main quality problem of the concrete pole is joint leakage of mortar. Joint leakage of mortar in the pole means that the cement mortar in the concrete at the joint of the pole is lost, and sand and stones are exposed on the concrete surface. Due to the occurrence of leakage, the compactness of the concrete is affected, and even capillary pores may extend into the interior of the concrete. Chloride ions, oxygen, carbon dioxide, and moisture are likely to penetrate, causing the concrete to be easily carbonized, and chloride ions are also likely to reach the surface of the steel bars, causing the steel bars to rust, thereby shortening the service life of the pole. Joint leakage of mortar is the main item causing the unqualified appearance quality of the pole. Therefore, it is necessary to monitor and trace back the production process, transportation process, and application process.

[0110] Among them, if the steel formwork used for producing the pole does not meet the requirements of JC364 - 86 "Steel Formwork for Circular Prestressed Concrete Poles", and the gap between the assemblies of the steel formwork is too large, it is easy to cause joint leakage of mortar.

[0111] During the production process, the outside of the joints were not cleaned after the concrete pouring was completed, and the outside of the joints were not cleaned each time the mold was removed, resulting in hardened cement mortar remaining on the parting surface and notches of the steel mold, making the steel mold joints loose and causing leakage at the joints.

[0112] When assembling the steel mold, the bolt tightening method is improper, the bolts cannot be tightened symmetrically and evenly, and there are even cases where the bolts are not tightened, causing the two joints of the steel mold to be unevenly stressed in length and direction, resulting in local looseness in the joints and leakage of slurry.

[0113] Due to the failure to meet the requirements for the installation of the centrifuge, the large tolerance of the outer diameter of the centrifuge support wheel and the deformation of the steel mold, the steel mold will jump during the centrifugal forming of the pole. In severe cases, the bolts will loosen and cause leakage in the joints.

[0114] There are two types of concrete poles: ordinary reinforced concrete poles and prestressed concrete poles. The cross-section of the poles is square, octagonal, I-shaped, circular or other special-shaped sections. The most commonly used are circular and square sections. The length of the pole is generally 4.5 to 15 meters. There are two types of circular poles: tapered poles and equal-diameter poles. The tip diameter of the tapered pole is generally 100 to 230 mm, and the taper is 1:75; the diameter of the equal-diameter pole is 300 to 550 mm; the wall thickness of both is 30 to 60 mm.

[0115] The above data will be used in the production process.

[0116] In this embodiment, the materials of the cable trench cover are reinforced concrete, reinforced concrete and steel, and the manufacturing requirements are as follows: the cover frame should be straight, without burrs and torque deformation, the length and diagonal size deviation should be less than 1.5mm, and the flatness after installation should be less than 2mm.

[0117] The beneficial effect of the above technical solution is: by tracking the quality of the production process, transportation process and application process of the target power product, it is convenient to timely lock the abnormal location of the product, avoid attributing all the abnormalities to quality problems caused by production, and realize effective traceability management of the product.

[0118] The present invention provides a power product quality traceability management method based on big data, which obtains the preset producer, the preset transporter and the preset user of the target power product, and sets a unique code 300 for the matching target power product in combination with the production serial number of the target power product, including:

[0119] Obtain the manufacturer number of the preset manufacturer of the target power product;

[0120] Obtaining the transporter number of the preset transporter of the target power product;

[0121] Obtain the application party number of the preset application party of the target power product;

[0122] Based on the production party number, the transportation party number, the application party number, and the production serial number, obtain the unique code 300.

[0123] The beneficial effects of the above technical solution are: By combining the codes corresponding to the three processes with the production serial number, it is convenient to ensure the uniqueness of the power product and provide an accurate basis for the reasonable traceability of the product.

[0124] The present invention provides a method for tracing and managing the quality of power products based on big data, which performs the first quality tracing on the production process of the preset production party of the target power product, including:

[0125] Obtain the standard production results and the actual production results of each production stage in the production process, and construct a conventional comparison matrix and a special comparison matrix according to the conventional production factors and the special production factors of each production process;

[0126] Perform the first analysis on the conventional comparison matrix, perform the second analysis on the special comparison matrix, and perform factor fusion on the conventional production factors and the special production factors according to the production nature of the corresponding production stage to obtain the final comparison matrix, and perform the third analysis on the final comparison matrix;

[0127] Extract the first feature based on the first analysis result, the second feature based on the second analysis result, and the third feature based on the third analysis result;

[0128] Perform mutual feature analysis on the first feature and the second feature with the third feature to obtain a mutual exclusion value;

[0129]

[0130] Among them, T1 represents the first feature; T2 represents the second feature; T3 represents the third feature; ∪ represents the union symbol; ∩ represents the intersection symbol; ln represents the natural logarithm function symbol with base e; lg represents the common logarithm function symbol with base 10; n1 represents the number of intersection features corresponding to (T1 ∪ T2) ∩ T3; p i represents the historical intersection probability of the i-th intersection feature; represents the fine-tuning function of; H1 represents the corresponding mutual exclusion value;

[0131] When the mutual exclusion value is less than the first preset value, set the first quality label for the corresponding production stage according to the third analysis result;

[0132] Otherwise, obtain the information amount x1 of the first abnormal information of the first analysis result and the second analysis result, and the information amount x2 of the second abnormal information of the third analysis result. According to max{x1, x2}, use the analysis result with the larger information amount as the main analysis result, and the analysis result with the smaller information amount as the secondary analysis result. Extract the non-intersecting abnormal results with a weight ratio greater than the preset ratio in the secondary analysis result, and perform result fusion with the main analysis result, and set the second quality label for the corresponding production stage.

[0133] Obtain the production label vector of the corresponding target power product according to the quality labels of each production stage in the production process, and realize the first quality tracking.

[0134] In this embodiment, due to reasons such as lax process control, poor raw material quality, weak quality management, old production equipment, and vicious competition, the appearance quality of the circular concrete pole products is poor, the dimensional deviation is large, and there are mechanical property defects. Therefore, it is necessary to analyze the combination of the production standards and the actual situation of each production stage to determine the abnormalities existing in the corresponding stage.

[0135] In this embodiment, since each power product has corresponding production setting parameters and corresponding production operations are performed according to the set parameters, there will be production results corresponding to the standards of different stages. And by monitoring the actual production process of each stage, the actual production results are obtained. Because each production process involves several factors, including conventional factors and specifically set factors, a matrix for conventional factors and specifically set factors is constructed.

[0136] Among them, conventional factors, such as working current and working voltage, and special production factors: the mixing amount of concrete.

[0137] At this time:

[0138]

[0139] In this embodiment,

[0140]

[0141] In this embodiment, factor fusion means placing the corresponding factors together.

[0142] In this embodiment, the analysis results caused by different factors corresponding to the matrix are different. Therefore, consider from three aspects: conventional, special, and fusion, and calculate the existing mutually exclusive values.

[0143] In this embodiment, the features corresponding to different analysis results are used to judge the analysis results based on a pre-trained model to obtain matching features. This model is trained on a neural network model based on different training samples (features that can be extracted from factors and different combinations of factors, mainly production features) to obtain the features of the analysis results in different situations. Since the analysis results are the elements and element differences in different matrices.

[0144] In this embodiment, the first preset value is 0.5.

[0145] In this embodiment, the information volume refers to the anomalies existing in the corresponding analysis results. Since there are several production indicators (factors) in each production stage, there will be different information volumes of anomalies.

[0146] In this embodiment, if x1 is greater than x2, at this time, the analysis result corresponding to x1 is used as the main analysis result, and the analysis result corresponding to x2 is used as the secondary analysis result.

[0147] In this embodiment, the secondary analysis results: abnormal result 01 - 0.1 (corresponding weight), abnormal result 02 - 0.2 (corresponding weight). At this time, the preset ratio is 0.1, and the abnormal result 02 is a non-intersecting abnormal result (there is no intersection with the anomalies of the other two analysis results). At this time, the abnormal result 02 is fused.

[0148] In this embodiment, the quality label is mapped from the result-label mapping table based on the abnormal results existing in the corresponding stage. The result-label mapping table includes abnormal combinations in different stages and labels consistent with the abnormal combinations, mainly for the effective acquisition of labels.

[0149] In this embodiment, the production label vector = [quality label of production stage 01, quality label of production stage 02,...].

[0150] The beneficial effects of the above technical solution are: by obtaining the standard results and actual results of each production stage, constructing conventional and special matrices, and then through the comparative analysis and feature extraction of the three matrices to calculate the exclusive value, setting effective labels for each subsequent production stage to ensure the reliability of the first quality tracking and providing an effective basis for traceability.

[0151] The present invention provides a method for tracing and managing the quality of power products based on big data, which performs second quality tracking on the transportation process of a preset transportation party, including:

[0152] Extracting the transportation path in the transportation log generated by the preset transportation party during the transportation process and the stage transportation impact factors of each transportation stage in the transportation path;

[0153] Obtain the transportation constraints for each transportation stage and set valid transportation tags for the corresponding transportation stage;

[0154] Extract the constraint factors in the transportation constraints and the constraint range of each constraint factor, and perform a consistency analysis between the constraint factors and the stage transportation impact factors;

[0155] When there is a constraint factor that is consistent with the stage transportation impact factor and the impact value of the corresponding stage transportation impact factor is within the constraint range, set a factor consistency value of 1 for the corresponding stage transportation impact factor;

[0156] When there is a constraint factor that is consistent with the stage transportation impact factor and the impact value of the corresponding stage transportation impact factor is not within the constraint range, if then set a factor consistency value of 0 for the corresponding stage transportation impact factor, where maxy1 represents the maximum value y1 based on the constraint range, miny2 represents the minimum value y2 based on the constraint range; y0 represents the impact value of the corresponding stage transportation impact factor, where the values of y0, miny2, and maxy1 are greater than or equal to 0, and maxy1 is greater than miny2;

[0157] If then set a factor consistency value of a1 for the corresponding stage transportation impact factor, where the value range of a1 is (0, 1);

[0158] When there is a constraint factor that is inconsistent with the stage transportation impact factor, determine whether the existing constraint factors cover all stage transportation impact factors;

[0159] If it covers, determine the factor consistency value of the corresponding stage transportation impact factor according to the corresponding setting result;

[0160] If it does not cover, determine the occurrence frequency of the stage transportation impact factor based on the entire transportation path;

[0161] When set a factor consistency value of -1 for the corresponding stage transportation impact factor, where p1 represents the individual occurrence frequency of the corresponding stage transportation impact factor based on the entire transportation path; p2 represents the non - individual occurrence frequency of the corresponding stage transportation impact factor based on the entire transportation path;

[0162] When set a factor consistency value of a2 for the corresponding stage transportation impact factor, where the value range of a2 is (-1, 0);

[0163] Calculate the stage consistency value of the corresponding transportation stage according to the factor consistency value;

[0164] Match and obtain a valid transportation label related to the value consistent with the said stage from the value-label mapping table;

[0165] Based on the said valid transportation label, obtain a transportation label vector for the corresponding target power product to achieve secondary quality tracking.

[0166] In this embodiment, the single-occurrence frequency refers to the number of occurrences of a situation where there is no constraint factor consistent with the transportation factor of the corresponding transportation stage in the corresponding transportation stage; the non-single-occurrence frequency refers to the number of occurrences of a situation where there is a constraint factor consistent with the transportation factor of the corresponding transportation stage in the corresponding transportation stage. For example, if there is no constraint factor 1 in transportation stage 1, but there is a stage transportation factor 1, and there is also no constraint factor 1 in transportation stage 2, but there is a stage transportation factor 1, then at this time, the single-occurrence frequency is regarded as 2. If there is a constraint factor 1 in transportation stage 2, then at this time, the single-occurrence frequency is regarded as 1, and the non-single-occurrence frequency is 1.

[0167] In this embodiment, the transportation log includes a transportation route, that is, the route from the transportation starting point to the transportation ending point. Since the transportation route includes different sections, the influencing factors of different transportation sections are determined, and each transportation section is the corresponding transportation stage.

[0168] In this embodiment, the transportation constraint conditions refer to the ruggedness of different transportation sections, weather conditions, the transportation ability of the transportation personnel themselves, unexpected situations (emergency braking) during transportation, etc. during transportation, which will cause certain damage to the product. Therefore, transportation constraint conditions are set according to each transportation section.

[0169] In this embodiment, the set valid transportation label is determined by the factor consistent value of the corresponding transportation section.

[0170] In this embodiment, for example, constraint condition 1: the ruggedness of the transportation road is in the range of level 1 to level 2. Then, if the driving safety degree of the corresponding section during the actual transportation meets the ruggedness of level 1 to level 2, it is determined that the factor consistent value is 1.

[0171] In this embodiment, the constraint range of each factor is preset in advance, mainly serving as a reference, and different constraint factors are also obtained based on the transportation constraint conditions.

[0172] In this embodiment, the influence value of the stage transportation influence factor is obtained from the factor-influence mapping table. Because the actual value of this factor can be captured during the actual transportation process, the influence value can be obtained from the factor-influence mapping table according to the actual value of this factor. For example, if the driving speed is too fast on a rough road, it will increase the collision force between products. Then, according to the factor corresponding to this actual driving speed, the influence value corresponding to this factor under this rough road can be obtained.

[0173] In this embodiment, the stage consistency value = the sum of the products of the consistency value of each factor and the weight of the corresponding factor.

[0174] In this embodiment, the value-label mapping table includes the combination of the factor consistency values corresponding to different factors, the stage consistency value, and the labels matched with them. Therefore, the corresponding effective transportation label can be obtained.

[0175] In this embodiment, the transportation label vector = [the label of transportation stage 01, the label of transportation stage 02,...].

[0176] In this embodiment, the transportation label vector includes the possible abnormal influence factors and the corresponding abnormal stages, which can be represented by labels.

[0177] The beneficial effects of the above technical solution are as follows: By analyzing the influence factors of each transportation section and comparing and analyzing them with the constraint conditions, the consistency value of the factor is set for the influence factors of different transportation stages. Then, the stage consistency value is obtained through calculation, which provides a basis for constructing the transportation label vector in the follow-up and ensures the accuracy of subsequent traceability.

[0178] The present invention provides a method for tracing and managing the quality of power products based on big data, which conducts the third quality traceability for the application process of a preset application party, including:

[0179] According to the monitoring results of each application stage in the application process of the preset application party, construct the placement matrix of the stage placement result and the standard placement result of each application stage;

[0180] Set placement labels for each placement matrix and construct the application label vector of the corresponding target power product to achieve the third quality traceability.

[0181] In this embodiment, taking a concrete pole as an example:

[0182] During the application process:

[0183] Step 01: Place the concrete pole at the reserved installation position, fix the base and anchor bolts with expansion bolts and tighten the nuts on the bolts. Then, pour concrete to the design elevation and tamp it to form, and the basic construction work can be completed.

[0184] Step 02: After laying the wires, use wire clips to fix the wires on the cross arm at the top of the pole.

[0185] Among them, Step 01 and Step 02 are corresponding application stages. The monitoring results in Application Stage 01 are related to the installation position, bolt fixing force, and concrete pouring height. The monitoring results in Application Stage 02 are related to the wire laying length and clip fixing position.

[0186] During the actual monitoring process, the actual installation position, actual fixing force, actual pouring height, actual laying length, and actual fixing position will be monitored.

[0187] Placement matrix for Stage 01:

[0188] Among them, the first row in the matrix is the stage placement result, and the second row in the matrix is the standard placement result.

[0189] In this embodiment, the setting of the placement label is mapped from the element combinations in each column of the matrix in the element combination - label database. This element combination - label database includes various combinations of actual and standard under the set elements corresponding to different power products at corresponding stages, as well as the label setting results corresponding to various combinations. Therefore, the placement label for this stage can be obtained. Among them, the placement label is mainly to highlight the abnormal elements existing in the corresponding matrix. For example, if there is inconsistency in the fixing force, the fixing force element is mainly highlighted.

[0190] In this embodiment, the application label vector = [label of Application Stage 01, label of Application Stage 02, label of Application Stage 03,...].

[0191] In this embodiment, due to operation errors in some stages during the application process, it may lead to problems in the quality of the product. For example, the service life is reduced. At this time, it is possible to trace back to determine which stage caused this result.

[0192] The beneficial effects of the above technical solution are: By monitoring each stage in the application process, a placement matrix for each stage is constructed, and then an application vector is obtained. Through effective analysis of each stage, a basis is provided for subsequent quality traceability.

[0193] The present invention provides a method for quality traceability and tracking management of power products based on big data. Based on the quality tracking results, comprehensive quality analysis is performed on the target power products, including:

[0194] Perform a first comparative analysis on the production label vector of the first quality tracking result and the standard production vector, a second comparative analysis on the transportation label vector of the second quality tracking result and the standard transportation vector, and a third comparative analysis on the application label vector of the third quality tracking result and the standard application label;

[0195] Based on the comparison results, determine the quality problems corresponding to each process and the problem-related information of the production process, transportation process, and application process.

[0196] In this embodiment, each process has its own standard vector. Therefore, after the comparative analysis, the quality problems that may exist in each process can be determined.

[0197] In this embodiment, the quality problems existing in each process are caused by improper operations in the corresponding stages. Therefore, the quality problems corresponding to different stages are different.

[0198] In this embodiment, there is quality problem 1 in the production process, quality problem 2 in the transportation process, and quality problem 3 in the application process. Among them, quality problem 2 may lead to the occurrence of quality problem 3. For example, in the transportation process, the power product is worn. In the application process, due to the wear, the pouring height becomes lower, which will further lead to the reduction of the product life. That is, the problem-related information is caused by the direct influence relationship between different processes.

[0199] The beneficial effect of the above technical solution is: By comparing and analyzing the vectors of each process, the existing quality problems are determined, providing a basis for subsequent traceability.

[0200] The present invention provides a method for tracing and managing the quality of power products based on big data, which locks the abnormal stage of the target power product and the abnormal factor corresponding to the abnormal stage, including:

[0201] Based on the quality problems of each process, lock the abnormal stage and the initial factors existing in the abnormal stage;

[0202] According to the problem-related information of the production process, transportation process, and application process, optimize the initial factors to obtain the abnormal factors corresponding to the abnormal stage.

[0203] In this embodiment, the problem-related information refers to the correlation between the quality problems existing in different processes. For example, the quality problem caused by the transportation process will directly affect the application process. At this time, it is necessary to optimize the quality problem caused by the application process according to the quality problem caused by the transportation process to determine the true abnormality of the application process.

[0204] In this embodiment, the wear of the product during the transportation stage 02 in the transportation process directly causes the height of the product to not reach the required height after pouring during the application process. For example:

[0205] The height of the product itself is 10 meters, the standard pouring height is 1 meter, and the wear is 0.5 meters. The corresponding standard height exposed above the ground should be: 9 meters. At this time, the height exposed above the ground under the condition of the standard pouring height should be: 10 - 0.5 - 1 = 8.5 meters. However, the actually measured height is 8.0 meters. That is, at this time, there is a problem with the pouring height. Therefore, based on the problem-related information, that is, the wear of 0.5 meters, the initial factor is optimized, that is, the actual pouring height of 1.5 meters can be obtained essentially.

[0206] If calculated directly from the height exposed above the ground and the height of the product itself, the pouring height is 1 meter. However, due to wear, the pouring height is 1.5 meters.

[0207] The beneficial effects of the above technical solution are: by locking the abnormal stage and the initial factor, the initial factor is optimized according to the problem-related information to ensure the accuracy of obtaining the abnormal factor, for

[0208] The present invention provides a method for tracing and managing the quality of power products based on big data. Based on the unique code 300 of the corresponding power product and the abnormal factor, an abnormal storage block is constructed, including:

[0209] Process chains for each process are constructed respectively, where the process chain includes several process stages;

[0210] The abnormal factors involved in each process and the abnormal stages of the corresponding abnormal factors are set on the matching process stages to obtain the corresponding storage chain;

[0211] According to the chain space of each storage chain of the target power product with the unique code 300, an abnormal storage block larger than the total chain space is constructed.

[0212] In this embodiment, the storage chain: production process - transportation process - application process.

[0213] In this embodiment, suppose there are 2 stages in the production process, 1 stage in the transportation process, and 2 stages in the application process. An abnormality exists in the first stage of the production process, and the remaining processes are normal. At this time, the storage chain: production stage 1 (abnormality c1) - production stage 2 - transportation stage 2 - application stage 1 - application stage 2, where production stage 1 (abnormality c1) - production stage 2 is the corresponding process chain.

[0214] In this embodiment, the chain space refers to the capacity space where information related to each process can be placed, and the abnormal storage block is the storage unit, and the storage capacity is greater than the total chain space corresponding to all power products, ensuring the complete storage of data.

[0215] The beneficial effects of the above technical solution are: by constructing a process chain, it is convenient to understand the stage situation of each process, and by constructing an abnormal storage block, it is convenient to store the storage chain, facilitating subsequent effective traceability.

[0216] The present invention provides a method for tracing and managing the quality of power products based on big data, constructing an abnormal storage block, and performing abnormal management on the target power products, including:

[0217] Associating the abnormal storage blocks of power products of the same type, and constructing a corresponding association framework based on the block positions of the abnormal storage blocks of power products of the same type;

[0218] Performing the first annotation display on the most prominent abnormalities of each storage block on the association framework and the second annotation display on the high-frequency abnormalities, and performing the same-abnormality management and prominent-abnormality management on power products of the same type.

[0219] In this embodiment, power products of the same type refer to products with the same production model. The same-type association means associating all products with the same production model and constructing an association framework according to the production order of the same batch.

[0220] In this embodiment, the most prominent abnormality refers to the first annotation display of the most prominent stage abnormality existing after comparing the standard vector with the process vector, that is, the greater the difference between the standard and the actual, the greater the corresponding abnormality, and the more prominent it is.

[0221] In this embodiment, the high-frequency abnormality refers to the number of abnormalities that occur at the same stage for products of the same type. For example, products 1, 2, and 3 all have abnormalities in production stage 2. At this time, the number of abnormalities is 3, and abnormalities exceeding 1 are regarded as high-frequency abnormalities.

[0222] As Figure 5 shown, it is the structure diagram of the association framework targeted. Assuming there are two batches, there are 2 power products of the same type in the first batch and 1 power product of the same type in the second batch.

[0223] The beneficial effects of the above technical solution are: by constructing an association framework and abnormal annotations, effective management of abnormalities is achieved, and thus it is convenient for effective traceability of quality.

[0224] The present invention provides a system for tracing and managing the quality of power products based on big data, as Figure 4 shown, including:

[0225] An encoding setting module, configured to obtain a preset manufacturer, a preset transporter, and a preset application party of a target power product, and combine the production serial number of the target power product to set a unique code 300 for the matching target power product;

[0226] A quality tracking module, configured to perform first quality tracking on the production process of the preset manufacturer of the target power product, second quality tracking on the transportation process of the preset transporter, and third quality tracking on the application process of the preset application party;

[0227] An anomaly locking module, configured to perform comprehensive quality analysis on the target power product based on the quality tracking results, and lock the abnormal stage of the target power product and the abnormal factor corresponding to the abnormal stage;

[0228] An anomaly management module, configured to construct an anomaly storage block based on the unique code 300 of the corresponding power product and the abnormal factor, and perform anomaly management on the target power product.

[0229] If the insulated concrete composite electric pole cracks, the cause of the quality problem may involve one or two or even all of the production process, transportation process, and application process.

[0230] The beneficial effects of the above technical solution are as follows: By performing quality tracking on the production process, transportation process, and application process of the target power product (insulated concrete composite electric pole), it is convenient to lock the abnormal position of the product in time, avoid attributing all the anomalies to the quality problems caused by production, and can realize effective traceability management of the product. Thus, effective failure analysis can be carried out through big data, so as to avoid the recurrence of the same problem. Also, based on the reasons for the failure analysis, the production process (technology), transportation plan, or application process (construction) can be re-formulated, and the same power product quality traceability tracking management system based on big data is also applied to track the whole process of the newly formulated production process, transportation process, and application process, and when encountering new problems, the same system is used to find out the reasons and continuously optimize.

[0231] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the present invention is not limited to the described embodiments. For those skilled in the art, without departing from the principle and spirit of the present invention, various changes, modifications, substitutions, and variations to these embodiments still fall within the protection scope of the present invention.

Claims

1. An insulated concrete composite electric pole, characterized in that: It is composed of a main body part and an insulating part, and the main body part is surrounded by the insulating part; wherein, the main body is prepared from composite concrete materials, multiple insulating glass fiber reinforced plastic main bars, and multiple layers of insulating grid fiberglass cloth wound around the main bars; in the preparation process of the insulating concrete composite electric pole, a quality traceability and tracking management method for electric power products based on big data is adopted; wherein, through the quality traceability and tracking management method for electric power products based on big data, each insulating concrete composite electric pole is set with a unique code, and the quality is tracked according to the unique code.

2. The insulated concrete composite electric pole according to claim 1, wherein: The composite concrete material includes graphene oxide; the insulating part is a polymer insulating material, and the polymer insulating material includes rubber, nano zinc oxide, nano silicon dioxide, and fillers, and the rubber and fillers are prepared from municipal solid waste; the main body part includes at least one whole section. The quality includes at least one of the quality in the production process, the quality in the transportation process, and the quality in the application process.

3. The insulated concrete composite electric pole according to claim 1, characterized in that: The main body part is formed by splicing multiple sections or integrally formed. The quality traceability and tracking management method for electric power products based on big data includes: Step 1: Obtain the preset producer, preset transporter, and preset user of the target electric power product, and combine the production serial number of the target electric power product to set a unique code for the matching target electric power product. Step 2: Conduct the first quality tracking on the production process of the preset producer of the target electric power product, the second quality tracking on the transportation process of the preset transporter, and the third quality tracking on the application process of the preset user. Step 3: Based on the quality tracking results, conduct a comprehensive quality analysis on the target electric power product, and lock the abnormal stage of the target electric power product and the abnormal factor corresponding to the abnormal stage. Step 4: Based on the unique code of the corresponding electric power product and the abnormal factor, construct an abnormal storage block, and conduct abnormal management on the target electric power product. Among them, conducting the third quality tracking on the application process of the preset user includes: According to the monitoring results of each application stage in the application process of the preset user, construct a placement matrix between the stage placement result and the standard placement result of each application stage. Set a placement label for each placement matrix, and construct an application label vector corresponding to the target electric power product to achieve the third quality tracking. Among them, obtaining the preset producer, preset transporter, and preset user of the target electric power product, and combining the production serial number of the target electric power product to set a unique code for the matching target electric power product includes: Obtain the producer number of the preset producer of the target electric power product. Obtain the transporter number of the preset transporter of the target electric power product. Obtain the user number of the preset user of the target electric power product. Based on the producer number, transporter number, user number, and production serial number, obtain the unique code.

4. The insulated concrete composite electric pole according to claim 3, wherein: The conduct of the first quality tracking on the production process of the preset producer of the target electric power product includes: Obtain the standard production result and the actual production result of the production mold in each production stage during the production process, and construct a conventional comparison matrix and a special comparison matrix according to the conventional production factors and special production factors of each production process. Perform a first analysis on the conventional comparison matrix, a second analysis on the special comparison matrix, and factor fusion of the conventional production factors and special production factors according to the production nature of the corresponding production stage to obtain a final comparison matrix, and perform a third analysis on the final comparison matrix; Extract a first feature based on the first analysis result, a second feature based on the second analysis result, and a third feature based on the third analysis result; Perform a cross-feature analysis on the first feature and the second feature with the third feature to obtain a mutually exclusive value; Among them, T1 represents the first feature; T2 represents the second feature; T3 represents the third feature; ∪ represents the union symbol; ∩ represents the intersection symbol; ln represents the natural logarithm function symbol with base e; lg represents the common logarithm function symbol with base 10; n1 represents the number of intersection features corresponding to (T1 ∪ t2) ∩ T3; p i represents the historical intersection probability of the i-th intersection feature; represents the fine-tuning function of; H1 represents the corresponding exclusive value; When the mutually exclusive value is less than a first preset value, set a first quality label for the corresponding production stage according to the third analysis result; Otherwise, obtain the information amount x1 of the first abnormal information of the first analysis result and the second analysis result, and the information amount x2 of the second abnormal information of the third analysis result. According to max{x1, x2}, use the analysis result with the larger information amount as the main analysis result, and the analysis result with the smaller information amount as the secondary analysis result. Extract the non-intersection abnormal results with a weight ratio greater than the preset ratio in the secondary analysis result, and perform result fusion with the main analysis result, and set a second quality label for the corresponding production stage; Obtain a production label vector of the corresponding target power product according to the quality labels of each production stage in the production process to achieve the first quality tracking.

5. The insulated concrete composite electric pole according to claim 3, characterized in that: The second quality tracking of the transportation process of the preset transportation party includes: Extract the transportation path in the transportation log generated by the preset transportation party during the transportation process and the stage transportation influence factors of each transportation stage in the transportation path; Obtain the transportation constraint conditions of each transportation stage, and set an effective transportation label for the corresponding transportation stage; Extract the constraint factors in the transportation constraint conditions and the constraint range of each constraint factor, and perform a consistency analysis on the constraint factors and the stage transportation influence factors; When there is a constraint factor consistent with the stage transportation influence factor and the influence value of the corresponding stage transportation influence factor is within the constraint range, set a factor consistency value of 1 for the corresponding stage transportation influence factor; When there is a constraint factor consistent with the stage transportation impact factor and the impact value of the corresponding stage transportation impact factor is not within the constraint range, if then set the factor consistent value corresponding to the stage transportation impact factor to 0, where maxy1 represents the maximum value y1 based on the constraint range, miny2 represents the minimum value y2 based on the constraint range; y0 represents the impact value of the corresponding stage transportation impact factor, where the values of y0, miny2, and maxy1 are greater than or equal to 0, and maxy1 is greater than miny2; If then set the factor consistent value with the transportation impact factor set to a1 for the corresponding stage, where the value range of a1 is (0, 1); When there is a constraint factor inconsistent with the stage transportation influence factor, determine whether the existing constraint factors cover all the stage transportation influence factors; If it covers, determine the factor consistency value of the corresponding stage transportation influence factor according to the corresponding setting result; If it does not cover, determine the occurrence frequency of the stage transportation influence factor based on the entire transportation path; Set the factor consistency value of the transportation impact factor with a value of -1 for the corresponding stage, where p1 represents the individual occurrence frequency of the transportation impact factor in the corresponding stage based on the entire transportation path; p2 represents the non-individual occurrence frequency of the transportation impact factor in the corresponding stage based on the entire transportation path; When Set the factor consistent value with the transportation influence factor for the corresponding stage to a2, where the value range of a2 is (-1, 0); Calculate the stage consistency value of the corresponding transportation stage according to the factor consistency value; Match and obtain the effective transportation label related to the stage consistency value from the value-label mapping table; Based on the effective transportation label, obtain a transportation label vector of the corresponding target power product to achieve the second quality tracking.

6. The insulated concrete composite electric pole according to claim 3, characterized in that: The comprehensive quality analysis of the target power product based on the quality tracking results includes: Perform a first comparison analysis on the production label vector of the first quality tracking result and the standard production vector, a second comparison analysis on the transportation label vector of the second quality tracking result and the standard transportation vector, and a third comparison analysis on the application label vector of the third quality tracking result and the standard application label; According to the comparison results, determine the quality problems corresponding to each process and the problem-related information of the production process, transportation process, and application process; lock the abnormal stage of the target power product and the abnormal factors corresponding to the abnormal stage, including: According to the quality problems of each process, lock the abnormal stage and the initial factors existing in the abnormal stage; According to the problem-related information of the production process, transportation process, and application process, optimize the initial factors to obtain the abnormal factors corresponding to the abnormal stage.

7. A power product quality traceability and tracking management method based on big data, characterized in that: It is applied to the production of the insulated concrete composite electric pole described in any one of claims 1-6.

8. The method for traceability management of power product quality based on big data according to claim 7, characterized in that: Based on the unique code of the corresponding power product and the abnormal factors, construct an abnormal storage block, including: Construct the process chain of each process respectively, where the process chain includes several process stages; Set the abnormal factors involved in each process and the abnormal stages corresponding to the abnormal factors on the matching process stages to obtain the corresponding storage chain; According to the chain space of each storage chain of the target power product with a unique code, construct an abnormal storage block larger than the total chain space; Construct an abnormal storage block and perform abnormal management on the target power product, including: Associate the abnormal storage blocks of the same type of power products, and construct a corresponding association framework based on the block positions of the abnormal storage blocks of the same type of power products; Perform the first annotation display on the most prominent abnormality of each storage block on the association framework and the second annotation display on the high-frequency abnormality, and perform the same abnormality management and prominent abnormality management on the same type of power products.

9. The method for tracing and managing the quality of power products based on big data according to claim 7, characterized in that: The power product quality traceability and tracking management method based on big data further includes a system, and the system includes: A coding setting module, which is used to obtain the preset production party, preset transportation party, and preset application party of the target power product, and combine the production serial number of the target power product to set a unique code for the matching target power product; A quality tracking module, which is used to perform the first quality tracking on the production process of the preset production party of the target power product, the second quality tracking on the transportation process of the preset transportation party, and the third quality tracking on the application process of the preset application party; An abnormality locking module, which is used to perform a comprehensive quality analysis on the target power product based on the quality tracking results, and lock the abnormal stage of the target power product and the abnormal factors corresponding to the abnormal stage; An abnormality management module, which is used to construct an abnormal storage block based on the unique code of the corresponding power product and the abnormal factors, and perform abnormality management on the target power product.

Images