Oil-to-electricity material intelligent management system and method

Abstract

The invention relates to the technical field of intelligent management, in particular to an oil-to-electricity material intelligent management system and method, and the system comprises a label collection module, a progress mapping module, a matching evaluation module, an early warning judgment module and a machine account updating module. According to the invention, RFID identification and dynamic reading are carried out on an AC charging pile equipment cabinet body, a DC charging gun cable assembly and a low-voltage distribution cable section, so that material information has clear space and time coordinates; the method comprises the following steps: calculating a progress percentage by combining actual construction duration and a standard construction period, establishing a corresponding relation with a designed use amount, calculating a theoretical consumption value, performing difference operation with an existing number, forming quantifiable deviation information, counting an abnormal proportion on the basis, introducing time interval analysis, and linking a material state, a construction rhythm and a time dimension, so as to obtain a quantitative result. And a continuous data chain is constructed, the material configuration matching precision and the anomaly recognition sensitivity are improved, and the whole-process tracking and dynamic correction capability is enhanced.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology, and in particular to an intelligent management system and method for materials used in oil-to-electricity conversion projects. Background Technology

[0002] The field of intelligent management technology involves the efficient, accurate, and real-time management of various resources, systems, and processes through information technology and automation. It is widely applied in manufacturing, logistics, warehousing, and other fields. Core aspects include data acquisition, automated control, IoT technology, and big data analysis. The aim is to achieve precise resource scheduling, real-time data monitoring, and full-process traceability management through information technology, thereby improving efficiency, reducing errors, and optimizing decision-making processes. Traditional oil-to-electricity conversion material management in such projects relies on manual recording and experience, leading to problems such as incorrect, missed, and mixed materials. Furthermore, it fails to achieve real-time matching and closed-loop data management of material flow. Traditional methods primarily use manual recording, Excel spreadsheets, or simple inventory management systems for material tracking, but these suffer from untimely data updates and difficulties in traceability. An intelligent material management system for oil-to-electricity conversion aims to optimize material management efficiency and accuracy by integrating real-time data acquisition, automated tracking, and closed-loop management functions, ensuring precise control and data traceability throughout the project's assembly and refactoring process.

[0003] Traditional material management for oil-to-electricity conversion relies heavily on on-site personnel's experience in recording material entry, exit, and usage. Record-keeping is primarily done using paper documents or scattered tables, and information collection is done manually, leading to data lag. There is a lack of close correlation between parking space and work process dimensions, making it difficult to establish a quantitative mapping between construction progress and material quantity. On-site managers often rely on visual inspection or verbal confirmation to determine material sufficiency, lacking a unified calculation standard. This easily results in localized overstocking and shortages in other areas during peak construction phases. Regarding anomaly identification, most methods rely on post-event inventory checks or investigations after problems are exposed, failing to perform proportional analysis and trend judgment in the early stages of discrepancies. If a batch of materials is not matched to the corresponding work process in a timely manner, the problem may only be discovered after it has spread to multiple parking spaces, increasing rework and coordination costs. Record updates rely on manual entry, lacking automatic correlation between time information and construction milestones, causing gaps in material flow history. The traceability process requires repeatedly checking different record sources, resulting in low efficiency and inconsistencies, which in turn affects the accuracy of decision-making and the overall project rhythm control. Summary of the Invention

[0004] To address the technical problems existing in the prior art, embodiments of the present invention provide an intelligent management system and method for oil-to-electricity conversion materials. The technical solution is as follows: On the one hand, an intelligent management system for materials in oil-to-electricity conversion is provided, the system including: The tag collection module uses RFID technology to identify and track AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable YJV cable sections at the oil-to-electricity conversion construction site. It collects tag numbers, material codes, and arrival times, and aggregates them by parking space number to generate a parking space material arrival list. Based on the parking space material arrival list, the progress mapping module collects the actual construction time of the parking space construction process, compares it with the standard construction period of the construction plan, and generates a parking space construction progress record table. The matching and evaluation module calculates the theoretical material consumption of the parking space based on the parking space construction progress record table and the design usage in the construction drawing budget, and compares it with the material arrival quantity in the parking space material arrival list to generate a parking space material difference detail table. The early warning judgment module filters parking spaces with material difference less than zero based on the parking space material difference details table, calculates the proportion and compares it with the preset construction abnormality proportion threshold, and generates a list of parking spaces with material abnormality. The ledger update module collects the RFID reading time and the most recent process completion time of the corresponding parking space based on the material abnormal parking space list, calculates the time interval and compares it with the preset time threshold, marks the parking spaces that exceed the time threshold and updates them to the oil-to-electricity project material management ledger, generating a material management ledger update record.

[0005] As a further aspect of the present invention, the parking space material arrival list includes the arriving parking space number, arrival tag number, arriving material code, and material arrival time; the parking space construction progress record table includes the construction parking space number, construction process name, actual construction duration, standard construction period, and construction progress percentage; the parking space material difference details table includes the difference parking space number, theoretical material consumption of the process, material arrival quantity, material difference amount, and material difference status; the abnormal parking space list includes the abnormal parking space number, abnormal status identifier, abnormal parking space percentage, and abnormal percentage threshold; the material management ledger update record includes the updated parking space number, RFID reading time, most recent process completion time, time interval value, and threshold status marking result.

[0006] As a further aspect of the present invention, the material difference is the quantity of materials arriving in the parking space material arrival list minus the theoretical material consumption of the parking space.

[0007] As a further aspect of the present invention, the ratio is the ratio between the number of parking spaces with material difference less than zero and the total number of parking spaces in the parking space construction progress record table.

[0008] As a further aspect of the present invention, the tag acquisition module includes: The tag reading submodule uses RFID technology to identify and track AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable YJV cable sections at the oil-to-electricity conversion construction site. It collects tag numbers, material codes, and arrival time data, obtains the read frame byte sequence, calculates the frame length difference, and performs consistency judgment with the set frame length benchmark value. It accumulates the judgment to determine the number of frames that pass the length check and generates the RFID record quantity. The data verification submodule obtains the corresponding tag number, material code and arrival time data sequence based on the RFID record quantity, calculates the number of times the tag number appears in the same time window and compares it with the single arrival discrimination threshold, performs duplicate number removal and calculates the ratio of the number of retained records to the original number of records, and generates the record data retained after removing duplicate numbers; The parking space collection submodule calls the retained record sequence based on the record data retained after removing duplicate numbers, obtains the parking space number field, performs number collection and counting operations, and sequentially writes the label number, material code and arrival time data according to the parking space number to form a structured table item, generating a parking space material arrival list.

[0009] As a further aspect of the present invention, the progress mapping module includes: The process duration collection submodule collects parking space number, construction process identifier and corresponding start time and completion time records based on the parking space material arrival list. It performs time difference calculation for process records under the same parking space, judges the integrity of timestamps and removes missing items, and forms a set of construction duration values ​​associated with parking space number and process identifier, and generates the actual duration value of parking space process. The construction period comparison submodule obtains the standard construction period value under the corresponding process identifier in the construction plan based on the actual time value of the parking space process. It performs the ratio calculation of actual time and standard construction period for the same parking space and the same process, limits the ratio range and completes the value regularization, forms the process progress percentage data item under the parking space dimension, and generates the process progress percentage value. The progress summary submodule calls the process progress percentage value, performs a weighted summation operation on the process progress percentage according to the parking space number, and takes the weight from the process sequence identifier in the construction plan to complete the merging of progress values ​​at the parking space level. Then, it writes the parking space number and progress percentage into a structured data table to generate a parking space construction progress record table.

[0010] As a further aspect of the present invention, the matching evaluation module includes: The theoretical consumption calculation submodule calculates the theoretical consumption of materials corresponding to the parking space construction process based on the parking space construction progress record table and the design consumption data of the construction drawing budget or bill of quantities, summarizes the material consumption data of the parking space dimension, and obtains the theoretical consumption value of the parking space. The arrival quantity summary submodule obtains the parking space material arrival list, summarizes the arrival quantity of materials for each parking space, generates parking space-level material arrival quantity data, and obtains the parking space material arrival quantity. The difference calculation submodule compares the theoretical consumption value of the parking space with the quantity of materials arriving at the parking space to calculate the material difference and generate a detailed table of parking space material differences.

[0011] As a further aspect of the present invention, the early warning determination module includes: The negative difference screening submodule reads the material difference amount field and the parking space number field from the parking space material difference details table, performs interval judgment according to the difference amount value interval, collects the parking space records with the difference amount below zero into the abnormal candidate set, and performs counting and statistical calculation on the parking space numbers in the candidate set to obtain the number of negative difference parking spaces. The proportional calculation submodule calls the negative difference parking space quantity value, obtains the list of all construction parking spaces and extracts the total number of parking space numbers, performs proportional calculation based on the quantity correspondence, forms the quantity ratio range between the number of negative difference parking spaces and the total number of construction parking spaces, and obtains the abnormal parking space ratio value. The anomaly generation submodule obtains the preset construction anomaly ratio threshold range data based on the anomaly parking space ratio value, performs range comparison judgment and outputs judgment identifier, writes the judgment identifier into the negative difference parking space number set, generates structured data including parking space number and status identifier fields, and obtains the material anomaly parking space list.

[0012] As a further aspect of the present invention, the ledger update module includes: The RFID data acquisition submodule obtains the RFID reading time and the most recent process completion time for each parking space based on the material abnormal parking space list, extracts the corresponding field data, and establishes a mapping relationship between parking space number and RFID reading time and process completion time to obtain parking space RFID reading and process completion time data. The time interval calculation submodule calculates the time interval between the RFID reading time and the process completion time based on the parking space RFID reading and process completion time data, and compares it with a preset time threshold to obtain the time interval comparison result. The ledger update submodule marks the status of parking spaces that exceed the threshold based on the comparison results of the time interval. The marking results and parking space numbers are written into the material management ledger of the oil-to-electricity conversion project, generating an update record that includes the parking space number and status identifier, thus obtaining the material management ledger update record.

[0013] On the other hand, an intelligent management method for oil-to-electricity conversion materials, based on the aforementioned intelligent management system for oil-to-electricity conversion materials, includes the following steps: S1: Using RFID technology, the AC charging pile equipment cabinet, DC charging gun cable assembly, and low-voltage power distribution cable YJV cable section at the oil-to-electricity conversion construction site are identified and tracked. The tag number, material code and arrival time data are collected. The read data is verified for integrity and duplicate data is removed. The data is then collected by parking space number to generate a parking space material arrival list. S2: Based on the parking space material arrival list, collect the actual construction time of the parking space construction process, compare it with the standard construction period in the construction plan, calculate the construction progress percentage, and generate a parking space construction progress record table. S3: Based on the parking space construction progress record sheet, combined with the design quantities in the construction drawing budget or bill of quantities, calculate the theoretical material consumption of the corresponding process of the parking space, compare it with the material arrival quantity in the parking space material arrival list, calculate the material difference, generate a parking space material difference detail sheet, and record the material difference of the parking space. S4: Based on the parking space material difference details table, filter the parking spaces with material difference less than zero, count the proportion of the parking spaces in all construction parking spaces, compare the proportion with the preset construction abnormality proportion threshold, generate a list of abnormal parking spaces, and record the abnormal parking space number and corresponding status identifier. S5: Based on the list of abnormal material parking spaces, collect the RFID reading time and the most recent process completion time of the corresponding parking space, calculate the interval between the times, compare it with the preset time threshold, mark the status of parking spaces that exceed the time threshold, and write the marking result into the material management ledger of the oil-to-electricity conversion project to generate a material management ledger update record.

[0014] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: By using RFID tags and dynamic reading to identify AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable sections, material information is given clear spatial and temporal coordinates. The progress percentage is calculated by combining the actual construction time with the standard construction period, and a corresponding relationship is established with the design usage to estimate the theoretical consumption value. The difference between the actual consumption value and the quantity delivered is calculated to form quantifiable deviation information. Based on this, the anomaly ratio is statistically analyzed and time interval analysis is introduced. The material status, construction rhythm, and time dimension are linked to build a continuous data chain, improve the accuracy of material configuration matching and the sensitivity of anomaly identification, and enhance the ability to track and dynamically correct the entire process. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of an intelligent material management system for oil-to-electricity conversion provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the system framework of the present invention; Figure 3 This is a flowchart of the tag acquisition module in this invention; Figure 4 This is a flowchart of the progress mapping module in this invention; Figure 5 This is a flowchart of the matching evaluation module in this invention; Figure 6 This is a flowchart of the early warning determination module in this invention; Figure 7 This is a flowchart of the ledger update module in this invention; Figure 8 This is a flowchart of an intelligent material management method for oil-to-electric conversion provided by an embodiment of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0019] This invention provides an intelligent management system for materials used in oil-to-electricity conversion projects, such as... Figure 1-2 The diagram shown illustrates an intelligent material management system for oil-to-electricity conversion. The system includes: The tag collection module uses RFID technology to identify and track AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable YJV cable sections at the oil-to-electricity conversion construction site. It collects tag numbers, material codes, and arrival time data, performs integrity verification and duplicate data removal on the read data, and collects them according to parking space number to generate a parking space material arrival list. The progress mapping module collects the actual construction time of the parking space construction process based on the parking space material arrival list, compares it with the standard construction period in the construction plan, calculates the construction progress percentage, and generates a parking space construction progress record table. The matching and evaluation module calculates the theoretical material consumption of the corresponding process of the parking space based on the parking space construction progress record table and the design usage in the construction drawing budget or bill of quantities. It then compares this with the material arrival quantity in the parking space material arrival list to calculate the material difference and generate a parking space material difference detail table to record the material difference of the parking space. The early warning judgment module filters parking spaces with material differences less than zero based on the parking space material difference details table, calculates the proportion of parking spaces in all construction parking spaces, compares the proportion with the preset construction abnormality proportion threshold, generates a list of abnormal parking spaces, and records the abnormal parking space number and corresponding status identifier. The ledger update module collects the RFID reading time and the most recent process completion time of the corresponding parking space based on the list of abnormal material parking spaces, calculates the interval between the time intervals, compares them with the preset time thresholds, marks the status of parking spaces that exceed the time thresholds, and writes the marking results into the material management ledger of the oil-to-electricity conversion project, generating a material management ledger update record.

[0020] The parking space material arrival list includes the arriving parking space number, arrival tag number, arriving material code, and material arrival time; the parking space construction progress record includes the construction parking space number, construction process name, actual construction duration, standard construction period, and construction progress percentage; the parking space material difference details list includes the difference parking space number, theoretical material consumption for the process, material arrival quantity, material difference amount, and material difference status; the abnormal parking space list includes the abnormal parking space number, abnormal status identifier, abnormal parking space percentage, and abnormal percentage threshold; the material management ledger update record includes the updated parking space number, RFID reading time, most recent process completion time, time interval value, and threshold status marking result.

[0021] Specifically, such as Figure 2 , 3 As shown, the tag acquisition module includes: The tag reading submodule uses RFID technology to identify and track AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable YJV cable sections at the oil-to-electricity conversion construction site. It collects tag numbers, material codes, and arrival time data, obtains the read frame byte sequence, calculates the frame length difference, and performs consistency judgment with the set frame length benchmark value. It accumulates the judgment to determine the number of frames that pass the length check and generates the RFID record quantity. At the oil-to-electricity conversion construction site, material identification actions are bound to the entry points of AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage distribution cable YJV cable sections. During operation, the label installation location is first determined according to the material form, and an installation record is created. For AC charging pile equipment cabinets, the label is fixed at the upper edge inside the cabinet door. For DC charging gun cable assemblies, the cable sheath is wrapped and fixed 300 mm from the gun head connection end. For low-voltage distribution cable sections, the cable sheath is fixed with a cable tie 200 mm from the end and covered with a transparent protective layer. Subsequently, one reading / writing point is set up at the construction vehicle entrance and one at the material temporary storage area. These reading / writing points are used to identify items entering the designated reading area. The tags are read continuously. Read frames are entered into the buffer queue as byte sequences and a read timestamp is synchronously written. The read timestamp is taken from the local clock of the reading / writing device and recorded in seconds. Simultaneously, the tag number is associated with the material code, which comes from the on-site barcode scanning record of the construction material code table and is bound to the tag number. In the read frame consistency judgment stage, the standard read frames collected by the reading / writing device in an idle state are first used as the set frame length benchmark value. The benchmark value is calculated by continuously collecting 1000 idle frames. The frame length with the most frequent occurrences is taken as the benchmark and fixed in the configuration file. For example, in a certain calibration, the idle frame length... The data is concentrated in bytes 48 and 49, with byte 48 appearing 860 times and byte 49 appearing 140 times. The frame length baseline is set to 48 bytes. When any frame is read on-site, the actual length of the frame is compared with the set frame length baseline. The absolute difference is taken and used to determine the interval using a consistency threshold. The consistency threshold is determined by calibrating the on-site interference intensity. The calibration method involves collecting 2000 frames under both metal obstruction and personnel movement conditions and statistically analyzing the length offset distribution. The maximum offset corresponding to a proportion of offsets not exceeding 2 bytes reaching 0.95 is used as the threshold. Therefore, the consistency threshold is set to 2 bytes. When the difference of a certain frame... If the length is less than 2 bytes, it is considered to have passed the length check. The number of frames that have passed the length check is accumulated. The accumulation period adopts a time window method with a time window length of 10 seconds. The time window length is determined by the actual measurement of the passage speed of the parking space on site. The measurement method is to record the passage time of the trolley passing through the reading and writing point 20 times. The passage time is distributed between 6 seconds and 9 seconds. The upper limit is taken and a 1-second margin is left to get 10 seconds. Within a single time window, the number of frames that have passed the length check is generated and the RFID record quantity is generated. The RFID record quantity is written to the record table field. When the field is written, the corresponding tag number, material code and arrival time data are retained for subsequent verification.

[0022] The data verification submodule obtains the corresponding tag number, material code and arrival time data sequence based on the RFID record volume, calculates the number of times the tag number appears in the same time window and compares it with the single arrival discrimination threshold, performs duplicate number removal and calculates the ratio of the number of retained records to the original number of records, and generates the record data retained after removing duplicate numbers; After obtaining the RFID record volume, the corresponding data sequence is retrieved. The tag number, material code, and arrival time are grouped into a record sequence according to the time window and then processed for duplicate number removal. First, the number of times the tag number appears within the same time window is counted, with the counting object being the tag number field. The counting granularity is limited to the same read / write point and the same time window. Then, the number of occurrences is compared with a single arrival threshold, which is determined through field testing. The test method involves pushing the same material into the reading area and keeping it there for 3 to 8 seconds, recording the distribution of the number of times it is read within a 10-second window. The common distribution range is 5 to 18 times. To avoid misjudging multiple reads as multiple arrivals, the single arrival threshold is set to 2, meaning that when the same tag appears 2 or more times within the same time window, it is classified as a candidate for the same arrival event. When performing duplicate number removal on candidate records, the first record is retained, sorted by arrival time from earliest to latest. Records with the same label number are marked as duplicates and removed from the retained sequence. The removal mark is written to the audit field for backtracking. After removal, the ratio of the retained record count to the original record count is calculated to generate the retained record data after removing duplicate numbers. The ratio is calculated by dividing the retained record count by the original record count and rounding to two decimal places. For example, if a parking space entrance read / write point originally had 20 records within a 10-second window, the retained record count after removal is 8, and the retained record data after removing duplicate numbers is 0.40. To verify the rationality of the threshold setting, 30 actual attendance events were manually checked on-site. The manual check was based on entry registration and video playback counting of the number of materials present. When using a threshold of 2 times, the matching rate between the retained records after removing duplicate numbers and the manually checked attendance events was 0.93; when using a threshold of 3 times, the matching rate was 0.88. Therefore, the single attendance discrimination threshold was fixed at 2 times, and the above experimental data was written into the parameter verification record.

[0023] The parking space collection submodule calls the retained record sequence based on the record data retained after removing duplicate numbers, obtains the parking space number field and performs number collection and counting operations, and sequentially writes the label number, material code and arrival time data according to the parking space number to form a structured table item, generating a parking space material arrival list; The system reads the parking space number field from each record. The parking space number comes from the on-site parking space QR code scan result and is written during arrival registration. If a record is missing a parking space number, it is filled in using the default parking space mapping table for the same read / write point. The default parking space mapping table is formed from the distance measurement results at the point installation. The distance measurement uses laser ranging to record the distance from the point to the center of the parking space marking, and the parking space with the smallest distance is selected as the default parking space. Then, a number aggregation and counting operation is performed, aggregating and counting records with the same parking space number and generating a parking space-level record index. During the sequential writing phase, records with the same parking space number are sorted from earliest to latest arrival time, including label number and material... The code and arrival time are sequentially written into the structured table entries. After each entry is written, a serial number field is appended. The serial number increments from 1 according to the order within the parking space and is used for subsequent batch identification. When multiple batches arrive at a parking space on the same day, the batch boundary is determined by the arrival time interval. The arrival time interval threshold is determined by the on-site unloading rhythm. The determination method is to count the arrival interval between two adjacent materials during 20 unloading operations. The interval is mostly no more than 120 seconds. The threshold is set to 300 seconds. When the arrival time interval between two adjacent records exceeds 300 seconds, a new batch is started and the batch number is written into the field. Finally, a parking space material arrival list is generated and output to subsequent modules for use.

[0024] Table 1. Sample Original Record of Materials Arriving at Parking Space

[0025] As shown in Table 1, the number of bytes for reading the frame length is used for length verification, the "whether to retain" field reflects the retention result after removing duplicate numbers, and the "parking space number" field is used for subsequent collection and writing into the parking space material arrival list.

[0026] Specifically, such as Figure 2 , 4 As shown, the progress mapping module includes: The process duration collection submodule collects parking space number, construction process identifier and corresponding start time and completion time records based on the parking space material arrival list. It performs time difference calculation for process records under the same parking space, judges the integrity of timestamps and removes missing items, and forms a set of construction duration values ​​associated with parking space number and process identifier, generating the actual duration value of parking space process. After accessing the parking space material arrival list, the parking space number is used as the primary key to retrieve construction record sources. These sources are derived from a merged table of on-site process check-in terminals and supervisor confirmation records. The collected fields are fixed as parking space number, construction process identifier, start time, and completion time. The construction process identifier is taken from the construction plan process dictionary and uses a unified coding rule, which is released and distributed by the terminal at project startup. When multiple process records for the same parking space are collected, they are first grouped by construction process identifier, and each group is sorted by start time. Then, a time difference calculation is performed on each record. The time difference is obtained by subtracting the start time from the completion time. The duration field is written in minutes; in the timestamp integrity judgment stage, the start time and completion time of each record are checked to see if they exist at the same time. If either timestamp is missing, the record is marked as missing and removed from the duration set. At the same time, the reason for the missing time is written as "missing start time" or "missing completion time". To avoid negative durations caused by misfilling, an order consistency check is added. If the completion time of the same record is earlier than the start time, it is judged as abnormal and removed. At the same time, the abnormality type is written as "order error". After forming a set of construction duration values ​​associated with parking space number and process identifier, the actual duration value of parking space process is generated and written into the parking space dimension index table. In the example, the cable laying process for parking space 001 started at 10:05:00 on February 27, 2024, and ended at 12:35:00 on the same day, with an actual duration of 150 minutes. The charging pile cabinet installation process for parking space 001 started at 13:10:00 on February 27, 2024, and ended at 14:40:00 on the same day, with an actual duration of 90 minutes. For parking space 002, if there is a missing completion time record, this record is removed before forming the set, but its index is retained in the missing records list. To verify the timestamp integrity rule, 40 records were randomly selected on-site and compared with the supervisor's paper signature time. After removing missing and out-of-order records, the consistency rate between the duration set and the paper records reached 0.95, compared to 0.86 before removal. The verification data was written into the quality control report.

[0027] The construction period comparison submodule obtains the standard construction period value under the corresponding process identifier in the construction plan based on the actual time value of the parking space process. It calculates the ratio of the actual time to the standard construction period for the same parking space and the same process, limits the ratio range and completes the value normalization, forms the process progress percentage data item under the parking space dimension, and generates the process progress percentage value. After obtaining the actual duration of the parking space process, the standard duration value corresponding to the same process identifier is retrieved from the construction schedule table. The standard duration value is formed based on construction statistics of similar sites during project planning, and the standard minutes are defined for each parking space process. Subsequently, a ratio calculation is performed for the same parking space and the same process. The ratio is the actual duration divided by the standard duration to obtain the initial value of the process progress percentage. To limit the range of the ratio, the ratio is trimmed, with a lower limit of 0.00 and an upper limit of 1.20. The upper limit is determined through historical deviation statistics, which are obtained by summarizing the distribution of the ratio of the actual duration to the standard duration of the process for the past 50 parking spaces. The coverage ratio of 20 reached 0.97, so the upper limit was fixed at 1.20. After the trimming was completed, the values ​​were normalized by keeping two decimal places and recording values ​​exceeding 1.00 in the overdue field. The overdue field was written with the overdue ratio value. In the example, the standard duration of the cable laying process is 120 minutes, the actual duration of parking space 001 is 150 minutes, the ratio is 1.25, the process progress ratio after trimming is 1.20, and the overdue field is written with 0.25. The standard duration of the charging pile cabinet installation process is 100 minutes, the actual duration of parking space 001 is 90 minutes, the ratio is 0.90, after trimming, it is kept at 0.90 and written with the process progress ratio value. To verify the impact of the upper limit value on the stability of the progress calculation, 20 parking spaces were used as a sample on site to compare the fluctuations of the results with upper limits of 1.10, 1.20, and 1.30. The fluctuations were represented by the standard deviation of the total progress of the parking spaces. The standard deviation was 0.07 when the upper limit was 1.20, 0.11 when the upper limit was 1.10, and 0.09 when the upper limit was 1.30. 1.20 was adopted and a record was made.

[0028] The progress summary submodule calls the process progress percentage value, performs a weighted summation calculation of the process progress percentage according to the parking space number, and takes the weight from the process sequence identifier in the construction plan to complete the merging of the progress values ​​at the parking space level, and writes the parking space number and progress percentage into the structured data table to generate the parking space construction progress record table. After calling the process progress percentage, the data is aggregated by parking space number and a weighted summation is performed. The weights are taken from the process sequence identifiers in the construction plan. The process sequence identifiers correspond to the order of processes in the plan table and are mapped to weight values. The weights are determined using the planned duration percentage method. First, the total standard duration of all processes applicable to the parking space is summed. Then, the standard duration of each process is divided by the total to obtain the weight. The weights are rounded to two decimal places, and the total is ensured to be 1.00. If the total deviates from 1.00 due to rounding, the weight of the last process is compensated and corrected. In the example, parking space 001 includes 120 minutes for cable laying, 100 minutes for charging pile cabinet installation, and 80 minutes for power-on commissioning, totaling 3. 00 minutes, corresponding to weights of 0.40, 0.33, and 0.27; when the progress percentages of the process are 1.20, 0.90, and 0.50 respectively, the weighted sum is used to obtain a parking space progress percentage of 0.91, which is then written into the structured data table. The percentage is written with two decimal places and simultaneously written with the progress calculation timestamp; after generating the parking space construction progress record table, a consistency check is added. If the progress percentage of the same parking space regresses, the regression judgment threshold is set to 0.05. The threshold is determined by the statistical analysis of the timestamp correction deviation caused by terminal data entry. If the regression exceeds 0.05, the parking space record is written into the review queue and the original value and the new value are retained; this review queue is used as a reference input in subsequent difference calculation.

[0029] Table 2. Sample Table of Parking Space Process Duration and Weight

[0030] As shown in Table 2, the actual duration in minutes and the standard duration in minutes are used to form the percentage of the process progress. The process weight value is derived from the standard duration percentage calculation and used for the progress summary at the parking space level.

[0031] Specifically, such as Figure 2 , 5 As shown, the matching evaluation module includes: The theoretical consumption calculation submodule calculates the theoretical consumption of materials corresponding to the parking space construction process based on the parking space construction progress record table and the design consumption data of the construction drawing budget or bill of quantities, summarizes the material consumption data of the parking space dimension, and obtains the theoretical consumption value of the parking space. After connecting to the parking space construction progress record table, the theoretical consumption calculation submodule first reads the progress percentage for each parking space and establishes a mapping with the design consumption data from the construction drawing budget or bill of quantities. The design consumption data provides a material list and corresponding design quantity at the parking space level. The data source is the budget preparation table imported and locked with the version number signed by the supervisor. During consumption derivation, the module reads the process identifier and material correspondence table for each parking space. The material correspondence table is determined by the construction organization design. The table gives the types of materials consumed in each process and the proportion of the design consumption. The proportion is obtained through statistics from similar historical projects and calibrated by trial assembly and testing in 10 parking spaces before construction begins. The calibration method is to record the ratio of the actual quantity used during the trial assembly to the design consumption and take the average. After the correspondence is loaded, the design consumption and the process progress percentage are linked and calculated according to the parking space and process. The linkage rule is to use the process progress percentage as the completion rate. The completion rate is multiplied by the design usage share of the corresponding material for that process and summarized into the parking space material dimension. The summation forms the theoretical consumption value for the parking space. In the example, the design usage of the YJV cable segment of the low-voltage power distribution cable for parking space 001 is 28 meters. The share ratio corresponding to the cable laying process is 1.00, and the process progress ratio is 1.20. After linkage, the theoretical consumption of the cable is 33.60 meters and recorded to two decimal places. The design usage of the DC charging gun cable assembly for parking space 001 is 1 set. The share ratio corresponding to the cabinet installation process is 0.80, and the process progress ratio is 0.90. After linkage, the theoretical consumption is 0.72 sets. When the material measurement unit is a set or unit, etc., a quantification rule is executed. The quantification rule is given by the measurement dictionary. The discrete unit uses 0.50 as the trigger boundary for requisition. A quantity exceeding 0.50 is recorded as 1 piece, and a quantity not exceeding 0.50 is recorded as 0 pieces. Therefore, 0.72 sets are quantified as 1 set and written into the discrete theoretical consumption field. To verify the effectiveness of the share ratio calibration, the average deviation between the actual cable usage and the theoretical consumption in the 10 trial installations was 0.08, while it was 0.15 before calibration. The calibration data was archived.

[0032] The arrival quantity summary submodule obtains the parking space material arrival list, summarizes the arrival quantity of materials for each parking space, generates parking space-level material arrival quantity data, and obtains the parking space material arrival quantity. After obtaining the material arrival list for each parking space, the arrival quantity summary submodule summarizes the material arrival quantity by parking space number. The summary rule is to merge materials by material code and accumulate the quantity of materials with the same material code. The quantity source is the number of records with the same material code in the arrival list for the same parking space. If the same record contains a quantity field, the quantity field is used, and the number of records is used as a validation field. For cable materials, the unit of quantity is meters, and the length of the cable segment arriving at the site needs to be written. The cable segment length is imported from the measurement record during the on-site acceptance. The measurement record is read using a tape measure or meter counter and marked with 0. Record the length with an accuracy of 0.1 meters, and then associate the length with the arrival item. In the example, there are 3 cable segments recorded for parking space 001, with lengths of 12.0 meters, 10.0 meters, and 12.0 meters respectively, and the total number of arrivals is 34.0 meters. There is 1 DC charging gun cable assembly recorded for parking space 001, and the total number of arrivals is 1 set. In order to avoid the same material being mistakenly grouped across parking spaces, a parking space number consistency check is performed. If the same label number appears in different parking spaces, the most recent manual parking space scan record shall prevail, and the conflict record shall be written into the conflict list for review.

[0033] The variance calculation submodule compares the theoretical consumption value of parking spaces with the quantity of materials arriving at the parking spaces to calculate the material variance and generate a detailed table of parking space material variances. The variance calculation submodule compares the theoretical consumption value and the quantity of materials delivered to the parking space with the actual consumption value and calculates the material variance. The variance is calculated by subtracting the theoretical consumption value from the delivered quantity and writing it into the variance field, which then generates a detailed table of parking space material variances. Integer variances are used for discrete unit materials, while two decimal places are retained for continuous unit materials. In the example, the quantity of cable delivered to parking space 001 is 34.0 meters, the theoretical consumption is 33.60 meters, and the variance is 0.40 meters, which is written as a positive difference. The quantity of DC charging gun cable assembly delivered to parking space 001 is 1 set, the discrete theoretical consumption is 1 set, and the variance is 0 sets. If a negative difference record appears, for example... The quantity of cable delivered to parking space 002 is 20.0 meters, the theoretical consumption is 26.40 meters, and the difference is -6.40 meters, which is recorded as a negative difference. To ensure that the difference result is consistent with the progress mapping, the calculation of the theoretical consumption of 26.40 meters for parking space 002 will be substituted with the results of the aforementioned progress percentage of parking space 002 and the design consumption data, and written into the calculation tracking field. A reasonable range for the difference will be set for verification. The verification range will be determined by material loss experience. Under normal construction conditions, the positive difference for cable materials will not exceed 3.00 meters, and the negative difference will not exceed -8.00 meters. Records exceeding the range will be written into the review queue and marked as abnormal range.

[0034] Specifically, such as Figure 2 , 6 As shown, the early warning determination module includes: The negative difference screening submodule reads the material difference quantity field and the parking space number field from the parking space material difference details table, performs interval judgment according to the difference quantity value range, collects the parking space records with the difference quantity below zero into the abnormal candidate set, and performs counting and statistical calculation on the parking space numbers in the candidate set to obtain the number of negative difference parking spaces. The negative difference screening submodule reads the difference quantity field and parking space number field from the parking space material difference details table. It first establishes a difference quantity value interval rule table based on material category. This rule table is determined by the project's material loss control target and verified through on-site testing. The testing method involves statistically analyzing cable scraps and returned materials after construction is completed in five parking spaces to form the actual loss distribution. Cable negative differences typically arise from missed registrations or cross-parking space misappropriation. The acceptable lower limit for negative differences in the test is -2.00 meters. The negative difference screening interval is set as follows: a difference quantity less than 0 and not less than -2.00 meters is considered a minor anomaly candidate, and a difference quantity less than -2.00 meters is considered a severe anomaly candidate. During screening, interval judgment is performed on each record. Parking space records falling into the interval below zero are collected into the anomaly candidate set and sorted according to severity priority. The sorting rule is to first sort by difference quantity from smallest to largest. The system first sorts the parking spaces by arrival time from earliest to latest. Then, it performs sequential coding on the candidate parking space numbers, incrementing from 1 and writing the codes into the candidate sequence number field. Simultaneously, it counts the number of parking spaces with negative discrepancies. In the example, parking space 002, with a discrepancy of -6.40 meters, enters the severe anomaly candidate and is coded as 1; parking space 005, with a discrepancy of -0.80 meters, enters the mild anomaly candidate and is coded as 2. The total number of parking spaces with negative discrepancies is 2. To verify the interval threshold setting, a manual inventory was conducted on-site as a control. The actual cable length of 15 parking spaces was measured and compared with the recorded arrival count. When the lower limit of the negative discrepancy was -2.00 meters, the match rate between the severe anomaly candidate and manually discovered cross-parking space misappropriation events was 0.87; when it was -3.00 meters, the match rate was 0.74. Therefore, -2.00 meters was fixed as the severe discrepancy boundary.

[0035] The proportional calculation submodule calls the negative difference parking space quantity value, obtains the list of all construction parking spaces and extracts the total number of parking space numbers, performs proportional calculation based on the quantity correspondence, forms the quantity ratio range between the number of negative difference parking spaces and the total number of construction parking spaces, and obtains the abnormal parking space ratio value. After obtaining the number of negative error parking spaces, the proportional calculation submodule retrieves the total number of parking space numbers from the complete construction parking space list. The parking space list comes from the project parking space ledger and is locked before construction begins. Then, the proportional calculation is performed based on the quantity correspondence. The proportional is calculated by dividing the number of negative error parking spaces by the total number of construction parking spaces and retaining two decimal places. In the example, the total number of construction parking spaces is 60, the number of negative error parking spaces is 2, and the abnormal parking space proportional value is 0.03. To improve the stability of the proportional calculation, a rolling window is used, with a window length of 1 day. The number of newly added negative error parking spaces on the current day is counted and compared with the total to calculate the daily proportional. At the same time, the average proportional of the most recent 7 days is calculated and written into the trend field. The window length and average number of days are determined by the early warning response rhythm. The project management stipulates that a material meeting is held once a week, so the 7-day average proportional is used for the meeting summary.

[0036] The anomaly generation submodule obtains the preset construction anomaly ratio threshold range data based on the anomaly parking space ratio value, performs range comparison judgment and outputs judgment flag, writes the judgment flag into the negative difference parking space number set, generates structured data including parking space number and status flag fields, and obtains the material anomaly parking space list. The anomaly generation submodule obtains the preset construction anomaly ratio threshold range data based on the abnormal parking space ratio value and performs interval comparison judgment. The threshold range is set through historical project statistics, and the statistical object is the distribution of negative difference parking space ratios of 10 similar projects. The median of the distribution is 0.04 and the 75th percentile is 0.07. Therefore, the preset construction anomaly ratio threshold range is set to 0.06 to 0.10. When the abnormal parking space ratio value falls within 0.06 to 0.10, the judgment label is output as general anomaly. When the abnormal parking space ratio value is greater than 0.10, the judgment label is output as severe anomaly. When the abnormal parking space ratio value is less than 0.06, the judgment label is output as normal but candidate is retained. In the example, the abnormal parking space ratio value of 0.03 is lower than 0.06, and the judgment label is normal but candidate is retained. At the same time, the judgment label is written into the negative difference parking space number set and a package is generated. Structured data, including parking space number and status identifier fields, is used to form a list of parking spaces with material anomalies. To meet the requirements of empirical data, the threshold range is compared with the traditional fixed threshold of 0.05 on site. The number of warning triggers and manual confirmations of anomalies are counted over 20 construction days. When using the 0.06 to 0.10 range rule, there were 40 warning triggers and 32 manual confirmations, with a confirmation ratio of 0.80. When using the fixed threshold of 0.05, there were 55 warning triggers and 33 manual confirmations, with a confirmation ratio of 0.60. The experimental results show that the confirmation ratio of the range threshold rule is 20 percentage points higher than that of the fixed threshold. The data is written into the verification record. The advantage of this operation logic is that by simultaneously introducing negative difference range classification and the threshold range of the entire parking space ratio, the generation of anomalies can distinguish between local occasional errors and overall anomaly trends.

[0037] Specifically, such as Figure 2 ,7 As shown, the ledger update module includes: The RFID data acquisition submodule obtains the RFID reading time and the most recent process completion time for each parking space based on the material abnormal parking space list, extracts the corresponding field data, and establishes a mapping relationship between parking space number and RFID reading time and process completion time to obtain parking space RFID reading and process completion time data. Based on the material anomaly parking space list, the execution time field of each parking space is retrieved. First, the RFID reading time of the parking space is obtained. The reading time comes from the arrival time of the last retained record in the parking space's material arrival list. For multiple materials in the same parking space, the maximum arrival time is taken as the most recent RFID reading time. At the same time, the most recent process completion time is obtained. The process completion time comes from the completion time field of the process record corresponding to the actual duration value of the process in the parking space. The latest completion time among all processes in the parking space is taken as the most recent process completion time. After completing the extraction of these two types of times, a mapping relationship between parking space number and RFID reading time and process completion time is established and written into a mapping table. Each record in the mapping table is appended with a data source field. The source of RFID reading time is marked as arrival list, and the source of process completion time is marked as construction record. In the example, the most recent RFID reading time of parking space 002 is 2024-02-27 09:18:40, and the most recent process completion time is 2024-02-27 11:55:00. The mapping table is written with these two times and retains the accuracy to the second.

[0038] The time interval calculation submodule calculates the time interval between RFID reading time and process completion time based on parking space RFID reading and process completion time data, and compares it with a preset time threshold to obtain the time interval comparison result. The time interval calculation submodule calculates the time interval between RFID reading time and process completion time based on the mapping table. The interval is calculated by subtracting the RFID reading time from the process completion time and converting it to minutes, which is then written into the interval field. The minutes are then compared with a preset time threshold, which is jointly calibrated by the abnormal handling response requirements and the on-site logistics rhythm. The calibration method involves statistically analyzing the distribution of the intervals from material arrival to process completion in 30 normal construction scenarios. The median interval is 180 minutes, and the 90th percentile is 420 minutes; therefore, the time threshold is set to 480 minutes. When the interval exceeds 480 minutes, it is considered to have exceeded the threshold, and the time interval comparison result is written as "timeout"; otherwise, it is written as "no timeout". In the example, the interval for parking space 002 is 156 minutes, and it is written as "no timeout". If the RFID reading time for parking space 010 is 2024-02-26 15:10:00, and the most recent process completion time is 2024-02-27 12:10:00, the interval is 1260 minutes, and it is written as "timeout". To verify the differentiation effect of the 480-minute threshold, anomaly tracking was conducted on 25 parking spaces on-site. The proportion of parking spaces with actual clues of cross-day storage without being put into storage or misappropriation in the timeout set was 0.76%. The proportion was 0.58 when the threshold was 360 minutes and 0.72 when the threshold was 600 minutes. The 480-minute threshold was adopted and fixed.

[0039] The ledger update submodule marks the status of parking spaces that exceed the threshold based on the comparison results of the time interval. The marking results and parking space numbers are written into the material management ledger of the oil-to-electricity conversion project, generating an update record that includes the parking space number and status identifier, thus obtaining the material management ledger update record. The ledger update submodule marks parking spaces that exceed a threshold based on the time interval comparison results. The marking field uses a status identifier and is written to the oil-to-electricity project material management ledger along with the parking space number. The writing method is to append an update record and retain the historical status. The update record fields include parking space number, status identifier, update time, and trigger reason. The status identifier value rules are linked to the early warning judgment. When the parking space is in the material abnormal parking space list as generally abnormal and the time interval comparison result is timed out, the status identifier is written as "requires review". When the parking space is seriously abnormal and timed out, the status identifier is written as "issue needs to be stopped". When the parking space is normal but retained as a candidate and... If a timeout occurs, the status flag is written as "needs random inspection". In the example, if parking space 010 is classified as "generally abnormal" in the early warning judgment and the interval is 1260 minutes, the logbook will write the status flag as "needs review" and record the triggering reason as "negative difference heavy candidate and timeout superposition". For parking spaces that have not exceeded the threshold, no negative flag is written, but a status write-back record is written once, and the status flag is "tracked" for closed-loop statistics. After generating the material management logbook update record, a consistency check is performed. The status flags of the three most recent update records of the same parking space in the logbook are checked in sequence. If a "needs to stop" error occurs and then directly returns to "tracked", the audit prompt field is written and a review confirmation is required.

[0040] Table 3. Sample Table of Parking Space Differences, Early Warnings, and Ledger Updates

[0041] As shown in Table 3, after the difference value enters the negative difference classification, it forms the abnormal parking space ratio value and triggers the judgment mark. The interval between the RFID reading time and the completion time of the most recent process in minutes is compared with the threshold and then drives the ledger status mark to be written. For parking space 010, the interval in minutes exceeds 480 minutes and the abnormal parking space ratio value falls within the range of 0.06 to 0.10. Therefore, the writing of the ledger status mark needs to be reviewed and kept consistent with the material abnormal parking space list.

[0042] Please see Figure 8 The intelligent management method for oil-to-electricity conversion materials is implemented based on the aforementioned intelligent management system for oil-to-electricity conversion materials, and includes the following steps: S1: Using RFID technology, the AC charging pile equipment cabinet, DC charging gun cable assembly, and low-voltage power distribution cable YJV cable section at the oil-to-electricity conversion construction site are identified and tracked. The tag number, material code and arrival time data are collected. The read data is verified for integrity and duplicate data is removed. The data is then collected by parking space number to generate a parking space material arrival list. S2: Based on the parking space material arrival list, collect the actual construction time of the parking space construction process, compare it with the standard construction period in the construction plan, calculate the construction progress percentage, and generate a parking space construction progress record table. S3: Based on the parking space construction progress record sheet and the design quantities in the construction drawing budget or bill of quantities, calculate the theoretical material consumption of the corresponding process of the parking space, compare it with the material arrival quantity in the parking space material arrival list, calculate the material difference, generate a parking space material difference detail sheet, and record the material difference of the parking space. S4: Based on the parking space material difference details table, filter the parking spaces with material difference less than zero, count the proportion of the parking spaces in all construction parking spaces, compare the proportion with the preset construction abnormality proportion threshold, generate a list of abnormal parking spaces, and record the abnormal parking space number and corresponding status identifier. S5: Based on the list of abnormal material parking spaces, collect the RFID reading time and the most recent process completion time of the corresponding parking space, calculate the interval between the times, compare it with the preset time threshold, mark the status of parking spaces that exceed the time threshold, and write the marking results into the material management ledger of the oil-to-electricity conversion project to generate a material management ledger update record.

[0043] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An intelligent management system for materials from oil-to-electricity conversion projects, characterized in that, The system includes: The tag collection module uses RFID technology to identify and track AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable YJV cable sections at the oil-to-electricity conversion construction site. It collects tag numbers, material codes, and arrival times, and aggregates them by parking space number to generate a parking space material arrival list. Based on the parking space material arrival list, the progress mapping module collects the actual construction time of the parking space construction process, compares it with the standard construction period of the construction plan, and generates a parking space construction progress record table. The matching and evaluation module calculates the theoretical material consumption of the parking space based on the parking space construction progress record table and the design usage in the construction drawing budget, and compares it with the material arrival quantity in the parking space material arrival list to generate a parking space material difference detail table. The early warning judgment module filters parking spaces with material differences less than zero based on the parking space material difference details table, calculates the proportion and compares it with the preset construction abnormality proportion threshold, and generates a list of parking spaces with material abnormalities. The ledger update module collects the RFID reading time and the most recent process completion time of the corresponding parking space based on the material abnormal parking space list, calculates the time interval and compares it with the preset time threshold, marks the parking spaces that exceed the time threshold and updates them to the oil-to-electricity project material management ledger, generating a material management ledger update record.

2. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that: The parking space material arrival list includes the arriving parking space number, arrival tag number, arriving material code, and material arrival time; the parking space construction progress record includes the construction parking space number, construction process name, actual construction duration, standard construction period, and construction progress percentage; the parking space material difference details table includes the difference parking space number, theoretical material consumption for the process, material arrival quantity, material difference amount, and material difference status; the abnormal parking space list includes the abnormal parking space number, abnormal status identifier, abnormal parking space percentage, and abnormal percentage threshold; the material management ledger update record includes the updated parking space number, RFID reading time, most recent process completion time, time interval value, and threshold status marking result.

3. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that: The material variance is the quantity of materials arriving in the parking space material arrival list minus the theoretical material consumption of the parking space.

4. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that: The ratio is the ratio between the number of parking spaces with material difference less than zero and the total number of parking spaces in the parking space construction progress record table.

5. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that, The tag acquisition module includes: The tag reading submodule uses RFID technology to identify and track AC charging pile equipment cabinets, DC charging gun cable assemblies, and low-voltage power distribution cable YJV cable sections at the oil-to-electricity conversion construction site. It collects tag numbers, material codes, and arrival time data, obtains the read frame byte sequence, calculates the frame length difference, and performs consistency judgment with the set frame length benchmark value. It accumulates the judgment to determine the number of frames that pass the length check and generates the RFID record quantity. The data verification submodule obtains the corresponding tag number, material code and arrival time data sequence based on the RFID record quantity, calculates the number of times the tag number appears in the same time window and compares it with the single arrival discrimination threshold, performs duplicate number removal and calculates the ratio of the number of retained records to the original number of records, and generates the record data retained after removing duplicate numbers; The parking space collection submodule calls the retained record sequence based on the record data retained after removing duplicate numbers, obtains the parking space number field, performs number collection and counting operations, and sequentially writes the label number, material code and arrival time data according to the parking space number to form a structured table item, generating a parking space material arrival list.

6. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that, The progress mapping module includes: The process duration collection submodule collects parking space number, construction process identifier and corresponding start time and completion time records based on the parking space material arrival list. It performs time difference calculation for process records under the same parking space, judges the integrity of timestamps and removes missing items, and forms a set of construction duration values ​​associated with parking space number and process identifier, and generates the actual duration value of parking space process. The construction period comparison submodule obtains the standard construction period value under the corresponding process identifier in the construction plan based on the actual time value of the parking space process. It performs the ratio calculation of actual time and standard construction period for the same parking space and the same process, limits the ratio range and completes the value regularization, forms the process progress percentage data item under the parking space dimension, and generates the process progress percentage value. The progress summary submodule calls the process progress percentage value, performs a weighted summation operation on the process progress percentage according to the parking space number, and takes the weight from the process sequence identifier in the construction plan to complete the merging of progress values ​​at the parking space level. Then, it writes the parking space number and progress percentage into a structured data table to generate a parking space construction progress record table.

7. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that, The matching assessment module includes: The theoretical consumption calculation submodule calculates the theoretical consumption of materials corresponding to the parking space construction process based on the parking space construction progress record table and the design consumption data of the construction drawing budget or bill of quantities, summarizes the material consumption data of the parking space dimension, and obtains the theoretical consumption value of the parking space. The arrival quantity summary submodule obtains the parking space material arrival list, summarizes the arrival quantity of materials for the parking spaces, generates parking space-level material arrival quantity data, and obtains the parking space material arrival quantity. The difference calculation submodule compares the theoretical consumption value of the parking space with the quantity of materials arriving at the parking space to calculate the material difference and generate a detailed table of parking space material differences.

8. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that, The early warning determination module includes: The negative difference screening submodule reads the material difference amount field and the parking space number field from the parking space material difference details table, performs interval judgment according to the difference amount value interval, collects the parking space records with the difference amount below zero into the abnormal candidate set, and performs counting and statistical calculation on the parking space numbers in the candidate set to obtain the number of negative difference parking spaces. The proportional calculation submodule calls the negative difference parking space quantity value, obtains the list of all construction parking spaces and extracts the total number of parking space numbers, performs proportional calculation based on the quantity correspondence, forms the quantity ratio range between the number of negative difference parking spaces and the total number of construction parking spaces, and obtains the abnormal parking space ratio value. The anomaly generation submodule obtains the preset construction anomaly ratio threshold range data based on the anomaly parking space ratio value, performs range comparison judgment and outputs judgment identifier, writes the judgment identifier into the negative difference parking space number set, generates structured data including parking space number and status identifier fields, and obtains the material anomaly parking space list.

9. The intelligent material management system for oil-to-electricity conversion according to claim 1, characterized in that, The ledger update module includes: The RFID data acquisition submodule obtains the RFID reading time and the most recent process completion time for each parking space based on the material abnormal parking space list, extracts the corresponding field data, and establishes a mapping relationship between parking space number and RFID reading time and process completion time to obtain parking space RFID reading and process completion time data. The time interval calculation submodule calculates the time interval between the RFID reading time and the process completion time based on the parking space RFID reading and process completion time data, and compares it with a preset time threshold to obtain the time interval comparison result. The ledger update submodule marks the status of parking spaces that exceed the threshold based on the comparison results of the time interval. The marking results and parking space numbers are written into the material management ledger of the oil-to-electricity conversion project, generating an update record that includes the parking space number and status identifier, thus obtaining the material management ledger update record.

10. A method for intelligent management of materials in oil-to-electricity conversion, characterized in that, The intelligent management system for oil-to-electricity material conversion according to any one of claims 1-9 includes the following steps: S1: Using RFID technology, the AC charging pile equipment cabinet, DC charging gun cable assembly, and low-voltage power distribution cable YJV cable section at the oil-to-electricity conversion construction site are identified and tracked. The tag number, material code and arrival time data are collected. The read data is checked for integrity and duplicate data is removed. The data is then collected by parking space number to generate a parking space material arrival list. S2: Based on the parking space material arrival list, collect the actual construction time of the parking space construction process, compare it with the standard construction period in the construction plan, and generate a parking space construction progress record table. S3: Based on the parking space construction progress record table, combined with the design quantities in the construction drawing budget or bill of quantities, calculate the theoretical material consumption of the corresponding process of the parking space, compare it with the material arrival quantity in the parking space material arrival list, calculate the material difference, and generate a parking space material difference detail table. S4: Based on the parking space material difference details table, filter the parking spaces with material difference less than zero, count the proportion of the parking spaces in all construction parking spaces, and compare the proportion with the preset construction abnormality proportion threshold to generate a list of parking spaces with material abnormality. S5: Based on the list of abnormal material parking spaces, collect the RFID reading time and the most recent process completion time of the corresponding parking space, calculate the interval between the times, compare it with the preset time threshold, mark the status of parking spaces that exceed the time threshold, and write the marking result into the material management ledger of the oil-to-electricity conversion project to generate a material management ledger update record.

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