Temperature measurement point arrangement method of automatic temperature measurement system of anchor cable frame beam winter construction heat preservation shed

Abstract

The invention discloses a temperature measurement point arrangement method of an automatic temperature measurement system for an anchor cable frame beam winter construction thermal insulation shed. According to the method, grids are uniformly divided on a surface to be subjected to temperature measurement, and a first batch of temperature measurement sensors are arranged at grid nodes; and calculating a semi-variance function between different temperature measurement points by using temperature measurement data so as to evaluate the temperature correlation between the nodes, and dynamically adjusting the arrangement of the temperature measurement points through the data. The strategy is helpful for accurately identifying blind areas of temperature monitoring, and temperature measuring sensors are additionally arranged in the key areas, so that sufficient maintenance and construction quality of concrete are ensured, and cost is optimized at the same time.

Description

Technical Field

[0001] The invention relates to a temperature measuring point arrangement method of an automatic temperature measuring system of a heat preservation shed for winter construction of an anchor cable frame beam, and belongs to the technical field of concrete temperature measuring point arrangement. Background Art

[0002] To ensure the quality of winter concrete construction, during the concrete curing stage, after the concrete pouring is completed, the pile body and frame beam area are covered with thermal insulation tarpaulins, and electric steam is used inside the tarpaulins for mold curing, so that the ambient temperature of the concrete structure to be cured is not less than 10°C. At the same time, the temperature in the insulation shed is continuously monitored from the completion of concrete pouring to the removal of the mold.

[0003] In order to comprehensively monitor the temperature measurement surface of the concrete being maintained, the existing temperature measurement points are usually evenly arranged on the surface to be measured. However, the problem with this arrangement method is that the arrangement plan has no basis. It is assumed that the environment and properties of all positions of the surface to be measured are consistent. If too few temperature measurement points are set, blind spots may occur, resulting in partial maintenance failure. If the temperature measurement points are evenly increased, the cost of temperature measurement sensors and construction will increase quadratically.

[0004] How to avoid it is a problem that the existing technology needs to solve urgently.

[0005] Contents

[0006] The technical problem to be solved by the present invention is to provide a method for arranging temperature measurement points of an automatic temperature measurement system for a winter construction insulation shed of an anchor cable frame beam, so as to overcome the shortcomings of the prior art.

[0007] The technical solution of the present invention is: a method for arranging temperature measurement points of an automatic temperature measurement system for a winter construction insulation shed of an anchor cable frame beam, the method comprising:

[0008] The surface to be measured is divided into grids evenly to obtain a first grid;

[0009] Arrange the first batch of temperature measurement sensors at the nodes of the first grid;

[0010] Obtain the temperature measurement time series of each temperature sensor;

[0011] further dividing the first grid into a second grid with a smaller mesh size;

[0012] Calculate the distance between the nodes of the second grid and the nodes of the first grid at each time point;

[0013] Calculate the semi-variance values ​​between all nodes of the first grid at each time point;

[0014] Fitting the semivariance values ​​between all nodes of the first grid at each time point with the distances between all nodes of the first grid to obtain the first semivariance function at each time point;

[0015] Calculate the semivariance value between all nodes of the second grid and the nodes of the first grid at each time point through the first semivariance function at each time point;

[0016] Calculate the influence factor of each node of the first grid on the nodes of the second grid at each time point;

[0017] Sum the influence factors of each node of the first grid on the nodes of the second grid to obtain the total influence value at each time point;

[0018] The total impact values ​​at each time point were averaged to obtain the average impact index;

[0019] A second batch of temperature measuring sensors are arranged at points where the average influence index is less than the first set threshold value.

[0020] Furthermore, it also includes:

[0021] Calculate the average of the average influence indexes of the four nodes of all the grids of the second grid within the first grid to obtain the spatial influence average value;

[0022] If the spatial influence average value of the grids of the second grid is greater than the second set threshold, setting the grids of the second grid as the grids to be subdivided;

[0023] Divide the interior of the grid to be subdivided into grids to obtain a third grid;

[0024] Obtain the temperature measurement time series of each temperature sensor;

[0025] Calculate the distance between the node of the third grid and each temperature sensor at each time point;

[0026] Calculate the semi-variance value of each temperature sensor;

[0027] Fitting the semivariance value of each temperature sensor with the distance between all temperature sensors to obtain a second semivariance function;

[0028] The semivariance values ​​between all nodes of the third grid and all temperature sensors are calculated by the second semivariance function;

[0029] Calculate the impact factor of each temperature sensor on the nodes of the third grid;

[0030] The influence factor of each temperature sensor on the nodes of the third grid is summed to obtain the total influence value at each time point;

[0031] The total impact values ​​at each time point were averaged to obtain the average impact index;

[0032] A third batch of temperature measuring sensors are arranged at points where the average influence index is less than the first set threshold value.

[0033] Preferably, the conditions for arranging the second batch of temperature measuring sensors also include:

[0034] In each grid of the first grid, only the nodes of the second grid with the highest average influence index are selected to arrange the second batch of temperature measurement sensors.

[0035] Specifically, the method for calculating the semi-variance values ​​between all nodes of the first grid at each time point is:

[0036]

[0037] Among them, t(x i ,y i ,t) and t(x j ,y j ,t) distribution represents the temperature values ​​of nodes j and j of the first grid at time t.

[0038] Specifically, the method of fitting the semi-variance values ​​between all nodes of the first grid at each time point with the distances between all nodes of the first grid to obtain the first semi-variance function at each time point is:

[0039] All ψ at time t ij (d ij ,t) and d ij For fitting function ψ(d), The fitted parameter values ​​a and c are calculated to obtain the fitting function ψ(d).

[0040] Specifically, the method for calculating the influence factor of each node of the first grid on the nodes of the second grid at each time point is:

[0041]

[0042] in, represents the influence factor of the node of the i-th first grid on the temperature at the node of the k-th second grid, n represents the number of nodes in the first grid, λ represents the auxiliary parameter calculated by the equation, ψ i1 represents the semivariance between the node of the ith first grid and the node of the 1st second grid, It represents the semivariance of the node of the i-th first grid to the node of the k-th second grid.

[0043] The beneficial effects of the present invention are: compared with the prior art,

[0044] 1) The present invention pre-sets the first grid and the second grid, and sets the first batch of temperature measuring sensors at the grid points of the first grid, calculates the influence factor of each node of the first grid on the node of the second grid, sums the influence factor of each node of the first grid on the node of the second grid to obtain the total influence value at each time point, and finally averages the total influence value at each time point to obtain the average influence index, and arranges the second batch of temperature measuring sensors at the points where the average influence index is less than the first set threshold value, thereby avoiding the blindness of arranging the temperature measuring sensors. The points where the average influence index is less than the first set threshold value can be regarded as temperature measurement blind areas, and the second batch of temperature measuring sensors are arranged in the temperature measurement blind areas, and the precise positions of the temperature measuring sensors are also given, and the points where the average influence index is greater than the first set threshold value can be regarded as accurate temperature measurement areas, and there is no need to increase the temperature measuring sensors. In this way, the number of arranged temperature measuring sensors is increased in weak areas, and the original number of arranged temperature measuring sensors is maintained in non-weak areas, thereby achieving a balance between avoiding detection blind areas and costs;

[0045] 2) The present invention calculates the influence factors of all temperature sensors on the nodes of the third grid through all the temperature sensors to which the second batch of temperature sensors have been added, and further calculates the influence factors of each temperature sensor on the nodes of the third grid to sum up to obtain the total influence value at each time point, and obtains the average influence index by averaging the total influence values ​​at each time point, and arranges the third batch of temperature sensors at the points where the average influence index is less than the first set threshold value, thereby further finding the temperature detection weak area in the grid of the second grid, realizing further refinement of the detection weak area, and making the arrangement of the temperature sensors more accurate;

[0046] 3) The present invention adds the following conditions to the arrangement of the second batch of temperature sensors: in each grid of the first grid, only the nodes of the second grid with the highest average influence index are selected to arrange the second batch of temperature sensors, thereby avoiding the problem of increased redundant cost of temperature sensors caused by indiscriminately arranging the second batch of temperature sensors in each grid of the first grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0048] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0049] Implementation Example 1:

[0050] Since the environment and properties of all locations on the surface to be measured cannot be consistent, each area is closely related to factors such as its material, slope, windward and leeward, moisture content and ambient temperature. If the temperature measurement points are simply arranged evenly, detection blind spots are likely to occur. If the temperature measurement sensors are simply encrypted, the number of temperature measurement points will increase exponentially, resulting in a situation where you cannot have both reduced detection blind spots and reduced costs.

[0051] In order to solve the above problems, this embodiment provides a method for arranging temperature measurement points of an automatic temperature measurement system for a winter construction insulation shed for anchor cable frame beams. Figure 1 , the method comprising:

[0052] The surface to be measured is divided into grids evenly to obtain a first grid;

[0053] Arrange the first batch of temperature measurement sensors at the nodes of the first grid;

[0054] Obtain the temperature measurement time series of each temperature sensor;

[0055] further dividing the first grid into a second grid with a smaller mesh size;

[0056] Calculate the distance between the nodes of the second grid and the nodes of the first grid at each time point;

[0057] Calculate the semi-variance values ​​between all nodes of the first grid at each time point;

[0058] Fitting the semivariance values ​​between all nodes of the first grid at each time point with the distances between all nodes of the first grid to obtain the first semivariance function at each time point;

[0059] Calculate the semivariance value between all nodes of the second grid and the nodes of the first grid at each time point through the first semivariance function at each time point;

[0060] Calculate the influence factor of each node of the first grid on the nodes of the second grid at each time point;

[0061] Sum the influence factors of each node of the first grid on the nodes of the second grid to obtain the total influence value at each time point;

[0062] The total impact values ​​at each time point were averaged to obtain the average impact index;

[0063] A second batch of temperature measuring sensors are arranged at points where the average influence index is less than the first set threshold value.

[0064] Furthermore, it also includes:

[0065] Calculate the average of the average influence indexes of the four nodes of all the grids of the second grid within the first grid to obtain the spatial influence average value;

[0066] If the spatial influence average value of the grids of the second grid is greater than the second set threshold, setting the grids of the second grid as the grids to be subdivided;

[0067] Divide the interior of the grid to be subdivided into grids to obtain a third grid;

[0068] Obtain the temperature measurement time series of each temperature sensor;

[0069] Calculate the distance between the node of the third grid and each temperature sensor at each time point;

[0070] Calculate the semi-variance value of each temperature sensor;

[0071] Fitting the semivariance value of each temperature sensor with the distance between all temperature sensors to obtain a second semivariance function;

[0072] The semivariance values ​​between all nodes of the third grid and all temperature sensors are calculated by the second semivariance function;

[0073] Calculate the impact factor of each temperature sensor on the nodes of the third grid;

[0074] The influence factor of each temperature sensor on the nodes of the third grid is summed to obtain the total influence value at each time point;

[0075] The total impact values ​​at each time point were averaged to obtain the average impact index;

[0076] A third batch of temperature measuring sensors are arranged at points where the average influence index is less than the first set threshold value.

[0077] Preferably, the conditions for arranging the second batch of temperature measuring sensors also include:

[0078] In each grid of the first grid, only the nodes of the second grid with the highest average influence index are selected to arrange the second batch of temperature measurement sensors.

[0079] Specifically, the method for calculating the semi-variance values ​​between all nodes of the first grid at each time point is:

[0080]

[0081] Among them, t(x i ,y i ,t) and t(x j ,y j ,t) distribution represents the temperature values ​​of nodes j and j of the first grid at time t.

[0082] Specifically, the method of fitting the semi-variance values ​​between all nodes of the first grid at each time point with the distances between all nodes of the first grid to obtain the first semi-variance function at each time point is:

[0083] All ψ at time t ij (d ij ,t) and d ij For fitting function ψ(d), The fitted parameter values ​​a and c are calculated to obtain the fitting function ψ(d).

[0084] Specifically, the method for calculating the influence factor of each node of the first grid on the nodes of the second grid at each time point is:

[0085]

[0086] in, represents the influence factor of the node of the i-th first grid on the temperature at the node of the k-th second grid, n represents the number of nodes in the first grid, λ represents the auxiliary parameter calculated by the equation, ψ i1 represents the semivariance between the node of the ith first grid and the node of the 1st second grid, It represents the semivariance of the node of the i-th first grid to the node of the k-th second grid.

[0087] Working principle: This method first divides the surface to be measured into a grid and sets up a batch of temperature sensors. Then, the semivariance function between each temperature measurement point is calculated based on the temperature measurement data to evaluate the temperature correlation between different points. Through this semivariance analysis, the blind areas of temperature measurement are determined, and additional temperature sensors are arranged in these areas. This method allows the arrangement of temperature measurement points to be adjusted dynamically, ensuring comprehensive and cost-effective coverage, thereby improving the quality control of winter concrete construction.

[0088] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. Arrangement method of temperature measurement points of automatic temperature measurement system for winter construction insulation shed of anchor cable frame beam, It is characterized in that The method comprises: The surface to be measured is divided into grids evenly to obtain a first grid; Arrange the first batch of temperature measurement sensors at the nodes of the first grid; Obtain the temperature measurement time series of each temperature sensor; further dividing the first grid into a second grid with a smaller mesh size; Calculate the distance between the nodes of the second grid and the nodes of the first grid at each time point; Calculate the semi-variance values ​​between all nodes of the first grid at each time point; Fitting the semivariance values ​​between all nodes of the first grid at each time point with the distances between all nodes of the first grid to obtain the first semivariance function at each time point; Calculate the semivariance value between all nodes of the second grid and the nodes of the first grid at each time point through the first semivariance function at each time point; Calculate the influence factor of each node of the first grid on the nodes of the second grid at each time point; Sum the influence factors of each node of the first grid on the nodes of the second grid to obtain the total influence value at each time point; The total impact values ​​at each time point were averaged to obtain the average impact index; A second batch of temperature measuring sensors are arranged at points where the average influence index is less than the first set threshold value.

2. The temperature measurement point arrangement method of the automatic temperature measurement system for the winter construction insulation shed of the anchor cable frame beam according to claim 1, It is characterized in that Also includes: Calculate the average of the average influence indexes of the four nodes of all the grids of the second grid within the first grid to obtain the spatial influence average value; If the spatial influence average value of the grids of the second grid is greater than the second set threshold, setting the grids of the second grid as the grids to be subdivided; Divide the interior of the grid to be subdivided into grids to obtain a third grid; Obtain the temperature measurement time series of each temperature sensor; Calculate the distance between the node of the third grid and each temperature sensor at each time point; Calculate the semi-variance value of each temperature sensor; Fitting the semivariance value of each temperature sensor with the distance between all temperature sensors to obtain a second semivariance function; The semivariance values ​​between all nodes of the third grid and all temperature sensors are calculated by the second semivariance function; Calculate the impact factor of each temperature sensor on the nodes of the third grid; The influence factor of each temperature sensor on the nodes of the third grid is summed to obtain the total influence value at each time point; The total impact values ​​at each time point were averaged to obtain the average impact index; A third batch of temperature measuring sensors are arranged at points where the average influence index is less than the first set threshold value.

3. The temperature measurement point arrangement method of the automatic temperature measurement system for the winter construction insulation shed of the anchor cable frame beam according to claim 1, It is characterized in that The conditions for arranging the second batch of temperature sensors also include: In each grid of the first grid, only the nodes of the second grid with the highest average influence index are selected to arrange the second batch of temperature measurement sensors.

4. The temperature measurement point arrangement method of the automatic temperature measurement system for the winter construction insulation shed of the anchor cable frame beam according to claim 1, It is characterized in that The method for calculating the semi-variance values ​​between all nodes of the first grid at each time point is: Among them, t(x i ,y i ,t) and t(x j ,y j ,t) distribution represents the temperature values ​​of nodes j and j of the first grid at time t.

5. The temperature measurement point arrangement method of the automatic temperature measurement system for the winter construction insulation shed of the anchor cable frame beam according to claim 4, It is characterized in that The method of fitting the semi-variance values ​​between all nodes of the first grid at each time point with the distances between all nodes of the first grid to obtain the first semi-variance function at each time point is: All ψ at time t ij (d ij ,t) and d ij For fitting function ψ(d), The fitted parameter values ​​a and c are calculated to obtain the fitting function ψ(d).

6. The temperature measurement point arrangement method of the automatic temperature measurement system for the winter construction insulation shed of the anchor cable frame beam according to claim 4, It is characterized in that The method for calculating the influence factor of each node of the first grid on the nodes of the second grid at each time point is: in, represents the influence factor of the node of the i-th first grid on the temperature at the node of the k-th second grid, n represents the number of nodes in the first grid, λ represents the auxiliary parameter calculated by the equation, ψ i1 represents the semivariance between the node of the ith first grid and the node of the 1st second grid, It represents the semivariance of the node of the i-th first grid to the node of the k-th second grid.

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