A temperature detection method, system and device

Abstract

The present invention discloses a temperature detection method, system and equipment thereof, including collecting concrete composition information, wherein the concrete composition information includes cement ratio, water ratio, sand ratio and additive ratio; collecting concrete pouring position information, wherein the concrete pouring position information includes pouring structure information and environmental information; wherein the environmental information includes environmental temperature and environmental humidity; configuring temperature distribution influencing factors, wherein the temperature distribution influencing factors include concrete composition information, pouring structure information and environmental information; constructing a temperature field model according to the configured temperature distribution influencing factors, and using the KMeans algorithm to partition a single temperature field model to generate a temperature field list; traversing the temperature field after each partition, obtaining the cluster ID therein, and marking the position corresponding to each cluster ID as the layout position of the temperature measuring point, and generating a temperature measuring point layout list. The present invention can achieve the accuracy of the detection position and improve the accuracy of temperature measurement.

Description

Technical Field

[0001] The present invention relates to the field of detection technology, and in particular to a temperature detection method, system and equipment thereof. Background Art

[0002] There are many factors that affect the performance of concrete, among which temperature will directly affect the performance of concrete. Therefore, the detection of concrete temperature is particularly important.

[0003] There are many existing measurement methods for concrete temperature measurement. These measurements often require manual cooperation and still rely on experience to set measurement points. Therefore, there is uncertainty in both uniformity and accuracy. That is, the temperature measurement is not accurate due to inaccurate detection positions. The present invention proposes a temperature detection method to address this problem. Summary of the Invention

[0004] In view of the above technical deficiencies, the object of the present invention is to provide a temperature detection method to achieve the accuracy of the detection position and improve the accuracy of temperature measurement.

[0005] A first aspect of the present invention provides a temperature detection method, comprising the following steps:

[0006] Collecting concrete composition information, wherein the concrete composition information includes cement ratio, water ratio, sand ratio, and additive ratio;

[0007] Collecting concrete pouring location information, the concrete pouring location information includes pouring structure information and environmental information; wherein the environmental information includes ambient temperature and ambient humidity;

[0008] Configuring temperature distribution influencing factors, wherein the temperature distribution influencing factors include concrete composition information, pouring structure information, and environmental information;

[0009] According to the configured temperature distribution influencing factors, a temperature field model is constructed, and the KMeans algorithm is used to partition the single temperature field model to generate a temperature field list;

[0010] Traverse the temperature field after each partition, obtain the cluster ID, and mark the position corresponding to each cluster ID as the layout position of the temperature measurement point, and generate a temperature measurement point layout list.

[0011] Furthermore, the collection of concrete composition information and concrete pouring location information includes:

[0012] Define concrete composition information conditions, pouring structure information conditions, ambient temperature conditions, and ambient humidity conditions, and build a condition list;

[0013] Group the condition list according to the concrete composition information condition;

[0014] Traverse the condition list, obtain the concrete composition information in the current condition list, and calculate the weighted average of the current concrete composition information;

[0015] If the current weighted average is greater than the maximum weighted average, update the maximum weighted average and the condition list;

[0016] If the current weighted average is equal to the maximum weighted average, then add it to the current weighted average equal to the maximum weighted average;

[0017] If the current weighted average value is less than the maximum weighted average value, no addition is made.

[0018] Furthermore, the condition list is traversed to obtain the concrete composition information in the current condition list, including:

[0019] Traverse the condition list and obtain the cement ratio, water ratio, sand ratio and additive ratio in the current condition list;

[0020] If one or more of the cement ratio, water ratio, sand ratio, and additive ratio is not in the condition list, a new corresponding ratio value is added.

[0021] Furthermore, based on the configured temperature distribution influencing factors, a temperature field model is constructed, and the KMeans algorithm is used to partition the single temperature field model to generate a temperature field list, including:

[0022] Generate a three-dimensional grid model based on the casting structure information and grid size, and generate grid coordinate points;

[0023] Traverse each grid coordinate point, simulate the grid temperature change according to the concrete composition information and environmental information, and assign a temperature value to each grid coordinate point;

[0024] The temperature value is input into the KMeans algorithm as a feature, and the grid points are divided into several temperature regions;

[0025] According to the KMeans algorithm partitioning, different colors are assigned to different temperature areas to generate a temperature field list, in which the temperature value is defined as the sorting rule to sort the temperature field list.

[0026] A second aspect of the present invention provides a temperature detection system, the system comprising:

[0027] A concrete composition information collection module, wherein the concrete composition information collection module is used to collect concrete composition information, wherein the concrete composition information includes cement ratio, water ratio, sand ratio and additive ratio;

[0028] A concrete pouring position information acquisition module, wherein the concrete pouring position information acquisition module is used to collect concrete pouring position information, wherein the concrete pouring position information includes pouring structure information and environmental information; wherein the environmental information includes ambient temperature and ambient humidity;

[0029] A temperature field model generation module is used to construct a temperature field model according to the configured temperature distribution influencing factors, and to partition a single temperature field model using a KMeans algorithm to generate a temperature field list;

[0030] The temperature measurement point layout module is used to traverse the temperature field after each partition, obtain the cluster ID therein, and mark the position corresponding to each cluster ID as the layout position of the temperature measurement point, and generate a temperature measurement point layout list.

[0031] In a third aspect, the present invention further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program and the processor is used for the above-mentioned temperature detection method steps.

[0032] The beneficial effects of the present invention are that: the temperature distribution influencing factors can be configured according to the concrete composition information and the concrete pouring position information, and the temperature field model can be constructed to generate a temperature field list, thereby forming an accurate layout of the temperature measurement point positions, thereby making the temperature measurement more accurate;

[0033] At the same time, the KMeans algorithm is used to partition the single temperature field model and generate a temperature field list, which further improves the accuracy of temperature measurement and the visibility of distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 This is a flow chart of the temperature detection method provided by the present invention.

[0036] Figure 2 This is a schematic diagram of the temperature detection system provided by the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Example 1:

[0039] like Figure 1 As shown, the present invention provides a method for detecting concrete temperature, the method comprising:

[0040] S1: Collecting concrete composition information, where the concrete composition information includes cement ratio, water ratio, sand ratio and additive ratio;

[0041] Specifically, the concrete composition information is based on pre-known parameters, such as a cement ratio of 0.4, a water ratio of 0.3, a sand ratio of 0.2, and an additive ratio of 0.1 (note that this is only an example and the actual ratio needs to be allocated according to the actual situation). In this embodiment, the additive refers to mixed additives, such as additives that change the rheological properties of concrete, additives for setting and hardening, durability additives, etc.

[0042] S2: Collect concrete pouring location information, which includes pouring structure information and environmental information; wherein, the environmental information includes ambient temperature and ambient humidity; which are on-site environmental parameters, such as if the ambient temperature is 25 degrees Celsius, on-site collection is required, and the collection method is conventional in this field.

[0043] Furthermore, the collection of concrete composition information and concrete pouring location information includes:

[0044] Define concrete composition information conditions, pouring structure information conditions, ambient temperature conditions, and ambient humidity conditions, and build a condition list;

[0045] Group the condition list according to the concrete composition information condition;

[0046] Traverse the condition list, obtain the concrete composition information in the current condition list, and calculate the weighted average of the current concrete composition information.

[0047] If the current weighted average is greater than the maximum weighted average, update the maximum weighted average and the condition list;

[0048] If the current weighted average is equal to the maximum weighted average, then add it to the current weighted average equal to the maximum weighted average;

[0049] If the current weighted average value is less than the maximum weighted average value, no addition is made.

[0050] The accuracy of the assessment is improved through a weighted average. The casting structure information, ambient temperature, and humidity conditions are used as constants. Data is recorded based on the concrete composition information and grouped together to form a condition list. The calculation process assigns weights to the concrete composition information, including the cement ratio, water ratio, sand ratio, and additive ratio (this assignment can be based on experience and actual conditions). The weighted average is then used to calculate the precise temperature influencing factors at a specific location. If one or more of the cement ratio, water ratio, sand ratio, or additive ratio is not in the condition list, a new corresponding ratio value is added. This new corresponding ratio value is a constant defined based on experience to further ensure the accuracy of the calculation.

[0051] S3: Build a temperature field model based on the configured temperature distribution influencing factors, and use the KMeans algorithm to partition the single temperature field model to generate a temperature field list;

[0052] Specifically, a three-dimensional grid model is generated according to the casting structure information and the grid size, and grid coordinate points are generated; the grid size here is already defined.

[0053] Traverse each grid coordinate point, simulate the grid temperature change according to the concrete composition information and environmental information, and assign a temperature value to each grid coordinate point;

[0054] The temperature value is input into the KMeans algorithm as a feature, and the grid points are divided into several temperature regions;

[0055] Based on the KMeans algorithm partitioning, different colors are assigned to different temperature areas to generate a temperature field list. Among them, the temperature value can be defined as a sorting rule to sort the temperature field list.

[0056] Example 2:

[0057] Based on the first embodiment, Figure 2 As shown, this embodiment provides a temperature detection system, which includes:

[0058] The concrete composition information collection module 100 is used to collect concrete composition information, wherein the concrete composition information includes cement ratio, water ratio, sand ratio and additive ratio.

[0059] The concrete pouring position information collection module 200 is used to collect concrete pouring position information, and the concrete pouring position information includes pouring structure information and environmental information; wherein the environmental information includes environmental temperature and environmental humidity.

[0060] The temperature field model generation module 300 is used to construct a temperature field model according to the configured temperature distribution influencing factors, and use the KMeans algorithm to partition a single temperature field model to generate a temperature field list.

[0061] The temperature measurement point layout module 400 is used to traverse the temperature field after each partition, obtain the cluster ID therein, and mark the position corresponding to each cluster ID as the layout position of the temperature measurement point, and generate a temperature measurement point layout list.

[0062] Furthermore, the temperature field model generation module 300 is further configured to perform the following steps:

[0063] Generate a three-dimensional grid model based on the casting structure information and grid size, and generate grid coordinate points;

[0064] Traverse each grid coordinate point, simulate the grid temperature change according to the concrete composition information and environmental information, and assign a temperature value to each grid coordinate point;

[0065] The temperature value is input into the KMeans algorithm as a feature, and the grid points are divided into several temperature regions;

[0066] According to the KMeans algorithm partitioning, different colors are assigned to different temperature areas, a temperature field list is generated, and the temperature value is defined as the sorting rule to sort the temperature field list.

[0067] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A temperature detection method, characterized in that: The method comprises: Collecting concrete composition information, wherein the concrete composition information includes cement ratio, water ratio, sand ratio and additive ratio; Collecting concrete pouring location information, the concrete pouring location information includes pouring structure information and environmental information; wherein the environmental information includes environmental temperature and environmental humidity; Configuring temperature distribution influencing factors, wherein the temperature distribution influencing factors include concrete composition information, casting structure information, and environmental information; According to the configured temperature distribution influencing factors, a temperature field model is constructed, and the KMeans algorithm is used to partition a single temperature field model to generate a temperature field list; Traverse the temperature field after each partition, obtain the cluster ID, and mark the position corresponding to each cluster ID as the layout position of the temperature measurement point, and generate a temperature measurement point layout list; Among them, collecting concrete composition information and collecting concrete pouring location information include: Define concrete composition information conditions, pouring structure information conditions, ambient temperature conditions and ambient humidity conditions, and construct a condition list; Group the condition list according to the concrete composition information condition; Traverse the condition list, obtain the concrete composition information in the current condition list, and calculate the weighted average of the current concrete composition information; If the current weighted average is greater than the maximum weighted average, update the maximum weighted average and the condition list; If the current weighted average is equal to the maximum weighted average, then add it to the current weighted average equal to the maximum weighted average; If the current weighted average is less than the maximum weighted average, it will not be added.

2. A temperature detection method according to claim 1, characterized in that: Traverse the condition list and obtain the concrete composition information in the current condition list, including: Traverse the condition list and obtain the cement ratio, water ratio, sand ratio and additive ratio in the current condition list; If one or more of the cement ratio, water ratio, sand ratio and additive ratio is not in the condition list, a new corresponding ratio value is added.

3. A temperature detection method according to claim 1, characterized in that: According to the configured temperature distribution influencing factors, a temperature field model is constructed, and the KMeans algorithm is used to partition a single temperature field model to generate a temperature field list, including: Generate a three-dimensional mesh model based on the casting structure information and mesh size, and generate mesh coordinate points; Traverse each grid coordinate point, simulate the grid temperature change according to the concrete composition information and environmental information, and assign a temperature value to each grid coordinate point; The temperature value is input into the KMeans algorithm as a feature, and the grid points are divided into several temperature regions; According to the KMeans algorithm partitioning, different colors are assigned to different temperature areas to generate a temperature field list.

4. A temperature detection method as claimed in claim 3, characterized in that: According to the KMeans algorithm partitioning, different colors are assigned to different temperature areas, and a temperature field list is generated, including: Define the temperature value as the sorting rule to sort the temperature field list.

5. A temperature detection system, characterized in that: Used to perform the temperature detection method according to any one of claims 1 to 4, the system comprises: A concrete component information collection module, wherein the concrete component information collection module is used to collect concrete component information, wherein the concrete component information includes cement ratio, water ratio, sand ratio and additive ratio; A concrete pouring position information acquisition module, wherein the concrete pouring position information acquisition module is used to acquire concrete pouring position information, wherein the concrete pouring position information includes pouring structure information and environmental information; wherein the environmental information includes environmental temperature and environmental humidity; A temperature field model generation module, which is used to construct a temperature field model according to the configured temperature distribution influencing factors, and partition a single temperature field model using a KMeans algorithm to generate a temperature field list; The temperature measurement point layout module is used to traverse the temperature field after each partition, obtain the cluster ID therein, and mark the position corresponding to each cluster ID as the layout position of the temperature measurement point, and generate a temperature measurement point layout list.

6. A computer device comprising a memory and a processor, wherein a computer program is stored in the memory, wherein: The processor is used to execute the temperature detection method according to any one of claims 1 to 4.

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