A fuel entry acceptance and data association monitoring system and method for the entire process

Abstract

This invention relates to the field of fuel acceptance technology, specifically to a system and method for the full-process acceptance and data-related supervision of fuel arrival. It includes a risk pre-assessment module, a weighbridge arrival verification module, a batch coding verification module, a dynamic quality inspection and acceptance module, an unloading and warehousing control module, and an evidence closed-loop supervision module. The risk pre-assessment module is used before vehicles enter the site to collect relevant information on procurement, suppliers, transportation, and contract acceptance, and calculates the risk level by combining historical supplier performance and transportation risk data. By constructing the risk pre-assessment module, the fuel arrival acceptance model is upgraded from passive verification after arrival to proactive risk identification before arrival. The system collects multi-dimensional information such as procurement, suppliers, transportation, and contracts in advance, quantifies the supplier risk level by combining historical performance data, and matches differentiated acceptance strategies, thus preventing various potential problems such as supply performance, fuel quality, and transportation safety from the source.

Description

Technical Field

[0001] This invention relates to the field of fuel acceptance technology, and more specifically, to a fuel entry acceptance and data association monitoring system and method for the entire process. Background Technology

[0002] As a core production raw material in industries such as power, metallurgy, and chemicals, the acceptance process for fuel upon arrival is a critical control point to ensure the quality and compliance of production raw materials, the accuracy of measurement data, the security and stability of the supply chain, and the fairness of enterprise cost accounting. Existing fuel arrival acceptance technologies mainly revolve around basic steps such as verifying procurement information, weighing vehicles on weighbridges, sampling and quality inspection of fuel, warehousing registration, and financial settlement. The aim is to achieve basic control over the fuel arrival process through manual verification and basic data recording, ensuring that the fuel entering the site meets the contractual agreement and production and use requirements.

[0003] Existing fuel entry acceptance technologies mostly involve passive verification after transport vehicles arrive at the site. The entire process relies on manual offline operations. The core work scenarios are concentrated on weighing at the weighbridge, on-site sampling, laboratory quality inspection, warehousing and document transfer after the vehicle enters the site. Each acceptance link is deployed in independent positions and systems such as procurement management, weighbridge measurement, quality inspection, warehousing management and financial settlement. There is no unified coordination mechanism for data collection and business execution.

[0004] In scenarios involving passive verification upon arrival, existing technologies suffer from several inherent flaws: the lack of a pre-entry supplier risk assessment mechanism makes it impossible to implement differentiated management for suppliers with different risk levels; the absence of stable judgment and unified triggering logic for weighbridge data easily leads to inconsistencies in the timing of weighing, image, seal, and waybill data; the lack of a unified digital identity for fuel batches results in data breaks and difficulties in traceability during sampling, quality inspection, warehousing, and settlement; the use of fixed rules for sampling and quality inspection makes it impossible to dynamically adjust the verification intensity based on risk and quality fluctuations; and the lack of weight closure verification and batch evolution management for unloading and warehousing easily leads to measurement deviations and inventory chaos. Therefore, this paper proposes a fuel entry full-process acceptance and data association supervision system and method. Summary of the Invention

[0005] The purpose of this invention is to provide a system and method for the whole process of fuel entry acceptance and data association supervision, so as to solve the problems mentioned in the background art.

[0006] To address the aforementioned technical problems, one objective of this invention is to provide a fuel entry acceptance and data association monitoring system, including a risk reservation and pre-assessment module, a weighbridge arrival verification module, a batch coding verification module, a dynamic quality inspection and acceptance module, an unloading and warehousing control module, and an evidence closed-loop monitoring module. The risk reservation and assessment module is used to collect relevant information on procurement, suppliers, transportation and contract acceptance before vehicles enter the site. It calculates the risk level by combining the supplier's historical performance and transportation risk data, and presets differentiated pre-acceptance strategies based on the risk level to achieve proactive risk prediction before vehicles enter the site. The weighbridge arrival verification module is used to collect weighing data in real time and determine the data stability after a fuel vehicle enters the weighbridge area. After the data is stable, the module simultaneously completes the identification of the vehicle, license plate, seal, waybill, and gross weight lock. When abnormalities are detected in the vehicle, weighbridge, seal, etc., the acceptance is suspended and an abnormality prompt is triggered. The batch coding verification module is used to generate a unique digital identity code for the fuel batch after weighing and basic identification, which serves as a unified traceability index for the entire process. It performs consistency verification on multi-source data such as vehicle, waybill, seal, and weight, and determines the corresponding acceptance and disposal method based on data matching and risk situation. The dynamic quality inspection and acceptance module is used to dynamically adjust the sampling quality inspection intensity and perform sampling quality inspection operations based on the supplier's risk level, historical fluctuations in fuel quality, contract acceptance standards, and abnormal situations during on-site verification. It compares the measured data with the acceptance standards at all levels and outputs the quality acceptance judgment results. The unloading and warehousing control module is used to issue unloading instructions after the fuel has passed the acceptance test, based on the inventory and unloading conditions, bind the batch digital identity code with the warehousing flow data, re-measure the tare weight after unloading to calculate the net weight and complete the weight closure verification, and build a batch identity evolution traceability chain for various fuel flow change scenarios. The evidence closed-loop supervision module is used to collect the entire process acceptance records to form a complete evidence chain, with the batch digital identity code as the link.

[0007] As a further improvement to this technical solution, the risk reservation and pre-assessment module synchronously connects to the enterprise fuel procurement management system, supplier management database, and transportation dispatch management portal. It pre-collects detailed information on the procurement plan for the fuel to be delivered, basic qualifications and cooperation history of cooperating suppliers, vehicle registration information for this transport, official waybill information, specific fuel category and specifications, and all mandatory acceptance requirements and quality control standards explicitly stipulated in the procurement contract signed by both the supplier and the buyer. Retrieve historical full-cycle performance records of suppliers, including historical supply performance completion rate, long-term stability test data of fuel quality, records of abnormal violations during transportation, records of settlement disputes between suppliers and buyers, and data on routine transportation safety risks in the transportation routes. Input all kinds of quantitative data into the preset supplier risk assessment algorithm model.

[0008] As a further improvement to this technical solution, the risk reservation and pre-assessment module uses a risk assessment algorithm model to calculate the high, medium and low real-time risk levels of the supplier corresponding to this batch of fuel. The higher the risk level value, the greater the probability of safety and quality hazards in the supplier's supply and transportation performance. Automatically match the corresponding pre-acceptance control strategy according to the risk level; For high-risk suppliers, the overall intensity of on-site verification will be automatically increased, the proportion of fuel sampling and testing will be increased, a special manual review and approval node will be added, and the fast-track release authority for vehicles will be closed. For low-risk suppliers, the routine verification process is appropriately simplified, basic verification nodes are retained, and a compliant fast release channel is opened, so that the fuel entry acceptance is transformed from passive post-event verification after the vehicle arrives to proactive pre-event risk identification and control before the vehicle enters the site.

[0009] As a further improvement to this technical solution, the weighbridge arrival verification module senses the vehicle entering the weighbridge verification area in real time, continuously collects dynamic weighing data at high frequency and monitors the fluctuation and duration of the values. At the same time when the weighbridge weighing value does not exceed the threshold within a preset time and is determined to have reached a stable and effective state, it simultaneously links a multi-view camera to collect images of the entire vehicle body, automatically completes the identification of license plate and vehicle registration, identification of the compliant status of the truck bed sealing, verification of RFID electronic tags and transport electronic seals, identification of waybill information, and simultaneously locks the gross weight data of the vehicle for this weighing. Simultaneously verify the vehicle's parking position on the weighbridge, the stability of the weighbridge data, and the compliance status of the electronic seal and the truck bed coverage. If any violation is detected, such as abnormal weighing, excessive data fluctuation, damaged seal, or unsealed truck bed, the entire acceptance process will be immediately locked and suspended. At the same time, abnormal warnings will be pushed to the site and the terminal. The stability of the weighbridge data will be used as the unified triggering benchmark throughout the process to ensure that all verification data is consistent with the arrival time.

[0010] As a further improvement to this technical solution, in the batch coding verification module, after the vehicle completes stable weighing on the weighbridge and compliance verification of basic arrival information, the system summarizes and integrates core data such as supplier, procurement plan, transport vehicle, waybill, electronic seal, weighbridge gross weight and fuel category, and generates a unique and non-repeatable digital identity code for the fuel batch through a dedicated coding algorithm. This identity code serves as a unified core association index for all circulation links in subsequent sampling and quality inspection, unloading and warehousing, inventory control, financial settlement and full-cycle traceability. The system retrieves multi-source data from vehicle identification, waybill verification, procurement filing, seal verification, weighbridge weighing, and image recognition for cross-consistency comparison. It focuses on verifying the compliance of license plate, vehicle, fuel type, planned batch, transportation document, seal status, and weighing weight. Based on the degree of data difference and the level of abnormal risk, it automatically outputs graded acceptance and disposal instructions for normal progress, manual review, restricted unloading, and refusal of entry.

[0011] As a further improvement to this technical solution, the dynamic quality inspection and acceptance module combines fuel type and specifications, supplier pre-risk level, historical fuel quality fluctuation data, contract and enterprise internal control acceptance standards, and abnormal situations during initial on-site verification. It abandons fixed acceptance rules and uses a dynamic acceptance rule engine to adaptively adjust the sampling ratio, quality inspection items, and intensity of manual review for this fuel sampling inspection. It automatically upgrades the acceptance control standards to stricter standards for high-risk suppliers, vehicles with abnormal verification, and fuel batches with large quality fluctuations. Based on dynamically adjusted parameters, it automatically generates dedicated tasks for sampling and quality inspection, records the original data of the entire process of sampling, testing, and preliminary judgment, and compares the actual quality inspection results with contract standards, enterprise internal control standards, and industry regulatory thresholds in multiple dimensions through a rule engine. Finally, it automatically outputs differentiated quality acceptance judgment results such as qualified acceptance, concessionary acceptance, deduction of quantity and price, re-inspection and verification, and rejection of the whole vehicle.

[0012] As a further improvement to this technical solution, in the unloading and warehousing control module, after the fuel passes the entry verification and quality acceptance, the system automatically generates the optimal unloading scheduling and warehousing positioning instructions based on the fuel type, quality inspection level, storage capacity of the stockpile, and availability of equipment and site in the unloading area. The unique digital identification code of the fuel batch is deeply bound to the unloading location, warehousing weight, inventory status, and subsequent consumption destination. After the vehicle unloads, the empty vehicle tare weight is re-measured to accurately calculate the net weight of the fuel and perform weight closure verification with the waybill, procurement plan, and warehousing measurement data. For special circulation scenarios such as fuel splitting and warehousing, mixed warehousing, transfer and relocation, re-inspection and return, and quality grade change, the system automatically generates parent and child batches, mixed batches and status evolution relationships, completely retains the original batch ledger records, and builds a continuous and uninterrupted batch identity evolution traceability chain to eliminate control loopholes such as unclear source, unknown sample, inventory gap, and inconsistent settlement basis during the fuel circulation process.

[0013] As a further improvement to this technical solution, the evidence closed-loop supervision module uses the fuel batch digital identity code as the core associated primary key to collect the entire process operation records, including appointment registration, vehicle identification, weighbridge weighing, waybill verification, seal verification, sampling and quality inspection, unloading and warehousing, abnormal handling, and settlement suggestions, forming a complete evidence chain for fuel entry acceptance that is fully traceable, tamper-proof, and retrievable at any time.

[0014] The second objective of this invention is to provide a method for full-process acceptance and data association monitoring of fuel entry, used in any of the above-mentioned fuel entry full-process acceptance and data association monitoring systems, comprising the following steps: S1. Before vehicles enter the site, collect relevant information on procurement, suppliers, transportation and contract acceptance, calculate the risk level by combining the supplier's historical performance and transportation risk data, and pre-set differentiated pre-acceptance strategies based on the risk level to achieve proactive risk prediction before entering the site. S2. After the fuel vehicle enters the weighbridge area, the weighing data is collected in real time and the data stability is judged. After the data is stable, the vehicle, license plate, seal, waybill identification and gross weight locking are completed simultaneously. When abnormalities are detected in the vehicle, weighbridge, seal, etc., the acceptance is suspended and an abnormality prompt is triggered. After the weighing and basic identification are completed, a unique digital identity code for the fuel batch is generated as a unified traceability index for the whole process. Consistency verification is carried out on multi-source data such as vehicle, waybill, seal, weight, etc., and the corresponding acceptance and disposal method is determined according to data matching and risk situation. S3. Based on the supplier's risk level, historical fluctuations in fuel quality, contract acceptance standards, and abnormal situations during on-site verification, dynamically adjust the sampling and quality inspection intensity and execute sampling and quality inspection operations. Compare the measured data with the acceptance standards at all levels, output the quality acceptance judgment results, and after the fuel passes the acceptance test, issue unloading instructions in combination with inventory and unloading conditions. Bind the batch digital identity code and the warehousing flow data. After unloading, remeasure the tare weight to calculate the net weight and complete the weight closure verification. Build a batch identity evolution traceability chain for various fuel flow change scenarios. S4. Use batch digital identification codes as the link to collect the entire process of acceptance records to form a complete chain of evidence.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. A fuel entry acceptance and data association monitoring system and method, which upgrades the fuel entry acceptance model from passive verification after arrival to proactive risk identification before entry by constructing a risk reservation and pre-assessment module. The system collects multi-dimensional information such as procurement, suppliers, transportation, and contracts in advance, and combines historical performance data to quantify the supplier risk level and match differentiated acceptance strategies. It prevents various hidden dangers such as supply performance, fuel quality, and transportation safety from the source, greatly improves the pertinence and foresight of acceptance control, and effectively reduces control loopholes caused by high-risk batches entering the site.

[0016] 2. A fuel entry acceptance and data association monitoring system and method, which achieves full-process digital linkage through weighbridge arrival verification, batch coding verification, dynamic quality inspection and acceptance, and unloading and warehousing control. It uses the stability of weighbridge data as a unified trigger benchmark to ensure data consistency in time sequence, uses a unique digital identity code to achieve full-process data binding and association, uses a dynamic rule engine to adaptively adjust the quality inspection intensity, and uses weight closure verification and batch evolution chain to ensure measurement accuracy and traceability. It completely solves the problems of data silos, rigid verification standards, broken traceability chains, and measurement deviations in existing technologies. While improving acceptance efficiency, it significantly enhances the authenticity, consistency and credibility of verification data.

[0017] 3. A fuel entry acceptance and data association monitoring system and method, which collects the entire process operation records through an evidence closed-loop monitoring module with batch digital identity as the core, forming a complete and tamper-proof evidence chain. It can automatically complete the abnormal judgment and hierarchical handling, and generate standardized acceptance reports, regulatory ledgers and settlement basis, fundamentally eliminating problems such as unclear source, unknown sample, broken inventory chain, and inconsistent settlement basis in fuel circulation. It realizes the closed-loop monitoring of the entire process of fuel from reservation, arrival, weighing, verification, sampling, quality inspection, unloading, warehousing to settlement, and provides comprehensive support for the compliance, digitalization and refinement of enterprise fuel management. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 This is a structural schematic diagram of the risk reservation and pre-assessment module of the present invention; Figure 3 This is a schematic diagram of the structural principle of the weighbridge arrival verification module of the present invention; Figure 4 This is a schematic diagram of the batch coding verification module of the present invention. Figure 5 This is a schematic diagram of the dynamic quality inspection and acceptance module of the present invention. Figure 6 This is a schematic diagram of the unloading and warehousing control module of the present invention. Figure 7 This is a schematic diagram of the evidence closed-loop monitoring module of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] like Figures 1-7 As shown, one of the objectives of this invention is to provide a fuel entry process acceptance and data association supervision system, including a risk appointment and pre-assessment module, a weighbridge arrival verification module, a batch coding verification module, a dynamic quality inspection and acceptance module, an unloading and warehousing control module, and an evidence closed-loop supervision module. The risk pre-assessment module is used to collect relevant information on procurement, suppliers, transportation and contract acceptance before vehicles enter the site. It calculates the risk level by combining the supplier's historical performance and transportation risk data, and presets differentiated pre-acceptance strategies based on the risk level to achieve proactive risk prediction before vehicles enter the site. The risk reservation and pre-assessment module is integrated with the enterprise's fuel procurement management system, supplier management database, and transportation dispatch management portal. It pre-collects detailed information on the procurement plan for the fuel to be delivered, basic qualifications and cooperation history of cooperating suppliers, vehicle registration information for this transportation, official waybill information, specific fuel category and specifications, and all mandatory acceptance requirements and quality control standards clearly stipulated in the procurement contract signed by both the supplier and the buyer. Synchronously connect with the enterprise's fuel procurement management system, supplier management database, and transportation dispatch management portal to build a cross-system data interaction channel. Pre-collect all basic information on fuels to be delivered, including procurement plan details, supplier basic qualifications and cooperation history, transportation vehicle registration information, official waybill flow data, fuel category specifications, and acceptance rules and quality control standards stipulated in the procurement contract, and complete the unified summary of basic data before delivery. Retrieve historical full-cycle performance records of suppliers, including historical supply performance completion rate, long-term stability test data of fuel quality, records of abnormal violations during transportation, records of settlement disputes between suppliers and buyers, and data on routine transportation safety risks in the transportation routes. Input all kinds of quantitative data into the preset supplier risk assessment algorithm model.

[0021] The system retrieves the supplier's full-cycle performance ledger, and collects data on supply performance completion rate, long-term fuel quality stability testing, transportation anomaly and violation records, supply and demand settlement dispute records, and routine transportation area risk data. It then performs unified quantitative processing on various non-standard business data, unifies data statistical dimensions, and forms a computable standardized risk dataset. At the same time, it fully inputs the quantified performance data, quality data, transportation anomaly data, settlement dispute data, and regional transportation risk data into the preset supplier risk assessment algorithm model, providing a data input basis for risk level calculation. The weighted comprehensive scoring method is used as the optimal assessment algorithm to calculate the supplier's comprehensive risk score. In the risk reservation and assessment module, the risk assessment algorithm model is used to calculate the high, medium and low real-time risk levels of the supplier corresponding to this batch of fuel. The higher the risk level value, the greater the probability of safety and quality hazards in the supplier's delivery and transportation performance. Based on the input multi-dimensional risk quantification data, a weighted fusion calculation method is adopted, and a unified calculation is completed by relying on the preset risk assessment algorithm model to output the supplier's comprehensive risk value. Based on the value range, three levels of real-time risk are defined as high, medium and low. The risk value is positively correlated with the probability of occurrence of supply performance risks, fuel quality risks and transportation safety risks. Automatically match the corresponding pre-acceptance control strategy according to the risk level; For high-risk suppliers, the overall intensity of on-site verification will be automatically increased, the proportion of fuel sampling and testing will be increased, a special manual review and approval node will be added, and the fast-track release authority for vehicles will be closed. For low-risk suppliers, the routine verification process is appropriately simplified, basic verification nodes are retained, and a compliant fast release channel is opened, so that the fuel entry acceptance is transformed from passive post-event verification after the vehicle arrives to proactive pre-event risk identification and control before the vehicle enters the site.

[0022] The weighbridge arrival verification module is used to collect weighing data in real time and determine the stability of the data after a fuel vehicle enters the weighbridge area. Once the data is stable, the module simultaneously completes the identification of the vehicle, license plate, seal, waybill, and lock the gross weight. If any abnormality is detected in the vehicle, weighbridge, or seal, the verification is paused and an abnormality prompt is triggered. In the weighbridge arrival verification module, the system senses the vehicle entering the weighbridge verification area in real time, continuously collects dynamic weighing data at high frequency, and monitors the fluctuation and duration of the values. At the same time when the weighbridge weighing value does not exceed the threshold within a preset time and is determined to have reached a stable and effective state, the system simultaneously links a multi-view camera to collect images of the entire vehicle body, automatically completes the identification of license plates and vehicle registration, identification of the compliant status of the truck bed sealing, verification of RFID electronic tags and transport electronic seals, identification of waybill information, and simultaneously locks the gross weight data of the vehicle for this weighing. Real-time sensing of fuel transport vehicles entering the dedicated weighbridge verification area; the equipment continuously collects real-time dynamic weighing data of the vehicles at high frequency, continuously monitors the real-time fluctuation of the weighing value and the duration of stability, and provides a basic sampling basis for determining the validity of the data. According to the preset time period and fluctuation threshold, the system compares the fluctuation range of the weighing data in real time to determine whether the weighing value of the weighbridge has reached a legal, valid and stable state. Only when the stability condition is met can all subsequent verification actions be triggered. At the same time node when the weighbridge data is determined to be stable, the system synchronously links multi-view cameras to collect images of the entire vehicle body, automatically completes operations such as license plate registration recognition, truck bed sealing status recognition, RFID electronic tag reading, electronic seal verification, and waybill information recognition, and simultaneously permanently locks the gross weight of the vehicle for this weighing. Simultaneously verify the vehicle's parking position on the weighbridge, the stability of the weighbridge data, and the compliance status of the electronic seal and the truck bed coverage. If any violation is detected, such as abnormal weighing, excessive data fluctuation, damaged seal, or unsealed truck bed, the entire acceptance process will be immediately locked and suspended. At the same time, abnormal warnings will be pushed to the site and the terminal. The stability of the weighbridge data will be used as the unified triggering benchmark throughout the process to ensure that all verification data is consistent with the arrival time.

[0023] The system simultaneously checks whether the vehicle is parked in a standard position, whether the weighbridge data is stable, whether the electronic seal is intact, and whether the truck bed is properly covered. It comprehensively verifies whether the vehicle and equipment inspection status meets the standards. If any violation is detected, such as abnormal weighbridge position, excessive data fluctuation, damaged or ineffective seal, or unsealed truck bed, the system will immediately lock and suspend the entire acceptance process, and simultaneously push abnormal warning prompts to the on-site equipment and management terminal. Throughout the entire process, the stability of the weighbridge data is strictly used as the sole and unified triggering benchmark for all data collection actions. This ensures that all verification data, including images, weights, seals, waybills, and arrival times, are at the same point in time, guaranteeing the authenticity, reliability, and consistency of the data sequence.

[0024] The batch coding verification module is used to generate a unique digital identity code for fuel batches after weighing and basic identification, which serves as a unified traceability index for the entire process. It performs consistency verification on multi-source data such as vehicles, waybills, seals, and weights, and determines the corresponding acceptance and disposal methods based on data matching and risk conditions. In the batch coding verification module, after the vehicle completes stable weighing on the weighbridge and compliance verification of basic information upon arrival, the system summarizes and integrates core data such as supplier, procurement plan, transport vehicle, waybill, electronic seal, weighbridge gross weight and fuel category, and generates a unique and non-repeatable digital identity code for the fuel batch through a dedicated coding algorithm. This identity code serves as a unified core association index for all circulation links in subsequent sampling and quality inspection, unloading and warehousing, inventory control, financial settlement and full-cycle traceability. The system collects supplier information, procurement plan data, transport vehicle registration data, official waybill information, electronic seal verification data, weighbridge locked gross weight data, and core parameters of fuel category specifications to form a complete batch basic dataset. A unique, non-repeatable, and tamper-proof digital identification code for each fuel batch is generated using a proprietary coding algorithm. This code is used throughout all stages of the process, including sampling and quality inspection, unloading and warehousing, inventory control, financial settlement, and full-cycle traceability. It serves as the unified core association index primary key for all business operations, as shown in the following formula: ; in, A unique digital identification code for each fuel batch. It is a proprietary encoding algorithm for irreversible hash encryption. A unique code for the supplier. For the procurement plan batch number, Register the license plate number for the transport vehicle. This is the official unique waybill number. To ensure stable weighing on the weighbridge, a timestamp is locked.

[0025] The system retrieves multi-source data from vehicle identification, waybill verification, procurement filing, seal verification, weighbridge weighing, and image recognition for cross-consistency comparison. It focuses on verifying the compliance of license plate, vehicle, fuel type, planned batch, transportation document, seal status, and weighing weight. Based on the degree of data difference and the level of abnormal risk, it automatically outputs graded acceptance and disposal instructions for normal progress, manual review, restricted unloading, and refusal of entry.

[0026] The dynamic quality inspection and acceptance module is used to dynamically adjust the sampling quality inspection intensity and execute sampling quality inspection operations based on the supplier's risk level, historical fluctuations in fuel quality, contract acceptance standards, and abnormal situations during on-site verification. It compares the measured data with the acceptance standards at all levels and outputs the quality acceptance judgment results. In the dynamic quality inspection and acceptance module, the fixed acceptance rules are abandoned. The dynamic acceptance rule engine adaptively adjusts the sampling ratio, quality inspection items and manual review intensity of the current fuel sample through dynamic acceptance rule engine. For high-risk suppliers, vehicles with abnormal verification, and fuel batches with large quality fluctuations, the acceptance control standards are automatically upgraded to stricter. By comprehensively collecting data on fuel type and specifications, supplier pre-existing risk levels, historical fuel quality fluctuation records, procurement contract acceptance standards, internal control acceptance requirements, and abnormal vehicle entry inspection records, all the necessary basis for dynamic regulation and judgment is gathered. This approach abandons traditional, fixed acceptance rules and, through a dynamic acceptance rule engine, automatically and adaptively adjusts the fuel sampling inspection ratio, mandatory quality inspection items, and the intensity of manual review and control based on the overall risk situation. For high-risk suppliers, vehicles with abnormal entry inspections, and fuel batches with significant historical quality fluctuations, stricter acceptance control standards are automatically applied. The formula is as follows: ; in, This represents the actual sampling and inspection ratio implemented in this batch. The sampling rate for the company's routine basic standards. This is a supplier risk level adjustment factor. This is the historical fuel quality fluctuation adjustment coefficient. An adjustment coefficient is added to the initial entry verification anomaly. Based on dynamically adjusted parameters, it automatically generates dedicated tasks for sampling and quality inspection, records the original data of the entire process of sampling, testing, and preliminary judgment, and compares the actual quality inspection results with contract standards, enterprise internal control standards, and industry regulatory thresholds in multiple dimensions through a rule engine. Finally, it automatically outputs differentiated quality acceptance judgment results such as qualified acceptance, concessionary acceptance, deduction of quantity and price, re-inspection and verification, and rejection of the whole vehicle.

[0027] Based on the dynamically adjusted acceptance control parameters, the system generates corresponding batch-specific sampling tasks and laboratory quality inspection and testing tasks with one click, clearly defining sampling specifications, testing items, and verification requirements. The system is then deployed to the site for execution and records the entire sampling operation process, the unique sample number, the original data of various laboratory tests, and the preliminary quality judgment results. This ensures that data is traceable, verifiable, and tamper-proof throughout the entire process of sampling, testing, and preliminary review. Based on the acceptance rule engine, the actual fuel quality inspection results are compared and calculated with the contractual acceptance standards, the company's internal control acceptance standards, and the industry regulatory thresholds in multiple dimensions. According to the degree of matching, the system automatically outputs five different quality acceptance results: qualified acceptance, concession acceptance, deduction of quantity and price, re-inspection and verification, and vehicle rejection, thus completing a dynamic quality closed-loop acceptance.

[0028] The unloading and warehousing control module is used to issue unloading instructions after the fuel has passed the acceptance test, based on the inventory and unloading conditions. It binds the batch digital identity code with the warehousing flow data, re-measures the tare weight after unloading to calculate the net weight and completes the weight closure verification. It builds a batch identity evolution traceability chain for various fuel flow change scenarios. In the unloading and warehousing control module, after the fuel passes the entry verification and quality acceptance, the system automatically generates the optimal unloading scheduling and warehousing positioning instructions based on the fuel type, quality inspection level, storage capacity of the stockpile, and availability of equipment and site in the unloading area. The system deeply binds the unique digital identification code of the fuel batch with the unloading location, warehousing weight, inventory status, and subsequent consumption destination. After the vehicle unloads, the empty vehicle tare weight is remeasured to accurately calculate the net weight of the fuel and perform weight closure verification with the waybill, procurement plan, and warehousing measurement data. After passing the multi-source consistency verification and quality standard acceptance upon entry, the system officially starts the unloading and warehousing control process, with acceptance as the only prerequisite for unloading operations; combining fuel type and specifications, quality inspection and verification quality grade, real-time inventory capacity of each silo and yard, and availability of equipment and site in the unloading area, the system intelligently calculates and generates the optimal vehicle unloading scheduling instructions and precise warehousing positioning instructions. Using the unique digital identification code of each fuel batch as the core index, it is deeply linked and bound to the unloading location, storage information of the silo and stockpile, the verified weight upon entry, the inventory change status, and the subsequent production consumption destination in all dimensions to ensure that each item has a unique code and corresponds to the entire process. After the vehicle completes all unloading operations, the system automatically re-measures the empty vehicle tare weight data and accurately calculates the actual net weight data of the batch of fuel by the difference between the gross weight and the tare weight, which serves as the basis for warehousing and settlement. For special circulation scenarios such as fuel splitting and warehousing, mixed warehousing, transfer and relocation, re-inspection and return, and quality grade change, the system automatically generates parent and child batches, mixed batches and status evolution relationships, completely retains the original batch ledger records, and builds a continuous and uninterrupted batch identity evolution traceability chain to eliminate control loopholes such as unclear source, unknown sample, inventory gap, and inconsistent settlement basis during the fuel circulation process.

[0029] The evidence closed-loop supervision module is used to collect the entire process acceptance records to form a complete evidence chain, with the batch digital identity code as the link.

[0030] In the closed-loop evidence supervision module, the fuel batch digital identity code is used as the core associated key to collect the operation records of the entire process, including appointment registration, vehicle identification, weighbridge weighing, waybill verification, seal verification, sampling and quality inspection, unloading and warehousing, abnormal handling, and settlement suggestions. This forms a complete closed-loop evidence chain for fuel entry and acceptance that is fully traceable, tamper-proof, and retrievable at any time.

[0031] The second objective of this invention is to provide a method for full-process acceptance and data association monitoring of fuel entry, which is used in any of the above-mentioned fuel entry full-process acceptance and data association monitoring systems, including the following steps: S1. Before vehicles enter the site, collect relevant information on procurement, suppliers, transportation and contract acceptance, calculate the risk level by combining the supplier's historical performance and transportation risk data, and pre-set differentiated pre-acceptance strategies based on the risk level to achieve proactive risk prediction before entering the site. S2. After the fuel vehicle enters the weighbridge area, the weighing data is collected in real time and the data stability is judged. After the data is stable, the vehicle, license plate, seal, waybill identification and gross weight locking are completed simultaneously. When abnormalities are detected in the vehicle, weighbridge, seal, etc., the acceptance is suspended and an abnormality prompt is triggered. After the weighing and basic identification are completed, a unique digital identity code for the fuel batch is generated as a unified traceability index for the whole process. Consistency verification is carried out on multi-source data such as vehicle, waybill, seal, weight, etc., and the corresponding acceptance and disposal method is determined according to data matching and risk situation. S3. Based on the supplier's risk level, historical fluctuations in fuel quality, contract acceptance standards, and abnormal situations during on-site verification, dynamically adjust the sampling and quality inspection intensity and execute sampling and quality inspection operations. Compare the measured data with the acceptance standards at all levels, output the quality acceptance judgment results, and after the fuel passes the acceptance test, issue unloading instructions in combination with inventory and unloading conditions. Bind the batch digital identity code and the warehousing flow data. After unloading, remeasure the tare weight to calculate the net weight and complete the weight closure verification. Build a batch identity evolution traceability chain for various fuel flow change scenarios. S4. Use batch digital identification codes as the link to collect the entire process of acceptance records to form a complete chain of evidence.

[0032] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fuel entry acceptance and data association monitoring system for the entire process, characterized in that: It includes a risk appointment and pre-assessment module, a weighbridge on-site verification module, a batch coding verification module, a dynamic quality inspection and acceptance module, an unloading and warehousing control module, and an evidence closed-loop supervision module; The risk reservation and assessment module is used to collect relevant information on procurement, suppliers, transportation and contract acceptance before vehicles enter the site. It calculates the risk level by combining the supplier's historical performance and transportation risk data, and presets differentiated pre-acceptance strategies based on the risk level to achieve proactive risk prediction before vehicles enter the site. The weighbridge arrival verification module is used to collect weighing data in real time and determine the data stability after a fuel vehicle enters the weighbridge area. After the data is stable, the module simultaneously completes the identification of the vehicle, license plate, seal, waybill, and gross weight lock. When abnormalities are detected in the vehicle, weighbridge, seal, etc., the acceptance is suspended and an abnormality prompt is triggered. The batch coding verification module is used to generate a unique digital identity code for the fuel batch after weighing and basic identification, which serves as a unified traceability index for the entire process. It performs consistency verification on multi-source data such as vehicle, waybill, seal, and weight, and determines the corresponding acceptance and disposal method based on data matching and risk situation. The dynamic quality inspection and acceptance module is used to dynamically adjust the sampling quality inspection intensity and perform sampling quality inspection operations based on the supplier's risk level, historical fluctuations in fuel quality, contract acceptance standards, and abnormal situations during on-site verification. It compares the measured data with the acceptance standards at all levels and outputs the quality acceptance judgment results. The unloading and warehousing control module is used to issue unloading instructions after the fuel has passed the acceptance test, based on the inventory and unloading conditions, bind the batch digital identity code with the warehousing flow data, re-measure the tare weight after unloading to calculate the net weight and complete the weight closure verification, and build a batch identity evolution traceability chain for various fuel flow change scenarios. The evidence closed-loop supervision module is used to collect the entire process acceptance records to form a complete evidence chain, with the batch digital identity code as the link.

2. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: The risk reservation and pre-assessment module is synchronously connected to the enterprise's fuel procurement management system, supplier management database, and transportation dispatch management portal. It pre-collects detailed information on the procurement plan for the fuel to be delivered, basic qualifications and cooperation history of cooperating suppliers, vehicle registration information for this transportation, official waybill information, specific fuel category and specifications, and all mandatory acceptance requirements and quality control standards clearly stipulated in the procurement contract signed by both the supplier and the buyer. Retrieve historical full-cycle performance records of suppliers, including historical supply performance completion rate, long-term stability test data of fuel quality, records of abnormal violations during transportation, records of settlement disputes between suppliers and buyers, and data on routine transportation safety risks in the transportation routes. Input all kinds of quantitative data into the preset supplier risk assessment algorithm model.

3. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: In the risk reservation and assessment module, the risk assessment algorithm model is used to calculate the high, medium and low real-time risk levels of the supplier corresponding to the batch of fuel. The higher the risk level value, the greater the probability of safety and quality hazards in the supplier's supply and transportation performance. Automatically match the corresponding pre-acceptance control strategy according to the risk level; For high-risk suppliers, the overall intensity of on-site verification will be automatically increased, the proportion of fuel sampling and testing will be increased, a special manual review and approval node will be added, and the fast-track release authority for vehicles will be closed. For low-risk suppliers, the routine verification process is appropriately simplified, basic verification nodes are retained, and a compliant fast release channel is opened, so that the fuel entry acceptance is transformed from passive post-event verification after the vehicle arrives to proactive pre-event risk identification and control before the vehicle enters the site.

4. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: The weighbridge arrival verification module senses the vehicle entering the weighbridge verification area in real time, continuously collects dynamic weighing data at high frequency and monitors the fluctuation and duration of the values. At the same time when the weighbridge weighing value does not exceed the threshold within a preset time and is determined to have reached a stable and effective state, it simultaneously links a multi-view camera to collect images of the entire vehicle body, automatically completes the identification of license plate and vehicle registration, identification of the compliant status of the truck bed sealing, reading and verification of RFID electronic tags and transport electronic seals, identification of waybill information, and simultaneously locks the gross weight data of the vehicle for this weighing. Simultaneously verify the vehicle's parking position on the weighbridge, the stability of the weighbridge data, and the compliance status of the electronic seal and the truck bed coverage. If any violation is detected, such as abnormal weighing, excessive data fluctuation, damaged seal, or unsealed truck bed, the entire acceptance process will be immediately locked and suspended. At the same time, abnormal warnings will be pushed to the site and the terminal. The stability of the weighbridge data will be used as the unified triggering benchmark throughout the process to ensure that all verification data is consistent with the arrival time.

5. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: In the batch coding verification module, after the vehicle completes stable weighing on the weighbridge and compliance verification of basic information upon arrival, the system summarizes and integrates core data such as supplier, procurement plan, transport vehicle, waybill, electronic seal, weighbridge gross weight and fuel category, and generates a unique and non-repeatable digital identity code for the fuel batch through a dedicated coding algorithm. This identity code serves as a unified core association index for all circulation links in subsequent sampling and quality inspection, unloading and warehousing, inventory control, financial settlement and full-cycle traceability. The system retrieves multi-source data from vehicle identification, waybill verification, procurement filing, seal verification, weighbridge weighing, and image recognition for cross-consistency comparison. It focuses on verifying the compliance of license plate, vehicle, fuel type, planned batch, transportation document, seal status, and weighing weight. Based on the degree of data difference and the level of abnormal risk, it automatically outputs graded acceptance and disposal instructions for normal progress, manual review, restricted unloading, and refusal of entry.

6. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: The dynamic quality inspection and acceptance module combines fuel type and specifications, supplier pre-risk level, historical fuel quality fluctuation data, contract and enterprise internal control acceptance standards, and abnormal situations during initial on-site verification. It abandons fixed acceptance rules and uses a dynamic acceptance rule engine to adaptively adjust the sampling ratio, quality inspection items, and intensity of manual review for this fuel sampling. It automatically upgrades the acceptance and control standards to be stricter for high-risk suppliers, vehicles with abnormal verification, and fuel batches with large quality fluctuations. Based on dynamically adjusted parameters, it automatically generates dedicated tasks for sampling and quality inspection, records the original data of the entire process of sampling, testing, and preliminary judgment, and compares the actual quality inspection results with contract standards, enterprise internal control standards, and industry regulatory thresholds in multiple dimensions through a rule engine. Finally, it automatically outputs differentiated quality acceptance judgment results such as qualified acceptance, concessionary acceptance, deduction of quantity and price, re-inspection and verification, and rejection of the whole vehicle.

7. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: In the unloading and warehousing control module, after the fuel passes the entry verification and quality acceptance, the system automatically generates the optimal unloading scheduling and warehousing positioning instructions based on the fuel type, quality inspection level, storage capacity of the stockpile, and availability of equipment and site in the unloading area. The unique digital identification code of the fuel batch is deeply bound to the unloading location, warehousing weight, inventory status, and subsequent consumption destination. After the vehicle unloads, the empty vehicle tare weight is re-measured to accurately calculate the net weight of the fuel and perform weight closure verification with the waybill, procurement plan, and warehousing measurement data. For special circulation scenarios such as fuel splitting and warehousing, mixed warehousing, transfer and relocation, re-inspection and return, and quality grade change, the system automatically generates parent and child batches, mixed batches and status evolution relationships, completely retains the original batch ledger records, and builds a continuous and uninterrupted batch identity evolution traceability chain to eliminate control loopholes such as unclear source, unknown sample, inventory gap, and inconsistent settlement basis during the fuel circulation process.

8. The fuel entry acceptance and data association monitoring system according to claim 1, characterized in that: In the aforementioned closed-loop evidence supervision module, the fuel batch digital identity code is used as the core associated primary key to collect the entire process operation records, including appointment registration, vehicle identification, weighbridge weighing, waybill verification, seal verification, sampling and quality inspection, unloading and warehousing, abnormal handling, and settlement suggestions. This forms a complete closed-loop evidence chain for fuel entry and acceptance that is fully traceable, tamper-proof, and retrievable at any time.

9. A method for full-process acceptance and data association monitoring of fuel entry, used in the full-process acceptance and data association monitoring system for fuel entry as described in any one of claims 1-8, characterized in that: Includes the following steps: S1. Before vehicles enter the site, collect relevant information on procurement, suppliers, transportation and contract acceptance, calculate the risk level by combining the supplier's historical performance and transportation risk data, and pre-set differentiated pre-acceptance strategies based on the risk level to achieve proactive risk prediction before entering the site. S2. After the fuel vehicle enters the weighbridge area, the weighing data is collected in real time and the data stability is judged. After the data is stable, the vehicle, license plate, seal, waybill identification and gross weight locking are completed simultaneously. When abnormalities are detected in the vehicle, weighbridge, seal, etc., the acceptance is suspended and an abnormality prompt is triggered. After the weighing and basic identification are completed, a unique digital identity code for the fuel batch is generated as a unified traceability index for the whole process. Consistency verification is carried out on multi-source data such as vehicle, waybill, seal, weight, etc., and the corresponding acceptance and disposal method is determined according to data matching and risk situation. S3. Based on the supplier's risk level, historical fluctuations in fuel quality, contract acceptance standards, and abnormal situations during on-site verification, dynamically adjust the sampling and quality inspection intensity and execute sampling and quality inspection operations. Compare the measured data with the acceptance standards at all levels, output the quality acceptance judgment results, and after the fuel passes the acceptance test, issue unloading instructions in combination with inventory and unloading conditions. Bind the batch digital identity code and the warehousing flow data. After unloading, remeasure the tare weight to calculate the net weight and complete the weight closure verification. Build a batch identity evolution traceability chain for various fuel flow change scenarios. S4. Use batch digital identification codes as the link to collect the entire process of acceptance records to form a complete chain of evidence.

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