Method for monitoring sliding form rising process of face rockfill dam in high-cold and high-altitude area

Abstract

The application discloses a kind of panel rockfill dam slipform rising process monitoring methods for high-cold high-altitude area, comprising: in the vibration test phase: in test phase, obtain meteorological parameter, vibration maintenance duration and concrete test block solidification state information, construct and train concrete solidification state prediction model;In construction phase, carry out slipform real-time position, inclination angle sensing, and according to the intelligent early warning of slipform rising speed and inclination angle;Meteorological conditions in concrete pouring area are collected using a small weather collection device, and the current template position each layer solidification state is judged in combination with the concrete solidification state prediction model;Based on the current template position each layer solidification state analysis results, slipform real-time position sensing results, template sliding start condition analysis is carried out, and real-time reminder is carried out, and then feedback control of construction scheme is realized.The application can carry out template sliding start condition analysis, and real-time reminder is carried out, so as to provide data support for on-site construction process feedback control.

Description

Technical Field

[0001] This invention belongs to the field of construction progress analysis technology, specifically relating to a method for monitoring the slipform rising process of a rockfill dam with a concrete panel in high-altitude and cold regions. Background Technology

[0002] Due to their advantages such as smaller project scale, higher construction efficiency, and strong foundation adaptability, concrete-faced rockfill dams have become an important type of dam for water-retaining structures in current water conservancy and hydropower projects, especially in high-altitude and cold regions, such as the Mardang, Lawa, and Gushui projects. As the core component of water retention, the construction quality of the concrete face is crucial to ensuring the long-term stable operation of the project. To ensure the integrity and continuity of the concrete face pouring, the current method mainly uses sliding formwork (hereinafter referred to as slipform) for concrete pouring. During the slipform's ascent, the ascent speed and inclination are key control indicators, directly affecting the concrete construction quality and operational safety. Therefore, how to comprehensively consider the concrete solidification process and monitor the slipform's ascent process to ensure on-site operation quality and safety is a significant challenge for current concrete-faced rockfill dam projects.

[0003] Currently, the control of the slipform raising process in panel rockfill dams mainly relies on periodic manual measurements according to specifications, which makes it difficult to ensure that the slipform raising process is under control. Furthermore, the low temperatures and harsh climate of high-altitude and cold regions directly affect the maturity of the concrete, thus influencing the concrete setting process and the slipform raising speed. Therefore, existing technologies cannot effectively control the slipform raising process. Summary of the Invention

[0004] To address the problem that existing key technologies for monitoring the quality of concrete vibration are ill-suited for monitoring and analyzing the quality of concrete vibration in high-altitude and cold regions with continuous layer pouring characteristics, this invention provides a process monitoring method for continuous layer vibration operations of panel concrete. Based on vibration process parameters, the method integrates the intelligent prediction model of the vibration rod coverage radius and the prediction model of concrete performance indicators to predict the vibration coverage rate and concrete performance indicators.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for monitoring the slipform rise process of a panel rockfill dam in high-altitude and cold regions includes a testing phase and a construction phase, wherein:

[0007] During the experimental phase:

[0008] Obtain meteorological conditions, vibration curing time, and concrete specimen solidification state;

[0009] A concrete solidification state prediction model is constructed based on a neural network. The model is trained by taking the weather conditions of the concrete pouring area, the vibration curing time, and the solidification state of the concrete test block as inputs and the concrete solidification state as output. The training set of the weather conditions, vibration curing time, and concrete test block solidification state is then input into the neural network training model for training to obtain a trained concrete solidification state prediction model.

[0010] During the construction phase:

[0011] Based on high-precision BeiDou positioning technology and high-precision tilt angle sensing technology, the real-time position and tilt angle of the sliding mode are perceived to obtain sensing data including the sliding mode's ascent speed and tilt angle.

[0012] Based on the sliding formwork rising speed and the horizontal tilt angle of the template, a sliding formwork parameter early warning model is established to provide early warning during the sliding formwork rising process;

[0013] The solidification state of each layer at the current formwork position is judged by combining the meteorological conditions of the concrete pouring area with the trained concrete solidification state prediction model. Based on the analysis results of the solidification state of each layer at the current formwork position and the real-time position perception results of the sliding formwork, the conditions for starting the formwork sliding are analyzed, and real-time reminders are given.

[0014] In some implementations, the meteorological conditions include at least temperature, humidity, and rainfall.

[0015] In some embodiments, the vibration curing time t refers to the time calculated from the time Ti when the vibration of the embryo layer i is completed.

[0016] In some implementations, the solidification state analysis results of each embryo layer at the current template position are divided into two categories: unsolidified and non-sliding, and solidified and sliding.

[0017] In some implementations, the elevation H(t) of the top of the sliding mold is measured using high-precision BeiDou positioning technology, and the horizontal tilt angle θ(t) of the template is measured using a tilt sensor, where t is the measurement time.

[0018] In some implementations, the sliding mode parameter early warning model includes:

[0019] i. Establish an early warning model for the degree of deviation in the sliding mode ascent speed, with the following expression:

[0020] W v =f(v)

[0021] ii. Establish an early warning model for the degree of template horizontal tilt deviation, with the following expression:

[0022] W θ =f(θ(t))

[0023] Where v is the sliding mode rise speed, Δt is the time interval, and W v W is the warning intensity for the sliding mode ascent speed index. θ The intensity of the template horizontal tilt angle warning.

[0024] In some implementations, an alarm is triggered if the sliding mode rise speed v or θ(t) is greater than a set threshold.

[0025] In some implementations, if the concrete solidification state analysis results indicate that it has solidified and is ready to slide, a prompt is made to raise the concrete slipform.

[0026] Compared with the prior art, the beneficial technical effects of the present invention are as follows:

[0027] This invention acquires meteorological parameters, vibration curing time, and concrete specimen solidification state information during the experimental phase. These meteorological parameters and specimen solidification state are then input into a neural network to train a concrete solidification state prediction model based on meteorological factors. During construction, high-precision BeiDou positioning technology and high-precision tilt angle sensing technology are used to perceive the real-time position and tilt angle of the slipform, and intelligent early warnings are issued based on the slipform's rising speed and tilt angle. A small meteorological acquisition device collects meteorological parameters of the concrete pouring area, and this data is combined with the concrete solidification state prediction model to determine the solidification state of each layer at the current formwork position. Based on the analysis results of the solidification state of each layer at the current formwork position and the real-time position perception results of the slipform, the conditions for starting the formwork sliding are analyzed, and real-time alerts are provided, thus providing data support for feedback control of the on-site construction process. Attached Figure Description

[0028] Figure 1 This is an overall flowchart of the monitoring method for the slipform rise process of a panel rockfill dam in high-altitude and cold regions according to an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments in this specification clearer, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0030] like Figure 1 As shown, the present invention provides a method for monitoring the slipform rise process of a rockfill dam with a concrete panel in high-altitude and cold regions, including but not limited to steps S101 to S104:

[0031] Step S101: During the experimental phase, obtain meteorological conditions, vibration curing time and concrete specimen solidification state, and construct a concrete solidification state prediction model.

[0032] It should be noted that, based on the characteristics of rockfill dams in high-altitude and cold regions, the meteorological conditions mentioned include, but are not limited to, temperature, humidity, and rainfall; the concrete solidification state is divided into two categories: unsolidified and non-sliding, and solidified and sliding.

[0033] As one possible implementation of step S101, meteorological conditions and the solidification state of concrete test blocks are obtained, and the meteorological conditions and the on-site concrete solidification state are input into a neural network model to train a concrete solidification state prediction model based on meteorological factors, including:

[0034] Step S1011: It should be noted that, due to the complex meteorological conditions in high-altitude and cold regions, and considering the challenges faced by rockfill dam projects with concrete panels under such conditions, different meteorological parameters will directly affect the on-site concrete setting process. Therefore, a small weather station is used to acquire meteorological conditions, and test block experiments are used to determine the setting state under different conditions and different vibration curing times.

[0035] Step S1012: Construct a concrete solidification state prediction model based on a neural network. Take meteorological conditions, vibration curing time and concrete specimen solidification state as inputs and concrete solidification state as output to train the concrete solidification state prediction model. Input the training set of meteorological conditions, vibration curing time and concrete specimen solidification state into the neural network training model for training to obtain a trained concrete solidification state prediction model.

[0036] Step S102: During construction, based on high-precision Beidou positioning technology and high-precision tilt angle sensing technology, the real-time position and tilt angle of the sliding formwork are perceived, and intelligent early warning is designed based on the sliding formwork rising speed and tilt angle.

[0037] In an optional embodiment of step S102, the elevation H(t) of the top of the slipform is measured using high-precision BeiDou positioning technology, where t is the measurement time. The horizontal tilt angle θ(t) of the template is measured using a tilt sensor. The vibration completion time Ti of the embryo layer i is manually recorded, including:

[0038] Step S1021: Install a high-precision Beidou positioning device and tilt sensor on the top of the sliding formwork to achieve intelligent perception of the sliding formwork status and obtain perception data including the sliding formwork's rising speed and tilt angle.

[0039] Step S1022: Calculate the sliding formwork ascent speed based on the top elevation H(t) of the sliding formwork, as shown in the following expression:

[0040] v=(H(t+Δt)-H(t)) / Δt (1)

[0041] Establish a sliding mode parameter early warning model:

[0042] 1) Establish an early warning model for the degree of deviation in the sliding mode ascent speed, with the following expression:

[0043] W v =f(v) (2)

[0044] 2) Establish an early warning model for the degree of deviation of the template's horizontal tilt angle, with the following expression:

[0045] W θ =f(θ(t)) (3)

[0046] Where v is the sliding mode rise speed, Δt is the time interval, and W v The warning intensity for the slipform rise speed index, i.e., the degree of deviation between the actual slipform rise speed and the designed slipform rise speed, is W. θ The template horizontal tilt angle warning intensity is the degree of deviation between the actual template horizontal tilt angle and the designed template horizontal tilt angle. If v or θ(t) is greater than the set threshold, an alarm will be triggered.

[0047] Step S103: Use a small meteorological acquisition device to collect meteorological condition parameters of the concrete pouring area, combine them with the pouring time, and combine them with the concrete solidification state prediction model to judge the solidification state of each layer i at the current template position.

[0048] In an optional embodiment of step S103, the solidification state of each layer within the current template coverage area is obtained based on the concrete solidification state prediction model, and a reminder is given for the bottom layer that meets the solidification conditions.

[0049] Step S104: According to the classification of the concrete test block solidification state, if the concrete solidification state is "solidified and can be slidable", then prompt that the concrete slipform can be raised.

[0050] In one optional implementation of this embodiment, the method further includes:

[0051] The meteorological conditions, concrete solidification state, concrete slipform rising speed and inclination angle are stored in the basic database. At the same time, the meteorological parameters, vibration curing time and test block solidification state information are input into the neural network model. The model can be trained using a BP neural network to establish a concrete solidification state prediction model based on meteorological factors.

[0052] Based on the aforementioned publicly available information, during the experimental phase, meteorological parameters, vibration curing time, and concrete specimen solidification state information are acquired. These meteorological parameters and specimen solidification state are then input into a neural network to train a concrete solidification state prediction model based on meteorological factors. During construction, high-precision BeiDou positioning technology and high-precision tilt angle sensing technology are used to perceive the real-time position and tilt angle of the slipform, and intelligent early warnings are issued based on the slipform's rising speed and tilt angle. A small meteorological acquisition device is used to collect meteorological parameters of the concrete pouring area, and the concrete solidification state prediction model is combined to determine the solidification state of each layer at the current formwork position. Based on the analysis results of the solidification state of each layer at the current formwork position and the real-time position perception results of the slipform, the conditions for starting the formwork sliding are analyzed, and real-time reminders are provided, thereby achieving feedback control of the construction plan.

[0053] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for monitoring the sliding form rising process of a face rockfill dam in high-cold and high-altitude areas, characterized in that, Characterized in that, It comprises a test phase and a construction phase, wherein: In the test phase: Obtain meteorological conditions, vibration curing time and concrete test block solidification state; Based on neural network, a concrete solidification state prediction model is constructed, taking meteorological conditions, vibration curing time and concrete test block solidification state as input, and taking concrete solidification state as output, and the concrete solidification state prediction model is trained; the meteorological conditions, vibration curing time and concrete test block solidification state training set are input into the neural network training model for training, and a trained concrete solidification state prediction model is obtained; In the construction phase: Based on high-precision Beidou positioning technology and high-precision tilt angle sensing technology, the real-time position and inclination angle of the slip form are sensed to obtain sensing data of the slip form rising speed and inclination angle; And according to the slip form rising speed and the form horizontal inclination angle, a slip form parameter warning model is established to warn the slip form rising process; The meteorological conditions of the concrete pouring area are combined with the trained concrete solidification state prediction model to judge the solidification state of each layer of the current form position, and based on the solidification state analysis result of each layer of the current form position and the real-time position sensing result of the slip form, the form sliding start condition is analyzed and real-time reminding is performed.

2. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, The meteorological conditions at least include temperature, humidity and rainfall.

3. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, The vibration curing time t refers to the time calculated from the vibration completion time point Ti of the layer i.

4. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, The solidification state analysis result of each layer of the current form position is divided into two categories: un-solidified and non-slidable, and solidified and slidable.

5. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, The high-precision Beidou positioning technology is used to measure the elevation H(t) of the top of the slip form, and the inclination angle sensor is used to measure the form horizontal inclination angle θ(t), wherein t is the measurement time.

6. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, The slip form parameter warning model includes: i. A warning model for the deviation degree of the slip form rising speed is established, and the expression is as follows: W v = f(v) ii. A warning model for the deviation degree of the form horizontal inclination angle is established, and the expression is as follows: W θ = f(0(t)) Wherein, v is the sliding mode rising speed, Δt is the time interval, Wv is the sliding mode rising speed index early warning strength, W θ is the template horizontal inclination early warning strength.

7. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, If the slip form rising speed v or θ(t) is greater than the set threshold, an alarm is given.

8. The method for monitoring the sliding form rising process of a face rockfill dam in an alpine high-altitude area according to claim 1, characterized in that, If the concrete solidification state analysis result is solidified and slidable, it is reminded to perform concrete slip form rising.

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