Oil conveying pipeline heat loss monitoring system based on intelligent sensor

Abstract

The invention relates to the technical field of sensors and Internet of Things, in particular to an oil conveying pipeline heat loss monitoring system based on an intelligent sensor. According to the system, by monitoring the oil product temperature, the environment temperature, the pipeline key node temperature and the oil conveying flow speed, all detection parameters of the oil conveying pipe can be more accurately obtained; meanwhile, the first heat loss, namely the actual heat loss, of the oil conveying pipe at the current moment is calculated, the second heat loss, namely the preset heat loss, of the oil conveying pipe at the current moment is calculated, and the actual heat loss and the preset heat loss of the oil conveying pipe at the current moment can be calculated more accurately; finally, whether the heat loss meets the standard or not is judged through the absolute value of the difference value of the first heat loss and the second heat loss, a corresponding processing mode is generated based on the reason that the heat loss does not meet the standard, whether the heat loss meets the standard or not can be accurately judged, and the corresponding processing mode is more effectively generated under the condition that the heat loss does not meet the standard; therefore, the heat loss monitoring efficiency and the oil conveying efficiency in the oil conveying pipe are further improved.

Description

Technical Field

[0001] The present invention relates to the technical fields of sensors and the Internet of Things, and particularly to a heat loss monitoring system for an oil pipeline based on intelligent sensors. Background Art

[0002] Traditional heat loss monitoring requires manual use of hand-held infrared thermometers or contact sensors for regular spot checks. The data collection is discontinuous and the coverage is limited, resulting in low inspection efficiency. Moreover, sudden damage to the insulation layer or local leakage is difficult to detect in a timely manner, leading to the expansion of faults. However, the heat loss monitoring system based on intelligent sensors is an inevitable product of the upgrade of traditional pipeline operation and maintenance to digital and intelligent. It integrates the latest achievements in the Internet of Things, big data, energy thermodynamics, and industrial automation, aiming to solve the core pain points of energy waste, response lag, and high labor costs, and promote the transformation of the oil industry towards high efficiency, safety, and low carbon.

[0003] Chinese Patent Publication No.: CN114183203B discloses a method and system for intelligent layout of underground oil pipelines in mines based on the cloud. The invention includes the following: the cloud server draws a simulation oil pipeline model according to technical drawings and feeds it back to the user; the user completes the construction to obtain the oil pipeline according to the simulation oil pipeline model and the layout scheme of pressure sensors; the cloud server establishes an oil transmission pressure prediction model based on hydraulic loss calculation and determines the reasonable indication range corresponding to each pressure sensor; and makes corresponding adjustments according to the feedback results until the actual indication of each pressure sensor is within its reasonable indication range to complete the pressure test.

[0004] It can be seen that the existing technology has the following problems: due to the inability to accurately determine whether the heat loss meets the standard, the monitoring efficiency of the heat loss of the oil pipeline is low, and thus effective adjustment cannot be made according to the reasons for non-compliance, resulting in low oil transmission efficiency of the oil pipeline. Summary of the Invention

[0005] Therefore, the present invention provides a heat loss monitoring system for an oil pipeline based on intelligent sensors to overcome the problems in the existing technology that due to the inability to accurately determine whether the heat loss meets the standard, the monitoring efficiency of the heat loss of the oil pipeline is low, and thus effective adjustment cannot be made according to the reasons for non-compliance, resulting in low oil transmission efficiency of the oil pipeline.

[0006] To achieve the above object, the present invention provides a heat loss monitoring system for an oil pipeline based on intelligent sensors, including:

[0007] An oil product temperature detection unit, including several sensors for monitoring the temperature of the oil product;

[0008] An ambient temperature detection unit, including several sensors for monitoring the ambient temperature;

[0009] The pipe wall temperature detection unit includes several sensors for monitoring the temperatures of key nodes of the pipeline, where the key nodes are valves and elbows;

[0010] The flow rate detection unit includes a sensor for monitoring the oil transportation flow rate;

[0011] The heat loss calculation unit is connected to the oil product temperature detection unit and the flow rate detection unit, and is used to calculate the first heat loss of the oil pipeline based on the oil product temperature and the oil transportation flow rate;

[0012] The heat loss prediction unit is respectively connected to the ambient temperature detection unit and the pipe wall temperature detection unit, and is used to calculate the second heat loss of the oil pipeline based on the average value of the temperatures of the key nodes of the pipeline and the ambient temperature;

[0013] The analysis unit is respectively connected to the heat loss calculation unit and the heat loss prediction unit, and is used to determine whether the heat loss of the oil pipeline meets the standard based on the absolute value of the difference between the first heat loss and the second heat loss, and to generate corresponding processing methods according to the reasons for not meeting the standard. The processing methods include adjusting the detection interval, sending a notice of damaged insulation layer, and adjusting the thickness of the insulation layer;

[0014] The control unit is connected to the analysis unit and is used to control according to the processing methods obtained by the analysis unit.

[0015] Further, the analysis unit is also used to determine whether the heat loss meets the standard based on the ratio of the absolute value of the difference between the first heat loss and the second heat loss to a preset absolute value, and to analyze the reasons for the heat loss not meeting the standard based on the variance of the ratio at historical moments or based on the difference between the ratio and a preset ratio.

[0016] Further, the analysis unit is also used to generate corresponding processing methods based on the comparison result of the variance of the ratio at historical moments and a preset variance, including analyzing the reasons for the heat loss not meeting the standard based on the drawn time - first heat loss curve, or analyzing the reasons for the heat loss not meeting the standard based on the difference between the ratio and a preset ratio.

[0017] Further, the analysis unit is also used to determine whether the time - first heat loss curve has regularity based on the autocorrelation function, and to generate corresponding processing methods based on the determination result, including adjusting the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, or sending a notice to calibrate the flow rate sensor.

[0018] Further, the analysis unit is also used to increase the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, and the difference is proportional to the increase amplitude of the thickness.

[0019] Furthermore, the analysis unit is further configured to increase the oil transportation flow rate based on the difference between the adjusted thickness of the thermal insulation layer and a preset thickness, and the difference is proportional to the increase amplitude of the oil transportation flow rate.

[0020] Furthermore, the analysis unit is further configured to generate corresponding processing methods based on the comparison result between the difference between the ratio and a preset ratio and a preset difference, including based on the proportion of abnormal nodes detected by the oil product temperature sensor to the total number of nodes where the oil product temperature sensor is set, or based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at a critical moment to adjust the detection interval.

[0021] Furthermore, the analysis unit is further configured to generate corresponding processing methods based on the comparison result between the proportion of the abnormal nodes detected by the oil product temperature sensor to the total number of nodes where the oil product temperature sensor is set and a preset proportion, including analyzing the reason for the non - compliance of the heat loss based on the integral of the drawn node - oil product temperature curve, or sending a notice of thermal insulation layer damage; wherein, the abnormal node is a temperature detection node where the oil product temperature is lower than a preset oil product temperature.

[0022] Furthermore, the analysis unit is further configured to generate corresponding processing methods based on the comparison result between the integral of the drawn node - oil product temperature curve and a preset integral, including adjusting the thickness of the thermal insulation layer of the oil pipeline based on the difference between the variance and the preset variance, or sending a notice of thermal insulation layer damage.

[0023] Furthermore, the critical moment is the moment when the heat loss was last determined to be non - compliant. The analysis unit is further configured to increase the detection interval based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment, and the ratio is proportional to the increase amplitude of the detection interval.

[0024] Compared with the prior art, the beneficial effects of the present invention are as follows. The system can obtain each detection parameter of the oil pipeline more accurately by monitoring the oil product temperature, ambient temperature, key node temperature of the pipeline, and oil transportation flow rate; meanwhile, calculating the first heat loss, that is, the actual heat loss, of the oil pipeline at the current moment and calculating the second heat loss, that is, the preset heat loss, of the oil pipeline at the current moment can calculate the actual heat loss and preset heat loss of the oil pipeline at the current moment more accurately; finally, using the absolute value of the difference between the first heat loss and the second heat loss to determine whether the heat loss meets the standard, and generating corresponding processing methods based on the reasons for non - compliance of the heat loss can accurately determine whether the heat loss meets the standard, and more effectively generate corresponding processing methods in case of non - compliance, thereby further improving the monitoring efficiency of the heat loss of the oil pipeline and the oil transportation efficiency.

[0025] Further, the present invention also determines whether the heat loss meets the standard based on the ratio of the absolute value of the difference between the first heat loss and the second heat loss to a preset absolute value, which can more quickly determine whether the heat loss meets the standard, so that subsequent corresponding processing methods can be generated more effectively when the standard is not met, thereby further improving the monitoring efficiency of the heat loss of the oil pipeline.

[0026] Further, the present invention also generates corresponding processing methods based on the comparison result between the variance of the ratio at historical moments and a preset variance, which can more accurately determine the factors causing the heat loss not to meet the standard, so that subsequent adjustments can be made more effectively, thereby further improving the monitoring efficiency of the heat loss of the oil pipeline.

[0027] Further, the present invention also analyzes the reason for the heat loss not meeting the standard based on the drawn time - first heat loss curve, and can more accurately determine whether the heat loss does not meet the standard due to low winter temperature through whether the curve is regular, thereby further improving the monitoring efficiency of the heat loss of the oil pipeline.

[0028] Further, the present invention also increases the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, which can more accurately adjust the thickness of the insulation layer in winter, so that the heat loss meets the standard, further reducing the heat loss of the oil pipeline, and thereby further improving the oil transportation efficiency of the oil pipeline.

[0029] Further, the present invention also increases the oil flow rate based on the difference between the adjusted thickness of the insulation layer and the preset thickness, so that the heat loss meets the standard, further reducing the heat loss of the oil pipeline, and thereby further improving the oil transportation efficiency of the oil pipeline.

[0030] Further, the present invention also generates corresponding processing methods based on the comparison result between the difference between the ratio and the preset ratio and a preset difference, which can more accurately determine the reason for the heat loss of the oil pipeline not meeting the standard according to the data obtained by the heat loss monitoring system of the oil pipeline, so as to further reduce the heat loss of the oil pipeline, and thereby further improve the oil transportation efficiency of the oil pipeline.

[0031] Further, the present invention also generates corresponding processing methods based on the comparison result between the proportion of abnormal nodes detected by the oil product temperature sensor to the total number of oil product temperature sensors set and a preset proportion, which can more accurately determine whether the reason for the heat loss not meeting the standard is a problem with the insulation layer based on the comparison result, so that subsequent adjustments can be made more accurately for the reason not meeting the standard, thereby further reducing the heat loss of the oil pipeline and further improving the oil transportation efficiency of the oil pipeline.

[0032] Furthermore, the present invention also generates corresponding processing methods based on the comparison result between the integral of the plotted node-oil product temperature curve and the preset integral, which can more accurately determine the cause of this result, so that subsequent adjustments for reasons not meeting the standards can be made more accurately, further reducing the heat loss of the oil pipeline and further improving the oil transportation efficiency of the oil pipeline.

[0033] Furthermore, the present invention also increases the detection interval based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment, which can enable the detection of heat loss after a period of adjustment of the heat loss not meeting the standards, making the detection result more accurate, and further improving the monitoring efficiency of the heat loss of the oil pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic structural diagram of the oil pipeline heat loss monitoring system based on intelligent sensors according to an embodiment of the present invention;

[0035] Figure 2 It is a flowchart of the steps implemented by the oil pipeline heat loss monitoring system based on intelligent sensors according to an embodiment of the present invention;

[0036] Figure 3 It is a flowchart of the steps for determination based on the comparison result between the absolute value of the difference between the first heat loss and the second heat loss and the ratio of the preset absolute value to the preset ratio according to an embodiment of the present invention;

[0037] Figure 4 It is a flowchart of the steps for determination based on the comparison result between the difference between the ratio and the preset ratio and the preset difference according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] In order to make the objectives and advantages of the present invention clearer and more understandable, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0040] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installation", "connection", and "coupling" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, and it can be the communication inside two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0041] Please refer to Figure 1 as shown, which is a schematic structural diagram of the oil pipeline heat loss monitoring system based on intelligent sensors according to an embodiment of the present invention.

[0042] The system includes an oil temperature detection unit, an ambient temperature detection unit, a pipe wall temperature detection unit, a flow rate detection unit, a heat loss calculation unit, a heat loss prediction unit, an analysis unit, and a control unit.

[0043] The oil temperature detection unit includes a plurality of oil temperature sensors for monitoring the oil temperature;

[0044] The ambient temperature detection unit includes a plurality of ambient temperature sensors for monitoring the ambient temperature;

[0045] The pipe wall temperature detection unit includes a plurality of pipe node temperature sensors for monitoring the temperatures of key nodes of the pipeline, where the key nodes are valves and elbows;

[0046] The flow rate detection unit includes a flow rate sensor for monitoring the oil transportation flow rate;

[0047] The heat loss calculation unit is connected to the oil temperature detection unit and the flow rate detection unit, and is used to calculate the first heat loss of the oil pipeline based on the oil temperature and the oil transportation flow rate;

[0048] The heat loss prediction unit is respectively connected to the ambient temperature detection unit and the pipe wall temperature detection unit, and is used to calculate the second heat loss of the oil pipeline based on the average value of the temperatures of key pipeline nodes and the ambient temperature;

[0049] The analysis unit is respectively connected to the heat loss calculation unit and the heat loss prediction unit, and is used to determine whether the heat loss of the oil pipeline meets the standard based on the absolute value of the difference between the first heat loss and the second heat loss, and generate corresponding processing methods according to the reasons for not meeting the standard. The processing methods include adjusting the detection interval, sending a notice of damaged insulation layer, and adjusting the thickness of the insulation layer;

[0050] The control unit is connected to the analysis unit and is used to control according to the processing methods obtained by the analysis unit.

[0051] Specifically, in this embodiment, the sensors for detecting the oil temperature in the oil temperature detection unit are installed at multiple nodes of the pipeline, the sensors for detecting the ambient temperature in the ambient temperature detection unit are installed near the pipeline, the sensors for detecting the temperature of key pipeline nodes in the pipeline wall temperature detection unit are installed at pipeline valves or elbows, and the sensors for detecting the oil transportation flow rate in the flow rate detection unit are installed at the inlet or outlet of the pipeline.

[0052] Specifically, in this embodiment, the formula for calculating the first heat loss of the oil pipeline in the heat loss calculation unit is Where is the mass flow rate, C p is the specific heat capacity of the oil, T in is the temperature of the oil at the pipeline inlet, T out is the temperature of the oil at the pipeline outlet.

[0053] Specifically, in this embodiment, the heat loss prediction unit verifies the calculation result through the heat conduction formula between the pipeline wall and the environment, and the formula is Q loss2 = U·A·(T1 - T2), where U is the overall heat transfer coefficient, including the heat conduction of the pipe material, the performance of the insulation layer, and the convective / radiative heat dissipation, A is the surface area of the pipeline, T1 is the average temperature of the pipeline obtained by the pipeline wall temperature sensor, and T2 is the ambient temperature obtained by the ambient temperature detection unit.

[0054] Please refer to Figure 2 shown, which is the step flowchart of the implementation of the oil pipeline heat loss monitoring system based on intelligent sensors according to the embodiment of the present invention.

[0055] The implementation process of the oil pipeline heat loss monitoring system based on intelligent sensors includes:

[0056] S1, monitoring the oil temperature through several oil temperature sensors in the oil temperature detection unit;

[0057] S2, monitoring the ambient temperature through several ambient temperature sensors in the ambient temperature detection unit;

[0058] S3, monitoring the temperature of key pipeline nodes through several pipeline node temperature sensors in the pipeline wall temperature detection unit, where the key nodes are valves and elbows;

[0059] S4, monitoring the oil transportation flow rate through the flow rate sensors in the flow rate detection unit;

[0060] S5, calculating the first heat loss of the oil pipeline based on the oil temperature and the oil transportation flow rate through the heat loss calculation unit connected to the oil temperature detection unit and the flow rate detection unit;

[0061] S6, the heat loss prediction unit, which is connected to the ambient temperature detection unit and the pipe wall temperature detection unit respectively, calculates the second heat loss of the oil pipeline based on the average value of the key node temperatures of the pipeline and the ambient temperature;

[0062] S7, the analysis unit, which is connected to the heat loss calculation unit and the heat loss prediction unit respectively, determines whether the heat loss of the oil pipeline meets the standard based on the absolute value of the difference between the first heat loss and the second heat loss, and generates corresponding processing methods according to the reasons for not meeting the standard. The processing methods include adjusting the detection interval, sending a notice of damaged insulation layer, and adjusting the thickness of the insulation layer;

[0063] S8, the control unit, which is connected to the analysis unit, controls according to the processing method obtained by the analysis unit.

[0064] Please refer to Figure 3 As shown, it is a step flowchart for the determination in the embodiment of the present invention based on the comparison result of the ratio of the absolute value of the difference between the first heat loss and the second heat loss to the preset absolute value and the preset ratio. In the embodiment of the present invention, the analysis unit is also used to determine whether the heat loss meets the standard based on the ratio of the absolute value of the difference between the first heat loss and the second heat loss to the preset absolute value, and analyze the reasons for the heat loss not meeting the standard based on the variance of the ratio at historical moments or based on the difference between the ratio and the preset ratio.

[0065] Specifically, in this embodiment, the ratio L0 can be divided into a first preset ratio L1 and a second preset ratio L2. It is set that in the ratio standard, the first preset ratio L1 = 0.5 and the second preset ratio L2 = 0.9. It should be noted that in other embodiments, the values of L1 and L2 can also be determined based on the monitoring requirements of the heat loss of the oil pipeline, and the numerical values of the ratio are rounded up to two decimal places. The specific process of comparing the ratio L with L1 and L2 is as follows:

[0066] If the ratio L is less than or equal to the first preset ratio L1, it is determined that the heat loss of the oil pipeline meets the standard;

[0067] If the ratio L is greater than the first preset ratio L1 and less than the second preset ratio L2, it means that at this time, it is impossible to determine whether there are other factors causing this result. Therefore, a secondary determination of whether the heat loss meets the standard is made based on the variance P of the ratio at historical moments;

[0068] If the ratio L is greater than or equal to the second preset ratio L2, it is determined that the heat loss of the oil pipeline does not meet the standard, and the reasons for the heat loss not meeting the standard are analyzed based on the difference Q between the ratio and the preset ratio.

[0069] Specifically, in the embodiment of the present invention, the analysis unit is further configured to generate a corresponding processing method based on the comparison result between the variance of the historical moment ratio and the preset variance, including analyzing the reason why the heat loss does not meet the standard based on the drawn time-first heat loss curve, or analyzing the reason why the heat loss does not meet the standard based on the difference between the ratio and the preset ratio.

[0070] Specifically, in this embodiment, the preset variance P0 = 0.95, and the comparison process between the variance P of the historical moment ratio and the preset variance P0 is as follows:

[0071] If the variance P is greater than the preset variance P0, it indicates that the large heat loss may be caused by the low winter temperature. Then, draw the time-first heat loss curve and analyze the reason why the heat loss does not meet the standard based on whether the curve is regular;

[0072] If the variance P is less than or equal to the preset variance P0, it is determined that the heat loss does not meet the standard, and then analyze the reason why the heat loss does not meet the standard based on the difference between the ratio and the preset ratio.

[0073] Specifically, in the embodiment of the present invention, the analysis unit is further configured to determine whether the time-first heat loss curve is regular based on the autocorrelation function, and generate a corresponding processing method based on the determination result, including adjusting the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, or sending a notice to calibrate the flow velocity sensor.

[0074] Specifically, in this embodiment, the process of determining whether the time-first heat loss curve is regular based on the autocorrelation function specifically includes: First, perform data preparation, which includes a data acquisition step and a preprocessing step. The data acquisition is to collect cycle-stress data, and the preprocessing step is to remove trends and outliers to ensure data stability; Second, calculate the autocorrelation function, and use the autocorrelation function graph with the horizontal axis being the lag number and the vertical axis being the autocorrelation value to perform periodic judgment. If the autocorrelation function graph shows periodic peaks, it indicates that the data is regular.

[0075] Specifically, in this embodiment, the corresponding processing method based on the result of whether the curve is regular is as follows:

[0076] If the time-first heat loss curve is regular, it indicates that it is currently winter. Then, adjust the thickness of the insulation layer of the oil pipeline based on the difference R between the variance and the preset variance. It should be noted that here the thickness of the insulation layer is determined by using a notice, and what is actually determined is the thickness requirement or thickness standard, rather than directly changing the thickness to the corresponding value;

[0077] If the time-first heat loss curve is not regular, it indicates that there is a problem with the flow velocity sensor, and then send a notice to calibrate the flow velocity sensor.

[0078] Specifically, in the embodiments of the present invention, the analysis unit is further configured to increase the thickness of the heat-insulating layer of the oil pipeline based on the difference between the variance and the preset variance, and the difference is proportional to the increase amplitude of the thickness.

[0079] Specifically, in this embodiment, the preset difference R0 between the variance and the preset variance is 0.05. Then, the comparison process based on the difference R between the variance and the preset variance and the preset difference R0 is as follows:

[0080] If the difference R is less than or equal to the preset difference R0, adjust the thickness of the heat-insulating layer of the oil pipeline to 1.5 times the original thickness. It should be noted that the adjusted thickness value is rounded up to one decimal place.

[0081] If the difference R is greater than the preset difference R0, adjust the thickness of the heat-insulating layer of the oil pipeline to 2.3 times the original thickness. It should be noted that the adjusted thickness value is rounded up to one decimal place.

[0082] Specifically, in the embodiments of the present invention, the analysis unit is further configured to increase the oil flow rate based on the difference between the adjusted thickness of the heat-insulating layer and the preset thickness, and the difference is proportional to the increase amplitude of the oil flow rate.

[0083] Specifically, in this embodiment, the oil flow rate is determined by adjusting the valve opening, and the heat-insulating layer material used is polyurethane foam.

[0084] Specifically, in this embodiment, the preset difference T0 between the thickness of the heat-insulating layer and the preset thickness is 6 mm. Then, the comparison process based on the difference T and the preset difference T0 is as follows:

[0085] If the difference T is less than or equal to the preset difference T0, adjust the oil flow rate to 1.3 times the original oil flow rate.

[0086] If the difference T is less than or equal to the preset difference T0, adjust the oil flow rate to 1.9 times the original oil flow rate.

[0087] Please refer to Figure 4 As shown, it is the step flowchart for the determination based on the comparison result of the difference between the ratio and the preset ratio and the preset difference in the embodiments of the present invention. In the embodiments of the present invention, the analysis unit is further configured to generate corresponding processing methods based on the comparison result of the difference between the ratio and the preset ratio and the preset difference, including based on the proportion of the abnormal nodes detected by the oil product temperature sensor to the total number of nodes where the oil product temperature sensor is set, or based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment to adjust the detection interval.

[0088] Specifically, in this embodiment, the preset difference Q0 = 0.15. The comparison process of the difference Q between the ratio and the preset ratio and the preset difference Q0 is as follows:

[0089] If the difference Q is less than or equal to the preset difference Q0, it indicates that there is a problem with the insulation layer. Then, analyze the reason for the non - compliant heat loss based on the ratio U of the abnormal nodes detected by the oil - product temperature sensor to the total number of nodes where the oil - product temperature sensors are set.

[0090] If the difference Q is greater than the preset difference Q0, it indicates that the heat loss was not processed in time after being detected as non - compliant last time, that is, there is a problem with the detection interval. Then, adjust the detection interval based on the ratio W of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment.

[0091] Specifically, in the embodiment of the present invention, the analysis unit is further configured to generate a corresponding processing method based on the comparison result between the ratio of the abnormal nodes detected by the oil - product temperature sensor to the total number of nodes where the oil - product temperature sensors are set and the preset ratio, including analyzing the reason for the non - compliant heat loss based on the integral of the plotted node - oil - product temperature curve, or sending a notice of insulation layer damage; where the abnormal node is the temperature detection node where the oil - product temperature is lower than the preset oil - product temperature.

[0092] Specifically, in this embodiment, the preset ratio U0 = 0.5. The comparison process of the ratio U of the abnormal nodes detected by the oil - product temperature sensor to the total number of nodes where the oil - product temperature sensors are set and the preset ratio U0 is as follows:

[0093] If the ratio U is greater than the preset ratio U0, plot the node - temperature curve and analyze the reason for the non - compliant heat loss based on the integral M of the curve.

[0094] If the ratio U is less than or equal to the preset ratio U0, it indicates that the insulation layer is damaged, and then send a notice of insulation layer damage.

[0095] Specifically, in the embodiment of the present invention, the analysis unit is further configured to generate a corresponding processing method based on the comparison result between the integral of the plotted node - oil - product temperature curve and the preset integral, including adjusting the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, or sending a notice of insulation layer damage.

[0096] Specifically, in this embodiment, 20 sensors for monitoring the oil - product temperature are set in the pipeline. The preset integral M0 = 1000. The comparison process of the integral M of the plotted node - oil - product temperature curve and the preset integral M0 is as follows:

[0097] If the integral M is greater than the preset integral M0, it indicates that this result is caused by the ambient temperature. Then, adjust the thickness of the heat insulation layer of the oil pipeline based on the difference between the variance and the preset variance.

[0098] If the integral M is less than or equal to the preset integral M0, it indicates that the heat insulation layer is damaged. Then, send a notice of heat insulation layer damage.

[0099] Specifically, in the embodiment of the present invention, the critical moment is the moment when the heat loss was last determined to not meet the standard. The analysis unit is further configured to increase the detection interval based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment, and the ratio is directly proportional to the increase amplitude of the detection interval.

[0100] Specifically, in this embodiment, the preset ratio W0 of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment is 1.5. The comparison process of the ratio W of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment with the preset ratio W0 is as follows:

[0101] If the ratio W is less than or equal to the preset ratio W0, adjust the detection interval to 1.4 times the original detection interval.

[0102] If the ratio W is greater than the preset ratio W0, adjust the detection interval to 2.1 times the original detection interval.

[0103] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

[0104] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An oil pipeline heat loss monitoring system based on intelligent sensors, characterized in that, Comprising: An oil temperature detection unit, including a number of oil temperature sensors for monitoring the oil temperature; An ambient temperature detection unit, including a number of ambient temperature sensors for monitoring the ambient temperature; A pipe wall temperature detection unit, including a number of pipe node temperature sensors for monitoring the temperatures of key nodes of the pipeline, where the key nodes are valves and elbows; A flow rate detection unit, including a flow rate sensor for monitoring the oil transportation flow rate; A heat loss calculation unit, connected to the oil temperature detection unit and the flow rate detection unit, for calculating the first heat loss of the oil pipeline based on the oil temperature and the oil transportation flow rate; A heat loss prediction unit, respectively connected to the ambient temperature detection unit and the pipe wall temperature detection unit, for calculating the second heat loss of the oil pipeline based on the average value of the temperatures of the key pipeline nodes and the ambient temperature; An analysis unit, respectively connected to the heat loss calculation unit and the heat loss prediction unit, for determining whether the heat loss of the oil pipeline meets the standard based on the absolute value of the difference between the first heat loss and the second heat loss, and generating corresponding processing methods according to the reasons for not meeting the standard, where the processing methods include adjusting the detection interval, sending a notice of damaged insulation layer, and adjusting the thickness of the insulation layer; A control unit, connected to the analysis unit, for controlling according to the processing methods obtained by the analysis unit.

2. The oil pipeline heat loss monitoring system based on intelligent sensors according to claim 1, wherein The analysis unit is further configured to determine whether the heat loss meets the standard based on the ratio of the absolute value of the difference between the first heat loss and the second heat loss to a preset absolute value, and analyze the reasons for the heat loss not meeting the standard based on the variance of the ratio at historical moments or based on the difference between the ratio and a preset ratio.

3. The monitoring system for heat loss of oil pipelines based on intelligent sensors according to claim 2, wherein The analysis unit is further configured to generate corresponding processing methods based on the comparison result of the variance of the ratio at historical moments and a preset variance, including analyzing the reasons for the heat loss not meeting the standard based on the drawn time - first heat loss curve, or analyzing the reasons for the heat loss not meeting the standard based on the difference between the ratio and a preset ratio.

4. The monitoring system for heat loss of an oil pipeline based on intelligent sensors according to claim 3, characterized in that, The analysis unit is further configured to determine whether the time - first heat loss curve has regularity based on the autocorrelation function, and generate corresponding processing methods based on the determination result, including adjusting the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, or sending a notice to calibrate the flow rate sensor.

5. The monitoring system for heat loss of an oil pipeline based on intelligent sensors according to claim 4, characterized in that, The analysis unit is further configured to increase the thickness of the insulation layer of the oil pipeline based on the difference between the variance and the preset variance, and the difference is proportional to the increase amplitude of the thickness.

6. The monitoring system for heat loss of an oil pipeline based on intelligent sensors according to claim 5, characterized in that, The analysis unit is further configured to increase the oil transportation flow rate based on the difference between the adjusted thickness of the insulation layer and a preset thickness, and the difference is proportional to the increase amplitude of the flow rate.

7. The monitoring system for heat loss of oil pipelines based on intelligent sensors according to claim 2, characterized in that, The analysis unit is further configured to generate corresponding processing methods based on the comparison result of the difference between the ratio and a preset ratio and a preset difference, including based on the proportion of abnormal nodes detected by the oil temperature sensor to the total number of nodes where the oil temperature sensors are set, or adjusting the detection interval based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at a critical moment.

8. The oil pipeline heat loss monitoring system based on intelligent sensors according to claim 7, characterized in that, The analysis unit is further configured to generate a corresponding processing method based on the comparison result between the proportion of the abnormal nodes detected by the oil product temperature sensor and the total number of nodes where the oil product temperature sensors are set and a preset proportion, including analyzing the reason for the non-compliance of the heat loss based on the integral of the plotted node-oil product temperature curve, or issuing a notice of damaged thermal insulation layer; Among them, the abnormal node is a temperature detection node where the oil product temperature is lower than the preset oil product temperature.

9. The monitoring system for heat loss of oil pipelines based on intelligent sensors according to claim 8, characterized in that, The analysis unit is further configured to generate a corresponding processing method based on the comparison result between the integral of the plotted node-oil product temperature curve and a preset integral, including adjusting the thickness of the thermal insulation layer of the oil pipeline based on the difference between the variance and the preset variance, or issuing a notice of damaged thermal insulation layer.

10. The monitoring system for heat loss of an oil pipeline based on intelligent sensors according to claim 7, characterized in that, The critical moment is the moment when the heat loss was last determined to be non-compliant. The analysis unit is further configured to increase the detection interval based on the ratio of the first heat loss obtained at the current moment to the historical first heat loss obtained at the critical moment, and the ratio is directly proportional to the increase amplitude of the detection interval.

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