CN117875722A - Data management system and method based on intelligent oil depot - Google Patents
Data management system and method based on intelligent oil depot Download PDFInfo
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Abstract
The invention discloses a data management system and a method based on an intelligent oil depot, which particularly relate to the technical field of oil depot management, and realize comprehensive monitoring and early warning of the safety of a conveying system by comprehensively utilizing a leakage detection system, external environment data, valve operation data and crude oil flow data, and effectively divide the conveying environment into risks or normal states by analyzing the frequent degree of leakage safety accidents and the hidden danger degree of pipeline risks; meanwhile, multiple references are provided for early warning through monitoring valve operation data and crude oil flow data, and finally, under the identification risk conveying environment, comprehensive analysis is carried out on pipeline, valve and crude oil stability, so that timely early warning on the safety of a conveying system is realized, potential safety hazards are found in advance, accident risks are reduced, and the safe and stable operation of an intelligent oil depot is guaranteed.
Description
Technical Field
The invention relates to the technical field of oil depot management, in particular to a data management system and method based on an intelligent oil depot.
Background
The intelligent oil depot is a system for intelligent management and monitoring of the oil depot by utilizing advanced information technology and Internet of things technology, and the intelligent oil depot is used for realizing the monitoring and management of the running state, the equipment state, the environmental condition and other aspects of the oil depot by collecting, transmitting and analyzing data in real time, so that the safety, the running efficiency and the management level of the oil depot are improved. The intelligent oil depot comprises a conveying system, wherein the conveying system is a part of the intelligent oil depot, and is responsible for conveying crude oil, petroleum products and the like from a production place to an oil storage tank, processing equipment or a sales terminal, so that the intelligent oil depot is one of key links of operation of the oil depot.
At present, safety monitoring of a conveying system is usually carried out by monitoring data in real time through a sensor, and the safety monitoring system alarms when a safety accident is about to happen, and cannot early warn the safety of the conveying system in advance, so that emergency treatment time is urgent, treatment measures are not timely, and the risk and loss of the accident of the conveying system and even the whole intelligent oil depot are increased.
In order to solve the above problems, a technical solution is now provided.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, embodiments of the present invention provide a data management system and method based on an intelligent oil depot to solve the above-mentioned problems in the prior art.
In order to achieve the above purpose, the present invention provides the following technical solutions:
a data management method based on an intelligent oil depot comprises the following steps:
s1: acquiring the frequency of the leakage safety accidents of the conveying system monitored within a set period of the leakage detection system; acquiring external environment data of a conveying system, and acquiring the risk hidden danger degree of the pipeline according to the external environment data of the conveying system;
s2: dividing the conveying environment of the conveying system into a risk conveying environment or a normal conveying environment according to the frequency degree of the leakage safety accidents of the conveying system and the hidden danger degree of the pipeline, which are monitored in the set period of the leakage detection system;
S3: acquiring valve operation data of a conveying system, and acquiring the stability degree of a valve of the conveying system based on the valve operation data of the conveying system;
s4: acquiring flow data of crude oil in a conveying system, and obtaining the stability degree of the crude oil in the conveying system based on the flow data of the crude oil in the conveying system;
s5: when the conveying environment of the conveying system is a risk conveying environment, comprehensively analyzing the hidden danger degree of the pipeline risk, the stability degree of a valve of the conveying system and the stability degree of crude oil in the conveying system, and pre-warning the operation safety of the conveying system.
In a preferred embodiment, in S1, the frequency of the leakage safety accidents of the conveying system monitored within the set period of the leakage detection system is obtained, specifically:
setting a leakage monitoring period; the method comprises the steps of obtaining the occurrence times of the leakage safety accidents of the conveying system in a leakage monitoring period, and marking the ratio of the occurrence times of the leakage safety accidents of the conveying system in the leakage monitoring period to the time length corresponding to the leakage monitoring period as a conveying leakage risk frequency value.
In a preferred embodiment, the real-time delivery ambient data of the delivery system includes temperature data; the temperature data are temperature values of the environment outside the pipeline of the conveying system;
Setting a temperature data observation interval; a plurality of temperature values are uniformly acquired in a temperature data observation interval, the temperature values in the temperature data observation interval are numbered, the degree of deviation of the temperature values in the temperature data observation interval from a safe temperature value is analyzed, and a temperature deviation hidden danger value is calculated, wherein the expression is as follows:wherein->For the temperature deviation hidden trouble value +.>Is the +.>Temperature value->For safe temperature value, < >>For the corresponding time length of the temperature data observation interval, < >>The number of temperature values in the temperature data observation interval and the number of temperature values in the temperature data observation interval are respectively +.>，/>Are integers greater than 1.
In a preferred embodiment, in S2, a transport leakage risk frequency threshold is set, and the transport leakage risk frequency value is compared with the transport leakage risk frequency threshold:
when the conveying leakage risk frequency value is larger than the conveying leakage risk frequency threshold value, generating a leakage frequency high signal; when the conveying leakage risk frequency value is smaller than or equal to the conveying leakage risk frequency threshold value, generating a leakage frequency normal signal;
setting a temperature deviation hidden danger threshold value, and comparing the temperature deviation hidden danger value with the temperature deviation hidden danger threshold value:
When the temperature deviation hidden danger value is larger than the temperature deviation hidden danger threshold value, generating a temperature deviation hidden danger signal; when the temperature deviation hidden danger value is smaller than or equal to the temperature deviation hidden danger threshold value, generating a temperature deviation hidden danger normal signal;
dividing the conveying environment of the conveying system into risk conveying environments as long as one of a leakage frequency high signal or a temperature deviation hidden danger high signal is generated; otherwise, the conveying environment of the conveying system is divided into normal conveying environments.
In a preferred embodiment, in S3, the valve operation data comprises real-time pressure data of the valve;
setting a valve pressure monitoring interval; uniformly acquiring a plurality of valve pressure values in a valve pressure monitoring interval;
the method comprises the steps of obtaining an optimal safety valve pressure value, numbering the valve pressure value in a valve pressure monitoring interval, analyzing the degree of deviation of the valve pressure value in the valve pressure monitoring interval from the optimal safety valve pressure value, and calculating a valve pressure health index, wherein the expression is as follows:wherein->Is valve pressure health index>Is the valve pressure monitoring interval +.>Valve pressure value->For the optimal safety valve pressure value->For the corresponding time length of the valve pressure monitoring interval, < > >The number of valve pressure values in the valve pressure monitoring interval and the number of valve pressure values in the valve pressure monitoring interval are respectively +.>，/>Are integers greater than 1.
In a preferred embodiment, in S4, the flow data of the crude oil in the transportation system includes pipeline vibration data;
setting a pipeline vibration monitoring interval; acquiring vibration acceleration in a pipeline vibration monitoring interval based on pipeline vibration data; setting a vibration acceleration threshold value; and acquiring the time length occupied by the vibration acceleration in the pipeline vibration monitoring interval being greater than the vibration acceleration threshold value, and marking the ratio of the time length occupied by the vibration acceleration in the pipeline vibration monitoring interval being greater than the vibration acceleration threshold value to the time length corresponding to the pipeline vibration monitoring interval as the pipeline vibration hidden danger ratio.
In a preferred embodiment, in S5, when the conveying environment of the conveying system is a risk conveying environment, normalizing the temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio, and calculating to obtain a conveying safety early warning evaluation coefficient by respectively endowing the normalized temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio with preset proportionality coefficients;
Setting a conveying safety early warning evaluation threshold; and carrying out early warning on the operation safety of the conveying system according to the comparison between the conveying safety early warning evaluation coefficient and the conveying safety early warning evaluation threshold value:
when the conveying safety early warning evaluation coefficient is larger than the conveying safety early warning evaluation threshold value, a conveying risk early warning signal is generated;
and when the conveying safety early warning evaluation coefficient is smaller than or equal to the conveying safety early warning evaluation threshold value, generating a conveying normal signal.
In a preferred embodiment, a data management system based on an intelligent oil depot comprises a leakage monitoring module, an external influence module, an environment dividing module, a valve operation monitoring module, a flow vibration monitoring module and a conveying safety early warning module;
the leakage monitoring module acquires the frequency of the leakage safety accidents of the conveying system monitored within a set period of the leakage detection system;
the external influence module acquires external environment data of the conveying system, and obtains the hidden danger degree of the pipeline risk according to the external environment data of the conveying system;
the environment dividing module divides the conveying environment of the conveying system into a risk conveying environment or a normal conveying environment according to the frequency degree of the leakage safety accidents of the conveying system and the hidden danger degree of the pipeline risk, which are monitored in the set period of the leakage detection system;
The valve operation monitoring module acquires valve operation data of the conveying system, and obtains the stability degree of the valve of the conveying system based on the valve operation data of the conveying system;
the flow vibration monitoring module acquires flow data of the crude oil in the conveying system, and obtains the stability degree of the crude oil in the conveying system based on the flow data of the crude oil in the conveying system;
when the conveying environment of the conveying system is a risk conveying environment, the conveying safety early warning module comprehensively analyzes the hidden danger degree of the pipeline, the stability degree of a valve of the conveying system and the stability degree of crude oil in the conveying system, and early warns the operation safety of the conveying system.
The intelligent oil depot-based data management system and method have the technical effects and advantages that:
by comprehensively utilizing the leakage detection system, external environment data, valve operation data and crude oil flow data, the comprehensive monitoring and early warning of the safety of the conveying system are realized. By analyzing the frequent degree of leakage safety accidents and the hidden danger degree of the pipeline risk, the conveying environment is effectively divided into a risk state or a normal state, and a foundation is provided for subsequent early warning. Meanwhile, by monitoring valve operation data and crude oil flow data, system stability is evaluated, and multiple references are provided for early warning. Finally, under the identification risk conveying environment, comprehensive analysis is carried out on the pipeline, the valve and the crude oil stability, so that timely early warning of the safety of a conveying system is realized, potential safety hazards are found in advance, the accident risk is reduced, and the safe and stable operation of the intelligent oil depot is ensured.
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FIG. 1 is a flow chart of a data management method based on an intelligent oil depot according to the invention;
fig. 2 is a schematic structural diagram of a data management system based on an intelligent oil depot according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
Fig. 1 shows a flow chart of a data management method based on an intelligent oil depot, which comprises the following steps:
s1: acquiring the frequency of the leakage safety accidents of the conveying system monitored within a set period of the leakage detection system; and acquiring external environment data of the conveying system, and obtaining the risk hidden danger degree of the pipeline according to the external environment data of the conveying system.
S2: and dividing the conveying environment of the conveying system into a risk conveying environment or a normal conveying environment according to the frequency degree of the leakage safety accidents of the conveying system and the hidden danger degree of the pipeline risk, which are monitored in the set period of the leakage detection system.
S3: and acquiring valve operation data of the conveying system, and obtaining the stability degree of the valve of the conveying system based on the valve operation data of the conveying system.
S4: and obtaining the flow data of the crude oil in the conveying system, and obtaining the stability degree of the crude oil in the conveying system based on the flow data of the crude oil in the conveying system.
S5: when the conveying environment of the conveying system is a risk conveying environment, comprehensively analyzing the hidden danger degree of the pipeline risk, the stability degree of a valve of the conveying system and the stability degree of crude oil in the conveying system, and pre-warning the operation safety of the conveying system.
In S1, it is important to determine the conveying environment of the conveying system to acquire the frequency of the conveying system leakage safety accidents monitored in the set period of the leakage detection system. The frequent degree of leakage safety accidents reflects the overall safety and stability of the conveying system, and the judgment and management of the conveying environment are directly affected. Firstly, the leakage risk of the conveying system can be evaluated through the frequent degree of the leakage safety accidents monitored in the set period of the leakage detection system. Frequent leakage safety accidents may suggest serious leaks or damage to the delivery pipe, valve or other equipment, requiring immediate action to repair or replace to prevent further accidents. Secondly, the frequency of leakage safety accidents can reflect the maintenance condition and the management level of the conveying system. If the leakage safety accident happens frequently, the maintenance of the conveying system is not in place or is not managed in place, and the problems of equipment aging, material corrosion, misoperation and the like exist, so that the management and maintenance work of the conveying system are required to be enhanced, and the stability and the safety of the system are improved. In addition, the frequency of leakage safety accidents can also be used as one of indexes for evaluating the operation efficiency of the conveying system. Frequent leakage safety accidents not only can influence the safety of the system, but also can cause the problems of production interruption, resource waste, environmental pollution and the like, and the operation efficiency and economic benefit of the conveying system are reduced.
The method comprises the steps of obtaining the frequent degree of the leakage safety accidents of the conveying system monitored within the set period of the leakage detection system, and specifically comprises the following steps:
the leakage monitoring period is set, and the time length of the leakage monitoring period is set according to the actual monitoring requirement of the leakage safety accident, which is not described herein.
Acquiring the occurrence times of the leakage safety accidents of the conveying system in the leakage monitoring period, wherein the occurrence times of the leakage safety accidents of the conveying system in the leakage monitoring period are acquired through a leakage detection system: the leakage detection system generally automatically monitors leakage conditions of devices such as pipelines, storage tanks and the like, and records information such as occurrence time, place, leakage quantity and the like of each leakage event. The number of leakage security incidents can be obtained by looking up a record of the leakage detection system.
The leakage safety accident refers to an accident of unexpected leakage of oil products in the conveying system. These leakage events may occur in the delivery lines, tanks, valves, or other equipment, resulting in the escape of material into the surrounding environment, which may be hazardous or detrimental to personnel, facilities, the environment, etc. The severity of the leakage safety accident can be evaluated according to the leakage quality, leakage amount, leakage rate, leakage position and other factors, and some leakage safety accidents can be only slight leakage points, and some leakage safety accidents can cause serious environmental pollution, fire, explosion and other serious consequences. Therefore, timely monitoring, preventing and treating the leakage safety accidents is one of important measures for guaranteeing the safe operation of the conveying system.
And marking the ratio of the occurrence times of the leakage safety accidents of the conveying system in the leakage monitoring period to the time length corresponding to the leakage monitoring period as a conveying leakage risk frequency value, wherein the greater the conveying leakage risk frequency value is, the higher the frequency of the leakage safety accidents of the conveying system monitored in the set period is.
The temperature data in the real-time external environment data of the conveying system has an important influence on the risk degree of the conveying environment of the conveying system; the high temperature environment can cause the liquid or gas conveyed in the pipeline to expand by heating, so that the pressure inside the pipeline is increased, and the risk of bursting or cracking of the pipeline is increased; the monitoring of the temperature data in the high-temperature environment in real time can remind operators of the risk of the heated expansion of the pipeline, and measures are timely taken to reduce the pressure in the pipeline, such as reducing the conveying flow or increasing the opening degree of the pressure relief valve; the low temperature environment may cause the liquid or coolant in the delivery conduit to freeze or solidify, risking blockage or rupture of the interior of the conduit; the monitoring of temperature data in a low-temperature environment in real time can remind operators that the pipeline may be frozen or solidified, so that measures can be taken in time, such as heating the pipeline or adding an insulating layer to prevent the pipeline coolant from solidifying; the temperature data in the real-time transmission external environment data of the transmission system has direct influence on the risk degree of the transmission environment of the transmission system.
Acquiring real-time external environment data of a conveying system, wherein the real-time external environment data of the conveying system comprise temperature data, and specifically comprises the following steps:
the temperature data observation interval is set, the corresponding time length of the temperature data observation interval is fixed, and is set by a person skilled in the art according to the monitoring requirement on the temperature of the conveying system and other practical conditions, the temperature data observation interval is a real-time interval, namely, the end point of the temperature data observation interval is always a real-time point, and the range of the temperature data observation interval is changed along with the change of the real-time point.
Wherein the temperature data is a temperature value of an environment outside the pipeline of the conveying system.
A plurality of temperature values are uniformly acquired in a temperature data observation interval, and the pipe of a conveying system can be subjected to excessive or insufficient temperature valuesThe method comprises the steps of numbering temperature values in a temperature data observation interval, analyzing the degree of deviation of the temperature values in the temperature data observation interval from a safe temperature value, and calculating the value of the potential deviation of the temperature, wherein the expression is as follows:wherein->For the temperature deviation hidden trouble value +.>Is the +.>Temperature value- >For safe temperature value, < >>For the corresponding time length of the temperature data observation interval, < >>The number of temperature values in the temperature data observation interval and the number of temperature values in the temperature data observation interval are respectively +.>，/>Are integers greater than 1.
The greater the temperature deviation hidden danger value, the greater the degree of risk hidden danger of the pipeline.
The safety temperature value is set by a person skilled in the art according to a safety requirement standard for the temperature value of the pipeline of the conveying system, and will not be described here again.
In S2, the conveying environment of the conveying system is classified into a risk conveying environment or a normal conveying environment, specifically:
the conveying leakage risk frequency threshold is set by a person skilled in the art according to the magnitude of the conveying leakage risk frequency value and other actual conditions such as safety requirement standards for the occurrence frequency of the conveying system leakage safety accidents.
Comparing the transport leakage risk frequency value to a transport leakage risk frequency threshold value:
when the conveying leakage risk frequency value is larger than the conveying leakage risk frequency threshold value, a leakage frequency high signal is generated, and at the moment, the occurrence frequency of the conveying system leakage safety accidents is high.
When the conveying leakage risk frequency value is smaller than or equal to the conveying leakage risk frequency threshold value, a leakage frequency normal signal is generated, and the occurrence frequency of the conveying system leakage safety accidents is within a normal range.
The temperature deviation hidden danger threshold is set by a person skilled in the art according to the magnitude of the temperature deviation hidden danger value and other practical conditions such as safety requirement standards for the temperature of the conveying system.
Comparing the temperature deviation hidden danger value with a temperature deviation hidden danger threshold value:
when the temperature deviation hidden danger value is larger than the temperature deviation hidden danger threshold value, a temperature deviation hidden danger signal is generated, and at the moment, the degree of deviation of the temperature value from the safe temperature value is higher, and the degree of risk hidden danger of the pipeline is larger.
When the temperature deviation hidden danger value is smaller than or equal to the temperature deviation hidden danger threshold value, a temperature deviation hidden danger normal signal is generated, the degree of deviation of the temperature value from the safety temperature value is normal, and the pipeline risk hidden danger degree is in a safety range.
Dividing the conveying environment of the conveying system into risk conveying environments as long as one of a leakage frequency high signal or a temperature deviation hidden danger high signal is generated; otherwise, the conveying environment of the conveying system is divided into normal conveying environments.
In S3, valve operation data of a delivery system is acquired, and the delivery system in the intelligent oil depot typically includes various valves for controlling the flow and pressure of the oil in the pipeline.
The valve operating data includes real-time pressure data of the valve, and the real-time pressure data of the valve is usually obtained by means of a pressure sensor or a pressure monitoring device, through which the pressure condition of the position of the valve can be monitored in real time. The step of obtaining the valve real-time pressure data is as follows:
firstly, a corresponding pressure sensor or pressure monitoring device is installed at the position of the valve. These sensors are typically attached directly to the valve or mounted on a pipe near the valve.
The pressure sensor is connected to a monitoring system or a data acquisition system of the intelligent oil depot, and the sensor can send pressure data acquired in real time to the monitoring system.
The monitoring system will receive and record the pressure data sent by the sensor in real time. The data can be presented on the interface of the monitoring system of the intelligent oil depot in the form of a chart, a number and the like, so that operators can know the pressure condition of the valve at any time.
Setting a valve pressure monitoring interval, wherein the time length corresponding to the valve pressure monitoring interval is fixed, the valve pressure monitoring interval is set according to actual conditions, and is a real-time interval, namely, the end point of the valve pressure monitoring interval is always a real-time point, and the range of the valve pressure monitoring interval is changed along with the change of the real-time point.
A plurality of valve pressure values are uniformly acquired within the valve pressure monitoring interval, and the number of valve pressure values should be large enough to accurately monitor the change of the valve pressure.
The valve pressure value is obtained based on real-time pressure data of the valve, and will not be described herein.
In general, under a safety condition, the valve pressure is in a safety range, so that an optimal safety valve pressure value is obtained, the valve pressure value in a valve pressure monitoring interval is numbered, the degree of deviation of the valve pressure value in the valve pressure monitoring interval from the optimal safety valve pressure value is analyzed, and a valve pressure health index is calculated, so that the stability degree of a valve of a conveying system is evaluated, and the valve pressure health index has the following expression:wherein->Is valve pressure health index>Is the valve pressure monitoring interval +.>Valve pressure value->For an optimal value of the safety valve pressure,for the corresponding time length of the valve pressure monitoring interval, < >>The number of valve pressure values in the valve pressure monitoring interval and the number of valve pressure values in the valve pressure monitoring interval are respectively +.>，/>Are integers greater than 1.
The optimal relief valve pressure value is set according to the safety range of the valve pressure value in practice, and for example, the center point of the safety range of the valve pressure value may be set as the optimal relief valve pressure value.
The greater the valve pressure health index, the smaller the degree to which the valve pressure value deviates from the optimal safety valve pressure value in the valve pressure monitoring interval, the better the safety of the valve of the conveying system, the healthier the operation, the higher the stability degree of the valve of the conveying system, and conversely, the lower.
In S4, obtaining flow data of crude oil in a conveying system, where the flow data of crude oil in the conveying system includes pipeline vibration data, and the method for obtaining the pipeline vibration data includes:
vibration sensors are installed on pipelines of the conveying system, and the vibration sensors can sense vibration conditions of the pipelines and convert vibration signals into electric signals to be output.
The vibration sensor is connected to a data acquisition system or monitoring equipment of the intelligent oil depot so as to transmit vibration data to the monitoring system for processing and analysis.
Corresponding parameters are set in the monitoring system so as to acquire and record vibration data of the pipeline in real time. These data are typically recorded in digital form in a database for later analysis and use.
The monitoring system receives and records vibration data of the pipeline in real time. Operators can monitor and analyze the vibration condition of the pipeline in real time through an interface of a monitoring system or data analysis software.
Setting a pipeline vibration monitoring interval, wherein the time length corresponding to the pipeline vibration monitoring interval is fixed, and the pipeline vibration monitoring interval is set according to actual conditions, namely, the end point of the pipeline vibration monitoring interval is always a real-time point, and the range of the pipeline vibration monitoring interval is changed along with the change of the real-time point.
Acquiring vibration acceleration in a pipeline vibration monitoring interval based on pipeline vibration data, wherein the larger the vibration acceleration is, the higher the acceleration change rate of pipeline vibration is, the stronger the vibration force applied to the pipeline is, and the larger the vibration amplitude and frequency can be; abnormal vibration acceleration may mean that there are abnormal conditions in the pipe system, such as loosening of pipe structure, instability of pipe support, mechanical failure of the pipe, or abnormal flow of fluid within the pipe, etc. The large vibration acceleration can cause fatigue, damage or fracture of the pipeline, so that leakage, explosion or other safety accidents are caused, and therefore measures are needed to be taken in time to eliminate potential safety hazards, and the stability degree of crude oil in a conveying system is influenced by various factors, including the structure of the pipeline, the flowing state of fluid, the running condition of the system and the like; the greater vibratory acceleration may cause unstable, chaotic or choked flow of crude oil within the pipeline, thereby affecting the stability and flowability of the transportation system, thus also suggesting that the less stable the crude oil is in the transportation system.
The vibration acceleration threshold is set by a person skilled in the art according to other practical situations such as safety requirement standards for vibration of the pipeline in the conveying system, and will not be described here.
Obtaining the time length occupied by the vibration acceleration larger than the vibration acceleration threshold value in the pipeline vibration monitoring interval, marking the ratio of the time length occupied by the vibration acceleration larger than the vibration acceleration threshold value in the pipeline vibration monitoring interval to the time length corresponding to the pipeline vibration monitoring interval as the pipeline vibration hidden danger ratio, wherein the larger the pipeline vibration hidden danger ratio is, the worse the stability of crude oil in the conveying system is, specifically:
flow instability increases: the higher vibration hidden danger ratio means that the abnormal condition of the pipeline vibration exists for a long time, and the phenomenon that crude oil flows unstably, fluid vortex, blockage and the like even occur can be caused, so that the normal operation of a conveying system is influenced.
The transportation risk increases: with the increase of the vibration hidden danger ratio, the problems of fatigue, corrosion, looseness and the like of the pipeline can be aggravated by the vibration problem of the pipeline, and the risks of leakage, breakage and the like of the pipeline are increased, so that the hidden danger to the conveying system is increased.
The system maintenance cost increases: high vibration potential hazards may require more frequent system repairs and maintenance, including repair of pipe damage, replacement of damaged equipment, etc., increasing the operational and maintenance costs and maintenance workload of the system.
Affecting equipment life: long-time pipeline vibration abnormality can cause fatigue and damage to the pipeline and related equipment, shortens the service life of the pipeline and increases the frequency of equipment replacement and maintenance.
In S5, when the transportation environment of the transportation system is a risk transportation environment, comprehensively analyzing the risk hidden trouble degree of the pipeline, the stability degree of the valve of the transportation system and the stability degree of the crude oil in the transportation system, specifically:
and carrying out normalization processing on the temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio, respectively endowing preset proportionality coefficients to the normalized temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio, and calculating to obtain a conveying safety early warning evaluation coefficient.
For example, the invention can calculate the conveying safety precaution evaluation coefficient by adopting the following formula:wherein->The method is characterized in that a conveying safety early warning evaluation coefficient and a pipeline vibration hidden danger ratio are respectively determined>The preset proportional coefficients of the temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio are respectively +.>Are all greater than 0.
The larger the conveying safety early warning evaluation coefficient is, the poorer the running safety stability of the conveying system is.
The conveying safety early warning evaluation threshold is set by a person skilled in the art according to the size of the conveying safety early warning evaluation coefficient and other actual conditions such as safety requirement standard of the conveying system in practice, and is not described herein.
And carrying out early warning on the operation safety of the conveying system according to the comparison between the conveying safety early warning evaluation coefficient and the conveying safety early warning evaluation threshold value:
when the conveying safety early warning evaluation coefficient is larger than the conveying safety early warning evaluation threshold value, a conveying risk early warning signal is generated, and at the moment, the safety stability of a conveying system of the intelligent oil depot is poor, the operation and maintenance personnel is reminded of the poor safety stability of the system, and measures are needed to be taken in time for processing so as to avoid possible safety accidents.
When the conveying safety early warning evaluation coefficient is smaller than or equal to the conveying safety early warning evaluation threshold value, a conveying normal signal is generated, and at the moment, the safety stability of a conveying system of the intelligent oil depot is normal without taking measures.
The comprehensive analysis has the advantages that the safety and the stability of the system can be comprehensively evaluated when the conveying environment of the conveying system is a risk conveying environment, potential problems can be timely found, and corresponding measures can be taken for treatment. In particular, the benefits of doing so include:
Comprehensively evaluating risk factors: in a risk delivery environment, the risk hidden danger degree of the pipeline may be increased, and safety risks such as leakage and explosion may exist. By comprehensively analyzing the risk hidden danger degree, the valve stability degree and the crude oil stability degree of the pipeline, the risk level of the system can be more comprehensively estimated, and the risk source and possible influence can be determined.
Safety concerns are considered in many ways: the comprehensive analysis not only considers the risk of the pipeline, but also considers the stability of the valve and the stability degree of crude oil in the system. In this way, the safety of the system can be checked from multiple angles, and omission or misjudgment caused by single factor evaluation can be avoided.
Accurate decision and countermeasure: the source and the influence degree of the safety risk can be more accurately determined through comprehensive analysis, and countermeasures and emergency plans can be formulated in a targeted manner. This helps to improve the system's ability to cope with emergency situations, reducing the likelihood and extent of impact of the incident.
Continuous improvement and optimization: the comprehensive analysis can solve the existing problems, and can find potential defects and improvement space of the system. Through continuous improvement and optimization, the safety, stability and operation efficiency of the system can be improved, and the long-term stable operation of the conveying system is ensured.
And when the conveying environment of the conveying system is not a risk conveying environment, certain resources can be saved without comprehensive analysis, because the system can be in a relatively stable and normal running state at the moment, and the risk is low. The frequency of monitoring and evaluating the system can be reduced without comprehensive analysis, and related manpower, time and cost can be saved.
Example 2
Embodiment 2 of the present invention differs from embodiment 1 in that this embodiment describes a data management system based on an intelligent oil depot.
Fig. 2 shows a schematic structural diagram of a data management system based on an intelligent oil depot, which comprises a leakage monitoring module, an external influence module, an environment dividing module, a valve operation monitoring module, a flow vibration monitoring module and a conveying safety early warning module.
The leakage monitoring module acquires the frequency of the leakage safety accidents of the conveying system, which are monitored within a set period of the leakage detection system.
The external influence module acquires external environment data of the conveying system, and obtains the hidden danger degree of the pipeline risk according to the external environment data of the conveying system.
The environment dividing module divides the conveying environment of the conveying system into a risk conveying environment or a normal conveying environment according to the frequent degree of the leakage safety accidents of the conveying system and the hidden danger degree of the pipeline risk, which are monitored in the set period of the leakage detection system.
The valve operation monitoring module acquires valve operation data of the conveying system, and obtains the stability degree of the valve of the conveying system based on the valve operation data of the conveying system.
The flow vibration monitoring module acquires flow data of the crude oil in the conveying system, and obtains the stability degree of the crude oil in the conveying system based on the flow data of the crude oil in the conveying system.
When the conveying environment of the conveying system is a risk conveying environment, the conveying safety early warning module comprehensively analyzes the hidden danger degree of the pipeline, the stability degree of a valve of the conveying system and the stability degree of crude oil in the conveying system, and early warns the operation safety of the conveying system.
The above formulas are all formulas with dimensionality removed and numerical calculation, the formulas are formulas with the latest real situation obtained by software simulation through collecting a large amount of data, and preset parameters and threshold selection in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with embodiments of the present invention are produced in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system, apparatus and module may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely illustrative of the present invention, and the present invention is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. The data management method based on the intelligent oil depot is characterized by comprising the following steps of:
s1: acquiring the frequency of the leakage safety accidents of the conveying system monitored within a set period of the leakage detection system; acquiring external environment data of a conveying system, and acquiring the risk hidden danger degree of the pipeline according to the external environment data of the conveying system;
s2: dividing the conveying environment of the conveying system into a risk conveying environment or a normal conveying environment according to the frequency degree of the leakage safety accidents of the conveying system and the hidden danger degree of the pipeline, which are monitored in the set period of the leakage detection system;
S3: acquiring valve operation data of a conveying system, and acquiring the stability degree of a valve of the conveying system based on the valve operation data of the conveying system;
s4: acquiring flow data of crude oil in a conveying system, and obtaining the stability degree of the crude oil in the conveying system based on the flow data of the crude oil in the conveying system;
s5: when the conveying environment of the conveying system is a risk conveying environment, comprehensively analyzing the hidden danger degree of the pipeline risk, the stability degree of a valve of the conveying system and the stability degree of crude oil in the conveying system, and pre-warning the operation safety of the conveying system.
2. The intelligent oil depot based data management method of claim 1, wherein the intelligent oil depot based data management method comprises the following steps: in S1, the frequency of the leakage safety accidents of the conveying system monitored in the set period of the leakage detection system is obtained, which specifically includes:
setting a leakage monitoring period; the method comprises the steps of obtaining the occurrence times of the leakage safety accidents of the conveying system in a leakage monitoring period, and marking the ratio of the occurrence times of the leakage safety accidents of the conveying system in the leakage monitoring period to the time length corresponding to the leakage monitoring period as a conveying leakage risk frequency value.
3. The intelligent oil depot based data management method of claim 2, wherein: the real-time external environment data of the conveying system comprise temperature data; the temperature data are temperature values of the environment outside the pipeline of the conveying system;
Setting a temperature data observation interval; a plurality of temperature values are uniformly acquired in a temperature data observation interval, the temperature values in the temperature data observation interval are numbered, the degree of deviation of the temperature values in the temperature data observation interval from a safe temperature value is analyzed, and a temperature deviation hidden danger value is calculated, wherein the expression is as follows:wherein->For the temperature deviation hidden trouble value +.>Is the +.>Temperature value->For safe temperature value, < >>For the corresponding time length of the temperature data observation interval, < >>The number of temperature values in the temperature data observation interval and the number of temperature values in the temperature data observation interval are respectively +.>，/>Are integers greater than 1.
4. A data management method based on intelligent oil depot according to claim 3, wherein: in S2, a transport leakage risk frequency threshold is set, and the transport leakage risk frequency value is compared with the transport leakage risk frequency threshold:
when the conveying leakage risk frequency value is larger than the conveying leakage risk frequency threshold value, generating a leakage frequency high signal; when the conveying leakage risk frequency value is smaller than or equal to the conveying leakage risk frequency threshold value, generating a leakage frequency normal signal;
setting a temperature deviation hidden danger threshold value, and comparing the temperature deviation hidden danger value with the temperature deviation hidden danger threshold value:
When the temperature deviation hidden danger value is larger than the temperature deviation hidden danger threshold value, generating a temperature deviation hidden danger signal; when the temperature deviation hidden danger value is smaller than or equal to the temperature deviation hidden danger threshold value, generating a temperature deviation hidden danger normal signal;
dividing the conveying environment of the conveying system into risk conveying environments as long as one of a leakage frequency high signal or a temperature deviation hidden danger high signal is generated; otherwise, the conveying environment of the conveying system is divided into normal conveying environments.
5. The intelligent oil depot based data management method of claim 4, wherein: in S3, the valve operation data includes real-time pressure data of the valve;
setting a valve pressure monitoring interval; uniformly acquiring a plurality of valve pressure values in a valve pressure monitoring interval;
the method comprises the steps of obtaining an optimal safety valve pressure value, numbering the valve pressure value in a valve pressure monitoring interval, analyzing the degree of deviation of the valve pressure value in the valve pressure monitoring interval from the optimal safety valve pressure value, and calculating a valve pressure health index, wherein the expression is as follows:wherein->Is valve pressure health index>Is the valve pressure monitoring interval +.>Valve pressure value->For the optimal safety valve pressure value- >For the corresponding time length of the valve pressure monitoring interval, < >>The number of valve pressure values in the valve pressure monitoring interval and the number of valve pressure values in the valve pressure monitoring interval are respectively +.>，/>Are integers greater than 1.
6. The intelligent oil depot based data management method of claim 5, wherein the intelligent oil depot based data management method comprises the following steps: in S4, the flow data of the crude oil in the transportation system includes pipeline vibration data;
setting a pipeline vibration monitoring interval; acquiring vibration acceleration in a pipeline vibration monitoring interval based on pipeline vibration data; setting a vibration acceleration threshold value; and acquiring the time length occupied by the vibration acceleration in the pipeline vibration monitoring interval being greater than the vibration acceleration threshold value, and marking the ratio of the time length occupied by the vibration acceleration in the pipeline vibration monitoring interval being greater than the vibration acceleration threshold value to the time length corresponding to the pipeline vibration monitoring interval as the pipeline vibration hidden danger ratio.
7. The intelligent oil depot based data management method of claim 6, wherein: in S5, when the conveying environment of the conveying system is a risk conveying environment, carrying out normalization processing on the temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio, and respectively endowing preset proportionality coefficients to the temperature deviation hidden danger value, the valve pressure health index and the pipeline vibration hidden danger ratio after normalization processing, so as to calculate and obtain a conveying safety early warning evaluation coefficient;
Setting a conveying safety early warning evaluation threshold; and carrying out early warning on the operation safety of the conveying system according to the comparison between the conveying safety early warning evaluation coefficient and the conveying safety early warning evaluation threshold value:
when the conveying safety early warning evaluation coefficient is larger than the conveying safety early warning evaluation threshold value, a conveying risk early warning signal is generated;
and when the conveying safety early warning evaluation coefficient is smaller than or equal to the conveying safety early warning evaluation threshold value, generating a conveying normal signal.
8. A data management system based on an intelligent oil depot, for implementing the data management method based on the intelligent oil depot according to any one of claims 1 to 7, which is characterized in that: the system comprises a leakage monitoring module, an external influence module, an environment dividing module, a valve operation monitoring module, a flow vibration monitoring module and a conveying safety early warning module;
the leakage monitoring module acquires the frequency of the leakage safety accidents of the conveying system monitored within a set period of the leakage detection system;
the external influence module acquires external environment data of the conveying system, and obtains the hidden danger degree of the pipeline risk according to the external environment data of the conveying system;
the environment dividing module divides the conveying environment of the conveying system into a risk conveying environment or a normal conveying environment according to the frequency degree of the leakage safety accidents of the conveying system and the hidden danger degree of the pipeline risk, which are monitored in the set period of the leakage detection system;
The valve operation monitoring module acquires valve operation data of the conveying system, and obtains the stability degree of the valve of the conveying system based on the valve operation data of the conveying system;
the flow vibration monitoring module acquires flow data of the crude oil in the conveying system, and obtains the stability degree of the crude oil in the conveying system based on the flow data of the crude oil in the conveying system;
when the conveying environment of the conveying system is a risk conveying environment, the conveying safety early warning module comprehensively analyzes the hidden danger degree of the pipeline, the stability degree of a valve of the conveying system and the stability degree of crude oil in the conveying system, and early warns the operation safety of the conveying system.
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