Intelligent high-temperature and high-pressure pipeline system based on perception-calculation-configuration-repair integration

Abstract

The invention discloses an intelligent high-temperature and high-pressure pipeline system based on perception-calculation-configuration-repair integration, which comprises a pipeline body, and a perception-structure layer, an intelligent calculation-decision layer and a driving-repair layer which are integrally arranged with the pipeline body, and is characterized in that the perception-structure layer comprises a sensor network for collecting physical field information of the pipeline body in real time; the intelligent calculation-decision-making layer comprises calculation nodes for processing and diagnosing physical field information in real time, the driving-repairing layer comprises a repairing material and a repairing driving network which are arranged on the pipeline body, and the repairing driving network excites the repairing material to complete repairing of the damaged part of the pipeline body. Through the integrated design, the pipeline has the whole-course autonomous ability from damage perception, intelligent diagnosis to active repair, the fundamental defects of function separation, information lag and lack of repair ability of a traditional pipeline monitoring system are overcome, and the reliability, the safety and the operation and maintenance efficiency of the pipeline system are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent structures and marine propulsion system safety technology, and in particular to an intelligent high-temperature and high-pressure pipeline system capable of integrating self-sensing, self-diagnosis, self-decision-making, and self-repair functions. Background Technology

[0002] In fields such as marine propulsion systems, high-temperature and high-pressure pipelines (such as exhaust manifolds and steam pipelines) operate under harsh conditions for extended periods, and their failure modes are primarily caused by the initiation and propagation of fatigue cracks. Currently, safety monitoring of such pipelines mainly relies on externally attached sensing systems, which have the following inherent drawbacks: First, there is functional separation. This is mainly reflected in the fact that sensing, diagnostic, and repair functions are independent of each other, the system structure is complex, and the interfaces and connections between modules become weak links in the reliability chain.

[0003] Second, there is information lag. This is mainly reflected in the fact that the data collected by the sensors needs to be transmitted to a remote central processing system for analysis, resulting in long decision-making delays and making it difficult to meet the needs of real-time intervention for instantaneous risks such as crack initiation.

[0004] Third, there is a lack of proactive repair capabilities. This is mainly reflected in the fact that most existing technologies only have an "alarm" function and cannot directly "handle" damage on-site, thus failing to form a complete safety loop.

[0005] The academic community has conducted some explorations in the field of smart materials and structures. For example, structural health monitoring (SHM) technology monitors the condition of structures by embedding sensors (such as fiber optic gratings) in them, but its data processing usually relies on external systems, operating in an open-loop mode and lacking repair capabilities. Self-healing material technologies (such as microcapsules and shape memory alloys driving crack closure) focus on the passive response of materials, lacking intelligent perception and decision-making processes. Furthermore, although there is a macroscopic concept of "smart structures"—structures that can not only bear loads but also sense and respond to environmental changes—specific implementation schemes mostly remain at the conceptual stage or simple functional demonstrations (such as sensing or driving only). Achieving closed-loop autonomy in complex industrial pressure-bearing equipment such as high-temperature and high-pressure pipelines through deep integrated design of sensing, computing, and repair functions remains a gap in the current technological field.

[0006] Therefore, there is an urgent need for a new type of intelligent pipeline system that can fundamentally solve the above problems and achieve integrated real-time perception, intelligent decision-making and proactive repair. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of existing technologies and provide an intelligent high-temperature and high-pressure pipeline system based on the integration of "sensing-computing-configuration-repair". This system aims to incorporate sensing, computing, and repair functions as inherent attributes of the pipeline from the design stage, constructing a closed-loop autonomous system capable of real-time self-assessment of its own status, intelligent decision-making, and proactive repair, thereby fundamentally improving the pipeline's end-side safety control capabilities.

[0008] To achieve the above objectives, the present invention adopts the following technical solution.

[0009] An intelligent high-temperature and high-pressure pipeline system based on integrated sensing-computation-configuration-repair includes a pipeline body. The pipeline body is equipped with a sensing-structure layer, an intelligent computing-decision layer, and a drive-repair layer, all communicating via a communication network. The perception-structure layer includes a sensor network deployed on the pipe wall of the pipeline body, which is used to collect the physical field information of the pipeline body in real time and transmit the physical field information to the intelligent computing-decision layer; The intelligent computing-decision layer includes computing nodes that communicate with the sensor network to process and diagnose physical field information in real time and generate processing instructions. The drive-repair layer includes repair materials laid on the pipeline body and a repair drive network that drives the repair materials to repair the pipeline body; After receiving the processing instruction, the drive-repair layer sends a repair instruction to the repair drive network. After receiving the repair instruction, the repair drive network excites the repair material to complete the repair of the damaged parts of the pipeline body.

[0010] In some embodiments, the sensing-structure layer includes a structural body, which is embedded in the pipe body wall material in a functional-structural integrated manner with the sensor network.

[0011] In some embodiments, the sensor network is a micro / nano sensor network, deployed along the critical mechanical path of the pipe body wall.

[0012] In some embodiments, the micro / nano sensor network is a fiber optic grating sensor array.

[0013] In some embodiments, the computing node is a miniature edge computing node with a built-in lightweight AI algorithm model.

[0014] In some embodiments, the AI ​​algorithm model can identify the characteristic patterns of microcrack initiation and locate and assess the risk level of the cracks.

[0015] In some embodiments, the repair material is a shape memory alloy. The repair drive network electrically excites the shape memory alloy to undergo a phase transition and generate recovery stress, thereby completing the repair of the damaged parts of the pipeline body.

[0016] In some embodiments, the perception-structure layer, intelligent computing-decision layer, and drive-repair layer are integrated and planned in the design phase of the pipeline body, and their spatial distribution is integrated with the structural stress model of the pipeline body.

[0017] In some embodiments, the communication network is an internally integrated link, through which the system interacts with information and transmits instructions, realizing perception as computation and decision as execution.

[0018] In some embodiments, the system employs additive manufacturing or micro-packaging technologies to achieve integrated processing of the sensing-structure layer, intelligent computing-decision layer, drive-repair layer, and pipeline body.

[0019] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) System-level reliability: The functional modules interact through internal integrated links, avoiding complex external wiring and interfaces, with strong anti-interference ability and overall system reliability far higher than that of traditional patchwork systems.

[0020] (2) Real-time proactive safety: It realizes millisecond-level rapid response from damage perception to repair execution, transforming passive alarm into proactive intervention, and can contain potential safety hazards in the bud.

[0021] (3) Full life cycle management: The system continuously records the health data and repair history of the pipeline, providing accurate data support for predictive maintenance and greatly optimizing operation and maintenance costs and strategies.

[0022] (4) Design-led manufacturing: This invention first defines a complete system architecture and functional standards. Specific manufacturing processes (such as additive manufacturing and micro-packaging technology) are optional technical paths to achieve the design goal, which makes the solution more universal and forward-looking. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the overall architecture of the intelligent high-temperature and high-pressure pipeline system of the present invention; Figure 2 A schematic diagram of the sensor network deployment in the perception-structure layer; Figure 3 This is a schematic diagram illustrating the working principle of the present invention; Explanation of reference numerals in the attached drawings: Pipeline body 1, Structural body 21, Sensor network 22, Communication network 3, Repair drive network 41, Repair material 42. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0025] In the description of this invention, it should be understood that the terms "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and "circumferential," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. The interpretation of such terms should be made from the perspective of a person skilled in the art. For example, "above" or "below" should be understood as the positional relationship of the main structure or structure of a component, etc., in its initial state, which may be broken during movement. "...set on" should be understood as the general connection relationship of the components, not necessarily above.

[0026] In this invention, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly from the perspective of someone skilled in the art. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0027] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0028] refer to Figure 1-2In some embodiments of the present invention, an intelligent high-temperature and high-pressure pipeline system based on integrated sensing-computation-configuration-repair is proposed, the core of which lies in the design concept of distributed intelligence and closed-loop control. The system deeply integrates three functional layers on the pipeline body 1, logically forming a complete intelligent processing closed loop. The three functional layers, from the inside out or functionally, are "sensing-structure layer, intelligent computing-decision layer, and drive-repair layer," and communicate through a communication network 3. 1. Perception-Structure Layer.

[0029] The perception-structure layer includes a sensor network 22 deployed on the pipe wall of the pipe body 1, which is used to collect physical field information (such as strain, vibration, temperature, etc.) of the pipe body 1 in real time and transmit the physical field information to the intelligent computing-decision layer.

[0030] In some embodiments, the sensing-structure layer serves as both the load-bearing main body and the sensory nerve endings of the pipeline body 1. In other words, the sensing-structure layer also includes a structural body 21, which, along with the sensor network 22, is embedded in the pipe wall material of the pipeline body 1 in a functional-structural integrated manner. In this embodiment, the sensor network 22 is a sensing element used to collect physical field information such as strain, vibration, and temperature across the entire pipeline in real time. Simultaneously, the structural body 21 serves as a reinforcing phase, constituting part of the structure of the pipeline body 1.

[0031] In some embodiments, the sensor network 22 is a micro-nano sensor network, which is deployed on the critical mechanical path of the pipe body 1 (e.g., near bends and welds).

[0032] In some embodiments, the micro / nano sensor network is preferably a fiber Bragg grating sensor array.

[0033] 2. Intelligent computing - decision-making layer.

[0034] As the intelligent brain of the pipeline system, the intelligent computing-decision layer includes computing nodes that are connected to the sensor network 22 to process and diagnose physical field information in real time and generate processing instructions.

[0035] In some embodiments, the computing nodes are miniature edge computing nodes with built-in lightweight AI algorithm models. These miniature edge computing nodes are physically integrated with the sensor network 22 of the perception-structure layer. Each edge computing node has a built-in lightweight AI algorithm model to process real-time data from its assigned sensor network 22, enabling localized intelligent diagnostics. This includes identifying characteristic patterns of microcrack initiation and accurately locating and assessing the risk level of cracks by running a trained AI algorithm model. This design allows for real-time data processing at the point of origin, minimizing decision latency.

[0036] 3. Driver-Repair Layer.

[0037] As the actuator of the pipeline system, the drive-repair layer includes repair material 42 laid on the pipeline body 1 and repair drive network 41 that drives the repair material 42 to repair the pipeline body 1. After receiving the processing instruction, the drive-repair layer sends a repair instruction to the repair drive network 41. After receiving the repair instruction, the repair drive network 41 excites the repair material 42 to complete the repair of the damaged parts of the pipeline body 1.

[0038] In some embodiments, the repair material 42 is a shape memory alloy, and the repair driving network 41 is a shape memory alloy driving network, which is deployed in areas of the pipeline body 1 that are prone to cracking. When the intelligent computing-decision layer determines that damage has occurred at a certain location, the driving-repair layer immediately sends a repair command to the shape memory alloy driving network in the corresponding area. Under electrical excitation, the shape memory alloy undergoes a phase transition, generating recovery stress, which actively applies mechanical pressure to the crack, inhibiting its propagation, thereby achieving in-situ self-repair.

[0039] In some embodiments, the perception-structure layer, intelligent computing-decision layer, and drive-repair layer are integrated and planned in the design phase of the pipeline body 1, and their spatial distribution is integrated with the structural stress model of the pipeline body 1.

[0040] In some embodiments, the communication network 3 is an internal integrated link, through which the system performs information interaction and command transmission, realizing perception as computation and decision as execution.

[0041] In some embodiments, the system employs additive manufacturing or micro-packaging technology to achieve integrated processing of the sensing-structure layer, intelligent computing-decision layer, drive-repair layer, and pipeline body 1.

[0042] The intelligence of this invention, based on an integrated sensing-computing-configuration-repair intelligent high-temperature and high-pressure pipeline system, is manifested in the collaborative working mechanism of each functional layer, forming an autonomous closed loop: Integrated perception and computing: The raw data acquired by the perception-structure layer does not need to be transmitted over long distances. It is directly processed by nearby computing nodes, realizing perception as computing and ensuring real-time response.

[0043] Integrated computation and repair: The diagnostic decisions of the intelligent computation-decision layer are directly transformed into repair instructions for the drive-repair layer, which are triggered instantly through the internal integrated control circuit, realizing the execution of decisions.

[0044] Configuration-Function Integration: All intelligent units (sensing, computing, and driving) are laid out and planned as necessary functional components during the pipeline system design phase. Their spatial distribution, interface relationships, and structural stress model of the pipeline are deeply integrated, so that the intelligent pipeline system is designed and manufactured as a complete system product, rather than a simple superposition of "basic pipeline" and "intelligent accessories".

[0045] refer to Figure 3 The working principle of this invention is as follows: 1. Information input and perception stage.

[0046] Micro-nano sensor networks (such as fiber optic grating sensor arrays) act as the "nerve endings" of the system, acquiring real-time physical field information of the pipeline body 1 under high temperature and high pressure conditions, including multi-dimensional data such as strain, vibration, and temperature. This raw monitoring data serves as the initial input of the system and is transmitted to the next processing stage.

[0047] 2. Intelligent computing and decision-making stage.

[0048] Data collected at the perception-structure layer is directly input to the micro-edge computing nodes at the intelligent computing-decision layer. Each computing node runs a built-in lightweight AI algorithm model to perform real-time fusion analysis and intelligent diagnosis of sensor data within its jurisdiction. Through pattern recognition technology, the system can accurately identify microcrack initiation characteristics, complete damage localization and risk assessment, and generate corresponding repair decision instructions.

[0049] 3. Driver execution and repair phase.

[0050] Upon receiving a repair command, the drive-repair layer immediately activates the repair drive network 41 in the corresponding area. The repair material 42 is a shape memory alloy that undergoes a phase transformation under electrical excitation, generating significant recovery stress. This stress applies active mechanical compression to the identified damaged areas, effectively inhibiting crack propagation and achieving in-situ self-repair of the structure.

[0051] 4. Closed-loop feedback and optimization.

[0052] After the repair process is completed, the system collects physical field information of the repaired area again through the perception-structure layer, forming an information feedback loop. This feedback data can not only verify the repair effect but also provide data support for the system's self-optimization, further improving the diagnostic accuracy of the AI ​​model and achieving continuous performance improvement.

[0053] The working principle of this invention fully embodies the core design concept of "perception is computation, decision is execution". Through a complete closed loop of perception-computation-configuration-repair, it realizes autonomous intelligent management of the entire process from damage identification to active repair.

[0054] As can be seen from the above, the difference between this invention and structural health monitoring (SHM) lies in the fact that mainstream SHM research mainly focuses on "sensing," that is, data acquisition. The processing and analysis of SHM data usually rely on external computers or cloud systems, which is an open-loop model of "sensing-transmission-remote analysis," lacking integrated, local computational decision-making capabilities, and even less capable of performing repairs.

[0055] The difference between this invention and self-healing materials lies in the fact that self-healing materials focus on the "passive" repair mechanism of the material itself. That is, when the crack expands to a certain extent, a repair response is triggered. However, it lacks intelligent "perception" and "decision-making" processes, and cannot distinguish the type of damage or assess the risk level. It is a conditioned reflex rather than an intelligent decision-making process.

[0056] The technical function and effect of this invention are not reflected in the invention of individual technical components (such as FBG, SMA, AI chip), but in the integration of these known technologies into an unprecedented system architecture, resulting in a synergistic effect of "1+1+1>3".

[0057] Unlike existing technologies that are mostly simple combinations of "sensing systems," "structural systems," and "repair solutions," this invention proposes and designs for the first time an integrated embedded system architecture of "sensing-computing-repair." This deeply couples three originally independent functional modules during the design and manufacturing stages, forming a single, autonomous intelligent agent. This breaks the traditional paradigm of separating "monitoring" and "maintenance," creating a "living" structure capable of self-cognition, self-decision-making, and self-execution, thus realizing a paradigm shift from "passively bearing pressure" to "actively maintaining health."

[0058] The following example, “Implementation of a ship’s high-pressure steam pipeline system,” will be used to illustrate the specific implementation of the present invention in detail.

[0059] 1. System design and layout.

[0060] During the pipeline design phase, finite element analysis and other mechanical simulation methods are first used to determine the stress concentration areas and critical mechanical paths (such as elbows and areas near welds). Based on the simulation results, a digital prototype design of the intelligent pipeline is completed, and the spatial distribution and connection topology of the perception-structure layer, intelligent computing-decision layer, and drive-repair layer are planned.

[0061] The sensing-structure layer employs a fiber optic grating sensor array as a micro-nano sensor network, embedded in the pipe wall material of the pipe body 1 in a functional-structural integrated manner. The sensors are preferably deployed in stress concentration areas with a spacing of 30-100 mm to collect physical field information such as strain, vibration, and temperature in real time.

[0062] The intelligent computing-decision layer employs micro-edge computing nodes, each with a built-in lightweight AI algorithm model. These computing nodes are connected to the sensor network 22 via an internal integrated link and are deployed within a protective housing on the pipe surface. Each computing node processes data from multiple nearby sensors. The pre-trained AI algorithm model is capable of identifying characteristic patterns of microcrack initiation and pinpointing crack locations. Accurately locate the crack and assess the risk level based on its characteristics.

[0063] The repair material 42 of the drive-repair layer is a shape memory alloy, which is placed in the stress concentration area to form a repair drive network 41. The shape memory alloy actuator is connected to the computing node through internal integrated circuitry. When a repair command is received, the drive network causes the shape memory alloy to undergo a phase transition through electrical excitation, generating recovery stress, thereby applying mechanical pressure to the crack area and achieving crack closure.

[0064] 2. Manufacturing process.

[0065] To achieve integrated functionality with the pipeline body 1, laser additive manufacturing is preferred. Specifically, this includes: using high-temperature resistant alloy powder as the matrix material, constructing the pipeline body 1 layer by layer using 3D printing technology; embedding fiber optic sensors and shape memory alloy actuators at predetermined locations during the printing process; and integrating micro-computing nodes and communication lines onto the pipeline surface using micro-encapsulation technology to form a protective layer.

[0066] 3. Work process.

[0067] The system operates in an autonomous closed loop: the perception-structure layer collects physical field data in real time, the intelligent computing-decision layer processes and diagnoses the data in real time, and when damage characteristics are identified, a repair command is immediately generated. Upon receiving the command, the drive-repair layer excites the repair material 42 to complete the repair. The perception-structure layer can then monitor and verify the repair effect. Simultaneously, event logs and brief diagnostic results can be wirelessly transmitted to the monitoring center.

[0068] 4. Technical effects.

[0069] The system in this embodiment performed excellently in the test: the perception, analysis, decision-making and execution of the entire process were completed autonomously inside the pipeline, which fully demonstrated its autonomy as an intelligent agent; the system successfully identified and repaired microcracks, and the pressure-bearing capacity of the pipeline was significantly restored after the repair; the system adopted localized edge computing and achieved millisecond-level response; the integrated design significantly improved the system reliability.

[0070] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. An intelligent high-temperature and high-pressure pipeline system based on perception-computation-configuration-repair integration, characterized in that, It includes a pipeline body, which is provided with a perception-structure layer, an intelligent computing-decision layer and a driving-repair layer for communication through a communication network, wherein The perception-structure layer includes a sensor network arranged on the pipe wall of the pipeline body, which is used to collect physical field information of the pipeline body in real time and transmit the physical field information to the intelligent computing-decision layer; The intelligent computing-decision layer includes a computing node in communication connection with the sensor network, which is used to process and diagnose the physical field information in real time and generate processing instructions; The driving-repair layer includes a repair material arranged on the pipeline body and a repair driving network for driving the repair material to repair the pipeline body; After receiving the processing instructions, the driving-repair layer sends repair instructions to the repair driving network, and the repair driving network receives the repair instructions to stimulate the repair material to complete the repair of the damaged part of the pipeline body.

2. The intelligent high temperature high pressure piping system of claim 1, wherein, The perception-structure layer includes a structure body, which is embedded in the pipe wall material of the pipeline body in a functional-structural integrated manner with the sensor network.

3. The intelligent high temperature high pressure piping system of claim 1, wherein, The sensor network is a micro-nano sensor network arranged on the key mechanical path of the pipeline body.

4. The intelligent high temperature high pressure piping system of claim 3, wherein, The micro-nano sensor network is an optical fiber grating sensor array.

5. The intelligent high temperature high pressure piping system of claim 1, wherein, The computing node is a micro edge computing node with a built-in lightweight AI algorithm model.

6. The intelligent high temperature high pressure piping system of claim 5, wherein, The AI algorithm model can identify the characteristic pattern of micro crack initiation and locate and risk level assess the crack.

7. The intelligent high temperature high pressure piping system of claim 1, wherein, The repair material is a shape memory alloy, and the repair driving network electrically stimulates the shape memory alloy to change phase and generate a recovery stress to complete the repair of the damaged part of the pipeline body.

8. The intelligent high temperature high pressure piping system of claim 1, wherein, The perception-structure layer, intelligent computing-decision layer and driving-repair layer are integrated and laid out in the design stage of the pipeline body, and their spatial distribution is fused with the structure stress model of the pipeline body.

9. The smart high temperature high pressure piping system of any one of claims 1 to 8, wherein, The communication network is an internal integrated link, and the system realizes perception computing and decision execution through information interaction and instruction transmission through the internal integrated link.

10. The smart high temperature high pressure piping system of any one of claims 1 to 8, wherein, The system uses the manufacturing process of additive manufacturing or micro encapsulation technology to realize the integrated integration of the perception-structure layer, intelligent computing-decision layer, driving-repair layer and pipeline body.

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