Large-diameter deep shaft slip form system and construction method

Abstract

The invention relates to the technical field of shaft lining, and particularly discloses a large-diameter deep shaft slip form system and a construction method.The large-diameter deep shaft slip form system comprises a platform module, a formwork module, a pumping pouring module, a climbing module and a self-adaptive maintenance module; the jacking driving piece can slide and climb along the climbing rod to drive the platform module to move in the vertical direction so as to adapt to vertical shaft lining construction at different depth positions, and the construction efficiency is improved; in the construction process, the pumping pouring module can convey concrete to the pouring space between the formwork module and the inner wall of the vertical shaft, the self-adaptive curing module can conduct self-adaptive curing on the concrete in the pouring space, the situation that a lining cracks due to the large temperature difference in the extreme environment is avoided, the construction quality is effectively improved, and the construction period is shortened. And repairing and reworking are reduced, so that the vertical shaft slip form system can better adapt to various complex environment projects.

Description

Technical Field

[0001] This invention relates to the field of shaft lining technology, and in particular discloses a large-diameter deep shaft slipform system and construction method. Background Technology

[0002] In the field of water conservancy engineering, water conveyance tunnels, as key infrastructure for water resource allocation, play a crucial role in traversing complex terrain and achieving long-distance water conveyance. Among them, inverted siphon shafts, as an important component of water conveyance tunnels, undertake the critical task of regulating water flow, pressure, and water level differences; their stable operation is the guarantee of the efficient and safe operation of the entire water conveyance system. As water conservancy projects develop towards larger scale and greater complexity, the application of large-diameter inverted siphon shafts in deeply buried, long-distance water conveyance projects is becoming increasingly common. However, this trend has also brought unprecedented challenges to shaft construction technology, especially in the application of slipform systems.

[0003] For large-diameter vertical shaft projects, the construction of secondary lining of large-diameter vertical shafts mainly faces the following technical challenges: (1) The construction of secondary lining of large-diameter deep vertical shafts involves many procedures, such as steel reinforcement installation, concrete pouring, formwork support and adjustment, concrete curing and defect inspection. Due to the limited space in the shaft, how to scientifically and rationally plan and utilize this space to achieve efficient cross-operation between various procedures has become a key factor restricting the construction period. (2) Existing slipform technology methods are difficult to meet the requirements of uniform pouring of large-volume concrete at one time, and cannot guarantee the uniformity and stability of concrete during the pouring process, which can easily lead to concrete quality defects, such as cracks and pitting, thereby affecting the durability and mechanical properties of the vertical shaft lining structure, reducing the service life and safety of the project. (3) When dealing with extreme temperature difference environments, the curing process of existing slipform technology has become a weak link in quality control. Specifically, the traditional periodic watering and heat preservation measures cannot adapt to complex and changing environmental parameters in real time, resulting in frequent cracking and uneven strength of the concrete structure, which directly endangers the long-term stability and waterproof performance of the vertical shaft lining. At the same time, the maintenance model that relies on manual judgment is not only inefficient, but also reveals its lack of reliability in harsh engineering environments, making it difficult to guarantee project quality and progress. It is urgent to upgrade towards precision and intelligence.

[0004] Therefore, it is necessary to provide a new large-diameter deep vertical shaft slipform system and construction method to solve the above-mentioned technical problems. Summary of the Invention

[0005] The main objective of this invention is to provide a large-diameter deep vertical shaft slipform system and construction method, aiming to solve the problems of low construction efficiency and poor construction quality in existing technologies.

[0006] To achieve the above objectives, the present invention proposes a large-diameter deep vertical shaft slipform system for lining construction of the inner wall of a vertical shaft. The system is characterized by comprising a platform module, a template module, a pumping and pouring module, a climbing module, and an adaptive curing module. The template module is arranged opposite to the inner wall of the shaft to form a casting space, and the casting space is provided with lining steel bars. The template module is fixedly sleeved on the outside of the platform module. The pumping and pouring module is mounted on the platform module and is used to transport concrete into the pouring space. The climbing module includes a lifting drive component and a climbing rod. The lifting drive component is disposed on the platform module. The climbing rod is arranged vertically, and the bottom end of the climbing rod is welded to the bottom wall of the shaft. The climbing rod is also tied to the lining steel reinforcement. The lifting drive component is sleeved on the climbing rod and can slide and climb along the climbing rod to drive the platform module to move vertically. The adaptive curing module is installed on the template module and is used to adaptively cure the concrete in the pouring space.

[0007] Optionally, the platform module includes a lifting platform, a unloading platform, and columns. The lifting drive component is disposed on the lifting platform. The unloading platform is disposed on the lifting platform by a plurality of columns arranged circumferentially along the center of the lifting platform, and a hollow space is formed between the unloading platform and the lifting platform. The unloading platform is provided with an annular groove communicating with the hollow space. The pumping and casting module is disposed at the annular groove.

[0008] Optionally, the pumping and pouring module includes a pumping grouting device, a conveying and descent structure, a storage tank, a distribution tank, a distribution plate, a U-shaped chute structure, a rotary drive component, and a transmission component. The pumping grouting device is located at the shaft opening and is used to convey concrete. One end of the conveying and descent structure is connected to the pumping grouting device, and the other end is correspondingly located to the storage tank. The conveying and descent structure can adjust its length according to the lining construction progress. The storage tank is rotatably mounted on the unloading platform and is concentrically arranged with the annular trough. The distribution tank is located on the unloading platform and is correspondingly located to the outlet of the storage tank. The material distribution plate is disposed between the storage tank and the unloading platform, and is correspondingly disposed to the annular groove. The material distribution plate is provided with a through hole for the storage tank to pass through. The unloading platform is provided with a plurality of U-shaped chute structures arranged circumferentially along the annular groove, and the first end of each U-shaped chute structure is connected to the material distribution plate, and the other end extends into the pouring space. The rotary drive is disposed on the unloading platform. The rotary drive is connected to the storage tank through the transmission component. The rotary drive can drive the storage tank to rotate around the center of the annular groove so as to uniformly deliver concrete into the material distribution plate.

[0009] Optionally, the template module includes a surrounding ring, a template panel, and hooks. The outer periphery of the lifting platform is provided with at least two vertically spaced surrounding rings. One side of the template panel is positioned opposite to the inner wall of the shaft, and the other side is provided with hooks corresponding to the surrounding rings. The template panel is hung on the corresponding surrounding rings via the hooks. And / or, the large-diameter deep vertical shaft slipform system further includes a defect rectification platform, which includes an annular steel plate, hanging rods, a ladder and a safety net. The annular steel plate is connected to the bottom of the lifting platform by multiple evenly arranged hanging rods; the ladder is connected between the top of the lifting platform and the annular steel plate; and the safety net is set in the hollow part of the annular steel plate.

[0010] Optionally, the adaptive maintenance module includes a maintenance pipeline device, a temperature sensor group, a central control device, a data processing and analysis device, and an automatic execution device. The maintenance pipeline device includes a double-layer stainless steel pipe structure, solenoid valves, and an electric heating water tank. The double-layer stainless steel coil is embedded in the template panel in an S-shaped arrangement. The double-layer stainless steel pipe structure is equipped with multiple solenoid valves, which divide the double-layer stainless steel pipe structure into multiple independent temperature zones. The hot water pipe in the double-layer stainless steel coil is connected to the electric heating water tank to supply hot water to the hot water pipe in the double-layer stainless steel coil. The cold water pipe in the double-layer stainless steel coil is connected to the underground cold water tank to supply cold water to the cold water pipe in the double-layer stainless steel coil. The lining steel bars are provided with multiple temperature sensor groups spaced at predetermined intervals along the vertical direction and radially along the shaft. Each temperature sensor group includes multiple temperature sensor elements evenly arranged circumferentially along the lining steel bars. The central control device is electrically connected to each of the temperature sensors. The data processing and analysis device is electrically connected to the central control device and is used to process the real-time temperature data transmitted by the temperature sensors received by the central control system. The automatic execution device can control the solenoid valve of the double-layer stainless steel pipe structure according to the data transmitted by the temperature sensors to adjust the water flow rate corresponding to the independent temperature zone.

[0011] In addition, the present invention also provides a construction method for a large-diameter deep vertical shaft slipform system, which uses the large-diameter deep vertical shaft slipform system as described above to line the inner wall of the shaft, including the following steps: S1: Lining steel bars are installed in the shaft to be constructed, and a large-diameter deep data sliding membrane system is installed in the shaft to be constructed; wherein: multiple climbing rods are tied to the lining steel bars in the vertical direction, and adjacent climbing rods are connected by a male-female threaded connector. S2: Start the pumping and pouring module to pour concrete to a set height into the pouring space between the template panel and the shaft wall; S3: Based on the artificial intelligence algorithm that integrates fuzzy reasoning, neural network prediction and reinforcement learning, the concrete poured this time is adaptively cured through the adaptive curing module and template panel until the concrete initially sets and forms a concrete layer structure, which then enters S4. S4: Start the climbing module to drive the platform module to move vertically upward a unit distance. At the same time, the platform module drives the template panel to detach from the concrete layer structure formed by S3 and move vertically upward a corresponding unit distance. S5: Repeat S2 to S4 until the lining construction of the entire shaft to be constructed is completed.

[0012] Optionally, S3 includes: S3.1 The data processing and analysis device calculates the core control indicators based on the real-time temperature data transmitted by the temperature sensor received by the central control system. S3.2, Based on core control indicators, set time intervals The flow rate of each independent temperature zone is adaptively adjusted for one control cycle until the concrete has completed its initial setting; specifically including: S3.2.1, Set the control period =1. Initial Time =0, determine the control cycle. initial flow ; S3.2.2. Construct a two-layer inference engine based on fusion fuzzy inference. Use the two-layer inference engine to match the corresponding dominant control mode based on the core control indicators calculated from real-time temperature data, and calculate the flow rate corresponding to each independent temperature zone of the dominant control mode. S3.2.3 The automatic actuator adjusts the opening degree of each solenoid valve according to the flow rate corresponding to each independent temperature zone in the current dominant control mode; S3.2.4 Determine if the current dominant control mode has changed. If yes, return to S3.2.1; otherwise, further determine: like Then let ,when The initial flow rate for the second control cycle is determined at that time. Then with the initial flow Restart all solenoid valves with the double-layer stainless steel pipe structure, and return to S3.2.2; when If necessary, return directly to S3.2.2; like If so, it will directly return to S3.2.2; Continue until the concrete has completed its initial setting and enters S4.

[0013] Optionally, in S3.2.2, the dominant control modes include heating mode, emergency cooling mode, active cooling mode, balanced control mode, intermittent maintenance mode, preventive control mode, and minimum maintenance mode; When switching from zero flow, heating mode, intermittent maintenance mode to active cooling mode and balanced control mode, the initial flow rate is... The specific formula is as follows: ; in: For initial control error, , The initial maximum internal and external temperature difference for the current control cycle. The target temperature difference; To set the minimum flow rate; To set the maximum flow rate; The specific formula for the initial flow rate when switching from emergency cooling mode to active cooling mode and balanced control mode is as follows: ; in: The flow rate value for the last control cycle of the previous dominant control mode; In S3.2.2, the core control indicators include the maximum internal and external temperature difference. Circular temperature difference Volume-weighted average temperature change rate, surface average temperature and ambient temperature ; The pouring space is divided into three equal areas along the radius: the area closest to the inside of the shaft is the formwork layer, the middle area is the central layer, and the area closest to the outside of the shaft is the near-rock layer; the maximum internal and external temperature difference. The specific calculation formula is as follows: ; in: For the first A temperature sensor measures the temperature of the concrete in the center layer. For the first A temperature sensor measures the concrete temperature of the formwork layer; Circular temperature difference The specific calculation formula is as follows: ; Volume-weighted average temperature change rate The specific calculation formula is as follows: ; ; in: The temperature is a volume-weighted average. For a moment At that time, the first Readings from a temperature sensor; This represents the total number of temperature sensors currently capable of monitoring real-time temperature data. To monitor the total volume of concrete at the cross-section; For the first The concrete volume corresponding to each sensor, i.e., the volume weight, is calculated using the following formula: ; in: It can be 45° or 60°; The height interval between adjacent temperature sensors; For the first The outer diameter of the concrete in the area where the temperature sensor is located. For the first The inner diameter of the concrete in the area where each temperature sensor is located, denoted by the area number . Then the first outer diameter of the region And then the number Inner diameter of the region The specific calculation formula is as follows: ; in: When we take 1, 2, and 3, the corresponding regions are the template layer, the central layer, and the near-rock layer, respectively. The outer diameter of the shaft; This refers to the inner diameter of the shaft. Interlayer radial thickness; Average surface temperature The specific calculation formula is as follows: ; When the dominant control mode is active cooling mode or balanced control mode, after calculating the flow rate corresponding to each independent temperature zone in S3.2.2, the process further includes: calculating the fine-tuning factor corresponding to each independent temperature zone based on fuzzy inference and defuzzification process; fine-tuning the flow rate corresponding to the dominant control mode according to the fine-tuning factor to obtain the refined flow command for each independent temperature zone; in S3.2.3, the automatic actuator adjusts the opening degree of each solenoid valve according to the refined flow command for each independent temperature zone in the current dominant control mode.

[0014] Optionally, in S3.2.4, the initial flow rate The process of determining: ① Calculate the cooling efficiency for the first cycle. The specific formula is as follows:

[0015] in: This represents the maximum temperature difference of the concrete during the first cycle. ② Calculate the proportional gain coefficient of the adaptive incremental PID controller in the first cycle based on the cooling efficiency. The specific formula is as follows: ; ③ According to Calculate the initial flow rate The specific formula is as follows: ; in: The control error after the first cycle, .

[0016] Optionally, in S3.2.2, the matching mechanism of the dominant control mode and the flow calculation process corresponding to each dominant control mode are as follows: when or Matching heating mode, flow rate The specific calculation formula is as follows: ; when Matching emergency cooling mode, flow rate The specific calculation formula is as follows: ; In emergency cooling mode, if Then it will switch from emergency cooling mode to intermittent maintenance mode; when Matching active cooling mode, traffic The specific calculation formula is as follows: ; in: The flow rate is calculated using an adaptive incremental PID controller; This is the fine-tuning factor obtained through fuzzy reasoning; The predicted traffic output by the trained traffic prediction model; To reinforce the recommended flow rate output by the learning controller; When the circumferential temperature difference Furthermore, when in intermittent maintenance mode, preventative control mode, or minimum maintenance mode, a balanced control mode is required, necessitating differentiated flow distribution across each independent temperature zone. Each independent temperature zone corresponds to a flow rate The specific calculation formula is as follows: ; in: Based on the basic cooling flow rate, ; For the first The average surface temperature of each independent temperature zone This is the average surface temperature of all independent temperature zones; when The intermittent maintenance mode is matched, and the solenoid valves of the double-layer stainless steel pipe structure are set to: open for 2 minutes and close for 8 minutes, with a flow rate of [missing information] when open. The specific calculation formula is as follows: ; when and Time-matched preventative control mode, flow The specific calculation formula is as follows: ; when and Match the minimum maintenance mode at the time, and the flow rate The specific calculation formula is as follows: ; In S3.2.2, if the matching conditions of each dominant control mode interfere, the dominant control modes are matched according to the set priority order. The set priority order is: heating mode, emergency cooling mode, active cooling mode, balanced control mode, intermittent maintenance mode, preventive control mode, and minimum maintenance mode.

[0017] Optionally, traffic The specific calculation process is as follows: ; in: , For the first The proportional gain coefficient of a periodic adaptive incremental PID controller. ; For the first Cooling efficiency during the cycle, ; ; Fine-tuning factor obtained through fuzzy reasoning The specific calculation formula is as follows; ; in: It is an output variable The first uniformly discretized on its universe of discourse [-0.5, 0.5] One sampling point; At the sampling point After aggregation, output the membership values ​​of the fuzzy set; This represents the total number of sampling points.

[0018] Optionally, predict traffic. The acquisition process specifically includes: Construct a training dataset, which includes: historical temperature sequences, environmental parameters, concrete material and geometric parameters, and flow rates corresponding to each control cycle; A long short-term memory recurrent neural network is constructed, which takes the feature vectors of concrete-related parameters as input and the temperature difference change trend corresponding to the concrete-related parameters as output; wherein: the concrete-related parameters include historical temperature sequence, environmental parameters, control input, and concrete material and geometric parameters; The training dataset is divided into a training set, a validation set, and a test set. The training set is used to iteratively train the long short-term memory recurrent neural network. After each training cycle, the validation set is used to evaluate the model performance, and an early stopping strategy is implemented based on the validation loss to prevent overfitting. The trained model is evaluated on the test set, and the prediction error index is calculated. The parameters of the best-performing model are saved as the model parameters of the trained LSTM model. The trained LSTM model is embedded into the MPC model predictive control framework, and the optimal control proposal sequence is obtained by solving the optimal control problem in the finite time domain based on the set objective function. Take the first prediction result of the optimal control suggestion sequence as the predicted flow rate. .

[0019] Optionally, the suggested flow rate output by the reinforcement learning controller. Specifically, it includes: ① Construct a reinforcement learning controller. The reinforcement learning control module integrates an agent based on the proximal policy optimization (PPO) algorithm. This agent includes a policy network and a critic network. ② Train and learn online the agent in the reinforcement learning controller to obtain the trained agent; ③ After training the agent with the core control indicators of the current cycle and the flow rate input of the previous cycle, the flow rate adjustment sequence for each independent temperature zone is obtained. ; ④ The reinforcement learning controller calculates the average flow rate of each temperature zone in the previous cycle. and flow adjustment sequence The recommended flow rates for each independent temperature zone are calculated. The specific formula is as follows: .

[0020] In the technical solution of this invention, the lifting drive component can slide and climb along the climbing rod to drive the platform module to move vertically, so as to adapt to the lining construction of the shaft at different depths and improve the construction efficiency. During the construction process, the pumping and pouring module will transport concrete to the pouring space between the formwork module and the inner wall of the shaft, and the adaptive curing module can adaptively cure the concrete in the pouring space, avoiding the lining cracking caused by large temperature differences in extreme environments, effectively improving the construction quality and reducing repair and rework, so that the shaft slipform system can better adapt to various complex environmental engineering projects. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0022] Figure 1 This is a schematic diagram of the large-diameter deep vertical shaft slipform system in an embodiment of the present invention; Figure 2 This is a partial structural diagram of the pumping and casting module in an embodiment of the present invention; Figure 3 This is a schematic diagram of the conveying and descent structure in an embodiment of the present invention; Figure 4 This is a schematic diagram of the double-layer stainless steel tube structure in an embodiment of the present invention; Figure 5 This is a schematic diagram of the template module in an embodiment of the present invention; Figure 6 This is a schematic diagram of the installation structure of the surrounding ring in an embodiment of the present invention; Figure 7 This is a schematic diagram of the lifting drive component in an embodiment of the present invention; Figure 8 This is a structural schematic diagram of the construction method of the large-diameter deep vertical shaft slipform system in an embodiment of the present invention.

[0023] Explanation of icon numbers: 1. Platform Module, 1.1 Lifting Platform, 1.1.1 Radial Beam, 1.1.2 Lifting Frame, 1.1.3 Central Steel Cylinder, 1.2 Unloading Platform, 1.3 Column, 1.4 Hollow Space; 2. Template Module, 2.1 Enclosure, 2.2 Template Panel, 2.3 Hook, 2.4 Enclosure Connecting Plate; 3. Pumping and Casting Module, 3.1 Conveying and Descending Structure, 3.1.1 Chute, 3.1.2 Descending Device, A Upper Circular Pipe, B Buffer Plate, C Lower Circular Pipe, D Flange; 3.2 Storage Tank, 3.3 Distribution Tank, 3.4 Distribution Plate, 3.5 U-shaped Chute Structure, 3.6 Rotary Drive Component, 3.7 Transmission Component; 4. Climbing Module, 4.1 Lifting Drive Component, 4.1.1 Hydraulic Pump Station, 4.1.2 High-Pressure Oil Pipe, 4.1.3 Oil separator, 4.1.4 Through-type jack, 4.2 Climbing rod, 5.1 Double-layer stainless steel pipe structure, 5.2 Electric heating water tank, 6 Defect treatment platform, 6.1 Annular steel plate, 6.2 Hoisting rod, 6.3 Climbing ladder, 6.4 Safety net, 7 Downhole cold water pool, 8 Anchor bolt, 9 Wire rope, 10 Concrete.

[0024] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0026] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0027] Furthermore, in this invention, descriptions involving "first," "second," etc., are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0028] In this invention, unless otherwise explicitly specified and limited, the terms "connection," "fixed," etc., should be interpreted broadly. For example, "fixed" can mean a fixed connection, a detachable connection, or an integral part; it can mean a mechanical connection or an electrical connection; it can mean a direct connection or an indirect connection through an intermediate medium; it can mean 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.

[0029] Furthermore, the technical solutions of the various embodiments of the present invention can be combined with each other, but only if they are based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

[0030] This invention proposes a large-diameter deep vertical shaft slipform system, which aims to solve the problem of low operating efficiency of existing rail milling devices.

[0031] See Figures 1 to 6A large-diameter deep vertical shaft slipform system is used for lining construction of the inner wall of a vertical shaft. The system includes a platform module 1, a template module 2, a pumping and pouring module 3, a climbing module 4, and an adaptive curing module. The template module 2 is positioned opposite the inner wall of the shaft to enclose the pouring space, which is reinforced with lining steel. The template module 2 is fixedly fitted onto the platform module 1. The pumping and pouring module 3 is mounted on the platform module 1 and is used to transport concrete 10 to the pouring space. Inside the space; the climbing module 4 includes a lifting drive component and a climbing rod 4.2. The lifting drive component is set on the platform module 1, and the climbing rod 4.2 is set in the vertical direction. The bottom end of the climbing rod 4.2 is welded to the bottom wall of the shaft, and the climbing rod 4.2 is tied to the lining reinforcement. The lifting drive component is sleeved on the climbing rod 4.2, and the lifting drive component can slide and climb along the climbing rod 4.2 to drive the platform module 1 to move in the vertical direction; the adaptive curing module is set on the template module 2 and is used to adaptively cure the concrete 10 in the pouring space. The lifting drive component can slide and climb along the climbing rod to move the platform module vertically, adapting to shaft lining construction at different depths and improving construction efficiency. During construction, the pumping and pouring module delivers concrete to the pouring space between the formwork module and the inner wall of the shaft, and the adaptive curing module can adaptively cure the concrete in the pouring space, avoiding lining cracking due to large temperature differences in extreme environments. This effectively improves construction quality and reduces repairs and rework, enabling the shaft slipform system to better adapt to various complex environmental engineering projects.

[0032] See Figure 7 The lifting drive component 4.1 includes a hydraulic pump station 4.1.1, high-pressure oil pipes 4.1.2, an oil distributor 4.1.3, and multiple through-type jacks 4.1.4. The multiple through-type jacks are evenly arranged on the lifting frame. The climbing rods are made of seamless steel pipes and are inserted into the through-type jacks and the lifting support. The hydraulic pump station consists of a motor, hydraulic pump, oil tank, pressure sensor control valve, and electrical control system. By controlling the motor speed and the opening of the hydraulic valves, the pressure and flow of the hydraulic oil are adjusted to achieve synchronous lifting of the jacks, serving as the power source for the entire lifting system. The entire sliding diaphragm system is lifted by hydraulic cylinder jacks. The lifting frame and the base of the through-type jacks are bolted together. The climbing rods are fixed to the lining steel bars of the shaft by binding. The climbing rods use threaded joints to ensure concentricity during ultra-high lifting, and each climbing rod is equipped with a limiter to adjust the climbing height of the jacks. This drive structure is existing technology and will not be described in detail here.

[0033] In this embodiment, platform module 1 includes a lifting platform 1.1, a material unloading platform 1.2, and columns 1.3. The lifting drive is mounted on the lifting platform 1.1. The material unloading platform 1.2 is mounted on the lifting platform 1.1 via multiple columns 1.3 arranged circumferentially along the center of the lifting platform 1.1, and a hollow space 1.4 is formed between the material unloading platform 1.2 and the lifting platform 1.1. The material unloading platform 1.2 is provided with an annular groove communicating with the hollow space 1.4. The pumping and casting module 3 is located at the annular groove. Each platform is arranged vertically in a stepped manner, without affecting each other, enabling multi-process cross-operation, ensuring construction efficiency and forming quality. The lifting platform consists of radial beams 1.1.1 and a central steel cylinder 1.1.3. Each radial beam is arranged radially with the central steel cylinder as the center. The radial beams and the central steel cylinder are connected by a fixed plate. The central steel cylinder forms an integral whole with the lifting frame, the surrounding ring, and the template system through a structural beam of a certain height.

[0034] In this embodiment, the columns are distributed on the radial beams of the lifting platform, and all the columns are connected by cross bracing to form a mesh structure, which further improves the structural strength; the radial beams are made of double-backed angle steel to form the skeleton of the sliding membrane system; the radial beams are welded to the central steel cylinder; the central steel cylinder is pre-arched upwards.

[0035] In this embodiment, the platform module also includes a steel reinforcement installation platform. The steel reinforcement installation platform is designed as a disc shape connected to the vertical shaft, with a hollow center. The steel reinforcement installation platform is formed by combining I-beams and channel steel. A lifting platform is set on the steel reinforcement installation platform, and each column passes through the lifting platform and connects to the steel reinforcement installation platform.

[0036] In this embodiment, the pumping and pouring module 3 includes a pumping grouting device, a conveying and descent structure 3.1, a storage tank 3.2, a distribution tank 3.3, a distribution plate 3.4, a U-shaped chute structure, a rotary drive component 3.6, and a transmission component 3.7. The pumping grouting device is located at the wellhead of the vertical shaft and is used to convey concrete 10. One end of the conveying and descent structure 3.1 is connected to the pumping grouting device, and the other end is correspondingly set to the storage tank 3.2. The conveying and descent structure 3.1 can adjust its length according to the lining construction progress. The storage tank 3.2 is rotatably mounted on the unloading platform 1.2 and is concentrically arranged with the annular trough. The distribution tank 3.3 is set on the unloading platform 1.2 and is concentrically arranged with the storage tank 3.2. The discharge port is correspondingly set; the distribution plate 3.4 is set between the storage tank 3.2 and the unloading platform 1.2, and is set correspondingly to the annular groove. The distribution plate 3.4 is provided with a through hole for the storage tank 3.2 to pass through; the unloading platform 1.2 is provided with multiple U-shaped chute structures arranged along the circumference of the annular groove, and the first end of each U-shaped chute structure is connected to the distribution plate 3.4, and the other end extends into the pouring space; the rotary drive 3.6 is set on the unloading platform 1.2; the rotary drive 3.6 is connected to the storage tank 3.2 through the transmission component 3.7. The rotary drive 3.6 can drive the storage tank 3.2 to rotate around the center of the annular groove so as to evenly transport the concrete 10 into the distribution plate 3.4. The conveying and decelerating structure 3.1 consists of a chute and decelerators. The installation length of the conveying and decelerating structure can be flexibly adjusted according to the progress of the shaft lining construction. The decelerators are connected by the chute, and the spacing of the decelerators can be theoretically calculated and verified through engineering, ensuring construction quality, efficiency, and cost. The decelerator is composed of a flange D, bolt holes, an upper circular pipe A, a buffer plate B, and a lower circular pipe C. This pipeline structure consists of an N-shaped interlocking upper and lower circular pipes. The upper chute is connected to the upper circular pipe at the flange. Concrete is vertically conveyed from the chute to the buffer plate of the upper circular pipe, where it is decelerated and then enters the lower circular pipe. The chute and decelerators are precisely connected between segments using high-strength bolts. Ear plates are welded to the outside of the chute, which can be connected to the anchor bolts 8 pre-installed in the initial support of the shaft wall via steel wire ropes 9, ensuring that the pipe body will not shift or vibrate due to dynamic loads during concrete conveying, providing a reliable guarantee for continuous pouring operations.

[0037] In this embodiment, the storage tank has structural dimensions of 4m (length) × 4m (width) × 2.2m (height), and an internal volume of 1.5m³. 3 The rotary drive component 3.6 is a rotary motor, and the transmission component 3.7 is a belt. The material distribution plate is located below the material distribution tank and is supported by a U-shaped chute structure extending radially to the edge of the shaft at a certain angle. The unloading platform is supported by columns above the steel reinforcement platform, and two A20 steel wire ropes are installed on each of the four sides of the platform to connect it to the steel reinforcement platform.

[0038] In this embodiment, the template module 2 includes a surrounding ring 2.1, a template panel 2.2, and hooks 2.3. At least two vertically spaced surrounding rings 2.1 are provided on the outer periphery of the lifting platform 1.1. One side of the template panel 2.2 is opposite to the inner wall of the shaft, and the other side has hooks 2.3 corresponding to the surrounding rings 2.1. The template panel 2.2 is hung on the corresponding surrounding ring 2.1 via the hooks 2.3. The template panel is made of steel plate, and the surrounding ring adopts a two-tiered structure. The surrounding ring is welded to the outside of the lifting platform, and the surrounding ring is formed by connecting two opposing single structures with a connecting plate 32. In this embodiment, the template panel has a taper of 0.2% to 0.5%, and negative tapers are strictly prohibited. High-strength bolts are used to connect the template panels, and spring washers are used for compression. Hooks are used to connect the template panel and the surrounding ring, and the hooks are welded to the long edge of the template. High-strength bolts are used to connect the surrounding ring to the surrounding ring connecting plate at the connection point.

[0039] In this embodiment, the large-diameter deep vertical shaft slipform system also includes a defect rectification platform 6. The defect rectification platform 6 includes a ring-shaped steel plate 6.1, a hanging rod 6.2, a ladder 6.3, and a safety net 6.4. The ring-shaped steel plate 6.1 is connected to the bottom of the lifting platform 1.1 by multiple evenly arranged hanging rods 6.2; the ladder 6.3 is connected between the top of the lifting platform 1.1 and the ring-shaped steel plate 6.1; the safety net 6.4 is set in the hollow part of the ring-shaped steel plate 6.1. The ring-shaped steel plate is located at the bottom of the large-diameter deep vertical shaft slipform system. The platform is formed by angle steel to form a ring channel, and steel plates are laid on top. It is connected to the lifting platform by hanging rods. Safety guardrails are set around the outer end of the platform, and the empty part in the middle is closed with high-strength safety nets to improve the safety of operation.

[0040] In this embodiment, the adaptive maintenance module includes a maintenance pipeline device, a temperature sensor group, a central control device, a data processing and analysis device, and an automatic execution device. The maintenance pipeline device includes a double-layer stainless steel pipe structure 5.1, solenoid valves, and an electric heating water tank 5.2. The double-layer stainless steel coil is embedded in the template panel 2.2 in an S-shaped arrangement. Multiple solenoid valves are installed on the double-layer stainless steel pipe structure 5.1, dividing it into multiple independent temperature zones. The hot water pipe in the double-layer stainless steel coil is connected to the electric heating water tank to supply hot water. The cold water pipe in the double-layer stainless steel coil is connected to the underground cold water tank 7 to supply cold water. Lining Multiple temperature sensor groups are installed at predetermined intervals along the vertical direction of the reinforcing bars, and are arranged radially along the shaft. Each temperature sensor group includes multiple temperature sensor elements evenly arranged circumferentially along the reinforcing bars of the lining. The central control device is electrically connected to each temperature sensor. The data processing and analysis device is electrically connected to the central control device and is used to process the real-time temperature data transmitted by the temperature sensors received by the central control system. The automatic execution device can control the solenoid valves of the double-layer stainless steel pipe structure 5.1 according to the data transmitted by the temperature sensors to adjust the water flow of the corresponding independent temperature zone. Through artificial intelligence algorithms that integrate fuzzy reasoning, neural network prediction and reinforcement learning, it automatically controls the solenoid valves of the pipelines in each temperature zone to achieve adaptive and precise control of concrete temperature.

[0041] In this embodiment, the data processing and analysis device is used to process the data received by the central control system; the automatic execution device controls the flow rate of the solenoid valve in the pipeline based on the data transmitted by the MEMS temperature sensor.

[0042] In this embodiment, the temperature sensor is a miniature MEMS temperature sensor, which is installed at various measuring points by workers during the binding of reinforcing bars according to a layout strategy. The layout strategy is as follows: it is arranged in three layers along the thickness direction of the shaft wall, with the template layer, the central layer, and the near-rock layer arranged sequentially in the direction away from the center of the shaft. Between the template layer and the template panel, between the template layer and the central layer, and between the central layer and the near-rock layer, 8-12 sensor measuring points are evenly distributed in a ring at equal angles, with a ring angle of 45° or 60°. An additional set of sensors is added every 3m of slipform, covering the interface between the new and old concrete. This layout strategy enables direct and accurate measurement of the radial nonlinear temperature gradient of the concrete.

[0043] In this embodiment, the following functions can be achieved based on the temperature sensor group installed according to the arrangement strategy: a) Using numerical integration methods (such as Simpson's rule) to accurately calculate the representative average temperature at this location, rather than a simple arithmetic average, can better reflect the true thermal state.

[0044] The representative average temperature at each radial location was calculated using the Simpson numerical integration method. The specific formula is as follows:

[0045] in: , Interlayer distance, , The interpolated temperature was obtained using linear interpolation at the midpoint. For temperature sensors to measure the concrete temperature of the central layer, The temperature sensor measures the concrete temperature of the formwork layer. The temperature of the concrete near the rock layer is measured by a temperature sensor.

[0046] (b) The internal and external temperature difference at this location is calculated directly and in real time, which is the most direct and critical indicator for assessing the risk of surface cracking. This setup elevates the monitoring target from "temperature" itself to "temperature gradient (stress driving force)," achieving a fundamental shift from passive monitoring to proactive risk warning.

[0047] C) The circumferentially distributed layout strategy constitutes a circumferential temperature field diagnostic network, the uniqueness of which lies in: ① It can calculate the circumferential temperature difference in real time and promptly detect "hot spots" or "cold spots" caused by uneven distribution of sunlight, wind speed, cooling pipes, or local blockages, thus realizing online diagnosis of the working status of the cooling system.

[0048] ② It ensures that the true maximum internal and external temperature difference across the entire cross-section can be captured, avoiding measurement blind spots and missed judgments due to the randomness of measurement points.

[0049] ③ Based on the data obtained from the temperature sensor, the overall volume weighted average temperature of the concrete is obtained by using the volume weighted average temperature method to prevent the concrete from being damaged due to excessive temperature. ④ Based on the data obtained from the temperature sensor, calculate the local internal and external temperature difference of all radial measurement groups, and take the maximum temperature difference as the core indicator for concrete crack prevention. When the maximum temperature difference exceeds the set safety threshold (such as 25℃), an alarm is triggered immediately, indicating that the risk of surface cracking is extremely high. ⑤ Based on the data obtained from the temperature sensor, find the maximum and minimum values ​​of the temperature at all circumferential measuring points among the sensor data buried at the same horizontal cross section and the same radial depth. This is used to diagnose the uniformity of the system's operation. If the difference between the two values ​​is too large (e.g., 5℃), there may be problems such as pipe blockage, uneven sunlight exposure, or ventilation on the surface. ⑥ Based on the data obtained from the temperature sensor, the overall volume-weighted average temperature is differentiated with respect to time. This data is used to predict the temperature trend. A sudden, accelerated temperature rise is an early signal that the temperature is about to exceed the limit, and early intervention is required; an excessively rapid cooling rate (e.g., >2℃ / day) requires prevention of "cold shock" cracks.

[0050] See Figure 8 A construction method for a large-diameter deep vertical shaft slipform system, comprising the following steps: The method utilizes the aforementioned large-diameter deep vertical shaft slipform system to line the inner wall of the shaft. S1: Lining steel bars are installed in the shaft to be constructed, and a large-diameter deep data sliding membrane system is installed in the shaft to be constructed; wherein: multiple climbing rods 4.2 are tied to the lining steel bars in the vertical direction, and adjacent climbing rods (4.2) are connected by a male-female threaded connector. Specifically, the process involves several steps: First, pre-construction preparations are made, including leveling the site at the bottom of the shaft, surveying and setting out the baseline for the slipform system installation, and welding the bottom of the climbing rods to the shaft bottom wall according to the design position. Simultaneously, the climbing rods are vertically tied to the pre-installed lining reinforcement. Next, the platform modules are assembled sequentially. First, the lifting platform is installed, with the lifting drive components fitted onto the climbing rods and fixed in the preset position on the lifting platform. Then, the material unloading platform is installed above the lifting platform using columns, ensuring concentricity and forming a hollow space. Finally, the pumping and pouring module is installed at the annular groove, connecting the conveying and descent structure, storage tank, and distribution... The material tray and U-shaped chute structure were installed, and the rotary drive and transmission components were adjusted to ensure that the storage tank could rotate smoothly around the center of the annular chute. Next, the template modules were installed, and the surrounding ring was vertically fixed at intervals along the outer perimeter of the lifting platform. The template panels were then hung on the surrounding ring using hooks, so that the template panels and the inner wall of the shaft formed a pouring space that met the design dimensions. The sealing of the template panel joints was checked. Finally, the defect rectification platform was installed, and the annular steel plate was connected to the bottom of the lifting platform using hangers. A ladder was installed between the lifting platform and the annular steel plate, and a safety net was installed at the open sections of the annular steel plate, completing the installation and debugging of the entire slipform system.

[0051] S2: Start the pumping and pouring module 3 to pour concrete 10 to a set height into the pouring space between the template panel 2.2 and the shaft wall; S3: Based on the artificial intelligence algorithm that integrates fuzzy reasoning, neural network prediction and reinforcement learning, the concrete 10 poured this time is adaptively cured through the adaptive curing module and template panel 2.2 until the concrete 10 initially sets and forms a concrete 10 layer structure, which then enters S4. S3 includes: S3.1 The data processing and analysis device calculates the core control indicators based on the real-time temperature data transmitted by the temperature sensor received by the central control system. S3.2, Based on core control indicators, set time intervals The flow rate of each independent temperature zone is adaptively adjusted for one control cycle until the concrete reaches initial setting; specifically including: S3.2.1, Set the control period =1. Initial Time =0, determine the control cycle. initial flow ; S3.2.2. Construct a two-layer inference engine based on fused fuzzy inference. The core control indicators calculated based on real-time temperature data are matched with the corresponding dominant control mode using the two-layer inference engine, and the flow rate corresponding to each independent temperature zone of the dominant control mode is calculated. Specifically, based on the initial decision of fuzzy rules and pattern recognition, a two-layer inference engine containing multiple fuzzy variables such as temperature difference error, temperature difference change rate, and circumferential non-uniformity is constructed, as well as a fuzzy rule base containing 49 rules. And one of the seven predefined dominant control modes is matched according to the indicators calculated in real time. The matching mechanism is shown in Table 1.

[0052] Table 1 Matching Mechanism of Dominant Control Mode

[0053] The fuzzy variables and membership functions are defined as follows: The fuzzy inference system defines two input variables and one output variable: Input variable 1: Temperature difference error .in, The temperature varies depending on the mode (e.g., 25℃ in M3 mode). The basic universe of discourse for E is defined by the following fuzzy linguistic variables: {Negative Large (NB), Negative Medium (NM), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Medium (PM), Positive Large (PB)}. The membership function for each linguistic value is defined using a combination of symmetric triangular and trapezoidal functions, covering the entire universe of discourse.

[0054] Input variable 2: Temperature difference change rate EC. This is the rate of change of the temperature difference error E within the current control cycle, reflecting the development trend of the temperature difference. The basic domain of EC is {NB, NM, NS, ZO, PS, PM, PB}, and its fuzzy linguistic variables take the same values ​​as E.

[0055] Output variable: Flow fine-tuning factor This refers to the basic traffic. The correction amount is expressed in m³ / h. The basic domain of discourse is [-0.5, 0.5] m3 / h, {negative large (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), positive large (PB)}.

[0056] Establishing a fuzzy rule base: The core of fuzzy inference is a rule base containing multiple "IF-THEN" type fuzzy control rules. These rules are based on the experience of experts in temperature control of large-volume concrete and a large amount of historical data. The antecedent (IF part) of the rule is the combination of the linguistic values ​​of the input variables E and EC, and the consequent (THEN part) is the output variable... The language value. Some typical rule examples are as follows: If E is PB and EC is PB, then This is PB (Extremely large and rapidly increasing temperature difference, requiring a significant increase in cooling). If E is PM and EC is ZO, then It is PM. (The temperature difference is large but stable, requiring a moderate increase in cooling). If E is PS and EC is NS, then This is ZO. (The temperature difference is slightly excessive but trending downwards; no adjustment is needed.) If E is ZO and EC is NM, then is NS. (The temperature difference has reached the target but the temperature drop is too rapid; cooling needs to be slightly reduced to prevent "cold shock"). During fuzzy inference and defuzzification, fine-tuning is performed in each control cycle according to the following steps: Fuzzification: The precise input values ​​E and EC are converted into the membership degrees μ of the corresponding fuzzy linguistic values ​​according to their respective membership functions.

[0057] Rule evaluation and reasoning: The Mamdani minima-maxima reasoning method is used. For each rule, the minimum value of the membership degrees of the two conditions in the antecedent is taken as the activation strength of that rule. Use this activation strength to cut (minimum operation) the output fuzzy set corresponding to the consequent of this rule, and obtain a truncated output fuzzy set.

[0058] Rule aggregation: The truncated fuzzy output sets generated by all activated rules are maximized and merged to generate a total, irregularly shaped fuzzy output set, representing the flow fine-tuning factor. All possible values ​​and their membership degrees.

[0059] Defuzzification: To obtain a precise fine-tuning factor that can be used for control, the centroid method is used to defuzzify the aggregated output fuzzy set. The fine-tuning factor obtained through fuzzy inference will directly apply to the basic flow command under the current control mode.

[0060] The above steps endow the control system with the ability to cope with nonlinear, hysteresis and uncertain disturbances, making the control action smoother and more predictable, effectively avoiding the frequent oscillations or slow response problems of traditional PID control near the critical point, and significantly improving the overall control quality and stability of the concrete temperature field.

[0061] In S3.2.2, the matching mechanism of the dominant control mode and the flow calculation process corresponding to each dominant control mode are as follows: when or Matching heating mode, flow rate The specific calculation formula is as follows: ; when Matching emergency cooling mode, flow rate The specific calculation formula is as follows: ; In this embodiment, under emergency cooling mode, if Then it will switch from emergency cooling mode to intermittent maintenance mode; when Matching active cooling mode, traffic The specific calculation formula is as follows: ; in: The flow rate is calculated using an adaptive incremental PID controller; This is the fine-tuning factor obtained through fuzzy reasoning; The predicted traffic output by the trained traffic prediction model; To reinforce the recommended flow rate output by the learning controller; flow The specific calculation process is as follows: ; in: , For the first The proportional gain coefficient of a periodic adaptive incremental PID controller. ; For the first Cooling efficiency during the cycle, ; ; Fine-tuning factor obtained through fuzzy reasoning The specific calculation formula is as follows; ; in: It is an output variable The first uniformly discretized on its universe of discourse [-0.5, 0.5] One sampling point; At the sampling point After aggregation, output the membership values ​​of the fuzzy set; M is the total number of sampling points; to ensure accuracy, M is usually taken as ≥ 101.

[0062] Predicted traffic The acquisition process specifically includes: Construct a training dataset, which includes: historical temperature series, environmental parameters, concrete material and geometric parameters, and flow rate; A long short-term memory recurrent neural network is constructed, which takes the feature vectors of concrete-related parameters as input and the temperature difference change trend corresponding to the concrete-related parameters as output; wherein: the concrete-related parameters include historical temperature sequence, environmental parameters, control input, and concrete material and geometric parameters; The training dataset is divided into a training set, a validation set, and a test set. The training set is used to iteratively train the long short-term memory recurrent neural network. After each training cycle, the validation set is used to evaluate the model performance, and an early stopping strategy is implemented based on the validation loss to prevent overfitting. The trained model is evaluated on the test set, and the prediction error index is calculated. The parameters of the best-performing model are saved as the model parameters of the trained LSTM model. The trained LSTM model is embedded into the MPC model predictive control framework, and the optimal control proposal sequence is obtained by solving the optimal control problem in the finite time domain based on the set objective function. Take the first prediction result of the optimal control suggestion sequence as the predicted flow rate. ; In this embodiment, to overcome the large lag in concrete temperature changes, the system employs a Long Short-Term Memory (LSTM) recurrent neural network to predict future temperature trends. The network's input feature vector... This includes historical temperature sequences, environmental parameters, control inputs, and concrete material and geometric parameters. The LSTM unit utilizes its gating mechanism (forget gate). Input gate Output gate Update cell state With hidden state To predict the future Temperature difference change trend at each time step Based on this prediction, the system solves a finite-time optimal control problem within a model predictive control (MPC) framework, with the objective function being... This yields a forward-looking optimal control recommendation sequence. ,therefore .

[0063] After determining the dominant control mode and completing initial fuzzy fine-tuning, the system enters the core stage of closed-loop optimization. This step aims to generate precise control commands that can both quickly respond to current state errors and learn and optimize strategies from long-term operation. This embodiment creatively combines adaptive incremental PID control with proximal policy optimization (PPO) reinforcement learning to form a composite controller that combines speed, stability, and long-term optimality.

[0064] Recommended flow rate output by the reinforcement learning controller Specifically, it includes: To further enhance long-term adaptability and energy efficiency, the system integrates a reinforcement learning agent based on the proximal policy optimization (PPO) algorithm. This agent operates based on the system state. Input, adjusted by flow rate For the action, maximize the reward function To continuously optimize the control strategy. The update objective of the policy network is to maximize the alternative objective function after pruning. .

[0065] ① Construct a reinforcement learning controller. The reinforcement learning control module integrates an agent based on the proximal policy optimization (PPO) algorithm. This agent includes a policy network and a critic network. ② Train and learn online the agent in the reinforcement learning controller to obtain the trained agent; The online learning process is as follows: First, offline pre-training is performed, using a digital twin model based on the finite element method to generate a large amount of simulation data or historical engineering data to pre-train the PPO network offline, enabling it to master basic control laws; then, online experience collection and learning are carried out during actual operation, with the system continuously collecting experience tuples. The data is stored in an experience replay buffer. The system initiates network parameter updates during periods of low computational load (such as late at night) or when the buffer data volume reaches a threshold. During the network update phase, a batch of experience data is sampled from the buffer, and the dominance function is first estimated using the Critic network. (Using the Generalized Advantage Estimation Algorithm (GAE), and then according to the PPO pruning objective function) Update strategy network parameters ,parameter After the update, the system will update the Critic network synchronously, manage the learning process, and finally apply the new strategy trained to actual control, thus starting the next round of online learning cycle.

[0066] ; The range is [-0.5, 0.5]m 3 / h;

[0067]

[0068] in: This represents the probability ratio between the old and new strategies. ; This is the trimming parameter (usually taken as 0.1~0.2). ③ After training the agent with the core control indicators of the current cycle and the flow rate input of the previous cycle, the flow rate adjustment sequence for each independent temperature zone is obtained. ; ④ The reinforcement learning controller calculates the average flow rate of each temperature zone in the previous cycle. and flow adjustment sequence The recommended flow rates for each independent temperature zone are calculated. The specific formula is as follows: .

[0069] When the circumferential temperature difference Furthermore, when in intermittent maintenance mode, preventative control mode, or minimum maintenance mode, a balanced control mode is required, necessitating differentiated flow distribution across each independent temperature zone. Each independent temperature zone corresponds to a flow rate The specific calculation formula is as follows: ; in: Based on the basic cooling flow rate, ; For the first The average surface temperature of each independent temperature zone This is the average surface temperature of all independent temperature zones; when The intermittent maintenance mode is matched, and the solenoid valves of the double-layer stainless steel pipe structure are set to: open for 2 minutes and close for 8 minutes, with a flow rate of [missing information] when open. The specific calculation formula is as follows: ; when and Time-matched preventative control mode, flow The specific calculation formula is as follows: ; when and Match the minimum maintenance mode at the time, and the flow rate The specific calculation formula is as follows: ; In S3.2.2, if the matching conditions of each dominant control mode interfere, the dominant control modes are matched according to the set priority order. The set priority order is: heating mode, emergency cooling mode, active cooling mode, balanced control mode, intermittent maintenance mode, preventive control mode, and minimum maintenance mode.

[0070] In S3.2.2, the dominant control modes include heating mode, emergency cooling mode, active cooling mode, balanced control mode, intermittent maintenance mode, preventive control mode, and minimum maintenance mode; When switching from zero flow, heating mode, intermittent maintenance mode to active cooling mode and balanced control mode, the initial flow rate is... The specific formula is as follows: ; in: For initial control error, , The initial maximum internal and external temperature difference, The target temperature difference; To set the minimum flow rate, ; To set the maximum flow rate, ; The specific formula for the initial flow rate when switching from emergency cooling mode to active cooling mode and balanced control mode is as follows: ; in: The flow rate value for the last control cycle of the previous dominant control mode; In S3.2.2, the core control indicators include the maximum internal and external temperature difference. Circular temperature difference Volume-weighted average temperature change rate, surface average temperature and ambient temperature ; The pouring space is divided into three equal areas along the radius: the area closest to the inside of the shaft is the formwork layer, the middle area is the central layer, and the area closest to the outside of the shaft is the near-rock layer; the maximum internal and external temperature difference. The specific calculation formula is as follows: ; in: For the first A temperature sensor measures the temperature of the concrete in the center layer. For the first A temperature sensor measures the concrete temperature of the formwork layer; Circular temperature difference The specific calculation formula is as follows: ; Volume-weighted average temperature change rate The specific calculation formula is as follows: ; ; in: The temperature is a volume-weighted average. For a moment At that time, the first Readings from a temperature sensor; This represents the total number of temperature sensors currently capable of monitoring real-time temperature data. To monitor the total volume of concrete at the cross-section; For the first The concrete volume corresponding to each sensor, i.e., the volume weight, is calculated using the following formula: ; in: It can be 45° or 60°; The height interval between adjacent temperature sensors; For the first The outer diameter of the concrete in the area where the temperature sensor is located. For the first The inner diameter of the concrete in the area where each temperature sensor is located, denoted by the area number . Then the first outer diameter of the region And then the number Inner diameter of the region The specific calculation formula is as follows: ; in: When we take 1, 2, and 3, the corresponding regions are the template layer, the central layer, and the near-rock layer, respectively. The outer diameter of the shaft; This refers to the inner diameter of the shaft. Interlayer radial thickness; Average surface temperature The specific calculation formula is as follows: ; S3.2.3 The automatic actuator adjusts the opening degree of each solenoid valve according to the flow rate corresponding to each independent temperature zone in the current dominant control mode; When the dominant control mode is active cooling mode or balanced control mode, after calculating the flow rate corresponding to each independent temperature zone in S3.2.2, the process also includes: calculating the fine-tuning factor corresponding to each independent temperature zone based on fuzzy inference and defuzzification process; fine-tuning the flow rate corresponding to the dominant control mode according to the fine-tuning factor to obtain the refined flow command for each independent temperature zone; in S3.2.3, the automatic actuator adjusts the opening degree of each solenoid valve according to the refined flow command for each independent temperature zone in the current dominant control mode. S3.2.4 Determine if the current dominant control mode has changed. If yes, return to S3.2.1; otherwise, further determine: like Then let ,when The initial flow rate for the second control cycle is determined at that time. Then with the initial flow Restart all solenoid valves with the double-layer stainless steel pipe structure, and return to S3.2.2; when If necessary, return directly to S3.2.2; like If so, it will directly return to S3.2.2; Until the concrete has completed its initial setting.

[0071] In S3.2.4, the initial flow rate The process of determining: ① Calculate the cooling efficiency for the first cycle. The specific formula is as follows:

[0072] in: This represents the maximum temperature difference in the concrete during the first cycle. This represents the initial maximum internal and external temperature difference for the current control cycle. ② Calculate the proportional gain coefficient of the adaptive incremental PID controller in the first cycle based on the cooling efficiency. The specific formula is as follows: ; In this embodiment, if the cooling efficiency is very low (less than 0.2), a larger proportional gain is required; if the cooling efficiency is very high (greater than 2.0), a smaller proportional gain is required to prevent overshoot.

[0073] ③ According to Calculate the initial flow rate The specific formula is as follows: ; in: The control error after the first cycle, .

[0074] S4: Start the climbing module 4 to drive the platform module 1 to move upward a unit distance in the vertical direction. At the same time, the platform module 1 drives the template panel 2.2 to detach from the 10-layer concrete structure formed by S3 and move upward a corresponding unit distance in the vertical direction. S5: Repeat S2 to S4 until the lining construction of the entire shaft to be constructed is completed.

[0075] In this embodiment, the construction method of the large-diameter vertical shaft sliding membrane system utilizes climbing rods that are tied to the steel mesh of the vertical shaft lining as the support for the entire sliding membrane system. Through-type jacks on the climbing rods and a power-assisted system are used to move the sliding membrane system up and down. The template panels are fixed to the surrounding ring with hooks, and the support columns and the platform are all connected with bolts, which can achieve rapid installation and disassembly.

[0076] The large-diameter vertical shaft sliding formwork system has three working layers, which can be used for steel reinforcement installation, concrete pouring, and concrete curing and defect removal, respectively. Steel reinforcement installation does not affect the lower layer of concrete pouring. Concrete is pumped from the shaft opening into the storage tank of the distribution bin via the pouring system. After the discharge port is opened, the concrete is evenly distributed in the distribution tray by the uniform rotation of the distribution tank, and finally poured into the formwork through eight U-shaped chutes set on the platform, completing the vertical shaft lining concrete pouring. The lining concrete is poured to a height of 0.6m at a time. After the concrete has initially set and achieved a certain degree of self-stability, the sliding formwork is lifted. During the lifting process, 40 sets of through-hole hydraulic jacks operate synchronously under the control of a central hydraulic pump station and pressure regulating valves. After hydraulically driven climbing into position, the bottom automatically locks. The climbing speed is directly related to the size of the hydraulic pressure in each zone. By controlling the opening of the hydraulic pressure valves, the hydraulic cylinders are kept moving at a uniform and synchronous speed, preventing the sliding formwork from tilting and deforming. Each climbing rod is equipped with a limit device to ensure that all hydraulic cylinders extend with consistent stroke after each climb, maintaining the horizontal stability of the sliding formwork platform. The shaft lining was constructed using the slipform method. The key to this method is continuous pouring to avoid cold joints. Unlike conventional pouring, demolding begins during the slipform's lifting process, and concrete curing and defect correction are carried out simultaneously at the lowest platform. Special personnel are assigned to perform a secondary finishing of the exposed concrete surface as it slides upwards, repairing any honeycomb or pitted areas, and regularly watering the shaft lining concrete for curing.

[0077] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Any equivalent structural transformations made based on the inventive concept of the present invention and the contents of the specification and drawings of the present invention, or direct / indirect applications in other related technical fields, are included within the protection scope of the present invention.

Claims

1. A large-diameter deep vertical shaft slipform system for lining construction of the inner wall of a vertical shaft, characterized in that, The large-diameter deep vertical shaft slipform system includes a platform module (1), a template module (2), a pumping and casting module (3), a climbing module (4), and an adaptive curing module. The template module (2) is set opposite to the inner wall of the shaft to form a casting space by enclosing the inner wall of the shaft, and the casting space is provided with lining steel bars. The template module (2) is fixedly sleeved on the outside of the platform module (1). The pumping and pouring module (3) is installed on the platform module (1) and is used to transport concrete (10) into the pouring space. The climbing module (4) includes a lifting drive and a climbing rod (4.2). The lifting drive is mounted on the platform module (1). The climbing rod (4.2) is set vertically. The bottom end of the climbing rod (4.2) is welded to the bottom wall of the shaft. The climbing rod (4.2) is tied to the lining steel bars. The lifting drive is sleeved on the climbing rod (4.2). The lifting drive can slide and climb along the climbing rod (4.2) to drive the platform module (1) to move vertically. The adaptive curing module is installed on the template module (2) and is used to adaptively cure the concrete (10) in the pouring space.

2. The large-diameter deep vertical shaft slipform system as described in claim 1, characterized in that, The platform module (1) includes a lifting platform (1.1), a material unloading platform (1.2), and columns (1.3). The lifting drive component is disposed on the lifting platform (1.1). The material unloading platform (1.2) is disposed on the lifting platform (1.1) by a plurality of columns (1.3) arranged circumferentially along the center of the lifting platform (1.1), and a hollow space (1.4) is formed between the material unloading platform (1.2) and the lifting platform (1.1). The material unloading platform (1.2) is provided with an annular groove communicating with the hollow space (1.4). The pumping and casting module (3) is disposed at the annular groove.

3. The large-diameter deep vertical shaft slipform system as described in claim 2, characterized in that, The pumping and pouring module (3) includes a pumping grouting device, a conveying and descent structure (3.1), a storage tank (3.2), a distribution tank (3.3), a distribution plate (3.4), a U-shaped chute structure (3.5), a rotary drive component (3.6), and a transmission component (3.7). The pumping grouting device is located at the wellhead of the vertical shaft and is used to convey concrete (10). One end of the conveying and descent structure (3.1) is connected to the pumping grouting device, and the other end is correspondingly set to the storage tank (3.2). The conveying and descent structure (3.1) can adjust its length according to the lining construction progress. The storage tank (3.2) is rotatably set on the unloading platform (1.2) and is concentrically set with the annular trough. The distribution tank (3.3) is set on the unloading platform (1.2) and is correspondingly set to the outlet of the storage tank (3.2). The distribution plate (3.4) 3.4) The material distribution plate (3.4) is located between the storage tank (3.2) and the unloading platform (1.2) and is corresponding to the annular groove. The material distribution plate (3.4) is provided with a through hole for the storage tank (3.2) to pass through. The unloading platform (1.2) is provided with a plurality of U-shaped chute structures (3.5) arranged around the circumference of the annular groove. The first end of each U-shaped chute structure (3.5) is connected to the material distribution plate (3.4), and the other end extends into the pouring space. The rotary drive (3.6) is located on the unloading platform (1.2). The rotary drive (3.6) is connected to the storage tank (3.2) through the transmission component (3.7). The rotary drive (3.6) can drive the storage tank (3.2) to rotate around the center of the annular groove so as to uniformly transport the concrete (10) into the material distribution plate (3.4).

4. The large-diameter deep vertical shaft slipform system as described in claim 3, characterized in that, The template module (2) includes a surrounding ring (2.1), a template panel (2.2), and hooks (2.3). The outer periphery of the lifting platform (1.1) is provided with at least two surrounding rings (2.1) spaced apart in the vertical direction. One side of the template panel (2.2) is arranged opposite to the inner wall of the shaft, and the other side is provided with hooks (2.3) corresponding to the surrounding rings (2.1). The template panel (2.2) is hung on the corresponding surrounding rings (2.1) through the hooks (2.3). And / or, the large-diameter deep vertical shaft slipform system further includes a defect rectification platform (6), the defect rectification platform (6) includes an annular steel plate (6.1), a hanging rod (6.2), a ladder (6.3) and a safety net (6.4), the annular steel plate (6.1) is connected to the bottom of the lifting platform (1.1) by a plurality of evenly arranged hanging rods (6.2); the ladder (6.3) is connected between the top of the lifting platform (1.1) and the annular steel plate (6.1); the safety net (6.4) is set in the hollow part of the annular steel plate (6.1).

5. The large-diameter deep vertical shaft slipform system as described in claim 4, characterized in that, The adaptive maintenance module includes a maintenance pipeline device, a temperature sensor group, a central control device, a data processing and analysis device, and an automatic execution device. The maintenance pipeline device includes a double-layer stainless steel pipe structure (5.1), solenoid valves, and an electric heating water tank (5.2). The double-layer stainless steel coil is embedded in the template panel (2.2) in an S-shaped arrangement. The double-layer stainless steel pipe structure (5.1) is equipped with multiple solenoid valves, which divide the double-layer stainless steel pipe structure (5.1) into multiple independent temperature zones. The hot water pipeline in the double-layer stainless steel coil is connected to the electric heating water tank to supply hot water to the hot water pipeline in the double-layer stainless steel coil. The cold water pipeline in the double-layer stainless steel coil is connected to the underground cold water pool (7) to supply cold water to the cold water pipeline in the double-layer stainless steel coil. The lining steel bars are provided with multiple temperature sensor groups spaced at predetermined intervals along the vertical direction and radially along the shaft. Each temperature sensor group includes multiple temperature sensor elements uniformly arranged circumferentially along the lining steel bars. The central control device is electrically connected to each of the temperature sensors. The data processing and analysis device is electrically connected to the central control device and is used to process the real-time temperature data transmitted by the temperature sensors received by the central control system. The automatic execution device can control the solenoid valve of the double-layer stainless steel pipe structure (5.1) according to the data transmitted by the temperature sensors to adjust the water flow rate corresponding to the independent temperature zone.

6. A construction method for a large-diameter deep vertical shaft slipform system, comprising using the large-diameter deep vertical shaft slipform system as described in claim 5 to line the inner wall of the shaft, characterized in that, Includes the following steps: S1: Lining steel bars are installed in the shaft to be constructed, and a large-diameter deep data sliding membrane system is installed in the shaft to be constructed; wherein: multiple climbing rods (4.2) are tied to the lining steel bars in the vertical direction, and adjacent climbing rods (4.2) are connected by a male-female threaded connector. S2: Start the pumping and pouring module (3) to pour concrete (10) of a set height into the pouring space between the template panel (2.2) and the shaft wall; S3: Based on the artificial intelligence algorithm that integrates fuzzy reasoning, neural network prediction and reinforcement learning, the concrete (10) poured this time is adaptively cured through the adaptive curing module and template panel (2.2) until the concrete (10) initially sets and forms a concrete (10) layer structure, which then enters S4. S4: Start the climbing module (4) to drive the platform module (1) to move a unit distance upward in the vertical direction. At the same time, the platform module (1) drives the template panel (2.2) to detach from the concrete (10) layer structure formed by S3 and move a corresponding unit distance upward in the vertical direction. S5: Repeat S2 to S4 until the lining construction of the entire shaft to be constructed is completed.

7. The construction method for a large-diameter deep vertical shaft slipform system as described in claim 6, characterized in that, S3 includes: S3.1 The data processing and analysis device calculates the core control indicators based on the real-time temperature data transmitted by the temperature sensor received by the central control system. S3.2, Based on core control indicators, set time intervals The flow rate of each independent temperature zone is adaptively adjusted for one control cycle until the concrete (10) has completed its initial setting; specifically including: S3.2.1, Set the control period =1. Initial Time =0, determine the control cycle. initial flow ; S3.2.

2. Construct a two-layer inference engine based on fusion fuzzy inference. Use the two-layer inference engine to match the corresponding dominant control mode based on the core control indicators calculated from real-time temperature data, and calculate the flow rate corresponding to each independent temperature zone of the dominant control mode. S3.2.3 The automatic actuator adjusts the opening degree of each solenoid valve according to the flow rate corresponding to each independent temperature zone in the current dominant control mode; S3.2.4 Determine if the current dominant control mode has changed. If yes, return to S3.2.1; otherwise, further determine: like Then let ,when The initial flow rate for the second control cycle is determined at that time. Then with the initial flow Restart all solenoid valves with the double-layer stainless steel pipe structure, and return to S3.2.2; when If necessary, return directly to S3.2.2; like If so, it will directly return to S3.2.2; Continue until the concrete has completed its initial setting and enters S4.

8. The construction method of the large-diameter deep vertical shaft slipform system as described in claim 7, characterized in that, In S3.2.2, the dominant control modes include heating mode, emergency cooling mode, active cooling mode, balanced control mode, intermittent maintenance mode, preventive control mode, and minimum maintenance mode; When switching from zero flow, heating mode, intermittent maintenance mode to active cooling mode and balanced control mode, the initial flow rate is... The specific formula is as follows: ； in: For initial control error, , The initial maximum internal and external temperature difference for the current control cycle. The target temperature difference; To set the minimum flow rate; To set the maximum flow rate; The specific formula for the initial flow rate when switching from emergency cooling mode to active cooling mode and balanced control mode is as follows: ； in: The flow rate value for the last control cycle of the previous dominant control mode; In S3.2.2, the core control indicators include the maximum internal and external temperature difference. Circular temperature difference Volume-weighted average temperature change rate, surface average temperature and ambient temperature ; The pouring space is divided into three equal areas along the radius: the area closest to the inside of the shaft is the formwork layer, the middle area is the central layer, and the area closest to the outside of the shaft is the near-rock layer; the maximum internal and external temperature difference. The specific calculation formula is as follows: ； in: For the first A temperature sensor measures the temperature of the concrete in the center layer. For the first A temperature sensor measures the concrete temperature of the formwork layer; Circular temperature difference The specific calculation formula is as follows: ； Volume-weighted average temperature change rate The specific calculation formula is as follows: ； ； in: The temperature is a volume-weighted average. For a moment At that time, the first Readings from a temperature sensor; This represents the total number of temperature sensors currently capable of monitoring real-time temperature data. To monitor the total volume of concrete at the cross-section; For the first The concrete volume corresponding to each sensor, i.e., the volume weight, is calculated using the following formula: ； in: It can be 45° or 60°; The height interval between adjacent temperature sensors; For the first The outer diameter of the concrete in the area where the temperature sensor is located. For the first The inner diameter of the concrete in the area where each temperature sensor is located, denoted by the area number . Then the first outer diameter of the region And then the number Inner diameter of the region The specific calculation formula is as follows: ； in: When we take 1, 2, and 3, the corresponding regions are the template layer, the central layer, and the near-rock layer, respectively. The outer diameter of the shaft; This refers to the inner diameter of the shaft. Interlayer radial thickness; Average surface temperature The specific calculation formula is as follows: ； When the dominant control mode is active cooling mode or balanced control mode, after calculating the flow rate corresponding to each independent temperature zone in S3.2.2, the process further includes: calculating the fine-tuning factor corresponding to each independent temperature zone based on fuzzy inference and defuzzification process; fine-tuning the flow rate corresponding to the dominant control mode according to the fine-tuning factor to obtain the refined flow command for each independent temperature zone; in S3.2.3, the automatic actuator adjusts the opening degree of each solenoid valve according to the refined flow command for each independent temperature zone in the current dominant control mode.

9. The construction method for a large-diameter deep vertical shaft slipform system as described in claim 8, characterized in that, In S3.2.4, the initial flow rate The process of determining: ① Calculate the cooling efficiency for the first cycle. The specific formula is as follows: in: This represents the maximum temperature difference of the concrete during the first cycle. ② Calculate the proportional gain coefficient of the adaptive incremental PID controller in the first cycle based on the cooling efficiency. The specific formula is as follows: ； ③ According to Calculate the initial flow rate The specific formula is as follows: ； in: The control error after the first cycle, .

10. The construction method of the large-diameter deep vertical shaft slipform system as described in claim 9, characterized in that, In S3.2.2, the matching mechanism of the dominant control mode and the flow calculation process corresponding to each dominant control mode are as follows: when or Matching heating mode, flow rate The specific calculation formula is as follows: ； when Matching emergency cooling mode, flow rate The specific calculation formula is as follows: ； In emergency cooling mode, if Then it will switch from emergency cooling mode to intermittent maintenance mode; when Matching active cooling mode, traffic The specific calculation formula is as follows: ； in: The flow rate is calculated using an adaptive incremental PID controller; This is the fine-tuning factor obtained through fuzzy reasoning; The predicted traffic output by the trained traffic prediction model; To reinforce the recommended flow rate output by the learning controller; When the circumferential temperature difference Furthermore, when in intermittent maintenance mode, preventative control mode, or minimum maintenance mode, a balanced control mode is required, necessitating differentiated flow distribution across each independent temperature zone. Each independent temperature zone corresponds to a flow rate The specific calculation formula is as follows: ； in: Based on the basic cooling flow rate, ; For the first The average surface temperature of each independent temperature zone This is the average surface temperature of all independent temperature zones; when The intermittent maintenance mode is matched, and the solenoid valves of the double-layer stainless steel pipe structure are set to: open for 2 minutes and close for 8 minutes, with a flow rate of [missing information] when open. The specific calculation formula is as follows: ； when and Time-matched preventative control mode, flow The specific calculation formula is as follows: ； when and Match the minimum maintenance mode at the time, and the flow rate The specific calculation formula is as follows: ； In S3.2.2, if the matching conditions of each dominant control mode interfere, the dominant control modes are matched according to the set priority order. The set priority order is: heating mode, emergency cooling mode, active cooling mode, balanced control mode, intermittent maintenance mode, preventive control mode, and minimum maintenance mode.

11. The construction method of the large-diameter deep vertical shaft slipform system as described in claim 10, characterized in that, flow The specific calculation process is as follows: ； in: , For the first The proportional gain coefficient of a periodic adaptive incremental PID controller. ; For the first Cooling efficiency during the cycle, ; ; Fine-tuning factor obtained through fuzzy reasoning The specific calculation formula is as follows; ； in: It is an output variable The first uniformly discretized on its universe of discourse [-0.5, 0.5] One sampling point; At the sampling point After aggregation, output the membership values ​​of the fuzzy set; This represents the total number of sampling points.

12. The construction method for a large-diameter deep vertical shaft slipform system as described in claim 11, characterized in that, Predicted traffic The acquisition process specifically includes: Construct a training dataset, which includes: historical temperature sequences, environmental parameters, concrete material and geometric parameters, and flow rates corresponding to each control cycle; A long short-term memory recurrent neural network is constructed, which takes the feature vectors of concrete-related parameters as input and the temperature difference change trend corresponding to the concrete-related parameters as output; wherein: the concrete-related parameters include historical temperature sequence, environmental parameters, control input, and concrete material and geometric parameters; The training dataset is divided into a training set, a validation set, and a test set. The training set is used to iteratively train the long short-term memory recurrent neural network. After each training cycle, the validation set is used to evaluate the model performance, and an early stopping strategy is implemented based on the validation loss to prevent overfitting. The trained model is evaluated on the test set, and the prediction error index is calculated. The parameters of the best-performing model are saved as the model parameters of the trained LSTM model. The trained LSTM model is embedded into the MPC model predictive control framework, and the optimal control proposal sequence is obtained by solving the optimal control problem in the finite time domain based on the set objective function. Take the first prediction result of the optimal control suggestion sequence as the predicted flow rate. .

13. The construction method for a large-diameter deep vertical shaft slipform system as described in claim 12, characterized in that, Recommended flow rate output by the reinforcement learning controller Specifically, it includes: ① Construct a reinforcement learning controller. The reinforcement learning control module integrates an agent based on the proximal policy optimization (PPO) algorithm. This agent includes a policy network and a critic network. ② Train and learn online the agent in the reinforcement learning controller to obtain the trained agent; ③ After training the agent with the core control indicators of the current cycle and the flow rate input of the previous cycle, the flow rate adjustment sequence for each independent temperature zone is obtained. ; ④ The reinforcement learning controller calculates the average flow rate of each temperature zone in the previous cycle. and flow adjustment sequence The recommended flow rate for each independent temperature zone is calculated. The specific formula is as follows: 。

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