CN118776614A - A fuel storage monitoring system - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 171
- 239000000446 fuel Substances 0.000 title description 17
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- 238000007726 management method Methods 0.000 claims description 22
- 238000000034 method Methods 0.000 claims description 9
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 6
- 239000001301 oxygen Substances 0.000 claims description 6
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Abstract
本发明涉及仓储监测技术领域，具体公开了一种油料仓储监测系统，包括油料仓储监测区域划分模块、物联网感知模块、油料数据预处理模块、油料数据分析模块、油料数据综合分析模块、仓储管理判断模块、自动化控制模块，以及AR显示终端模块；本发明通过部署在油料仓储设施中的传感器网络，实时监测并采集温度、压力、气体浓度，以及液位参数，解决了数据采集滞后的问题；本发明结合了物联网技术和自动化管理，实现了对油料仓储环境的全方位、高精度的实时监测与智能分析，降低了人力成本，有效提升了油料仓储的安全性和管理效率。
The present invention relates to the field of storage monitoring technology, and specifically discloses an oil storage monitoring system, comprising an oil storage monitoring area division module, an Internet of Things perception module, an oil data preprocessing module, an oil data analysis module, an oil data comprehensive analysis module, a storage management judgment module, an automatic control module, and an AR display terminal module; the present invention monitors and collects temperature, pressure, gas concentration, and liquid level parameters in real time through a sensor network deployed in an oil storage facility, thereby solving the problem of data collection lag; the present invention combines the Internet of Things technology with automatic management, realizes all-round, high-precision real-time monitoring and intelligent analysis of the oil storage environment, reduces labor costs, and effectively improves the safety and management efficiency of oil storage.
Description
技术领域Technical Field
本发明涉及仓储监测技术领域，尤其涉及一种油料仓储监测系统。The present invention relates to the technical field of storage monitoring, and in particular to an oil storage monitoring system.
背景技术Background Art
油料仓储是石油产业链中不可或缺的一环，其安全、高效的管理直接关系到石油资源的合理利用以及环境安全。随着全球能源需求的持续增长，油料仓储规模不断扩大，管理难度也随之加大。Oil storage is an indispensable part of the oil industry chain. Its safe and efficient management is directly related to the rational use of oil resources and environmental safety. With the continuous growth of global energy demand, the scale of oil storage continues to expand, and the difficulty of management is also increasing.
传统油料存储监测主要依赖人工巡查和各类仪表监测，包括定期目视检查浮子式液位计、温度计、压力表等以获取液位、温度和压力数据；并通过手工采样进行油品质量、水分、杂质等理化属性分析。另外，配备单点报警系统，如液位超限报警或温度异常报警，以及基本的本地控制系统，如温控设备和泵机启停控制。这些方法均为现场直接监测，数据传递依赖人工记录和局部控制，具有直观、简易的特点，易于现场操作和初步判读的优点。Traditional oil storage monitoring mainly relies on manual inspections and various instrument monitoring, including regular visual inspections of float-type level gauges, thermometers, pressure gauges, etc. to obtain liquid level, temperature and pressure data; and manual sampling to analyze physical and chemical properties such as oil quality, moisture, impurities, etc. In addition, it is equipped with a single-point alarm system, such as liquid level over-limit alarm or temperature abnormality alarm, as well as basic local control systems such as temperature control equipment and pump start and stop control. These methods are all direct on-site monitoring, and data transmission relies on manual recording and local control. They are intuitive and simple, and easy to operate on-site and have the advantages of preliminary interpretation.
但是其在实际使用时，仍旧存在一些缺点，如传统油料存储监测技术依赖人工观测和记录，存在效率低、实时性差的问题，液位、温度、压力等数据更新慢，无法做到连续监测和远程传输，导致预警滞后；人工采样分析周期长、成本高，不能实时反映油料品质变化；单点报警系统功能有限，缺乏全面风险评估。此外，传统方法难以实现大规模、多点集中管理，且易受人为误差影响，不利于精细化管理和风险控制。However, there are still some shortcomings in its actual use. For example, traditional oil storage monitoring technology relies on manual observation and recording, which has problems of low efficiency and poor real-time performance. The data of liquid level, temperature, pressure, etc. are updated slowly, and continuous monitoring and remote transmission cannot be achieved, resulting in delayed warning. The manual sampling and analysis cycle is long and costly, and it cannot reflect the changes in oil quality in real time. The single-point alarm system has limited functions and lacks comprehensive risk assessment. In addition, traditional methods are difficult to achieve large-scale, multi-point centralized management, and are easily affected by human errors, which is not conducive to refined management and risk control.
传统的油料仓储管理方式已难以满足现代仓储的需求，因此，开发一种新型的油料仓储监测系统成为行业内的迫切需求。The traditional oil storage management method can no longer meet the needs of modern storage. Therefore, the development of a new type of oil storage monitoring system has become an urgent need in the industry.
发明内容Summary of the invention
为了克服现有技术的上述缺陷，本发明的实施例提供一种油料仓储监测系统，以解决上述背景技术中提出的问题。In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an oil storage monitoring system to solve the problems raised in the above-mentioned background technology.
为实现上述目的，本发明提供如下技术方案：一种油料仓储监测系统，包括油料仓储监测区域划分模块、物联网感知模块、油料数据预处理模块、油料数据分析模块、油料数据综合分析模块、仓储管理判断模块、自动化控制模块，以及AR显示终端模块。To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an oil storage monitoring system, comprising an oil storage monitoring area division module, an Internet of Things perception module, an oil data preprocessing module, an oil data analysis module, an oil data comprehensive analysis module, a storage management judgment module, an automation control module, and an AR display terminal module.
油料仓储监测区域划分模块：用于将目标油料仓储区确定为目标监测区域，按照油料仓储区内油料储罐的数量划分方式划分成各监测子区域，每个油料储罐作为一个监测子区域，并将各监测子区域依次编号为1，2，...，i，...，n；Oil storage monitoring area division module: used to determine the target oil storage area as the target monitoring area, and divide it into monitoring sub-areas according to the number of oil storage tanks in the oil storage area. Each oil storage tank is used as a monitoring sub-area, and the monitoring sub-areas are numbered 1, 2, ..., i, ..., n in sequence;
物联网感知模块：用于通过部署在油料仓储设施中的传感器，包括温度传感器、压力传感器、气体浓度传感器，以及液位传感器，组成物联网传感器网络，实时采集各监测子区域油料仓储环境中的综合数据，包括油料温度参数、油料压力参数、油料气体浓度参数，以及油料液位参数，并将各监测子区域的综合数据传输至油料数据预处理模块；IoT sensing module: used to form an IoT sensor network through sensors deployed in oil storage facilities, including temperature sensors, pressure sensors, gas concentration sensors, and liquid level sensors, to collect comprehensive data in the oil storage environment of each monitoring sub-area in real time, including oil temperature parameters, oil pressure parameters, oil gas concentration parameters, and oil liquid level parameters, and transmit the comprehensive data of each monitoring sub-area to the oil data preprocessing module;
油料数据预处理模块：用于将所述物联网感知模块采集到的综合数据进行预处理，并将预处理后的数据传输至油料数据分析模块；Oil data preprocessing module: used to preprocess the comprehensive data collected by the Internet of Things sensing module, and transmit the preprocessed data to the oil data analysis module;
油料数据分析模块：包括油料温度系数计算单元、油料压力系数计算单元、油料气体浓度系数计算单元，以及油料液位系数计算单元；所述油料温度系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料温度参数得到各监测子区域的油料温度系数；所述油料压力系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料压力参数得到各监测子区域的油料压力系数；所述油料气体浓度系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料气体浓度参数得到各监测子区域的油料气体浓度系数；所述油料液位系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料液位参数得到各监测子区域的油料液位系数；并将计算得到的油料温度系数、油料压力系数、油料气体浓度系数，以及油料液位系数传输至油料数据综合分析模块；Oil data analysis module: including an oil temperature coefficient calculation unit, an oil pressure coefficient calculation unit, an oil gas concentration coefficient calculation unit, and an oil level coefficient calculation unit; the oil temperature coefficient calculation unit is used to calculate the oil temperature parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil temperature coefficient of each monitoring sub-area; the oil pressure coefficient calculation unit is used to calculate the oil pressure parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil pressure coefficient of each monitoring sub-area; the oil gas concentration coefficient calculation unit is used to calculate the oil gas concentration parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil gas concentration coefficient of each monitoring sub-area; the oil level coefficient calculation unit is used to calculate the oil level parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil level coefficient of each monitoring sub-area; and the calculated oil temperature coefficient, oil pressure coefficient, oil gas concentration coefficient, and oil level coefficient are transmitted to the oil data comprehensive analysis module;
油料数据综合分析模块：用于将所述油料数据分析模块计算得到的油料温度系数、油料压力系数、油料气体浓度系数，以及油料液位系数导入到油料安全影响权重综合指数计算模型中，计算得到油料安全影响权重综合指数，并将所述油料安全影响权重综合指数传输至仓储管理判断模块；Fuel data comprehensive analysis module: used to import the fuel temperature coefficient, fuel pressure coefficient, fuel gas concentration coefficient, and fuel level coefficient calculated by the fuel data analysis module into the fuel safety impact weight comprehensive index calculation model, calculate the fuel safety impact weight comprehensive index, and transmit the fuel safety impact weight comprehensive index to the warehouse management judgment module;
仓储管理判断模块：用于将所述油料数据综合分析模块计算得到的油料安全影响权重综合指数与安全影响权重综合指数预设值进行对比，得出判断结果，并将所述判断结果传输至AR显示终端模块；Warehouse management judgment module: used to compare the comprehensive index of oil safety impact weight calculated by the comprehensive analysis module of oil data with the preset value of the comprehensive index of safety impact weight, obtain a judgment result, and transmit the judgment result to the AR display terminal module;
自动化控制模块：用于接收各监测子区域的监测数据，并根据预设的控制策略，自动调节油料仓储环境条件，自动调整温控设备、压力控制设备、储罐的进出油阀，以及泵设备的工作状态，实现油料仓储的自动化管理；Automation control module: used to receive monitoring data from each monitoring sub-area, and automatically adjust the oil storage environment conditions according to the preset control strategy, automatically adjust the temperature control equipment, pressure control equipment, the inlet and outlet valves of the storage tank, and the working status of the pump equipment to realize the automated management of oil storage;
AR显示终端模块：用于接收并显示油料仓储环境中的实时数据、分析报告、以及现实作业场景，并形成直观的三维可视化界面，供作业人员或管理人员进行实时监控、决策与指导。AR display terminal module: used to receive and display real-time data, analysis reports, and realistic operation scenarios in the oil storage environment, and form an intuitive three-dimensional visualization interface for operators or managers to conduct real-time monitoring, decision-making and guidance.
优选的，所述油料温度参数包括各监测子区域任一时间点的油料温度以及各监测子区域间隔时间t后的油料温度；Preferably, the oil temperature parameters include the oil temperature of each monitoring sub-area at any time point and the oil temperature of each monitoring sub-area after an interval of time t;
所述油料压力参数包括各监测子区域的油料储罐外部压力值以及各监测子区域的油料储罐内部压力值；The oil pressure parameters include the external pressure value of the oil storage tank in each monitoring sub-area and the internal pressure value of the oil storage tank in each monitoring sub-area;
所述油料气体浓度参数包括各监测子区域的甲醇浓度含量以及各监测子区域的氧气浓度含量；The oil gas concentration parameters include the methanol concentration content of each monitoring sub-area and the oxygen concentration content of each monitoring sub-area;
所述油料液位参数包括各监测子区域的油料输出量以及各监测子区域的油料输入量。The oil level parameters include the oil output of each monitoring sub-area and the oil input of each monitoring sub-area.
优选的，所述各监测子区域的油料温度系数具体计算模型如下：，其中，表示第i个监测子区域的油料温度系数，表示第i个监测子区域任一时间点的油料温度，表示第i个监测子区域间隔时间t后的油料温度，表示为预设的油料温度在监测过程中的允许温度误差值，分别表示为预设的温度误差影响因子；需要具体说明的是，通过物联网感知模块采集到不同时间点的温度值，通过和之间的温度变化率，以反映油料温度的动态变化；Preferably, the specific calculation model of the oil temperature coefficient of each monitoring sub-area is as follows: ,in, represents the oil temperature coefficient of the ith monitoring sub-area, represents the oil temperature at any time point in the i-th monitoring sub-area, represents the oil temperature of the i-th monitoring sub-area after the interval t, It is expressed as the allowable temperature error value of the preset oil temperature during the monitoring process. They are respectively represented as the preset temperature error influencing factors; it should be specifically noted that the temperature values at different time points are collected by the IoT sensing module. and The temperature change rate between the two to reflect the dynamic change of oil temperature;
优选的，所述各监测子区域的油料压力系数具体计算模型如下：表示第i个监测子区域的油料压力系数，表示第i个监测子区域油料仓储区油料储罐的外部压力值，表示第i个监测子区域油料仓储区油料储罐的内部压力值，表示第i个监测子区域当前的压力值，α表示油料压力系数的其他影响因子；Preferably, the specific calculation model of the oil pressure coefficient of each monitoring sub-area is as follows: represents the oil pressure coefficient of the ith monitoring sub-area, represents the external pressure value of the oil storage tank in the oil storage area of the i-th monitoring sub-area, represents the internal pressure value of the oil storage tank in the oil storage area of the i-th monitoring sub-area, represents the current pressure value of the i-th monitoring sub-area, α represents other influencing factors of the oil pressure coefficient;
优选的，所述各监测子区域的油料气体浓度系数具体计算模型如下：，其中，表示第i个监测子区域的气体浓度系数，表示第i个监测子区域的甲醇浓度，表示第i个监测子区域的氧气浓度，表示甲醇浓度含量的其他影响因子，表示甲醇浓度含量的其他影响因子，表示油料气体浓度的其他影响因子；Preferably, the specific calculation model of the oil gas concentration coefficient of each monitoring sub-area is as follows: ,in, represents the gas concentration coefficient of the i-th monitoring sub-area, represents the methanol concentration in the ith monitoring sub-area, represents the oxygen concentration in the ith monitoring sub-area, Other factors affecting methanol concentration, Other factors affecting methanol concentration, Other factors affecting the oil gas concentration;
优选的，所述各监测子区域的油料液位系数具体计算模型如下：，其中，表示第i个监测子区域的油料液位系数，表示第i个监测子区域的油料输出速率，表示第i个监测子区域的油料输入速率，t表示时间，表示油料速率的其他影响因子，表示油料液位系数的其他影响因子。Preferably, the specific calculation model of the oil level coefficient of each monitoring sub-area is as follows: ,in, represents the oil level coefficient of the ith monitoring sub-area, represents the oil output rate of the ith monitoring sub-area, represents the oil input rate of the ith monitoring sub-area, t represents the time, Represents other influencing factors of oil rate, Represents other influencing factors of the oil level coefficient.
优选的，所述各监测子区域的油料安全影响权重综合指数具体计算模型如下：，其中，表示第i个监测子区域的油料安全影响权重综合指数，表示第i个监测子区域的油料温度系数，表示第i个监测子区域的油料压力系数，表示第i个监测子区域的气体浓度系数，表示第i个监测子区域的油料液位系数，表示油料安全影响权重综合指数的其他影响因子。Preferably, the specific calculation model of the comprehensive index of oil safety impact weight of each monitoring sub-area is as follows: ,in, represents the comprehensive index of oil safety impact weight in the ith monitoring sub-area, represents the oil temperature coefficient of the ith monitoring sub-area, represents the oil pressure coefficient of the ith monitoring sub-area, represents the gas concentration coefficient of the i-th monitoring sub-area, represents the oil level coefficient of the ith monitoring sub-area, Represents other influencing factors of the comprehensive index of oil safety impact weight.
优选的，所述安全影响权重综合指数预设值表示为，当时，表示第i个监测子区域的油料安全影响权重综合指数大于安全影响权重综合指数预设值，说明第i个监测子区域的油料仓储环境安全性良好，则保持对各监测子区域的数据采集和分析；时，表示第i个监测子区域的油料安全影响权重综合指数小于安全影响权重综合指数预设值，说明第i个监测子区域的油料仓储环境安全性差，则将第i个监测子区域的数据生成分析报告并发出预警信号。Preferably, the preset value of the comprehensive index of safety impact weight is expressed as ,when When , it means that the comprehensive index of oil safety impact weight in the ith monitoring sub-area is greater than the preset value of the comprehensive index of safety impact weight, indicating that the oil storage environment safety in the ith monitoring sub-area is good, and the data collection and analysis of each monitoring sub-area should be maintained; When , it means that the comprehensive index of oil safety impact weight in the ith monitoring sub-area is less than the preset value of the comprehensive index of safety impact weight, indicating that the oil storage environment safety in the ith monitoring sub-area is poor, then the data of the ith monitoring sub-area will be generated into an analysis report and an early warning signal will be issued.
本发明的技术效果和优点：Technical effects and advantages of the present invention:
本发明通过部署在油料仓储设施中的传感器网络，实时监测并采集温度、压力、气体浓度，以及液位参数，解决了数据采集滞后的问题；The present invention solves the problem of data collection lag by deploying a sensor network in the oil storage facility to monitor and collect temperature, pressure, gas concentration, and liquid level parameters in real time;
本发明结合了物联网技术和自动化管理，实现了对油料仓储环境的全方位、高精度的实时监测与智能分析，降低了人力成本，有效提升了油料仓储的安全性和管理效率；The present invention combines Internet of Things technology and automated management to achieve all-round, high-precision real-time monitoring and intelligent analysis of the oil storage environment, reducing labor costs and effectively improving the safety and management efficiency of oil storage;
本发明通过实时监测和预警，有效预防重大安全事故的发生，减少油料损失和环境污染，同时提高油料利用率，为企业带来显著的经济效益和社会效益。The present invention can effectively prevent the occurrence of major safety accidents through real-time monitoring and early warning, reduce oil losses and environmental pollution, and improve oil utilization, thus bringing significant economic and social benefits to enterprises.
附图说明BRIEF DESCRIPTION OF THE DRAWINGS
利用附图对本发明作进一步说明，但附图中的实施例不构成对本发明的任何限制，对于本领域的普通技术人员，在不付出创造性劳动的前提下，还可以根据以下附图获得其它的附图。The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.
图1为本发明的整体系统结构示意图。FIG1 is a schematic diagram of the overall system structure of the present invention.
具体实施方式DETAILED DESCRIPTION
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
请参阅图1所示，本发明提供一种油料仓储监测系统，包括油料仓储监测区域划分模块、物联网感知模块、油料数据预处理模块、油料数据分析模块、油料数据综合分析模块、仓储管理判断模块、自动化控制模块，以及AR显示终端模块。Please refer to Figure 1, the present invention provides an oil storage monitoring system, including an oil storage monitoring area division module, an Internet of Things perception module, an oil data preprocessing module, an oil data analysis module, an oil data comprehensive analysis module, a storage management judgment module, an automation control module, and an AR display terminal module.
所述油料仓储监测区域划分模块输出端与物联网感知模块输入端电信连接，所述物联网感知模块输出端与油料数据预处理模块输入端电信连接，所述油料数据预处理模块输出端与油料数据分析模块输入端电信连接，所述油料数据分析模块输出端与油料数据综合分析模块输入端电信连接，所述油料数据综合分析模块输出端与仓储管理判断模块输入端电信连接，所述仓储管理判断模块输出端与自动化控制模块输入端电信连接，所述AR显示终端模块输入端分别与物联网感知模块输出端以及仓储管理判断模块输出端电信连接。The output end of the oil storage monitoring area division module is connected to the input end of the Internet of Things perception module by telecommunication, the output end of the Internet of Things perception module is connected to the input end of the oil data preprocessing module by telecommunication, the output end of the oil data preprocessing module is connected to the input end of the oil data analysis module by telecommunication, the output end of the oil data analysis module is connected to the input end of the oil data comprehensive analysis module by telecommunication, the output end of the oil data comprehensive analysis module is connected to the input end of the warehouse management judgment module by telecommunication, the output end of the warehouse management judgment module is connected to the input end of the automation control module by telecommunication, and the input end of the AR display terminal module is respectively connected to the output end of the Internet of Things perception module and the output end of the warehouse management judgment module.
油料仓储监测区域划分模块：用于将目标油料仓储区确定为目标监测区域，按照油料仓储区内油料储罐的数量划分方式划分成各监测子区域，每个油料储罐作为一个监测子区域，并将各监测子区域依次编号为1，2，...，i，...，n；Oil storage monitoring area division module: used to determine the target oil storage area as the target monitoring area, and divide it into monitoring sub-areas according to the number of oil storage tanks in the oil storage area. Each oil storage tank is used as a monitoring sub-area, and the monitoring sub-areas are numbered 1, 2, ..., i, ..., n in sequence;
物联网感知模块：用于通过部署在油料仓储设施中的传感器，包括温度传感器、压力传感器、气体浓度传感器，以及液位传感器，组成物联网传感器网络，实时采集各监测子区域油料仓储环境中的综合数据，包括油料温度参数、油料压力参数、油料气体浓度参数，以及油料液位参数，并将各监测子区域的综合数据传输至油料数据预处理模块；IoT sensing module: used to form an IoT sensor network through sensors deployed in oil storage facilities, including temperature sensors, pressure sensors, gas concentration sensors, and liquid level sensors, to collect comprehensive data in the oil storage environment of each monitoring sub-area in real time, including oil temperature parameters, oil pressure parameters, oil gas concentration parameters, and oil liquid level parameters, and transmit the comprehensive data of each monitoring sub-area to the oil data preprocessing module;
本实施例中，需要具体说明的是，所述油料温度参数包括各监测子区域任一时间点的油料温度以及各监测子区域间隔时间t后的油料温度；In this embodiment, it should be specifically explained that the oil temperature parameter includes the oil temperature of each monitoring sub-area at any time point and the oil temperature of each monitoring sub-area after an interval of time t;
所述油料压力参数包括各监测子区域的油料储罐外部压力值以及各监测子区域的油料储罐内部压力值；The oil pressure parameters include the external pressure value of the oil storage tank in each monitoring sub-area and the internal pressure value of the oil storage tank in each monitoring sub-area;
所述油料气体浓度参数包括各监测子区域的甲醇浓度含量以及各监测子区域的氧气浓度含量；The oil gas concentration parameters include the methanol concentration content of each monitoring sub-area and the oxygen concentration content of each monitoring sub-area;
所述油料液位参数包括各监测子区域的油料输出量以及各监测子区域的油料输入量；The oil level parameters include the oil output of each monitoring sub-area and the oil input of each monitoring sub-area;
油料数据预处理模块：用于将所述物联网感知模块采集到的综合数据进行预处理，并将预处理后的数据传输至油料数据分析模块；Oil data preprocessing module: used to preprocess the comprehensive data collected by the Internet of Things sensing module, and transmit the preprocessed data to the oil data analysis module;
所述油料数据预处理模块中的预处理方式包括去噪、异常值检测，以及异常值处理；The preprocessing methods in the oil data preprocessing module include denoising, outlier detection, and outlier processing;
油料数据分析模块：包括油料温度系数计算单元、油料压力系数计算单元、油料气体浓度系数计算单元，以及油料液位系数计算单元；所述油料温度系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料温度参数得到各监测子区域的油料温度系数；所述油料压力系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料压力参数得到各监测子区域的油料压力系数；所述油料气体浓度系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料气体浓度参数得到各监测子区域的油料气体浓度系数；所述油料液位系数计算单元用于计算所述油料数据预处理模块中预处理后获取的油料液位参数得到各监测子区域的油料液位系数；并将计算得到的油料温度系数、油料压力系数、油料气体浓度系数，以及油料液位系数传输至油料数据综合分析模块；Oil data analysis module: including an oil temperature coefficient calculation unit, an oil pressure coefficient calculation unit, an oil gas concentration coefficient calculation unit, and an oil level coefficient calculation unit; the oil temperature coefficient calculation unit is used to calculate the oil temperature parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil temperature coefficient of each monitoring sub-area; the oil pressure coefficient calculation unit is used to calculate the oil pressure parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil pressure coefficient of each monitoring sub-area; the oil gas concentration coefficient calculation unit is used to calculate the oil gas concentration parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil gas concentration coefficient of each monitoring sub-area; the oil level coefficient calculation unit is used to calculate the oil level parameter obtained after preprocessing in the oil data preprocessing module to obtain the oil level coefficient of each monitoring sub-area; and the calculated oil temperature coefficient, oil pressure coefficient, oil gas concentration coefficient, and oil level coefficient are transmitted to the oil data comprehensive analysis module;
本实施例中，需要具体说明的是，所述各监测子区域的油料温度系数具体计算模型如下：，其中，表示第i个监测子区域的油料温度系数，表示第i个监测子区域任一时间点的油料温度，表示第i个监测子区域间隔时间t后的油料温度，表示为预设的油料温度在监测过程中的允许温度误差值，分别表示为预设的温度误差影响因子；需要具体说明的是，通过物联网感知模块采集到不同时间点的温度值，通过Tt i 1 和Tt i 2 之间的温度变化率，以反映油料温度的动态变化；In this embodiment, it should be specifically explained that the specific calculation model of the oil temperature coefficient of each monitoring sub-area is as follows: ,in, represents the oil temperature coefficient of the ith monitoring sub-area, represents the oil temperature at any time point in the i-th monitoring sub-area, represents the oil temperature of the i-th monitoring sub-area after the interval t, It is expressed as the allowable temperature error value of the preset oil temperature during the monitoring process. They are respectively represented as the preset temperature error influencing factors; it should be specifically noted that the temperature values at different time points are collected by the IoT sensing module, and the temperature change rate between Tt i 1 and Tt i 2 is used to reflect the dynamic change of the oil temperature;
本实施例中，需要具体说明的是，所述各监测子区域的油料压力系数具体计算模型如下：，其中，表示第i个监测子区域的油料压力系数，表示第i个监测子区域油料仓储区油料储罐的外部压力值，表示第i个监测子区域油料仓储区油料储罐的内部压力值，表示第i个监测子区域当前的压力值，表示油料压力系数的其他影响因子；In this embodiment, it should be specifically explained that the specific calculation model of the oil pressure coefficient of each monitoring sub-area is as follows: ,in, represents the oil pressure coefficient of the ith monitoring sub-area, represents the external pressure value of the oil storage tank in the oil storage area of the i-th monitoring sub-area, represents the internal pressure value of the oil storage tank in the oil storage area of the i-th monitoring sub-area, Indicates the current pressure value of the i-th monitoring sub-area, Other factors affecting the oil pressure coefficient;
本实施例中，需要具体说明的是，所述各监测子区域的油料气体浓度系数具体计算模型如下：，其中，表示第i个监测子区域的气体浓度系数，表示第i个监测子区域的甲醇浓度，表示第i个监测子区域的氧气浓度，表示甲醇浓度含量的其他影响因子，表示甲醇浓度含量的其他影响因子，表示油料气体浓度的其他影响因子；In this embodiment, it should be specifically explained that the specific calculation model of the oil gas concentration coefficient of each monitoring sub-area is as follows: ,in, represents the gas concentration coefficient of the i-th monitoring sub-area, represents the methanol concentration in the ith monitoring sub-area, represents the oxygen concentration in the ith monitoring sub-area, Other factors affecting methanol concentration, Other factors affecting methanol concentration, Other factors affecting the oil gas concentration;
本实施例中，需要具体说明的是，所述各监测子区域的油料液位系数具体计算模型如下：，其中，表示第i个监测子区域的油料液位系数，表示第i个监测子区域的油料输出速率，表示第i个监测子区域的油料输入速率，t表示时间，表示油料速率的其他影响因子，表示油料液位系数的其他影响因子；In this embodiment, it should be specifically explained that the specific calculation model of the oil level coefficient of each monitoring sub-area is as follows: ,in, represents the oil level coefficient of the ith monitoring sub-area, represents the oil output rate of the ith monitoring sub-area, represents the oil input rate of the ith monitoring sub-area, t represents the time, Represents other influencing factors of oil rate, Indicates other influencing factors of the oil level coefficient;
油料数据综合分析模块：用于将所述油料数据分析模块计算得到的油料温度系数、油料压力系数、油料气体浓度系数，以及油料液位系数导入到油料安全影响权重综合指数计算模型中，计算得到油料安全影响权重综合指数，并将所述油料安全影响权重综合指数传输至仓储管理判断模块；Fuel data comprehensive analysis module: used to import the fuel temperature coefficient, fuel pressure coefficient, fuel gas concentration coefficient, and fuel level coefficient calculated by the fuel data analysis module into the fuel safety impact weight comprehensive index calculation model, calculate the fuel safety impact weight comprehensive index, and transmit the fuel safety impact weight comprehensive index to the warehouse management judgment module;
本实施例中，需要具体说明的是，所述各监测子区域的油料安全影响权重综合指数具体计算模型如下：，其中，表示第i个监测子区域的油料安全影响权重综合指数，表示第i个监测子区域的油料温度系数，表示第i个监测子区域的油料压力系数，表示第i个监测子区域的气体浓度系数，表示第i个监测子区域的油料液位系数，表示油料安全影响权重综合指数的其他影响因子；In this embodiment, it should be specifically explained that the specific calculation model of the comprehensive index of oil safety impact weight of each monitoring sub-area is as follows: ,in, represents the comprehensive index of oil safety impact weight in the ith monitoring sub-area, represents the oil temperature coefficient of the ith monitoring sub-area, represents the oil pressure coefficient of the ith monitoring sub-area, represents the gas concentration coefficient of the i-th monitoring sub-area, represents the oil level coefficient of the ith monitoring sub-area, Other influencing factors representing the comprehensive index of oil safety impact weight;
仓储管理判断模块：用于将所述油料数据综合分析模块计算得到的油料安全影响权重综合指数与安全影响权重综合指数预设值进行对比，得出判断结果，并将所述判断结果传输至AR显示终端模块；Warehouse management judgment module: used to compare the comprehensive index of oil safety impact weight calculated by the comprehensive analysis module of oil data with the preset value of the comprehensive index of safety impact weight, obtain a judgment result, and transmit the judgment result to the AR display terminal module;
本实施例中，需要具体说明的是，所述安全影响权重综合指数预设值表示为，当时，表示第i个监测子区域的油料安全影响权重综合指数大于安全影响权重综合指数预设值，说明第i个监测子区域的油料仓储环境安全性良好，则保持对各监测子区域的数据采集和分析；时，表示第i个监测子区域的油料安全影响权重综合指数小于安全影响权重综合指数预设值，说明第i个监测子区域的油料仓储环境安全性差，则将第i个监测子区域的数据生成分析报告并发出预警信号；In this embodiment, it should be specifically explained that the preset value of the comprehensive index of safety impact weight is expressed as ,when When , it means that the comprehensive index of oil safety impact weight in the ith monitoring sub-area is greater than the preset value of the comprehensive index of safety impact weight, indicating that the oil storage environment safety in the ith monitoring sub-area is good, and the data collection and analysis of each monitoring sub-area should be maintained; When , it means that the comprehensive index of oil safety impact weight in the ith monitoring sub-area is less than the preset value of the comprehensive index of safety impact weight, indicating that the oil storage environment safety in the ith monitoring sub-area is poor, then the data of the ith monitoring sub-area is generated into an analysis report and an early warning signal is issued;
自动化控制模块：用于接收各监测子区域的监测数据，并根据预设的控制策略，自动调节油料仓储环境条件，自动调整温控设备、压力控制设备、储罐的进出油阀，以及泵设备的工作状态，实现油料仓储的自动化管理；Automation control module: used to receive monitoring data from each monitoring sub-area, and automatically adjust the oil storage environment conditions according to the preset control strategy, automatically adjust the temperature control equipment, pressure control equipment, the inlet and outlet valves of the storage tank, and the working status of the pump equipment to realize the automated management of oil storage;
AR显示终端模块：用于接收并显示油料仓储环境中的实时数据、分析报告、以及现实作业场景，并形成直观的三维可视化界面，供作业人员或管理人员进行实时监控、决策与指导。AR display terminal module: used to receive and display real-time data, analysis reports, and realistic operation scenarios in the oil storage environment, and form an intuitive three-dimensional visualization interface for operators or managers to conduct real-time monitoring, decision-making and guidance.
本实施例中，需要具体说明的是，本实施与现有技术的区别主要在于本实施例通过设有油料仓储监测区域划分模块、物联网感知模块、油料数据预处理模块、油料数据分析模块、油料数据综合分析模块、仓储管理判断模块、自动化控制模块，以及AR显示终端模块，有利于一种油料仓储监测系统对油料仓储环境的安全判断，通过实时监测和综合分析，判断油料仓储系统安全影响权重情况，采取相应措施进行调整和优化，有助于油料仓储系统的安全性和稳定性。In the present embodiment, it should be specifically explained that the difference between the present embodiment and the prior art lies mainly in that the present embodiment is provided with an oil storage monitoring area division module, an Internet of Things perception module, an oil data preprocessing module, an oil data analysis module, an oil data comprehensive analysis module, a storage management judgment module, an automation control module, and an AR display terminal module, which is conducive to an oil storage monitoring system to judge the safety of the oil storage environment. Through real-time monitoring and comprehensive analysis, the safety impact weight of the oil storage system is judged, and corresponding measures are taken to adjust and optimize, which is conducive to the safety and stability of the oil storage system.
最后：以上所述仅为本发明的优选实施例而已，并不用于限制本发明，凡在本发明的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119178101A (en) * | 2024-11-26 | 2024-12-24 | 山东联合能源管道输送有限公司 | Intelligent monitoring system for storage tank risk early warning |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103163848A (en) * | 2011-12-15 | 2013-06-19 | 长沙市启仁信息技术有限公司 | Intelligent monitoring system and intelligent monitoring method of petroleum product state in petroleum product transportation based on Internet of things |
| CN111811576A (en) * | 2020-07-19 | 2020-10-23 | 智强通达科技（北京）有限公司 | Monitoring and warning integrated equipment for oil storage tank of finished oil |
| WO2021185177A1 (en) * | 2020-03-16 | 2021-09-23 | 福建省特种设备检验研究院 | Method for evaluating health status of petrochemical atmospheric oil storage tank using data from multiple sources |
| CN114615250A (en) * | 2022-03-17 | 2022-06-10 | 重庆益尔感知数据研究院有限公司 | Safety monitoring system and monitoring method for oil and gas storage station |
| CN117627627A (en) * | 2023-11-27 | 2024-03-01 | 长江大学 | Intelligent detection method for oil-gas well shaft safety |
| CN118247938A (en) * | 2024-05-21 | 2024-06-25 | 大庆亚兴安全科技股份有限公司 | Active safety early warning system |
-
2024
- 2024-09-10 CN CN202411265447.1A patent/CN118776614B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103163848A (en) * | 2011-12-15 | 2013-06-19 | 长沙市启仁信息技术有限公司 | Intelligent monitoring system and intelligent monitoring method of petroleum product state in petroleum product transportation based on Internet of things |
| WO2021185177A1 (en) * | 2020-03-16 | 2021-09-23 | 福建省特种设备检验研究院 | Method for evaluating health status of petrochemical atmospheric oil storage tank using data from multiple sources |
| CN111811576A (en) * | 2020-07-19 | 2020-10-23 | 智强通达科技（北京）有限公司 | Monitoring and warning integrated equipment for oil storage tank of finished oil |
| CN114615250A (en) * | 2022-03-17 | 2022-06-10 | 重庆益尔感知数据研究院有限公司 | Safety monitoring system and monitoring method for oil and gas storage station |
| CN117627627A (en) * | 2023-11-27 | 2024-03-01 | 长江大学 | Intelligent detection method for oil-gas well shaft safety |
| CN118247938A (en) * | 2024-05-21 | 2024-06-25 | 大庆亚兴安全科技股份有限公司 | Active safety early warning system |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119178101A (en) * | 2024-11-26 | 2024-12-24 | 山东联合能源管道输送有限公司 | Intelligent monitoring system for storage tank risk early warning |
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