An online monitoring cloud platform for energy transmission safety based on multi-dimensional feature analysis

Abstract

The present invention discloses an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis. By setting up a pipeline segment self-hazard monitoring module, a pipeline segment external environment hazard monitoring module, and setting up a high-definition camera, a gas leak detector, a flow meter and a pressure sensor, the self-hazard monitoring of the natural gas transmission pipeline is realized. At the same time, a rain gauge, a temperature sensor, an anemometer and a wind vane are set to realize the corresponding hazard monitoring of the external environment of the natural gas transmission pipeline. On the one hand, it can not only detect subtle hazard problems such as pipeline cracks and deformations, but also reduce detection blind spots, improve detection effects, and provide a stability basis for the hazard monitoring results of the natural gas pipeline. On the other hand, the amount of data collected is large, and the aging phenomenon of most natural gas pipelines is taken into account, so that dynamic monitoring of the natural gas pipeline is realized, and the reliability and stability of the safety monitoring of the natural gas pipeline are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy analysis and control, and specifically relates to an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis. Background Art

[0002] With the increasing demand for energy, the scale of natural gas field development is also expanding. The use of natural gas can effectively improve people's quality of life, and compared with other energy sources, it can effectively reduce the degree of air pollution. Natural gas is mostly transported by underground, above-ground and overhead pipelines, but the above-ground pipeline transportation of natural gas is an extremely large project. The above-ground natural gas pipelines are distributed over a wide mileage and are flammable and explosive. Any safety problem at any point will affect the normal operation of the entire transportation system. In this case, safety monitoring of the above-ground natural gas pipelines is particularly important.

[0003] Nowadays, the safety monitoring of natural gas pipelines on the ground is mostly done by manual and satellite network detection. However, both methods cannot collect data with an ideal level of precision and have certain drawbacks, which are specifically reflected in the following aspects:

[0004] (1) On the one hand, because long-distance natural gas pipelines often cross rivers, mountains and other areas with complex terrain, the use of manual inspection methods not only makes it difficult for workers to find dangerous problems such as pipeline cracks and deformations, but also has certain blind spots in detection, resulting in poor detection results and unable to provide a reliable basis for the dangerous monitoring results of natural gas pipelines. It also brings a huge workload to the inspection personnel.

[0005] (2) On the one hand, the detection method using satellite networks is usually small in scale due to the long distance and objective uncontrollable factors. In addition, since most natural gas pipelines are aging, the predefined data of satellite networks can no longer support the stability monitoring of natural gas pipelines, and there is a high maintenance cost.

[0006] (3) On the other hand, the detection methods of artificial and satellite networks only focus on the hazard monitoring of the natural gas transmission pipeline itself, and do not conduct corresponding hazard monitoring of the external environment of the natural gas transmission pipeline. Summary of the invention

[0007] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis, which can effectively solve the problems involved in the above-mentioned background technology.

[0008] The purpose of the present invention can be achieved by the following technical solutions:

[0009] The present invention provides an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis, the system includes a natural gas transmission pipeline segment division module, a pipeline segment monitoring equipment setting module, a pipeline segment self-hazard monitoring module, a pipeline segment external environment hazard monitoring module, a data processing cloud platform, a database and a management and control early warning display terminal;

[0010] The pipeline segment monitoring equipment setting module is respectively connected to the natural gas transmission pipeline segment division module, the pipeline segment self-hazard monitoring module and the pipeline segment external environment hazard monitoring module, and the data processing cloud platform is respectively connected to the pipeline segment self-hazard monitoring module, the pipeline segment external environment hazard monitoring module, the database and the control and early warning display terminal;

[0011] The natural gas transmission pipeline segment division module is used to obtain the length of the natural gas transmission pipeline and divide it into pipeline segments according to the set length intervals to obtain a plurality of pipeline segments;

[0012] The pipeline segment monitoring equipment setting module is used to identify the types of the divided pipeline segments, and then classify the pipeline segments of the same type to obtain a pipeline segment set corresponding to the straight segment type, a pipeline segment set corresponding to the curved segment type, and a pipeline segment set corresponding to the mixed segment type, and set monitoring equipment for each pipeline segment in the above pipeline segment set;

[0013] The pipeline segment self-danger monitoring module is used to perform self-danger monitoring on each divided pipeline segment to obtain the corresponding self-danger coefficient of each pipeline segment, wherein the pipeline segment self-danger monitoring module includes a straight pipeline segment self-danger monitoring unit, a curved pipeline segment self-danger monitoring unit and a mixed pipeline segment self-danger monitoring unit;

[0014] The pipeline segment external environment hazard monitoring module is used to monitor the external environment hazard of each divided pipeline segment to obtain the external environment hazard coefficient corresponding to each pipeline segment;

[0015] The data processing cloud platform is used to evaluate the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment based on the monitoring results of the pipeline segment's own risk monitoring module and the pipeline segment's external environment risk monitoring module;

[0016] The database is used to store the standard three-dimensional appearance image corresponding to each pipeline segment in each type of pipeline segment, the risk impact factor per unit area corresponding to various types of appearance defects, the allowable leakage concentration of natural gas, the precipitation, temperature and wind speed that each pipeline segment can withstand, the wind impact coefficient corresponding to various wind directions, the natural gas flow rate that each curved pipeline segment can withstand, the standard pressure difference between the inside and outside of the pipe wall, and the early warning comprehensive risk factor corresponding to each type of pipeline segment;

[0017] The control and early warning display terminal is used to display the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment, and compare the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment with the early warning comprehensive risk factor corresponding to the pipeline segment of this type in the data storage module. If the comprehensive risk factor corresponding to a pipeline segment in a certain type of pipeline segment is higher than the early warning comprehensive risk factor, an early warning is issued and the number and location information corresponding to the pipeline segment are displayed at the same time.

[0018] To further optimize the technical solution, the straight pipeline segment self-hazard monitoring unit is used to perform self-hazard monitoring on each straight pipeline segment, and the specific detection process includes the following steps:

[0019] A1: Use a high-definition camera to collect 3D images of each linear pipeline segment, and use a gas leakage detector to monitor the natural gas leakage at the interface of each linear pipeline segment, thereby obtaining the corresponding 3D appearance image of each linear pipeline segment and the natural gas leakage concentration at the interface;

[0020] A2: Compare the three-dimensional appearance image corresponding to each straight pipeline segment with the standard three-dimensional appearance image corresponding to each straight pipeline segment in the database, and then extract the appearance defect type and appearance defect area corresponding to each straight pipeline segment, match the appearance defect type of each straight pipeline segment with the hazard impact factor per unit area corresponding to each appearance defect type in the database, and obtain the hazard impact factor per unit area corresponding to the appearance defect type of each straight pipeline segment, and then calculate the appearance defect hazard coefficient of each straight pipeline segment based on this. The calculation formula is: Where a represents the number of the straight pipe segment, a=1,2.......c, β a It is expressed as the appearance defect risk factor of the a-th straight pipeline segment, j a and q a They are respectively expressed as the appearance defect area corresponding to the ath straight pipe segment and the risk impact factor of the unit defect area corresponding to the appearance defect type;

[0021] A3: Compare the interface natural gas leakage concentration corresponding to each straight pipeline section with the allowable natural gas leakage concentration in the database, and calculate the leakage risk factor of each straight pipeline section. The calculation formula is: where λ a It is expressed as the leakage risk factor of the ath straight pipeline section, d a It is represented as the interface natural gas leakage concentration corresponding to the ath straight pipeline segment, and d0 is represented as the allowable leakage concentration of natural gas;

[0022] A4: Based on the appearance defect risk factor and leakage risk factor of each straight pipeline segment, the inherent risk factor of each straight pipeline segment is calculated using the following formula: in Expressed as the inherent hazard coefficient of the ath straight pipeline segment.

[0023] To further optimize the technical solution, the curved pipeline segment self-hazard monitoring unit is used to perform self-hazard monitoring on each curved pipeline segment, wherein the curved pipeline segment self-hazard monitoring unit includes a curved pipeline segment wall impact hazard monitoring subunit, a curved pipeline segment appearance hazard monitoring subunit and a comprehensive analysis subunit.

[0024] To further optimize the technical solution, the curved pipeline segment wall impact hazard monitoring subunit is used to monitor the impact hazard of the wall of each curved pipeline segment, and the specific detection process includes the following steps:

[0025] B1: Monitor the natural gas flow rate of each curved pipeline section through a flow meter, and then obtain the natural gas flow rate in each curved pipeline section;

[0026] B2: Using a pressure sensor to monitor the internal and external pressures of each curved pipe section, obtain the internal and external pressures of the pipe wall corresponding to each curved pipe section, and then perform difference calculation to obtain the internal and external pressure difference of the pipe wall of each curved pipe section;

[0027] B3: Compare the natural gas flow rate in the pipe and the pressure difference between the inner and outer walls of each curved pipe section with the natural gas flow rate and the standard pressure difference between the inner and outer walls of each curved pipe section in the database, and calculate the pipe wall impact risk factor of each curved pipe section. The calculation formula is: Where k represents the number of the curved pipe section, k = 1, 2.......z, ζ k Expressed as the pipe wall impact hazard factor of the kth curved pipe section, V k and F k They are respectively represented as the natural gas flow rate in the kth curved pipeline section and the pressure difference between the inside and outside of the pipe wall, It is expressed as the natural gas flow rate that the k-th curved pipeline section can withstand, F 标 Expressed as the standard pressure difference between the inside and outside of the pipe wall.

[0028] To further optimize the technical solution, the curved pipeline segment appearance hazard monitoring subunit is used to perform hazard monitoring on the appearance of each curved pipeline segment, and the specific detection process includes the following steps:

[0029] C1: Use a high-definition camera to collect three-dimensional images of each curved pipeline segment, and use a gas leakage detector to monitor the natural gas leakage at the interface of each curved pipeline segment, thereby obtaining the corresponding three-dimensional appearance image of each curved pipeline segment and the natural gas leakage concentration at the interface;

[0030] C2: Compare the three-dimensional appearance image corresponding to each curved pipeline segment with the standard three-dimensional appearance image corresponding to each curved pipeline segment in the database, and then extract the appearance defect type and appearance defect area corresponding to each curved pipeline segment, match the appearance defect type of each curved pipeline segment with the hazard impact factor per unit area corresponding to each appearance defect type in the database, and obtain the hazard impact factor per unit area corresponding to the appearance defect type of each curved pipeline segment, and then calculate the appearance defect hazard coefficient of each curved pipeline segment based on this. The calculation formula is: where β k It is expressed as the appearance defect risk factor of the k-th curved pipe section, j k and q k They are respectively expressed as the appearance defect area corresponding to the k-th curved pipe section and the risk impact factor of the unit defect area corresponding to the appearance defect type;

[0031] C3: Compare the interface natural gas leakage concentration corresponding to each curved pipeline section with the allowable natural gas leakage concentration in the database, and calculate the leakage risk factor of each curved pipeline section. The calculation formula is: where λ k It is expressed as the leakage risk factor of the kth curved pipe section, d k It is represented as the interface natural gas leakage concentration corresponding to the k-th curved pipeline section, and d0 is represented as the allowable leakage concentration of natural gas;

[0032] C4: Calculate the apparent risk factor of each curved pipeline section based on the appearance defect risk factor and leakage risk factor of each curved pipeline section. The calculation formula is: where ω k It is expressed as the apparent hazard factor of the kth curved pipe section.

[0033] To further optimize the technical solution, the comprehensive analysis subunit is used to calculate the inherent risk factor of each curved pipeline segment based on the monitoring results of the curved pipeline segment wall impact risk monitoring subunit and the curved pipeline segment appearance risk monitoring subunit, and the calculation formula is: in Expressed as the inherent hazard coefficient of the kth curved pipe section.

[0034] To further optimize the technical solution, the hybrid pipeline segment self-hazard monitoring unit is used to monitor the hazard of each hybrid pipeline segment itself, and the specific detection process includes the following steps:

[0035] E1: Divide each mixing pipe section into a straight part and a curved part;

[0036] E2: Perform self-hazard monitoring on the straight part and the curved part corresponding to each mixed pipeline segment respectively, wherein the self-hazard monitoring method of the straight part is consistent with the self-hazard monitoring method corresponding to the straight pipeline segment, and the self-hazard monitoring method of the curved part is consistent with the self-hazard monitoring method corresponding to the curved pipeline segment, thereby obtaining the hazard coefficients of the straight part and the curved part corresponding to each mixed pipeline segment;

[0037] E3: The self-risk coefficient of each mixed pipeline section is obtained by adding the self-risk coefficient of the straight part and the self-risk coefficient of the curved part corresponding to each mixed pipeline section, which is recorded as Wherein, i represents the number of the mixing pipe section, i=1,2.......n.

[0038] To further optimize the technical solution, the pipeline segment external environment hazard monitoring module is used to monitor the atmospheric environment corresponding to the area to which each pipeline segment belongs, and the specific detection process includes the following steps:

[0039] F1: Monitor the precipitation and temperature of each pipeline section through rain gauges and temperature sensors, and then obtain the corresponding precipitation and temperature;

[0040] F2: Use an anemometer and a wind vane to monitor the wind speed and wind direction of each pipeline section, and then obtain the corresponding wind speed and wind direction angle;

[0041] F3: Match the wind direction angle corresponding to the area to which each pipeline section belongs with the wind impact coefficient corresponding to various wind direction angles in the database to obtain the wind impact coefficient corresponding to the wind direction angle of the area to which each pipeline section belongs, and record it as G g , where g represents the number of each pipeline segment, and g can be a, k, and i;

[0042] F4: Compare the precipitation, temperature and wind speed corresponding to the area to which each pipeline section belongs with the precipitation, temperature and wind speed that each pipeline section can withstand in the database, and calculate the atmospheric environment risk factor corresponding to the area to which each pipeline section belongs. The calculation formula is: where τ g It is expressed as the atmospheric environment hazard coefficient corresponding to the area where the g-th pipeline section belongs, L g , W g and H g They represent the precipitation, temperature and wind speed corresponding to the area where the g-th pipeline segment belongs, respectively. and They respectively represent the precipitation, temperature and wind speed that each pipeline section can withstand.

[0043] To further optimize this technical solution, the calculation formula for the comprehensive risk factor corresponding to each pipeline section is: where ψg Expressed as the comprehensive risk factor corresponding to the g-th pipeline section.

[0044] Compared with the prior art, the embodiments of the present invention have at least the following beneficial effects:

[0045] (1) The present invention realizes the self-hazard monitoring of the natural gas transmission pipeline in multiple dimensions by setting up a high-definition camera, a gas leakage detector, a flow meter and a pressure sensor. Compared with the traditional manual detection method, this monitoring method can detect subtle hazardous problems such as pipeline cracks and deformation, which not only reduces the detection blind area and improves the detection effect, but also provides a stable basis for the hazard monitoring results of the natural gas pipeline and greatly reduces the workload of the detection personnel.

[0046] (2) The present invention conducts intelligent analysis and control of natural gas transmission pipelines based on Internet of Things technology, thus avoiding the long distance and objective uncontrollable factors existing in satellite network detection methods. The amount of data collected is large, and the aging phenomenon of most natural gas pipelines is taken into account, thereby realizing dynamic monitoring of natural gas pipelines, thereby providing reliable monitoring results for natural gas pipelines and overcoming the high maintenance cost problem of satellite networks.

[0047] (3) The present invention also realizes corresponding risk monitoring of the external environment of the natural gas transmission pipeline by setting a rain gauge, a temperature sensor, an anemometer and a wind vane, overcoming the disadvantages of both manual and satellite network detection methods that only focus on risk monitoring of the natural gas transmission pipeline itself. The present invention conducts safety monitoring of the natural gas transmission pipeline from two perspectives: the risk itself and the risk of the external environment, thereby making the safety monitoring results of the natural gas transmission pipeline more comprehensive. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0049] Figure 1 It is a schematic diagram of the system structure connection of the present invention.

[0050] Figure 2 It is a schematic diagram of the connection of the pipeline segment self-hazard monitoring module of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] Reference Figure 1 As shown, the present invention provides an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis, including a natural gas transmission pipeline segment division module, a pipeline segment monitoring equipment setting module, a pipeline segment self-hazard monitoring module, a pipeline segment external environment hazard monitoring module, a data processing cloud platform, a database and a management and control early warning display terminal;

[0053] The pipeline segment monitoring equipment setting module is respectively connected to the natural gas transmission pipeline segment division module, the pipeline segment self-hazard monitoring module and the pipeline segment external environment hazard monitoring module, and the data processing cloud platform is respectively connected to the pipeline segment self-hazard monitoring module, the pipeline segment external environment hazard monitoring module, the database and the control and early warning display terminal;

[0054] The natural gas transmission pipeline segment division module is used to obtain the length of the natural gas transmission pipeline and divide it into pipeline segments according to the set length intervals to obtain a plurality of pipeline segments;

[0055] The pipeline segment monitoring equipment setting module is used to identify the types of the divided pipeline segments, and then classify the pipeline segments of the same type to obtain a pipeline segment set corresponding to the straight segment type, a pipeline segment set corresponding to the curved segment type, and a pipeline segment set corresponding to the mixed segment type, and set monitoring equipment for each pipeline segment in the above pipeline segment set;

[0056] It should be noted that the above-mentioned monitoring equipment settings include installing a high-definition camera in the straight pipeline section and a gas leakage detector at the interface of the straight pipeline section, installing a high-definition camera in the curved pipeline section and a gas leakage detector at the interface of the curved pipeline section, and at the same time installing a flow meter in the curved pipeline section and pressure sensors inside and outside the pipe wall of the curved pipeline section. The monitoring equipment setting for the straight part of the mixed pipeline segment is consistent with that for the straight pipeline segment, and the monitoring equipment setting for the curved part of the mixed pipeline segment is consistent with that for the curved pipeline segment.

[0057] The pipeline segment self-risk monitoring module is used to perform self-risk monitoring on each divided pipeline segment to obtain the corresponding self-risk coefficient of each pipeline segment.

[0058] Reference Figure 2As shown, the pipeline segment self-danger monitoring module includes a straight pipeline segment self-danger monitoring unit, a curved pipeline segment self-danger monitoring unit and a mixed pipeline segment self-danger monitoring unit;

[0059] Specifically, the linear pipeline segment self-danger monitoring unit is used to perform self-danger monitoring on each linear pipeline segment, and the specific detection process includes the following steps:

[0060] A1: Use a high-definition camera to collect 3D images of each linear pipeline segment, and use a gas leakage detector to monitor the natural gas leakage at the interface of each linear pipeline segment, thereby obtaining the corresponding 3D appearance image of each linear pipeline segment and the natural gas leakage concentration at the interface;

[0061] A2: Compare the three-dimensional appearance image corresponding to each straight pipeline segment with the standard three-dimensional appearance image corresponding to each straight pipeline segment in the database, and then extract the appearance defect type and appearance defect area corresponding to each straight pipeline segment, match the appearance defect type of each straight pipeline segment with the hazard impact factor per unit area corresponding to each appearance defect type in the database, and obtain the hazard impact factor per unit area corresponding to the appearance defect type of each straight pipeline segment, and then calculate the appearance defect hazard coefficient of each straight pipeline segment based on this. The calculation formula is: Where a represents the number of the straight pipe segment, a=1,2.......c, β a It is expressed as the appearance defect risk factor of the a-th straight pipeline segment, j a and q a They are respectively expressed as the appearance defect area corresponding to the ath straight pipe segment and the risk impact factor of the unit defect area corresponding to the appearance defect type;

[0062] It should be noted that in the above-mentioned formula for calculating the appearance defect risk factor of each straight pipeline segment, the smaller the product of the appearance defect area corresponding to the a-th straight pipeline segment and the risk impact factor of the unit defect area corresponding to the appearance defect type, the smaller the appearance defect risk factor of the a-th straight pipeline segment, indicating that the appearance of the a-th straight pipeline segment is more in line with the standard;

[0063] A3: Compare the interface natural gas leakage concentration corresponding to each straight pipeline section with the allowable natural gas leakage concentration in the database, and calculate the leakage risk factor of each straight pipeline section. The calculation formula is: where λ a It is expressed as the leakage risk factor of the ath straight pipeline section, d a It is represented as the interface natural gas leakage concentration corresponding to the ath straight pipeline segment, and d0 is represented as the allowable leakage concentration of natural gas;

[0064] It should be noted that in the above leakage risk factor calculation formula of each straight pipeline section, the smaller the difference between the interface natural gas leakage concentration corresponding to the a-th straight pipeline section and the allowable natural gas leakage concentration, the smaller the leakage risk factor of the a-th straight pipeline section, indicating that the interface of the a-th straight pipeline section is more in line with the standard;

[0065] A4: Based on the appearance defect risk factor and leakage risk factor of each straight pipeline segment, the inherent risk factor of each straight pipeline segment is calculated using the following formula: in Expressed as the inherent hazard coefficient of the ath straight pipeline segment.

[0066] It should be noted that, in the calculation formula for the inherent risk coefficient of the above-mentioned straight pipeline segments, the smaller the added value of the appearance defect risk coefficient of the a-th straight pipeline segment and the leakage risk coefficient of the a-th straight pipeline segment, the lower the inherent risk coefficient of the a-th straight pipeline segment, indicating that the a-th straight pipeline segment is more in compliance with the standards.

[0067] Specifically, the curved pipeline segment self-risk monitoring unit is used to perform self-risk monitoring on each curved pipeline segment to obtain the self-risk coefficient of each curved pipeline segment.

[0068] Furthermore, the curved pipeline segment self-hazard monitoring unit includes a curved pipeline segment pipe wall impact hazard monitoring subunit, a curved pipeline segment appearance hazard monitoring subunit and a comprehensive analysis subunit.

[0069] Furthermore, the curved pipeline section pipe wall impact hazard monitoring subunit is used to monitor the pipe wall impact hazard of each curved pipeline section, and the specific detection process includes the following steps:

[0070] B1: Monitor the natural gas flow rate of each curved pipeline section through a flow meter, and then obtain the natural gas flow rate in each curved pipeline section;

[0071] B2: Using a pressure sensor to monitor the internal and external pressures of each curved pipe section, obtain the internal and external pressures of the pipe wall corresponding to each curved pipe section, and then perform difference calculation to obtain the internal and external pressure difference of the pipe wall of each curved pipe section;

[0072] B3: Compare the natural gas flow rate in the pipe and the pressure difference between the inner and outer walls of each curved pipe section with the natural gas flow rate and the standard pressure difference between the inner and outer walls of each curved pipe section in the database, and calculate the pipe wall impact risk factor of each curved pipe section. The calculation formula is: Where k represents the number of the curved pipe section, k = 1, 2.......z, ζ k Expressed as the pipe wall impact hazard factor of the kth curved pipe section, V k and F kThey are respectively represented as the natural gas flow rate in the kth curved pipeline section and the pressure difference between the inside and outside of the pipe wall, It is expressed as the natural gas flow rate that the k-th curved pipeline section can withstand, F 标 Expressed as the standard pressure difference between the inside and outside of the pipe wall.

[0073] It should be noted that, in the calculation formula for the pipe wall impact hazard coefficient of the above-mentioned curved pipeline sections, the smaller the difference between the natural gas flow rate in the pipe and the pressure difference between the inside and outside of the pipe wall of the k-th curved pipeline section and the natural gas flow rate and the standard pressure difference between the inside and outside of the pipe wall that the curved pipeline section can withstand, the smaller the pipe wall impact hazard coefficient of the k-th curved pipeline section, indicating that the pipe wall impact of the k-th curved pipeline section is more in line with the standard.

[0074] Furthermore, the curved pipeline segment appearance hazard monitoring subunit is used to perform hazard monitoring on the appearance of each curved pipeline segment, and the specific detection process includes the following steps:

[0075] C1: Use a high-definition camera to collect three-dimensional images of each curved pipeline segment, and use a gas leakage detector to monitor the natural gas leakage at the interface of each curved pipeline segment, thereby obtaining the corresponding three-dimensional appearance image of each curved pipeline segment and the natural gas leakage concentration at the interface;

[0076] C2: Compare the three-dimensional appearance image corresponding to each curved pipeline segment with the standard three-dimensional appearance image corresponding to each curved pipeline segment in the database, and then extract the appearance defect type and appearance defect area corresponding to each curved pipeline segment, match the appearance defect type of each curved pipeline segment with the hazard impact factor per unit area corresponding to each appearance defect type in the database, and obtain the hazard impact factor per unit area corresponding to the appearance defect type of each curved pipeline segment, and then calculate the appearance defect hazard coefficient of each curved pipeline segment based on this. The calculation formula is: where β k It is expressed as the appearance defect risk factor of the k-th curved pipe section, j k and q k They are respectively expressed as the appearance defect area corresponding to the k-th curved pipe section and the risk impact factor of the unit defect area corresponding to the appearance defect type;

[0077] It should be noted that, in the above-mentioned calculation formula for the appearance defect risk factor of each curved pipe segment, the smaller the product of the appearance defect area corresponding to the k-th curved pipe segment and the risk impact factor of the unit defect area corresponding to the corresponding appearance defect type, the smaller the appearance defect risk factor of the k-th curved pipe segment, indicating that the appearance of the k-th curved pipe segment is more in line with the standard;

[0078] C3: Compare the interface natural gas leakage concentration corresponding to each curved pipeline section with the allowable natural gas leakage concentration in the database, and calculate the leakage risk factor of each curved pipeline section. The calculation formula is: where λ k It is expressed as the leakage risk factor of the kth curved pipe section, d k It is represented as the interface natural gas leakage concentration corresponding to the k-th curved pipeline section, and d0 is represented as the allowable leakage concentration of natural gas;

[0079] It should be noted that in the above-mentioned calculation formula for the leakage risk factor of each curved pipeline section, the smaller the difference between the interface natural gas leakage concentration corresponding to the k-th curved pipeline section and the allowable natural gas leakage concentration, the smaller the leakage risk factor of the k-th curved pipeline section, indicating that the interface of the k-th curved pipeline section is more in line with the standard;

[0080] C4: Calculate the apparent risk factor of each curved pipeline section based on the appearance defect risk factor and leakage risk factor of each curved pipeline section. The calculation formula is: where ω k It is expressed as the apparent hazard factor of the kth curved pipe section.

[0081] It should be noted that, in the calculation formula for the apparent hazard coefficient of the above-mentioned curved pipeline segments, the smaller the added value of the appearance defect hazard coefficient of the k-th curved pipeline segment and the leakage hazard coefficient of the k-th curved pipeline segment, the lower the apparent hazard coefficient of the k-th curved pipeline segment, indicating that the appearance of the k-th curved pipeline segment is more in line with the standard.

[0082] Furthermore, the comprehensive analysis subunit is used to calculate the inherent risk factor of each curved pipeline segment based on the monitoring results of the curved pipeline segment wall impact risk monitoring subunit and the curved pipeline segment appearance risk monitoring subunit, and the calculation formula is: in Expressed as the inherent hazard coefficient of the kth curved pipe section.

[0083] It should be noted that, in the above-mentioned calculation formula for the inherent risk coefficient of each curved pipeline section, the smaller the sum of the apparent risk coefficient of the k-th curved pipeline section and the leakage risk coefficient of the k-th curved pipeline section, the lower the inherent risk coefficient of the k-th curved pipeline section, indicating that the k-th curved pipeline section is more in compliance with the standard.

[0084] Specifically, the hybrid pipeline segment self-hazard monitoring unit is used to perform hazard monitoring on each hybrid pipeline segment itself, and the specific detection process includes the following steps:

[0085] E1: Divide each mixing pipe section into a straight part and a curved part;

[0086] E2: Perform self-hazard monitoring on the straight part and the curved part corresponding to each mixed pipeline segment respectively, wherein the self-hazard monitoring method of the straight part is consistent with the self-hazard monitoring method corresponding to the straight pipeline segment, and the self-hazard monitoring method of the curved part is consistent with the self-hazard monitoring method corresponding to the curved pipeline segment, thereby obtaining the hazard coefficients of the straight part and the curved part corresponding to each mixed pipeline segment;

[0087] E3: The self-risk coefficient of each mixed pipeline section is obtained by adding the self-risk coefficient of the straight part and the self-risk coefficient of the curved part corresponding to each mixed pipeline section, which is recorded as Wherein, i represents the number of the mixing pipe section, i=1,2.......n.

[0088] The embodiment of the present invention realizes the self-hazard monitoring of the natural gas transmission pipeline in multiple dimensions by setting up a high-definition camera, a gas leakage detector, a flow meter and a pressure sensor. Compared with the traditional manual detection method, it can detect subtle hazardous problems such as pipeline cracks and deformation, which not only reduces the detection blind spots and improves the detection effect, but also provides a stability basis for the hazard monitoring results of the natural gas pipeline and greatly reduces the workload of the detection personnel.

[0089] The pipeline segment external environment hazard monitoring module is used to monitor the external environment hazard of each divided pipeline segment to obtain the external environment hazard coefficient corresponding to each pipeline segment;

[0090] Specifically, the pipeline segment external environment hazard monitoring module is used to monitor the atmospheric environment corresponding to the area to which each pipeline segment belongs, and its specific detection process includes the following steps:

[0091] F1: Monitor the precipitation and temperature of each pipeline section through rain gauges and temperature sensors, and then obtain the corresponding precipitation and temperature;

[0092] F2: Use an anemometer and a wind vane to monitor the wind speed and wind direction of each pipeline section, and then obtain the corresponding wind speed and wind direction angle;

[0093] It should be noted that the above wind direction angle is the angle formed between the wind direction and the placement direction of the pipeline section;

[0094] F3: Match the wind direction angle corresponding to the area to which each pipeline section belongs with the wind impact coefficient corresponding to various wind direction angles in the database to obtain the wind impact coefficient corresponding to the wind direction angle of the area to which each pipeline section belongs, and record it as G g , where g represents the number of each pipeline segment, and g can be a, k, and i;

[0095] F4: Compare the precipitation, temperature and wind speed corresponding to the area to which each pipeline section belongs with the precipitation, temperature and wind speed that each pipeline section can withstand in the database, and calculate the atmospheric environment risk factor corresponding to the area to which each pipeline section belongs. The calculation formula is: where τ g It is expressed as the atmospheric environment hazard coefficient corresponding to the area where the g-th pipeline section belongs, L g , W g and H g They represent the precipitation, temperature and wind speed corresponding to the area where the g-th pipeline segment belongs, respectively. and They respectively represent the precipitation, temperature and wind speed that each pipeline section can withstand.

[0096] It should be noted that, in the calculation formula for the atmospheric environment hazard coefficient corresponding to the areas to which the above-mentioned pipeline sections belong, the smaller the difference between the precipitation, temperature and wind speed corresponding to the area to which the g-th pipeline section belongs and the precipitation, temperature and wind speed that each pipeline section can withstand, the smaller the atmospheric environment hazard coefficient corresponding to the area to which the g-th pipeline section belongs, indicating that the atmospheric environment quality corresponding to the area to which the g-th pipeline section belongs is more in line with the standards.

[0097] The embodiment of the present invention realizes corresponding danger monitoring of the external environment of the natural gas transmission pipeline by setting a rain gauge, a temperature sensor, an anemometer and a wind vane, overcoming the disadvantage that both manual and satellite network detection methods only focus on the danger monitoring of the natural gas transmission pipeline itself. The embodiment of the present invention performs safety monitoring of the natural gas transmission pipeline from two perspectives: the danger itself and the danger of the external environment, thereby making the safety monitoring result of the natural gas transmission pipeline more comprehensive.

[0098] The data processing cloud platform is used to evaluate the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment based on the monitoring results of the pipeline segment's own risk monitoring module and the pipeline segment's external environment risk monitoring module;

[0099] Specifically, the calculation formula for the comprehensive risk factor corresponding to each pipeline section is: where ψ g Expressed as the comprehensive risk factor corresponding to the g-th pipeline section.

[0100] It should be noted that in the calculation formula for the comprehensive risk factors corresponding to the above-mentioned pipeline sections, the smaller the product of the inherent risk factor of the g-th pipeline section and the atmospheric environment risk factor corresponding to the area to which the g-th pipeline section belongs, the smaller the comprehensive risk factor corresponding to the g-th pipeline section, indicating that the g-th pipeline section is safer.

[0101] The database is used to store the standard three-dimensional appearance image corresponding to each pipeline segment in each type of pipeline segment, the risk impact factor per unit area corresponding to various types of appearance defects, the allowable leakage concentration of natural gas, the precipitation, temperature and wind speed that each pipeline segment can withstand, the wind impact coefficient corresponding to various wind directions, the natural gas flow rate that each curved pipeline segment can withstand, the standard pressure difference between the inside and outside of the pipe wall, and the early warning comprehensive risk factor corresponding to each type of pipeline segment;

[0102] The control and early warning display terminal is used to display the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment, and compare the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment with the early warning comprehensive risk factor corresponding to the pipeline segment of this type in the data storage module. If the comprehensive risk factor corresponding to a pipeline segment in a certain type of pipeline segment is higher than the early warning comprehensive risk factor, an early warning is issued and the number and location information corresponding to the pipeline segment are displayed at the same time.

[0103] The embodiment of the present invention performs intelligent analysis and control of the natural gas transmission pipeline based on the Internet of Things technology, avoiding the long distance and objective uncontrollable factors existing in the satellite network detection method, and collects a large amount of data. It also takes into account the aging phenomenon of most natural gas pipelines, and realizes dynamic monitoring of the natural gas pipeline, thereby providing a reliable monitoring result for the natural gas pipeline and overcoming the high maintenance cost problem of the satellite network.

[0104] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. An energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis, characterized in that: include: A natural gas transmission pipeline segment division module is used to obtain the length of the natural gas transmission pipeline and divide it into pipeline segments according to a set length interval to obtain a number of pipeline segments; The pipeline segment monitoring equipment setting module is used to identify the types of the divided pipeline segments, and then classify the pipeline segments of the same type to obtain a pipeline segment set corresponding to the straight segment type, a pipeline segment set corresponding to the curved segment type, and a pipeline segment set corresponding to the mixed segment type, and set monitoring equipment for each pipeline segment in the above pipeline segment set; The pipeline segment self-danger monitoring module is used to perform self-danger monitoring on each divided pipeline segment to obtain the corresponding self-danger coefficient of each pipeline segment, wherein the pipeline segment self-danger monitoring module includes a straight pipeline segment self-danger monitoring unit, a curved pipeline segment self-danger monitoring unit and a mixed pipeline segment self-danger monitoring unit; The pipeline section external environment hazard monitoring module is used to monitor the external environment hazard of each divided pipeline section and obtain the external environment hazard coefficient corresponding to each pipeline section; A data processing cloud platform is used to evaluate the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment based on the monitoring results of the pipeline segment's own risk monitoring module and the pipeline segment's external environment risk monitoring module; A database for storing the standard three-dimensional appearance images corresponding to each type of pipeline segment, the risk impact factors per unit area corresponding to various types of appearance defects, the allowable leakage concentration of natural gas, the precipitation, temperature and wind speed that each pipeline segment can withstand, the wind impact coefficient corresponding to various wind directions, the natural gas flow rate that each curved pipeline segment can withstand, the standard pressure difference between the inside and outside of the pipe wall, and the early warning comprehensive risk factor corresponding to each type of pipeline segment; The control and early warning display terminal is used to display the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment, and compare the comprehensive risk factor corresponding to each pipeline segment in each type of pipeline segment with the early warning comprehensive risk factor corresponding to the pipeline segment of this type in the data storage module. If the comprehensive risk factor corresponding to a pipeline segment in a certain type of pipeline segment is higher than the early warning comprehensive risk factor, an early warning is issued and the number and location information corresponding to the pipeline segment are displayed at the same time; The curved pipeline segment self-risk monitoring unit is used to perform self-risk monitoring on each curved pipeline segment, wherein the curved pipeline segment self-risk monitoring unit includes a curved pipeline segment pipe wall impact hazard monitoring subunit, a curved pipeline segment appearance hazard monitoring subunit and a comprehensive analysis subunit; The curved pipeline section pipe wall impact hazard monitoring subunit is used to monitor the pipe wall impact hazard of each curved pipeline section, and its specific detection process includes the following steps: B1: Monitor the natural gas flow rate of each curved pipeline section through a flow meter, and then obtain the natural gas flow rate in each curved pipeline section; B2: Using a pressure sensor to monitor the internal and external pressures of each curved pipe section, obtain the internal and external pressures of the pipe wall corresponding to each curved pipe section, and then perform difference calculation to obtain the internal and external pressure difference of the pipe wall of each curved pipe section; B3: Compare the natural gas flow rate in the pipe and the pressure difference between the inner and outer walls of each curved pipe section with the natural gas flow rate and the standard pressure difference between the inner and outer walls of each curved pipe section in the database, and calculate the pipe wall impact risk factor of each curved pipe section. The calculation formula is: , where k represents the number of the curved pipe segment, k=1,2.......z, Expressed as The pipe wall impact risk factor of a curved pipe section, and Respectively expressed as The natural gas flow rate in the pipe and the pressure difference between the inside and outside of the pipe wall in a curved pipe section are Expressed as The natural gas flow rate that a curved pipe section can withstand, It is expressed as the standard pressure difference between the inside and outside of the pipe wall; The curved pipeline segment appearance hazard monitoring subunit is used to perform hazard monitoring on the appearance of each curved pipeline segment, and the specific detection process includes the following steps: C1: Use a high-definition camera to collect three-dimensional images of each curved pipeline segment, and use a gas leakage detector to monitor the natural gas leakage at the interface of each curved pipeline segment, thereby obtaining the corresponding three-dimensional appearance image of each curved pipeline segment and the natural gas leakage concentration at the interface; C2: Compare the three-dimensional appearance image corresponding to each curved pipeline segment with the standard three-dimensional appearance image corresponding to each curved pipeline segment in the database, and then extract the appearance defect type and appearance defect area corresponding to each curved pipeline segment, match the appearance defect type of each curved pipeline segment with the hazard impact factor per unit area corresponding to each appearance defect type in the database, and obtain the hazard impact factor per unit area corresponding to the appearance defect type of each curved pipeline segment, and then calculate the appearance defect hazard coefficient of each curved pipeline segment based on this. The calculation formula is: ,in Expressed as The appearance defect risk factor of a curved pipe section is and Respectively expressed as The appearance defect area corresponding to each curved pipe section and the risk impact factor of the unit defect area corresponding to the appearance defect type; C3: Compare the interface natural gas leakage concentration corresponding to each curved pipeline section with the allowable natural gas leakage concentration in the database, and calculate the leakage risk factor of each curved pipeline section. The calculation formula is: ,in Expressed as The leakage risk factor of a curved pipe section is Expressed as The natural gas leakage concentration at the interface corresponding to the curved pipeline section is Expressed as the allowable leakage concentration of natural gas; C4: Calculate the apparent risk factor of each curved pipeline section based on the appearance defect risk factor and leakage risk factor of each curved pipeline section. The calculation formula is: ,in Expressed as The apparent hazard factor of a curved pipe section; The comprehensive analysis subunit is used to calculate the inherent risk factor of each curved pipeline segment based on the monitoring results of the curved pipeline segment wall impact risk monitoring subunit and the curved pipeline segment appearance risk monitoring subunit, and the calculation formula is: ,in Expressed as The inherent hazard factor of a curved pipe section.

2. According to claim 1, an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis is characterized in that: The straight pipeline segment self-danger monitoring unit is used to perform self-danger monitoring on each straight pipeline segment, and the specific detection process includes the following steps: A1: Use a high-definition camera to collect 3D images of each linear pipeline segment, and use a gas leakage detector to monitor the natural gas leakage at the interface of each linear pipeline segment, thereby obtaining the corresponding 3D appearance image of each linear pipeline segment and the natural gas leakage concentration at the interface; A2: Compare the three-dimensional appearance image corresponding to each straight pipeline segment with the standard three-dimensional appearance image corresponding to each straight pipeline segment in the database, and then extract the appearance defect type and appearance defect area corresponding to each straight pipeline segment, match the appearance defect type of each straight pipeline segment with the hazard impact factor per unit area corresponding to each appearance defect type in the database, and obtain the hazard impact factor per unit area corresponding to the appearance defect type of each straight pipeline segment, and then calculate the appearance defect hazard coefficient of each straight pipeline segment based on this. The calculation formula is: , where a represents the number of the straight pipe segment, a=1,2.......c, Expressed as The appearance defect risk factor of a straight pipeline section is and Respectively expressed as The appearance defect area corresponding to each straight pipe segment and the risk impact factor of the unit defect area corresponding to the appearance defect type; A3: Compare the natural gas leakage concentration at the interface corresponding to each straight pipeline section with the allowable natural gas leakage concentration in the database, and calculate the leakage risk factor of each straight pipeline section. The calculation formula is: ,in Expressed as The leakage risk factor of a straight pipeline section is Expressed as The natural gas leakage concentration at the interface corresponding to the straight pipeline section is Expressed as the allowable leakage concentration of natural gas; A4: Based on the appearance defect risk factor and leakage risk factor of each straight pipeline segment, the inherent risk factor of each straight pipeline segment is calculated using the following formula: ,in Expressed as The inherent hazard factor of a straight pipeline section.

3. According to claim 1, an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis is characterized in that: The hybrid pipeline segment self-hazard monitoring unit is used to perform hazard monitoring on each hybrid pipeline segment itself, and the specific detection process includes the following steps: E1: Divide each mixing pipe section into a straight part and a curved part; E2: Perform self-hazard monitoring on the straight part and the curved part corresponding to each mixed pipeline segment respectively, wherein the self-hazard monitoring method of the straight part is consistent with the self-hazard monitoring method corresponding to the straight pipeline segment, and the self-hazard monitoring method of the curved part is consistent with the self-hazard monitoring method corresponding to the curved pipeline segment, thereby obtaining the hazard coefficients of the straight part and the curved part corresponding to each mixed pipeline segment; E3: The self-risk coefficient of each mixed pipeline section is obtained by adding the self-risk coefficient of the straight part and the self-risk coefficient of the curved part corresponding to each mixed pipeline section, which is recorded as , where i represents the number of the mixing pipe section, i=1,2.......n.

4. According to claim 1, an energy transmission safety online monitoring cloud platform based on multi-dimensional feature analysis is characterized in that: The pipeline segment external environment hazard monitoring module is used to monitor the atmospheric environment corresponding to the area to which each pipeline segment belongs, and its specific detection process includes the following steps: F1: Monitor the precipitation and temperature of each pipeline section through rain gauges and temperature sensors, and then obtain the corresponding precipitation and temperature; F2: Use an anemometer and a wind vane to monitor the wind speed and wind direction of each pipeline section, and then obtain the corresponding wind speed and wind direction angle; F3: Match the wind direction angle corresponding to the area to which each pipeline section belongs with the wind impact coefficient corresponding to various wind direction angles in the database to obtain the wind impact coefficient corresponding to the wind direction angle of the area to which each pipeline section belongs, and record it as , where g represents the number of each pipeline segment, and g can be a, k, and i; F4: Compare the precipitation, temperature and wind speed corresponding to the area to which each pipeline section belongs with the precipitation, temperature and wind speed that each pipeline section can withstand in the database, and calculate the atmospheric environment risk factor corresponding to the area to which each pipeline section belongs. The calculation formula is: ,in Expressed as The atmospheric environment hazard coefficient corresponding to the area where each pipeline section belongs, , and Respectively expressed as The precipitation, temperature and wind speed corresponding to the area where each pipeline section belongs, , ,and They respectively represent the precipitation, temperature and wind speed that each pipeline section can withstand.

5. The cloud platform for online monitoring of energy transmission safety based on multi-dimensional feature analysis according to claim 1 is characterized in that: The calculation formula for the comprehensive risk factor corresponding to each pipeline section is: ,in Expressed as The comprehensive risk factor corresponding to each pipeline section.

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