Pipeline corrosion depth monitoring system and method based on wireless passive sensor
By using wireless passive sensors and multi-parameter coupled calculation method in the pipeline corrosion monitoring system, the problems of low monitoring efficiency and low accuracy in the prior art are solved, and accurate monitoring and efficient early warning of pipeline corrosion depth are achieved.
Patent Information
- Application Number
- CN202510130451.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-05
- Publication Date
- 2025-05-23
AI Technical Summary
The existing pipeline corrosion monitoring technology has problems such as low efficiency, high cost, and inability to comprehensively and in real-time monitoring, especially in complex environments with low accuracy.
The pipeline corrosion depth monitoring system based on wireless passive sensors is adopted. A variety of physical and chemical parameters are collected in real time through a multi-function wireless passive sensor array. Combined with the data processing and analysis module and early warning module, the pipeline corrosion depth is calculated using a multi-parameter coupled calculation method and sending out early warning signals.
Accurate assessment and real-time monitoring of pipeline corrosion depth are achieved, the accuracy and timeliness of the early warning system are improved, maintenance costs are reduced, and pipeline safety is enhanced.
Smart Images
Figure CN120027752A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of pipeline detection, and in particular to a pipeline corrosion depth monitoring system and method based on a wireless passive sensor. Background Art
[0002] With the continuous advancement of industrialization, pipelines are core facilities in important industries such as oil, natural gas, and chemicals, and their safety and stability are crucial to the production process. Pipeline corrosion is one of the main issues affecting the service life and safety of pipelines. Corrosion not only reduces the strength of pipelines, but may also cause safety accidents such as pipeline rupture and leakage, posing a serious threat to the environment and personnel. The occurrence of corrosion is closely related to environmental factors (such as temperature, humidity, stress), pipeline materials, fluid properties and other factors. Therefore, early detection and accurate assessment of pipeline corrosion depth are of great significance to prevent accidents.
[0003] Existing pipeline corrosion monitoring technologies mainly include regular manual inspections, local detection and electrochemical monitoring. Manual inspections rely on manual inspections and regular maintenance. Although corrosion problems can be discovered in a timely manner, they have shortcomings such as low efficiency, high cost and long cycles. Local detection technologies usually rely on methods such as sound waves, magnetism, and infrared rays, which are suitable for specific areas, but often cannot fully monitor the status of the entire pipeline in real time. In addition, although traditional electrochemical monitoring methods can reflect the electrochemical process of corrosion to a certain extent, they usually only target one aspect of corrosion and have low accuracy in complex environments. Summary of the invention
[0004] In recent years, the application of wireless sensor network technology has provided new ideas for pipeline corrosion monitoring. Wireless passive sensors can collect a variety of physical and chemical parameters inside and outside the pipeline in real time through wireless communication technology, avoiding the limitations of traditional monitoring methods. However, the current pipeline corrosion monitoring technology based on wireless sensors is still in its early stages and faces many challenges, including: how to effectively integrate different types of sensor data, how to accurately evaluate the impact of different environmental factors on corrosion, and how to improve the accuracy and timeliness of the early warning system. In view of this, this application proposes a pipeline corrosion depth monitoring system and method based on wireless passive sensors, aiming to solve the above problems.
[0005] In the first aspect, the present application proposes a pipeline corrosion depth monitoring system based on wireless passive sensors, including a multifunctional wireless passive sensor array, a data processing and analysis module, and an early warning module;
[0006] The multifunctional wireless passive sensor array is configured to acquire real data of the monitoring pipeline in real time; wherein the real data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress;
[0007] The data processing and analysis module is configured to pre-process the actual data and calculate the pipeline corrosion depth based on a multi-parameter coupling calculation formula;
[0008] The early warning module is configured to display the calculation result of the pipeline corrosion depth and issue a corrosion risk early warning signal according to the calculation result.
[0009] Optionally, the multi-parameter coupling calculation formula is:
[0010]
[0011] Among them, d corr Indicates the pipeline corrosion depth value; E noise represents electrochemical noise; J represents local current density; S ij represents the electromagnetic scattering characteristic parameter; H represents the ambient humidity; T represents the ambient temperature; σ represents the pipeline stress; R t represents the solution resistance; f(H, T, σ) represents the joint influence function of ambient humidity, ambient temperature and stress; α, β, γ and δ represent the empirical fitting parameters respectively.
[0012] Optionally, the joint influence function of ambient humidity, ambient temperature and stress is defined as:
[0013] f(H, T, σ) = k 1 H+k 2 T+k 3 σ 2 ;
[0014] Among them, k 1 , k 2 and k 3 They represent the empirical fitting weight coefficients of ambient humidity, ambient temperature and pipeline stress respectively.
[0015] Optionally, calculate the electrochemical noise using the following calculation:
[0016]
[0017] Where N represents the number of sampling points, E i represents the potential value of the i-th sampling point, Represents the average potential value of the sampling point.
[0018] Optionally, calculate the local current density using the following formula:
[0019]
[0020] Where n represents the number of electron transfers; F represents the Faraday constant; M corr represents the mass of corrosion products; A represents the effective area of the electrode; t represents the reaction time.
[0021] Optionally, the electromagnetic scattering characteristic parameters are calculated using the following formula:
[0022]
[0023] Among them, E ref Indicates the reference electromagnetic wave intensity, E meas Indicates the actual measured electromagnetic wave intensity.
[0024] Optionally, the multifunctional wireless passive sensor array includes a capacitive humidity sensor; the capacitive humidity sensor is used to measure and obtain the ambient humidity through the following calculation formula:
[0025]
[0026] Among them, C meas Indicates the capacitance value of the sensor in the current environment; C dry Indicates the capacitance value under dry conditions; C wet Indicates the capacitance value under saturated humidity conditions.
[0027] Optionally, calculate the ambient temperature using the following formula:
[0028]
[0029] Among them, T wet , T dry Represent the corresponding temperature values under humidity and dry conditions respectively.
[0030] Optionally, calculate the pipe stress using the following calculation formula:
[0031]
[0032] Among them, ΔL represents the deformed length of the pipe; L0 represents the original length; and E represents the elastic modulus of the material.
[0033] Optionally, the system also includes: a data acquisition and transmission module; the data acquisition and transmission module is configured to perform preliminary processing on the actual data and transmit it to the edge computing node wirelessly; the preliminary processing of the actual data includes normalizing all the actual data; the normalization method is minimum-maximum normalization.
[0034] Optionally, the early warning module is configured to display the calculation result of the pipeline corrosion depth and issue a corrosion risk early warning signal according to the calculation result, including:
[0035] The calculation results are compared with the pre-set risk threshold range, the corrosion risk warning level is determined based on the comparison results, and a corrosion risk warning signal is issued based on the corrosion risk warning level.
[0036] Optionally, when the early warning module is configured to determine the corrosion risk early warning level according to the comparison result, it includes:
[0037] When 0≤calculated result<0.3, the corrosion risk warning level is determined to be primary;
[0038] When 0.3≤calculated result<1.0, the corrosion risk warning level is determined to be medium;
[0039] When 1.0≤calculated result, the corrosion risk warning level is determined to be high.
[0040] In a second aspect, a pipeline corrosion depth monitoring method based on a wireless passive sensor is provided, which is applied to any pipeline corrosion depth monitoring system based on a wireless passive sensor of the first aspect, including: real-time monitoring and acquisition of actual data of the pipeline; wherein the actual data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress; preprocessing the actual data, and calculating the pipeline corrosion depth based on a multi-parameter coupling calculation formula; displaying the calculation result of the pipeline corrosion depth, and issuing a corrosion risk warning signal according to the calculation result.
[0041] In a third aspect, a pipeline corrosion depth monitoring device based on a wireless passive sensor is provided, comprising a memory and a processor; the memory is used to store computer execution instructions, and the processor is connected to the memory through a bus; when the pipeline corrosion depth monitoring device based on the wireless passive sensor is running, the processor executes the computer execution instructions stored in the memory, so that the pipeline corrosion depth monitoring device based on the wireless passive sensor performs the pipeline corrosion depth monitoring method based on the wireless passive sensor described in the second aspect.
[0042] The pipeline corrosion depth monitoring device based on wireless passive sensors can be a network device, or a part of a network device, such as a chip system in the network device. The chip system is used to support the network device to implement the functions involved in the first aspect and any possible implementation thereof, for example, to obtain, determine, and send the data and / or information involved in the above-mentioned pipeline corrosion depth monitoring method based on wireless passive sensors. The chip system includes a chip, and may also include other discrete devices or circuit structures.
[0043] In a fourth aspect, a computer-readable storage medium is provided, the computer-readable storage medium comprising computer execution instructions, and when the computer execution instructions are executed on a computer, the computer executes the pipeline corrosion depth monitoring method based on wireless passive sensors described in the second aspect.
[0044] In a fifth aspect, a computer program product is also provided, which includes computer instructions. When the computer instructions are run on a pipeline corrosion depth monitoring device based on a wireless passive sensor, the pipeline corrosion depth monitoring device based on a wireless passive sensor performs the pipeline corrosion depth monitoring method based on a wireless passive sensor as described in the second aspect above.
[0045] It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer-readable storage medium may be packaged together with the processor of the pipeline corrosion depth monitoring device based on the wireless passive sensor, or may be packaged separately with the processor of the pipeline corrosion depth monitoring device based on the wireless passive sensor, and the embodiments of the present application are not limited to this.
[0046] The description of the second, third, fourth and fifth aspects of the present application can refer to the detailed description of the first aspect.
[0047] In the embodiments of the present application, the name of the above-mentioned pipeline corrosion depth monitoring device based on wireless passive sensor does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. For example, the receiving unit may also be called a receiving module, a receiver, etc. As long as the functions of each device or functional module are similar to those of the present application, they belong to the scope of the claims of the present application and their equivalent technologies.
[0048] This application discloses a pipeline corrosion depth monitoring system based on wireless passive sensors. The system uses a multi-parameter coupling calculation method to evaluate the corrosion depth of the pipeline in real time and issue an early warning signal. This system significantly improves the accuracy, real-time and comprehensiveness of corrosion monitoring, including:
[0049] 1. Accurately assess corrosion depth
[0050] By integrating multiple sensor data (such as electrochemical noise, current density, humidity, temperature, etc.) and combining it with advanced computational models, this system can accurately assess the corrosion depth of the pipeline. Compared with traditional methods, this system can comprehensively consider multiple influencing factors and provide a more accurate assessment of the corrosion status.
[0051] 2. Real-time monitoring and early warning
[0052] The system can collect and process environmental data around the pipeline in real time and respond quickly to changes in pipeline corrosion. When the corrosion depth reaches the preset risk threshold, the system immediately issues an alarm, prompting the operator or maintenance personnel to take timely repair measures, effectively reducing the possibility of accidents.
[0053] 3. Multi-parameter coupling calculation optimization
[0054] This system adopts a multi-parameter coupling calculation method, and overcomes the limitation that a single parameter cannot fully reflect the corrosion state through comprehensive analysis of multiple monitoring parameters such as electrochemical noise, current density, electromagnetic scattering, humidity, stress, etc. By reasonably weighting the influence of each parameter, the calculation result of the corrosion depth is more reasonable and accurate.
[0055] 4. Improve the adaptability and flexibility of the system
[0056] The system can dynamically adjust various calculation parameters and risk thresholds according to different pipeline environments and material characteristics, and has strong adaptability. Whether it is a city water supply network, oil pipeline, or chemical transportation pipeline, it can be customized according to actual conditions to meet different pipeline monitoring needs.
[0057] 5. Reduce maintenance costs and improve safety
[0058] Wireless passive sensors can achieve long-term stable operation without frequent battery replacement or maintenance, significantly reducing the system's operation and maintenance costs. At the same time, through accurate corrosion monitoring and early warning, major pipeline failures can be effectively avoided, thereby improving pipeline safety and reducing the occurrence of emergencies.
[0059] 6. Data visualization and remote monitoring
[0060] The system can intuitively present monitoring results to users in the form of charts, reports, etc., which is convenient for engineers and maintenance personnel to make decisions. At the same time, the system supports remote monitoring function, which can transmit monitoring data to the remote monitoring platform in real time through wireless network, which is convenient for centralized management and remote fault diagnosis.
[0061] In summary, this application can realize real-time and accurate monitoring of pipeline corrosion depth, provide effective corrosion assessment basis for pipeline managers, and ensure the safe operation of pipelines, which has important engineering application value. BRIEF DESCRIPTION OF THE DRAWINGS
[0062] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present application. Also, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:
[0063] Figure 1 A functional block diagram of a pipeline corrosion depth monitoring system based on a wireless passive sensor provided in an embodiment of the present application;
[0064] Figure 2 A flowchart of a pipeline corrosion depth monitoring method based on a wireless passive sensor provided in an embodiment of the present application;
[0065] Figure 3 A structural block diagram of a pipeline corrosion depth monitoring device based on a wireless passive sensor provided in an embodiment of the present application. DETAILED DESCRIPTION
[0066] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to be able to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.
[0067] See also Figure 1 ,This embodiment provides a pipeline corrosion depth monitoring system based on wireless passive sensors, including a multifunctional wireless passive sensor array, a data processing and analysis module, and an early warning module;
[0068] The multifunctional wireless passive sensor array is configured to monitor and obtain actual data of the pipeline in real time; wherein the actual data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress;
[0069] The data processing and analysis module is configured to pre-process the actual data and calculate the pipeline corrosion depth based on a multi-parameter coupling calculation formula;
[0070] The early warning module is configured to display the calculation result of the pipeline corrosion depth and issue a corrosion risk early warning signal according to the calculation result.
[0071] Optionally, the pipeline corrosion depth monitoring system based on wireless passive sensors also includes: a data acquisition and transmission module; the data acquisition and transmission module is configured to perform preliminary processing on actual data and transmit it to the edge computing node wirelessly.
[0072] It should be noted that when the data processing and analysis module is configured to preprocess the actual data, it can first perform preliminary processing (such as filtering, amplification, normalization, etc.), and then perform preprocessing (such as data format conversion, data fusion, etc.), or it can directly preprocess the actual data.
[0073] It can be seen that this embodiment provides a pipeline corrosion depth monitoring system based on wireless passive sensors, which can monitor and evaluate the corrosion status of the pipeline in real time and accurately, thereby providing guarantee for the safe operation of the pipeline. The system mainly consists of the following parts:
[0074] Multifunctional wireless passive sensor array: This array consists of multiple wireless passive sensors, which are arranged at key locations of the pipeline to monitor multiple key parameters of the pipeline in real time. These parameters include electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, and environmental stress. These data are crucial for assessing the corrosion condition of the pipeline.
[0075] Data acquisition and transmission module: This module is responsible for collecting raw data from the multifunctional wireless passive sensor array and performing preliminary processing on the data, such as filtering, amplification, etc. The processed data is transmitted wirelessly to the edge computing node for further analysis and processing.
[0076] Data processing and analysis module: This module receives data from the data acquisition and transmission module and performs preprocessing, such as data format conversion, data fusion, etc. After that, the module uses a multi-parameter coupling calculation formula to calculate the corrosion depth of the pipeline. The multi-parameter coupling calculation formula is a complex formula that comprehensively considers electrochemical noise, local current density, electromagnetic scattering characteristic parameters, ambient humidity, ambient temperature, pipeline stress, solution resistance, and the combined influence function of ambient humidity, temperature and stress. Among them, α, β, γ, and δ are empirical fitting parameters used to adjust the calculation model to adapt to corrosion conditions under different environmental and material conditions.
[0077] Early warning module: This module is responsible for receiving the calculation results of the data processing and analysis module and displaying them to the user. More importantly, the early warning module will determine whether there is a corrosion risk based on the calculated pipeline corrosion depth value, and issue an early warning signal when necessary to remind the operator to take corresponding maintenance or repair measures.
[0078] Through the collaborative work of the above modules, the pipeline corrosion depth monitoring system of this embodiment can achieve real-time monitoring and risk warning of pipeline corrosion conditions, thereby effectively preventing and reducing accidents caused by pipeline corrosion and ensuring the safe and stable operation of the pipeline.
[0079] It can be understood that this embodiment provides an innovative solution, which not only improves the accuracy of monitoring, but also reduces the physical intervention and maintenance costs of the pipeline through the application of wireless passive sensors. This system is particularly suitable for areas that are difficult to reach or require long-term monitoring, such as underground oil pipelines.
[0080] In practical applications, the system can be seamlessly integrated with existing pipeline maintenance and management processes, providing a scientific basis for pipeline maintenance decisions through real-time data collection and analysis. In addition, the setting of the early warning module ensures that when the corrosion risk reaches a certain threshold, timely measures can be taken to avoid potential safety accidents.
[0081] The system of this embodiment can also continuously optimize its monitoring and early warning model through machine learning algorithms. As data accumulates, the system will become more intelligent and able to more accurately predict and identify corrosion risks, thereby further improving the safety and reliability of pipeline operation.
[0082] In summary, the pipeline corrosion depth monitoring system of this embodiment has significant technical advantages and application value. It can not only effectively monitor and evaluate the corrosion condition of the pipeline, but also ensure the safe operation of the pipeline through an early warning mechanism. It is of great significance to industries such as petroleum, chemical industry, urban water supply and natural gas.
[0083] In some embodiments of the present application, the multi-parameter coupling calculation formula is:
[0084]
[0085] Wherein, dcorr represents the pipeline corrosion depth value; Enoi se represents electrochemical noise; J represents local current density; Si j represents electromagnetic scattering characteristic parameters; H represents ambient humidity; represents ambient temperature; σ represents pipeline stress; Rt represents solution resistance; f(H, T, σ) represents the joint influence function of ambient humidity, ambient temperature and stress; α, β, γ and δ represent empirical fitting parameters respectively.
[0086] In some embodiments of the present application, the combined influence function of ambient humidity, ambient temperature and stress is defined as:
[0087] f(H, T, σ) = k 1 H+k 2 T+k 3 σ 2 ;
[0088] Among them, k1, k2 and k3 represent the empirical fitting weight coefficients of ambient humidity, ambient temperature and pipeline stress respectively.
[0089] It can be understood that this embodiment provides a more accurate calculation method to evaluate the impact of environmental factors on pipeline corrosion. By introducing the empirical fitting weight coefficients k1, k2 and k3, the joint influence function f(H, T, σ) can be adjusted more finely to make it more suitable for actual environmental conditions and pipeline material properties. Such adjustments help to improve the accuracy of corrosion depth calculation and ensure the timeliness and reliability of early warning signals.
[0090] In actual applications, these weight coefficients can be adjusted and optimized based on historical data and field test results to adapt to different environments and pipeline conditions. For example, in a high humidity environment, the value of k1 may increase to reflect the significant effect of humidity on the corrosion rate; similarly, if the pipeline operates under extreme temperature conditions, the value of k2 will also be adjusted accordingly. For the influence of stress, the value of k3 will be adjusted according to the amount of stress the pipeline is subjected to.
[0091] In some embodiments of the present application, the electrochemical noise is calculated by the following formula:
[0092]
[0093] Where N represents the number of sampling points, E i represents the potential value of the i-th sampling point, Represents the average potential value of the sampling point.
[0094] It is understandable that this embodiment discloses an innovative method for accurate measurement of electrochemical noise, which is of vital importance for accurately evaluating and monitoring pipeline corrosion conditions. Through a carefully designed calculation process, we can accurately measure the potential value of each sampling point and compare it with the average potential value to obtain the precise value of electrochemical noise. This method not only significantly improves the accuracy of the data, but also provides the possibility for in-depth analysis and understanding of the corrosion process. In practical applications, by increasing the number of sampling points N, the resolution and accuracy of the measurement can be further improved, providing more solid and reliable data support for real-time monitoring and evaluation of pipeline corrosion. In addition, the calculation method also shows strong adaptability and can be applied to different types of pipeline materials and various complex environmental conditions, thereby ensuring the wide applicability and efficiency of the monitoring system.
[0095] In some embodiments of the present application, the local current density is calculated by the following formula:
[0096]
[0097] Where n represents the number of electron transfers; F represents the Faraday constant; M corr represents the mass of corrosion products; A represents the effective area of the electrode; t represents the reaction time.
[0098] It is understandable that in this embodiment, we have proposed an effective method for evaluating the local corrosion rate. By accurately measuring the mass change of corrosion products and the reaction time, combined with the two important electrochemical parameters of electron transfer number and Faraday constant, we can calculate the local current density. This parameter is of vital importance for a deep understanding of the electrochemical reaction rate during the corrosion process. The accurate calculation of the local current density is of great help in more accurately evaluating the corrosion degree and corrosion rate of the pipeline, thereby providing a scientific basis for the maintenance and repair of the pipeline. In addition, this calculation method is very flexible and can be applied to a variety of different corrosive environments and materials, which greatly enhances the practicality and adaptability of the monitoring system. Through the comprehensive application of these technologies, we can achieve real-time monitoring and long-term prediction of pipeline corrosion conditions, thereby providing a solid guarantee for the safe operation of the pipeline.
[0099] In some embodiments of the present application, the electromagnetic scattering characteristic parameters are calculated by the following calculation formula:
[0100]
[0101] Among them, E ref Indicates the reference electromagnetic wave intensity, E meas Indicates the actual measured electromagnetic wave intensity.
[0102] It can be understood that this embodiment proposes an innovative method that uses the scattering characteristics of electromagnetic waves to monitor and evaluate the corrosion condition of the pipeline. Specifically, by comparing the preset reference electromagnetic wave intensity with the actual measured electromagnetic wave intensity, we can obtain a series of electromagnetic scattering characteristic parameters. These parameters can directly reveal the corrosion state of the pipeline surface, because the corrosion process will cause the surface roughness of the pipeline to change, and this change will directly affect the scattering characteristics of the electromagnetic wave. By deeply analyzing and interpreting these electromagnetic scattering characteristic parameters, we can effectively evaluate and judge the degree of corrosion of the pipeline.
[0103] A significant advantage of this method is that it enables non-contact monitoring of pipelines, which makes it particularly suitable for areas with harsh environmental conditions and difficult to observe directly. In addition, since this technology does not require physical contact with the pipeline during implementation, it will not cause any interference or impact on the normal operation of the pipeline. In order to further improve the accuracy and comprehensiveness of the monitoring system, we also combined the measurement technology of electrochemical noise and local current density to provide a more comprehensive and multi-dimensional analysis framework for pipeline corrosion monitoring. This comprehensive analysis method can not only provide more accurate corrosion assessment, but also help to better understand the complexity of the corrosion process, providing a scientific basis for pipeline maintenance and management.
[0104] In some embodiments of the present application, the multifunctional wireless passive sensor array includes a capacitive humidity sensor; the capacitive humidity sensor is used to measure and obtain the ambient humidity through the following calculation formula:
[0105]
[0106] Among them, C meas Indicates the capacitance value of the sensor in the current environment; C dry Indicates the capacitance value under dry conditions; C wet Indicates the capacitance value under saturated humidity conditions.
[0107] It can be understood that this embodiment introduces an efficient and practical method for monitoring and evaluating the humidity level of the environment around the pipeline. The method involves using one or more sensors to measure the capacitance value in the current environment. These sensors are designed to accurately detect changes in ambient humidity. By comparing and analyzing these measured values with the capacitance values in a pre-set dry environment and the capacitance values under fully saturated humidity conditions, we can accurately calculate the humidity level of the current environment. The accuracy of this method is crucial to understanding the impact of ambient humidity on pipeline corrosion. Because the increase in humidity can significantly accelerate the corrosion process of metal pipelines, accurately monitoring humidity levels is extremely important for assessing the corrosion risk of pipelines and taking preventive measures. By monitoring the humidity changes around the pipeline in real time, we can provide timely and accurate data support for pipeline maintenance and corrosion control, thereby effectively extending the service life of the pipeline. In addition, the implementation of this monitoring technology does not need to rely on complex equipment or high costs, and can be achieved using only capacitive humidity sensors, which makes the entire monitoring system more cost-effective and easy to deploy and use in various environments. Combined with other monitoring parameters, such as the measurement of electrochemical noise, local current density and electromagnetic scattering characteristic parameters, the monitoring of ambient humidity further improves the functionality of the pipeline corrosion monitoring system, ensuring a comprehensive assessment and timely response to pipeline corrosion conditions.
[0108] In some embodiments of the present application, the ambient temperature is calculated by the following formula:
[0109]
[0110] Among them, T wet , T dry Represent the corresponding temperature values under humidity and dry conditions respectively.
[0111] It can be understood that in this embodiment, we have proposed an effective method for monitoring the ambient temperature around the pipeline. This method can accurately calculate the ambient temperature by measuring the temperature values under different humidity conditions. The ambient temperature has a significant effect on the physical and chemical properties of the pipeline material, which directly affects the corrosion rate of the material. For example, an increase in ambient temperature may accelerate the rate of chemical reactions, thereby exacerbating the corrosion process. Therefore, accurate monitoring of ambient temperature is crucial for pipeline maintenance and corrosion control, and it is the key to assessing pipeline corrosion risks and formulating corresponding maintenance strategies. By applying this calculation method, we can monitor the temperature changes around the pipeline in real time and provide timely data support for pipeline maintenance and corrosion control. In addition, the implementation of this technology does not rely on complex equipment and can be achieved only with a temperature sensor, which makes the monitoring system more economical and efficient. Combined with the measurement of electrochemical noise, local current density, electromagnetic scattering characteristic parameters and ambient humidity, the monitoring of ambient temperature further improves the function of the pipeline corrosion monitoring system and ensures a comprehensive assessment of the pipeline corrosion condition.
[0112] In some embodiments of the present application, the pipeline stress is calculated by the following formula:
[0113]
[0114] Among them, ΔL represents the deformed length of the pipe; L0 represents the original length; and E represents the elastic modulus of the material.
[0115] It is understandable that in this embodiment, we propose a method for evaluating and detecting the structural integrity of the pipeline. The method includes accurately measuring the deformed length of the pipeline and its original length, and then using these data and the elastic modulus of the pipeline material to further calculate the stress value of the pipeline. Pipeline stress is a key indicator that can help us determine whether the pipeline has been deformed or damaged. Because if the stress on the pipeline is too high, it may be at risk of rupture or leakage, which poses a potential threat to the safe operation of the pipeline. Through this measurement-based calculation method, we can achieve real-time monitoring of the pipeline stress state, thereby providing necessary safeguards for the safe operation of the pipeline. In addition, the implementation process of this technology does not require physical contact with the pipeline, so it will not cause any interference or impact on the normal operation of the pipeline. Further, combined with the measurement of electrochemical noise, local current density, electromagnetic scattering characteristic parameters, ambient humidity and ambient temperature, we can further improve the monitoring of pipeline stress. Such a comprehensive monitoring method further enhances the function of the pipeline corrosion monitoring system, ensures a comprehensive assessment of the pipeline corrosion condition and its structural integrity, and thus provides a more solid guarantee for the long-term safe operation of the pipeline.
[0116] In some embodiments of the present application, the data acquisition and transmission module is configured to perform preliminary processing on the actual data and transmit it to the edge computing node wirelessly; the preliminary processing of the actual data includes normalizing all the actual data; the normalization method is minimum-maximum normalization.
[0117] It is understandable that this embodiment introduces a data preprocessing technology that aims to improve the comparability and accuracy of monitoring data. By performing minimum-maximum normalization processing, data of different magnitudes and ranges can be uniformly converted to the same scale, thereby making subsequent data analysis and processing more efficient. Normalization processing helps to eliminate the dimensional differences between different sensor data, making the data more intuitive and convenient when comparing and analyzing. In addition, the normalized data is convenient for applying various algorithms for pattern recognition and trend analysis, which is of vital importance for real-time monitoring and prediction of pipeline corrosion status. Using this data preprocessing method can ensure that the monitoring system can more accurately assess the corrosion condition of the pipeline and provide a scientific basis for maintenance decisions.
[0118] In some embodiments of the present application, the early warning module is configured to display the calculation result of the pipeline corrosion depth and issue a corrosion risk early warning signal according to the calculation result, including:
[0119] The calculation results are compared with the pre-set risk threshold range, the corrosion risk warning level is determined based on the comparison results, and a corrosion risk warning signal is issued based on the corrosion risk warning level.
[0120] In some embodiments of the present application, when the early warning module is configured to determine the corrosion risk early warning level according to the comparison result, it includes:
[0121] When 0≤calculated result<0.3, the corrosion risk warning level is determined to be primary;
[0122] When 0.3≤calculated result<1.0, the corrosion risk warning level is determined to be medium;
[0123] When 1.0≤calculated result, the corrosion risk warning level is determined to be high.
[0124] In some embodiments, Figure 2 As shown, the embodiment of the present application also provides a pipeline corrosion depth monitoring method based on a wireless passive sensor, which is applied to the above Figure 1 The pipeline corrosion depth monitoring system based on wireless passive sensors includes:
[0125] S201. Monitor and obtain actual data of the pipeline in real time.
[0126] The actual data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress;
[0127] S202, preprocessing actual data, and calculating pipeline corrosion depth based on a multi-parameter coupling calculation formula.
[0128] S203. Display the calculation result of the pipeline corrosion depth, and issue a corrosion risk warning signal according to the calculation result.
[0129] Optionally, the multi-parameter coupling calculation formula is:
[0130]
[0131] Among them, d corr Indicates the pipeline corrosion depth value; E noise represents electrochemical noise; J represents local current density; S ij represents the electromagnetic scattering characteristic parameter; H represents the ambient humidity; T represents the ambient temperature; σ represents the pipeline stress; R t represents the solution resistance; f(H, T, σ) represents the joint influence function of ambient humidity, ambient temperature and stress; α, β, γ and δ represent the empirical fitting parameters respectively.
[0132] Optionally, the joint influence function of ambient humidity, ambient temperature and stress is defined as:
[0133] f(H, T, σ) = k 1 H+k 2 T+k 3 σ 2 ;
[0134] Among them, k 1 , k 2 and k 3 They represent the empirical fitting weight coefficients of ambient humidity, ambient temperature and pipeline stress respectively.
[0135] Optionally, calculate the electrochemical noise using the following calculation:
[0136]
[0137] Where N represents the number of sampling points, E i represents the potential value of the i-th sampling point, Represents the average potential value of the sampling point.
[0138] Optionally, calculate the local current density using the following formula:
[0139]
[0140] Where n represents the number of electron transfers; F represents the Faraday constant; M corr represents the mass of corrosion products; A represents the effective area of the electrode; t represents the reaction time.
[0141] Optionally, the electromagnetic scattering characteristic parameters are calculated using the following formula:
[0142]
[0143] Among them, E ref Indicates the reference electromagnetic wave intensity, E meas Indicates the actual measured electromagnetic wave intensity.
[0144] Optionally, the actual data of the pipeline can be obtained through a multifunctional wireless passive sensor array. The multifunctional wireless passive sensor array includes a capacitive humidity sensor; the capacitive humidity sensor is used to measure and obtain the ambient humidity through the following calculation formula:
[0145]
[0146] Among them, C meas Indicates the capacitance value of the sensor in the current environment; C dry Indicates the capacitance value under dry conditions; C wet Indicates the capacitance value under saturated humidity conditions.
[0147] Optionally, calculate the ambient temperature using the following formula:
[0148]
[0149] Among them, T wet , T dry Represent the corresponding temperature values under humidity and dry conditions respectively.
[0150] Optionally, calculate the pipe stress using the following calculation formula:
[0151]
[0152] Among them, ΔL represents the deformed length of the pipe; L0 represents the original length; and E represents the elastic modulus of the material.
[0153] Optionally, the method further includes:
[0154] S204: Perform preliminary processing on the actual data and transmit it to the edge computing node via wireless means.
[0155] The preliminary processing of the actual data includes normalizing all the actual data; the normalization method is minimum-maximum normalization.
[0156] Optionally, the calculation results of pipeline corrosion depth are displayed, and a corrosion risk warning signal is issued based on the calculation results, including:
[0157] The calculation results are compared with the pre-set risk threshold range, the corrosion risk warning level is determined based on the comparison results, and a corrosion risk warning signal is issued based on the corrosion risk warning level.
[0158] Optionally, when determining the corrosion risk warning level based on the comparison results, it includes:
[0159] When 0≤calculated result<0.3, the corrosion risk warning level is determined to be primary;
[0160] When 0.3≤calculated result<1.0, the corrosion risk warning level is determined to be medium;
[0161] When 1.0≤calculated result, the corrosion risk warning level is determined to be high.
[0162] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, it includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.
[0163] The embodiment of the present application can divide the functional modules of the pipeline corrosion depth monitoring device based on the wireless passive sensor according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware or in the form of software functional modules. Optionally, the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.
[0164] like Figure 3 , which is a schematic structural diagram of a pipeline corrosion depth monitoring device based on a wireless passive sensor provided in an embodiment of the present application. Figure 3 The pipeline corrosion depth monitoring device based on wireless passive sensor includes: a communication unit 301, a processing unit 302 and a display unit 303;
[0165] The communication unit 301 is used to obtain the actual data of the monitoring pipeline in real time; wherein the actual data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress;
[0166] The processing unit 302 is used to pre-process the actual data and calculate the pipeline corrosion depth based on the multi-parameter coupling calculation formula;
[0167] The display unit 303 is used to display the calculation result of the pipeline corrosion depth and issue a corrosion risk warning signal according to the calculation result.
[0168] Optionally, the multi-parameter coupling calculation formula is:
[0169]
[0170] Among them, d corr Indicates the pipeline corrosion depth value; E noise represents electrochemical noise; J represents local current density; S ij represents the electromagnetic scattering characteristic parameter; H represents the ambient humidity; T represents the ambient temperature; σ represents the pipeline stress; R t represents the solution resistance; f(H, T, σ) represents the joint influence function of ambient humidity, ambient temperature and stress; α, β, γ and δ represent the empirical fitting parameters respectively.
[0171] Optionally, the joint influence function of ambient humidity, ambient temperature and stress is defined as:
[0172] f(H, T, σ) = k 1 H+k 2 T+k 3 σ 2 ;
[0173] Among them, k 1 , k 2 and k 3 They represent the empirical fitting weight coefficients of ambient humidity, ambient temperature and pipeline stress respectively.
[0174] Optionally, calculate the electrochemical noise using the following calculation:
[0175]
[0176] Where N represents the number of sampling points, E i represents the potential value of the i-th sampling point, Represents the average potential value of the sampling point.
[0177] Optionally, calculate the local current density using the following formula:
[0178]
[0179] Where n represents the number of electron transfers; F represents the Faraday constant; M corr represents the mass of corrosion products; A represents the effective area of the electrode; t represents the reaction time.
[0180] Optionally, the electromagnetic scattering characteristic parameters are calculated using the following formula:
[0181]
[0182] Among them, E ref Indicates the reference electromagnetic wave intensity, E meas Indicates the actual measured electromagnetic wave intensity.
[0183] Optionally, the actual data of the monitoring pipeline can be obtained by a multifunctional wireless passive sensor array; the multifunctional wireless passive sensor array includes a capacitive humidity sensor; the capacitive humidity sensor is used to measure and obtain the ambient humidity through the following calculation formula:
[0184]
[0185] Among them, C meas Indicates the capacitance value of the sensor in the current environment; C dry Indicates the capacitance value under dry conditions; C wet Indicates the capacitance value under saturated humidity conditions.
[0186] Optionally, calculate the ambient temperature using the following formula:
[0187]
[0188] Among them, T wet , T dry Represent the corresponding temperature values under humidity and dry conditions respectively.
[0189] Optionally, calculate the pipe stress using the following calculation formula:
[0190]
[0191] Among them, ΔL represents the deformed length of the pipe; L0 represents the original length; and E represents the elastic modulus of the material.
[0192] Optionally, the communication unit 301 is also used to perform preliminary processing on the actual data and transmit it to the edge computing node wirelessly; the preliminary processing on the actual data includes normalizing all the actual data; the normalization method is minimum-maximum normalization.
[0193] Optionally, the processing unit 302 is specifically configured to:
[0194] The calculation results are compared with the pre-set risk threshold range, the corrosion risk warning level is determined based on the comparison results, and a corrosion risk warning signal is issued based on the corrosion risk warning level.
[0195] Optionally, the processing unit 302 is specifically configured to:
[0196] When 0≤calculated result<0.3, the corrosion risk warning level is determined to be primary;
[0197] When 0.3≤calculated result<1.0, the corrosion risk warning level is determined to be medium;
[0198] When 1.0≤calculated result, the corrosion risk warning level is determined to be high.
[0199] An embodiment of the present application also provides a computer-readable storage medium, which includes computer execution instructions. When the computer execution instructions are executed on a computer, the computer executes the pipeline corrosion depth monitoring method based on wireless passive sensors as provided in the above embodiment.
[0200] The embodiment of the present application also provides a computer program product, which can be directly loaded into a memory and contains software code. After being loaded and executed by a computer, the computer program product can implement the pipeline corrosion depth monitoring method based on a wireless passive sensor provided in the above embodiment. Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention is described in detail with reference to the preferred embodiments, ordinary technicians in this field should understand that they can still modify or replace the technical solution of the present invention, and these modifications or equivalent replacements cannot make the modified technical solution deviate from the spirit and scope of the technical solution of the present invention.
[0201] The system provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the modules or steps in the embodiments of the present invention can be decomposed or combined. For example, the modules in the above embodiment can be combined into one module, or further divided into multiple sub-modules to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not regarded as improper limitations of the present invention.
[0202] Those skilled in the art should be able to appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two, and the programs corresponding to the software modules and method steps can be placed in random access memory (RAM), internal memory, read-only memory (ROM), electrically erasable programmable ROM, registers, hard disks, removable disks, CD-ROMs or any other form of storage medium known in the technical field. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.
Claims
1. A pipeline corrosion depth monitoring system based on wireless passive sensor, characterized in that: It includes a multifunctional wireless passive sensor array, a data processing and analysis module, and an early warning module; The multifunctional wireless passive sensor array is configured to monitor and acquire actual data of the pipeline in real time; wherein the actual data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress; The data processing and analysis module is configured to pre-process the actual data and calculate the pipeline corrosion depth based on a multi-parameter coupling calculation formula; The early warning module is configured to display the calculation result of the pipeline corrosion depth and issue a corrosion risk early warning signal according to the calculation result.
2. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 1 is characterized in that: The multi-parameter coupling calculation formula is: Among them, d corr Indicates the pipeline corrosion depth value; E noise represents electrochemical noise; J represents local current density; S ij represents the electromagnetic scattering characteristic parameters; H represents ambient humidity; T represents ambient temperature; σ represents pipeline stress; Rt represents solution resistance; f(H, T, σ) represents the joint influence function of ambient humidity, ambient temperature and stress; α, β, γ and δ represent empirical fitting parameters respectively.
3. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 2 is characterized in that: The combined influence function of ambient humidity, ambient temperature and stress is defined as: f(H, T, σ)=k1H+k2T+k3σ 2 ; Among them, k1, k2 and k3 represent the empirical fitting weight coefficients of ambient humidity, ambient temperature and pipeline stress respectively.
4. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 2 is characterized in that: The electrochemical noise is calculated by the following formula: Where N represents the number of sampling points, Ei represents the potential value of the i-th sampling point, Represents the average potential value of the sampling point.
5. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 2 is characterized in that: The local current density is calculated by the following formula: Where n represents the number of electron transfers; F represents the Faraday constant; M corr represents the mass of corrosion products; A represents the effective area of the electrode; t represents the reaction time.
6. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 2 is characterized in that: The electromagnetic scattering characteristic parameters are calculated by the following formula: Among them, E ref Indicates the reference electromagnetic wave intensity, E meas Indicates the actual measured electromagnetic wave intensity.
7. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 2 is characterized in that: The multifunctional wireless passive sensor array includes a capacitive humidity sensor; the capacitive humidity sensor is used to measure and obtain the ambient humidity through the following calculation formula: Among them, C meas Indicates the capacitance value of the sensor in the current environment; C dry Indicates the capacitance value under dry conditions; C wet Indicates the capacitance value under saturated humidity conditions.
8. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 7 is characterized in that: The ambient temperature is calculated by the following formula: Among them, T wet , T dry Represent the corresponding temperature values under humidity and dry conditions respectively.
9. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 2 is characterized in that: The pipeline stress is calculated by the following formula: Among them, ΔL represents the deformed length of the pipe; L0 represents the original length; and E represents the elastic modulus of the material.
10. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 1 is characterized in that: Also includes: Data acquisition and transmission module; The data acquisition and transmission module is configured to perform preliminary processing on the actual data and transmit it to the edge computing node wirelessly; The preliminary processing of the actual data includes normalizing all the actual data; the normalization method is minimum-maximum normalization.
11. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 1 is characterized in that: The early warning module is configured to display the calculation result of the pipeline corrosion depth and issue a corrosion risk early warning signal according to the calculation result, including: The calculation result is compared with a preset risk threshold range, the corrosion risk warning level is determined according to the comparison result, and a corrosion risk warning signal is issued according to the corrosion risk warning level.
12. The pipeline corrosion depth monitoring system based on wireless passive sensor according to claim 11 is characterized in that: When the early warning module is configured to determine the corrosion risk early warning level according to the comparison result, it includes: When 0≤calculated result<0.3, the corrosion risk warning level is determined to be primary; When 0.3≤calculated result<1.0, the corrosion risk warning level is determined to be medium; When 1.0≤the calculated result, the corrosion risk warning level is determined to be high.
13. A pipeline corrosion depth monitoring method based on wireless passive sensor, characterized in that: include: Real-time monitoring and acquisition of actual data of the pipeline; wherein the actual data includes at least one of electrochemical noise, local current density, electromagnetic scattering characteristics, ambient humidity, ambient temperature and ambient stress; Preprocessing the actual data, and calculating the pipeline corrosion depth based on a multi-parameter coupling calculation formula; The calculation result of the pipeline corrosion depth is displayed, and a corrosion risk warning signal is issued according to the calculation result.