A tunnel secondary lining mass concrete pouring temperature monitoring and control method

Abstract

The application provides a tunnel secondary lining mass concrete pouring temperature monitoring and control method, which comprises the following steps: setting a monitoring section, arranging monitoring points, obtaining monitoring data, preventing data analysis and control of a top cavity, and preventing temperature analysis and control of excessively high temperature. Compared with conventional mass concrete temperature control means, the method can realize monitoring effect of the compactness of the concrete at the top of the tunnel and can be widely applied to the field of tunnel secondary lining construction.

Description

TECHNICAL FIELD

[0001] The present application relates to a tunnel secondary lining mass concrete pouring temperature monitoring and control method, which is suitable for the field of tunnel secondary lining construction. BACKGROUND

[0002] In tunnel engineering, secondary lining is an important link to ensure the safety and stability of tunnel structure. The use of mass concrete has significant advantages in improving structural strength and durability, but it also brings challenges to temperature control. During the hydration process, concrete releases a large amount of hydration heat, causing internal temperature rise. If temperature control is not proper, it may cause cracks in concrete, strength reduction and other problems, which seriously affect the safety and service life of the project.

[0003] With the continuous development of tunnel construction technology, the traditional temperature monitoring and control method has been unable to meet the requirements of modern engineering for accuracy and real-time. Therefore, it is particularly important to establish a scientific and systematic temperature monitoring and control method. By monitoring the temperature change in real time during concrete pouring and combining effective temperature control measures, the temperature gradient can be effectively reduced to prevent cracks caused by temperature stress and ensure the overall performance and structural safety of concrete. At the same time, in the process of paying attention to temperature change, we need to pay more attention to a more important problem: the problem of arch concrete segregation cavity, which is the most different point of tunnel secondary lining mass concrete from other mass concrete. The traditional mass temperature control is only to control the temperature not to reach the allowable temperature value to avoid cracks and other problems, but for tunnel secondary lining mass concrete, a method is needed, a temperature control method considering arch concrete cavity and segregation. SUMMARY

[0004] The purpose of the present application is to solve the defects of mass concrete temperature control at present and consider the problem of arch concrete cavity and segregation of tunnel secondary lining mass concrete. Therefore, a tunnel secondary lining mass concrete pouring temperature monitoring and control method is proposed,

[0005] The purpose of the present application can be achieved by adopting the following technical solutions:

[0006] A tunnel secondary lining mass concrete pouring temperature monitoring and control method, characterized in that the tunnel secondary lining mass concrete pouring temperature monitoring and control method comprises the following steps:

[0007] S101, setting a monitoring section;

[0008] The setting of the monitoring section comprises planning the tunnel secondary lining temperature monitoring section before the secondary lining construction, and the number n of the section is calculated according to the length L of the secondary lining as formula (1),

[0009] n = Floor(L / 4) (1)

[0010] In the formula, Floor is the upward rounding function;

[0011] S102, arranging monitoring points;

[0012] The arrangement of the monitoring points comprises arranging 5 temperature monitoring points in a certain order in a single monitoring section, the certain order being left arch foot-left arch wall-left arch shoulder-arch top-right arch shoulder-right arch wall-right arch foot, and the specific positions being adjusted according to installation convenience, and the temperature monitoring points being arranged in the middle part of the secondary lining thickness;

[0013] S103, obtaining monitoring data;

[0014] The obtaining of the monitoring data comprises obtaining temperature data of the monitoring points at a certain time interval during the concrete pouring of the secondary lining, wherein the temperature data of the monitoring points of the ith section at the jth time interval are recorded as Aij(left arch foot), Bij(left arch wall), Cij(left arch shoulder), Dij(arch top), Eij(right arch shoulder), Fij(right arch wall) and Gij(right arch foot);

[0015] S104, data analysis and control for preventing top cavity;

[0016] The data analysis and control for preventing the top cavity comprises using the Aij(left arch foot), Bij(left arch wall), Cij(left arch shoulder), Eij(right arch shoulder), Fij(right arch wall) and Gij(right arch foot) data to perform data fitting to obtain arch top temperature fitting data D'ij, and judging whether there is a top cavity phenomenon in the top of the secondary lining according to the measured Dij(arch top) and the arch top temperature fitting data D'ij;

[0017] S105, temperature analysis and control for preventing high temperature;

[0018] The temperature analysis and control for preventing high temperature comprises using a long short-term memory neural network to analyze the monitoring data of each monitoring point according to the obtained temperature monitoring data of each monitoring point, obtaining a prediction value, and judging the future development state of the temperature by comparing the obtained prediction value with a set temperature threshold value, and feeding back the construction in a timely manner.

[0019] Further, in the above S104, the step of obtaining the vault temperature fitting data D'ij is: a) taking the Aij (left side of the arch foot), Bij (left side of the arch wall), Cij (left side of the arch shoulder), Eij (right side of the arch shoulder), Fij (right side of the arch wall) and Gij (right side of the arch foot) data as the dependent variable, and the independent variable corresponds to using 1, 2, 3, 5, 6 and 7, to form a data set, b) polynomial function fitting is performed on the data set, c) the index of the fitting effect is obtained, and when the goodness of fit is greater than 0.90, it is considered that a good fitting curve is obtained, otherwise the fitting function model should be changed for re-fitting until the requirements are met, e) the obtained fitting function that meets the requirements is used to calculate the vault temperature fitting data D'ij.

[0020] Further, in the above S104, the method step of judging whether the top of the secondary lining has a top cavity phenomenon is: a) obtaining the vault temperature fitting data D'ij and the measured data Dij, b) if Dij≥0.8D'ij, it indicates that the vault temperature is not abnormal at this time, and no special treatment is needed, if Dij∈[0.6D'ij, 0.8D'ij), it indicates that the vault compactness may be insufficient and needs to be handled, and if Dij is less than 0.6D'ij, it indicates that the vault has a serious abnormality and needs to be handled immediately.

[0021] The tunnel secondary lining mass concrete pouring temperature monitoring and control method provided by the application has the following beneficial effects: compared with the traditional mass concrete temperature control method, the application creatively considers the problems of tunnel vault concrete cavity and segregation in the temperature control method in view of the actual problems faced by the tunnel secondary lining mass concrete pouring. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The flowchart of the tunnel secondary lining mass concrete pouring temperature monitoring and control method of the application;

[0023] Figure 2 The position diagram of the embedded monitoring point of the embodiment of the tunnel secondary lining mass concrete pouring temperature monitoring and control method of the application;

[0024] Figure 3 The example data fitting curve diagram of the embedded monitoring point of the embodiment of the tunnel secondary lining mass concrete pouring temperature monitoring and control method of the application. DETAILED DESCRIPTION

[0025] The specific embodiments of the application will be described in detail below with reference to the accompanying drawings; it should be understood that the specific embodiments given here are only used to illustrate and explain the application, and cannot be used to limit the application.

[0026] The following is a specific embodiment of a tunnel secondary lining mass concrete pouring temperature monitoring and control method.

[0027] The tunnel construction project on which the embodiment relies is: a tunnel construction engineering of a certain tunnel of China Railway Construction Malaysia East Coast Railway, the geological conditions of the tunnel are: the overall condition of the tunnel surrounding rock is good except the portal section, the preliminary survey shows that the surrounding rock in the tunnel site area is mainly granite, the karst cave is not developed in the region, the tunnel body section II and III grade surrounding rock accounts for more than 50%, the inclined shaft surrounding rock is mainly IV and V grade surrounding rock, the surrounding rock has good integrity and low weathering degree; the region is rich in precipitation, has more surface water system, and the possibility of surrounding rock fissure water occurrence is larger for IV, V and VI surrounding rock.

[0028] S101, setting a monitoring section;

[0029] The setting of the monitoring section includes planning the tunnel secondary lining temperature monitoring section before the secondary lining construction, and the number n of the section is calculated according to the length L of the secondary lining of one edition as formula (1),

[0030] n = Floor (L / 4) (1)

[0031] In the formula, Floor is a rounding up function;

[0032] In the embodiment, the length of one edition of secondary lining is set to 12m, and according to the calculation of formula (1), the number of monitoring sections is set to 3, and is arranged in combination with the actual situation.

[0033] S102, arranging monitoring points;

[0034] The arrangement of the monitoring points includes arranging 5 temperature monitoring points in a certain order in a single monitoring section, the certain order is left arch foot-left arch wall-left arch shoulder-arch top-right arch shoulder-right arch wall-right arch foot, the specific position is adjusted according to the convenience of installation, and the temperature detection point is arranged in the middle part of the secondary lining thickness;

[0035] In the embodiment, the temperature monitoring point is arranged by using a buried thermometer, and a buried thermometer produced by Meihua Instrument is used, and the parameters are shown in Table 1, in the embodiment, the position diagram of the buried monitoring point is as shown in Figure 1 The position diagram is only a general description, and the actual position and trolley used in actual construction are related, which is determined by the convenience of construction.

[0036] Table 1 Buried thermometer parameter table

[0037] project parameter Temperature measurement range -55℃~+125℃ Measurement accuracy 0.3℃ resolution 0.1℃ Number of sampling points ＜256 Inspection cycle 1-120 points alarm threshold -55℃～+125℃ Data output LCD color screen / PC Measuring point line length ＜80m Power supply method AC220V / Lithium Battery Battery life 10-30 days (optional) Battery life Charge and discharge > 500 times Rated power 5W Operating temperature -20℃～+60℃ Operating humidity Less than 90% RH

[0038] S103, obtaining monitoring data;

[0039] The monitoring data is obtained, including obtaining temperature data of the monitoring points at certain time intervals during the concrete pouring process of the secondary lining, wherein the temperature data of the jth time interval monitoring point of the ith section is recorded as Aij (left side springer), Bij (left side spring wall), Cij (left side spring shoulder), Dij (vault top), Eij (right side spring shoulder), Fij (right side spring wall), and Gij (right side springer);

[0040] S104, data analysis and control for preventing top voids;

[0041] The data analysis and control for preventing top voids includes data fitting using the Aij (left side springer), Bij (left side spring wall), Cij (left side spring shoulder), Eij (right side spring shoulder), Fij (right side spring wall), and Gij (right side springer) data to obtain vault top temperature fitting data D'ij, and determining whether there is a top void phenomenon in the secondary lining top according to the measured Dij (vault top) and the vault top temperature fitting data D'ij. Further, in the above S104, the step of obtaining the vault top temperature fitting data D'ij is: a) taking the Aij (left side springer), Bij (left side spring wall), Cij (left side spring shoulder), Eij (right side spring shoulder), Fij (right side spring wall), and Gij (right side springer) data as the dependent variable, and taking 1, 2, 3, 5, 6, and 7 as the independent variable to form a data set, b) performing polynomial function fitting on the data set, c) obtaining a fitting effect index of goodness of fit, and when the goodness of fit is greater than 0.90, it is considered that a good fitting curve is obtained, otherwise the fitting function model should be changed for re-fitting until the requirements are met, and e) using the obtained fitting function that meets the requirements to calculate the vault top temperature fitting data D'ij.

[0042] Further, in the above S104, the method step of determining whether there is a top void phenomenon in the secondary lining top is: a) obtaining the vault top temperature fitting data D'ij and the measured data Dij, b) if Dij ≥ 0.8D'ij, it indicates that the vault top temperature is not abnormal and no special treatment is needed, if Dij ∈ [0.6D'ij, 0.8D'ij), it indicates that the vault compactness may be insufficient and needs to be treated, and if Dij is less than 0.6D'ij, it indicates that the vault top has a serious abnormality and needs to be treated immediately.

[0043] In this embodiment, we give an example of a set of data from the left side springer to the right side springer, as follows: Figure 3 The measured data D is 59℃, and the fitting function formula is: y = -1.71x 2+13.7x+30.1, D' = 57.54℃ is calculated by fitting formula, based on this, considering Dij≥0.8D'ij, it is indicated that the vault temperature is not abnormal at this time, and special treatment is not required.

[0044] S105, temperature analysis and control for preventing temperature from being too high;

[0045] The temperature analysis and control for preventing temperature from being too high comprises: according to obtained temperature monitoring data of each monitoring point, analyzing the monitoring data of each monitoring point by using a long short-term memory neural network to obtain a prediction value, and comparing the obtained prediction value with a set temperature threshold to determine a future development state of the temperature and timely feedback construction.

[0046] In the embodiment, the method of using the long short-term memory neural network to analyze the prediction value and perform dynamic construction is a common technology in the industry, and thus the embodiment will not be described in detail.

[0047] In the above embodiment, the application discloses a tunnel secondary lining mass concrete pouring temperature monitoring and control method, which comprises the following steps: setting a monitoring section, arranging monitoring points, obtaining monitoring data, data analysis and control for preventing top cavities, and temperature analysis and control for preventing temperature from being too high. Compared with conventional mass concrete temperature control means, the method can realize monitoring effect on the compactness of the tunnel top concrete, and can be widely applied to the field of tunnel secondary lining construction.

[0048] The above is a preferred embodiment of the application, and does not limit the application. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the application should be included in the protection scope of the application.

Claims

1. A method for monitoring and controlling the pouring temperature of mass concrete for the secondary lining of a tunnel, characterized in that, The steps of the tunnel secondary lining mass concrete pouring temperature monitoring and control method are as follows: 1) setting monitoring sections; 2) arranging monitoring points; 3) obtaining monitoring data; 4) data analysis and control for preventing top cavity; 5) temperature analysis and control for preventing high temperature; The setting monitoring sections comprises planning tunnel secondary lining temperature monitoring sections before secondary lining construction, and the number n of the sections is obtained according to the length L of one secondary lining plate, and the calculation formula is formula (1), （1） In the formula, Floor is a floor function; The arranging monitoring points comprises arranging 7 temperature monitoring points in a certain order in a single monitoring section, the certain order is left arch foot-left arch wall-left arch shoulder-arch top-right arch shoulder-right arch wall-right arch foot, the specific position is adjusted according to installation convenience, and the temperature monitoring points are arranged in the middle part of the secondary lining thickness; The acquisition monitoring data comprises: obtaining temperature data of the monitoring points at certain time intervals during the concrete pouring process of the second lining, wherein the temperature data of the left spring, the left arch wall, the left haunch, the vault, the right haunch, the right arch wall and the right spring of the i-th section at the j-th time interval are respectively recorded as A ij , B ij , C ij , D ij , E ij , F ij and G ij ; The data analysis and control for preventing top cavity includes using the A ij , B ij , C ij , E ij , F ij , and G ij data to obtain vault temperature fitting data D' ij ; according to the measured D ij and the vault temperature fitting data D' ij , it is determined whether there is a top cavity phenomenon in the top of the secondary lining; the step of obtaining the vault temperature fitting data D' ij is: a) taking the A ij , B ij , C ij , E ij , F ij , and G ij data as dependent variables, and taking 1, 2, 3, 5, 6, and 7 as independent variables to form a data set, b) performing polynomial function fitting on the data set, c) obtaining an index of fitting effect, fitting goodness, when the index of fitting goodness is greater than 0.90, it is considered that a good fitting curve is obtained, otherwise the fitting function model should be changed for re-fitting until the requirement is met, e) using the obtained fitting function meeting the requirement to calculate the vault temperature fitting data D' ij ; the method steps for determining whether there is a top cavity phenomenon in the top of the secondary lining are: a) obtaining the vault temperature fitting data D' ij and the measured data D ij , b) if D ij ≥ 0.8 D' ij , it is indicated that the vault temperature is not abnormal at this time, and no special treatment is needed, if D ij ∈ [0.6 D' ij , 0.8 D' ij ], it is indicated that the vault compactness may be insufficient, and treatment is needed, if D ij is less than 0.6 D' ij , it is indicated that the vault has a serious abnormality, and immediate treatment is needed; The temperature analysis and control for preventing high temperature comprises analyzing the monitoring data of each monitoring point by using a long short-term memory neural network according to the obtained temperature monitoring data of each monitoring point, obtaining a predicted value, comparing the obtained predicted value with a set temperature threshold value, judging the future development state of the temperature, and feeding back the construction in time.

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