Hydraulic engineering construction information acquisition and processing system based on big data

Abstract

The invention relates to the technical field of construction information processing, in particular to a hydraulic engineering construction information collecting and processing system based on big data, the system comprises a processor and a memory, and the processor executes a computer program stored in the memory to achieve the following steps: obtaining a construction data point corresponding to the current moment and a preset initial threshold value, judging data points corresponding to future moments according to a first threshold range obtained by a preset initial threshold value to obtain archiving construction data points, a first sequence and a first inflection point; and according to the first sequence and the first inflection point, a preset initial threshold value is adjusted to obtain a first adjustment threshold value, traversal is continuously performed on the future moment according to a second threshold range obtained by the first adjustment threshold value until hydraulic engineering construction is finished, and all construction data points archived in the traversal process serve as compressed data. And by adjusting the threshold value, the water conservancy construction data can be compressed in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of construction information processing, and more particularly to a big data-based water conservancy project construction information acquisition and processing system. Background Art

[0002] Water conservancy projects are an important part of the infrastructure construction, and are of great significance for flood control, irrigation, water supply and ecological protection. Since water conservancy projects are usually located near rivers, lakes or other water bodies, and include various landforms such as steep slopes, wetlands, deep ditches, etc., in order to carry out reasonable resource scheduling and allocation and ensure construction safety, various sensor data will be used during the construction process to monitor the water level, flow velocity, pressure, etc. of the construction location of the water conservancy project. As the construction time increases, the monitored data will gradually increase. Currently, in order to improve management efficiency and save storage space, the sensor monitoring data will be compressed, and then the compressed data will be transmitted and stored for subsequent call analysis, etc.

[0003] Currently, the SDT Rotating Door Algorithm is used to perform real-time compression on the data collected by the sensors during compression. However, during the compression process, a fixed threshold value is generally used for compression. However, the construction data to be monitored in water conservancy projects will be affected by working conditions and the environment. The construction data includes, but is not limited to, the water level difference between upstream and downstream, seepage pressure of the dam foundation, seepage flow rate, groundwater level, precipitation, temperature, humidity, wind speed, river flow rate, etc. Therefore, if a fixed threshold value is used for compression, the compression effect will be poor. If a lower threshold value is used for compression, although more important information under complex working conditions and environments such as pouring, blasting, heavy rain, and strong wind can be captured, small fluctuation data under stable working conditions and good environments will also be captured, resulting in a decrease in the compression ratio. If a higher threshold value is used for compression, although the compression ratio for stable working conditions and good environments can be improved, the probability of losing important information under complex working conditions and environments will also increase, resulting in poor compression quality. Therefore, dynamically adjusting the threshold value during the real-time compression process to improve the compression effect has become an urgent problem to be solved. Summary of the Invention

[0004] In order to solve the above problems, the present invention provides a big data-based water conservancy project construction information acquisition and processing system, and the technical solutions adopted are as follows: An embodiment of the present invention provides a big data-based water conservancy project construction information acquisition and processing system, including a processor and a memory. The processor executes the computer program stored in the memory to implement the following steps: During the construction of the water conservancy project, obtain the construction data point corresponding to the current moment and the preset initial threshold value, and obtain the first threshold range according to the preset initial threshold value; If it is determined that the construction data points corresponding to the 1st future moment to the bth future moment are within the first threshold range, and the upper slope of the construction data points corresponding to the 1st future moment to the bth future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (b + 1)th future moment is not within the first threshold range or the upper slope of the construction data point corresponding to the (b + 1)th future moment is not less than the lower slope of the construction data point corresponding to the (b + 1)th future moment, then file the construction data points corresponding to the current moment and the bth future moment, and record the data point sequence formed by the construction data points corresponding to the current moment to the bth future moment as the first sequence, and record the construction data point corresponding to the (b + 1)th future moment as the first inflection point; according to the first sequence and the first inflection point, adjust the preset initial threshold value to obtain the 1st adjusted threshold value, and obtain the second threshold range according to the 1st adjusted threshold value. If it is continuously determined that the construction data points corresponding to the (b + 1)th future moment to the cth future moment are within the second threshold range, and the slope of the construction data points corresponding to the (b + 1)th future moment to the cth future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (c + 1)th future moment is not within the second threshold range or the upper slope of the construction data point corresponding to the (c + 1)th future moment is not less than the lower slope of the construction data point corresponding to the (c + 1)th future moment, then file the construction data point corresponding to the cth future moment, continue to traverse the future moments until the completion of the water conservancy project construction, and use all the construction data points filed during the traversal as the compressed data. The 1st future moment is the next moment of the current moment.

[0005] Beneficial effects: In the process of water conservancy project construction, the present invention first obtains the construction data points corresponding to the current moment and the preset initial threshold value, and obtains the first threshold range according to the preset initial threshold value. Then, if it is judged that the construction data points corresponding to the first future moment to the b-th future moment are within the first threshold range, and the upper slope of the construction data points corresponding to the first future moment to the b-th future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (b + 1)-th future moment is not within the first threshold range or the upper slope of the construction data point corresponding to the (b + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (b + 1)-th future moment, then the construction data points corresponding to the current moment and the b-th future moment are archived, and the data point sequence formed by the construction data points corresponding to the current moment to the b-th future moment is recorded as the first sequence, and the construction data point corresponding to the (b + 1)-th future moment is recorded as the first inflection point; according to the first sequence and the first inflection point, the preset initial threshold value is adjusted to obtain the first adjusted threshold value, and the second threshold range is obtained according to the first adjusted threshold value. If it is continuously judged that the construction data points corresponding to the (b + 1)-th future moment to the c-th future moment are within the second threshold range, and the slope of the construction data points corresponding to the (b + 1)-th future moment to the c-th future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (c + 1)-th future moment is not within the second threshold range or the upper slope of the construction data point corresponding to the (c + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (c + 1)-th future moment, then the construction data point corresponding to the c-th future moment is archived, and the future moments are continuously traversed until the completion of the water conservancy project construction, and all the construction data points archived during the traversal are used as compressed data. The first future moment is the next moment of the current moment. And through adjusting the threshold value, the present invention example can achieve the compression effect of real-time compression of water conservancy construction data. Description of the Drawings

[0006] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0007] Figure 1 It is a flowchart of a method for collecting and processing water conservancy project construction information based on big data according to the present invention. Detailed Embodiments

[0008] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art belong to the scope protected by the embodiments of the present invention.

[0009] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0010] This embodiment provides a big data-based water conservancy project construction information acquisition and processing system, including a processor and a memory. The processor executes the computer program stored in the memory to implement a big data-based water conservancy project construction information acquisition and processing method, as Figure 1 shown. The big data-based water conservancy project construction information acquisition and processing method includes the following steps: Step S001, during the construction of the water conservancy project, obtain the construction data point corresponding to the current moment and the preset initial threshold value, and obtain the first threshold range according to the preset initial threshold value.

[0011] The main purpose of this embodiment is to ensure or improve the compression ratio and compression quality when compressing the construction of the water conservancy project by dynamically adjusting the threshold value; and since there are many types of data to be monitored during the construction of the water conservancy project, that is, the types of data to be monitored include but are not limited to the upstream and downstream water level difference, dam foundation seepage pressure, seepage flow rate, groundwater level, precipitation, air temperature, humidity, wind speed, river flow rate, etc., then the types of sensors and the number of sensors to be configured are also many. In this embodiment, for the convenience of analysis and understanding, the subsequent description of this embodiment will be based on the threshold adjustment process during the real-time compression of any type of construction data to be monitored during the construction of any water conservancy project. For example, this embodiment mainly performs real-time compression on the groundwater level. And since multiple groundwater level monitoring positions are generally set during the construction of the water conservancy project, the data real-time monitored at any groundwater level monitoring position will be compressed in the subsequent description of this embodiment, and it is denoted as the target monitoring position, that is, the data that appears subsequently in this embodiment all comes from the data monitored at the same groundwater level monitoring position or the data that appears subsequently not only belongs to the same monitoring position but also has the same data type; the reason for setting multiple groundwater level monitoring points during the construction of the water conservancy project is that the groundwater level is a key data directly affecting the success or failure of the project and the sustainability of the surrounding environment, so the monitoring range needs to cover key areas. For example, it is generally necessary to arrange monitoring positions near the precipitation wells, inside the cut-off wall, near the surface water body, and outside the cut-off wall, and generally use sensors for monitoring, such as using a pressure-type water level sensor for water level monitoring; in addition, water conservancy projects are generally built at locations such as reservoirs, hydropower stations, and dams.

[0012] Therefore, in this embodiment, it is necessary to first obtain the construction data corresponding to the target monitoring position at the current moment during the construction of the water conservancy project, and then construct a two-dimensional space, map the construction data corresponding to the current moment and the current moment into the two-dimensional space to obtain the construction data point corresponding to the current moment. Since this embodiment analyzes taking the groundwater level as an example and the target monitoring position is the groundwater level monitoring point, the construction data collected at the current moment and the construction data collected at the future moment in this embodiment are both groundwater level data, that is, the horizontal axis of the two-dimensional space is time and the vertical axis is groundwater level data; in addition, this embodiment starts real-time compression from the current moment.

[0013] After obtaining the construction data point corresponding to the current moment, a preset initial threshold value is obtained. The preset initial threshold value is the tolerable error ratio coefficient, which is usually set according to historical experience and engineering requirements in practical applications. For example, generally take 0.5% to 2% of the data range. Or, for a pressure sensor with a range of 100 MPa, the preset initial threshold value can be set to 0.5 to 2 MPa.

[0014] After obtaining the preset initial threshold value, a first threshold range is obtained according to the preset initial threshold value. The specific process of obtaining the first threshold range according to the preset initial threshold value is as follows: Denote the sum of the ordinate value of the construction data point corresponding to the current moment and the preset initial threshold value as the upper threshold of the first threshold range, and denote the result of subtracting the preset initial threshold value from the ordinate value of the construction data point corresponding to the current moment as the lower threshold of the first threshold range. In this embodiment, the threshold range is one of the conditions for subsequent determination of whether a data point is archived, that is, if the ordinate value of the data point is not within the threshold range, archiving is triggered. In this embodiment, in addition to the threshold range, there is also a slope intersection. When the upper slope is greater than or equal to the lower slope of the corresponding data point, archiving is determined; in this embodiment, the archiving condition does not include time triggering, that is, in this embodiment, the threshold range and the slope intersection are the triggering archiving conditions.

[0015] Step S002, if it is determined that the construction data points corresponding to the 1st future moment to the bth future moment are within the first threshold range, and the upper slope of the construction data points corresponding to the 1st future moment to the bth future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (b + 1)th future moment is not within the first threshold range or the upper slope of the construction data point corresponding to the (b + 1)th future moment is not less than the lower slope of the construction data point corresponding to the (b + 1)th future moment, then file the construction data points corresponding to the current moment and the bth future moment, and record the data point sequence formed by the construction data points corresponding to the current moment to the bth future moment as the first sequence, and record the construction data point corresponding to the (b + 1)th future moment as the first inflection point; according to the first sequence and the first inflection point, adjust the preset initial threshold value to obtain the first adjusted threshold value, and obtain the second threshold range according to the first adjusted threshold value. If it is continuously determined that the construction data points corresponding to the (b + 1)th future moment to the cth future moment are within the second threshold range, and the slope of the construction data points corresponding to the (b + 1)th future moment to the cth future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (c + 1)th future moment is not within the second threshold range or the upper slope of the construction data point corresponding to the (c + 1)th future moment is not less than the lower slope of the construction data point corresponding to the (c + 1)th future moment, then file the construction data point corresponding to the cth future moment, continue to traverse the future moments until the completion of the water conservancy project construction, and use all the construction data points filed during the traversal as the compressed data.

[0016] After obtaining the construction data point corresponding to the current moment, continue to obtain the construction data point corresponding to the next moment of the current moment, which is recorded as the first future moment of the current moment; then continue to obtain the construction data point corresponding to the first future moment, and judge whether the construction data point corresponding to the first future moment is within the first threshold range and whether the upper slope of the construction data point corresponding to the first future moment is less than the lower slope of the corresponding construction data point. If both are true, continue to obtain the construction data point corresponding to the second future moment of the current moment, and judge whether the construction data point corresponding to the second future moment is within the first threshold range and whether the upper slope of the construction data point corresponding to the first future moment is less than the lower slope of the corresponding construction data point. If both are true, continue to obtain the construction data point corresponding to the future moment of the current moment. If it appears that the construction data points corresponding to the first future moment to the b-th future moment are all within the first threshold range and the upper slopes of the construction data points corresponding to the first future moment to the b-th future moment are all less than the lower slopes of the corresponding construction data points, and the construction data point corresponding to the (b + 1)-th future moment is not within the first threshold range or the upper slope of the construction data point corresponding to the (b + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (b + 1)-th future moment, then file the construction data points corresponding to the current moment and the b-th future moment, record the data point sequence formed by the construction data points corresponding to the current moment to the b-th future moment as the first sequence, and record the construction data point corresponding to the (b + 1)-th future moment as the first inflection point;Adjust the preset initial threshold value according to the first sequence and the first inflection point to obtain the first adjusted threshold value, and obtain the second threshold range according to the first adjusted threshold value. If it is continuously determined that the construction data points corresponding to the b-th future moment to the c-th future moment are within the second threshold range, the slope of the construction data points corresponding to the b-th future moment to the c-th future moment is less than the lower slope of the corresponding construction data points, the construction data point corresponding to the (c + 1)-th future moment is not within the second threshold range, or the upper slope of the construction data point corresponding to the (c + 1)-th future moment is less than the lower slope of the construction data point corresponding to the (c + 1)-th future moment, then file the construction data point corresponding to the c-th future moment, record the data point sequence formed by the construction data points corresponding to the b-th future moment to the c-th future moment as the second sequence, record the construction data point corresponding to the (c + 1)-th future moment as the second inflection point, adjust the first adjusted threshold value according to the second sequence and the second inflection point to obtain the second adjusted threshold value, and obtain the third threshold range according to the second adjusted threshold value. If it is continuously determined that the construction data points corresponding to the (c + 1)-th future moment to the d-th future moment are within the third threshold range and the slope of the construction data points corresponding to the (c + 1)-th future moment to the d-th future moment is less than the lower slope of the corresponding construction data points, the construction data point corresponding to the (d + 1)-th future moment is not within the third threshold range, or the upper slope of the construction data point corresponding to the (d + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (d + 1)-th future moment, then file the construction data point corresponding to the d-th future moment, continue to traverse the future moments until the end of the water conservancy project construction, and use all the construction data points filed during the traversal as the compressed data. The d-th future moment is after the c-th future moment, and the c-th future moment is after the b-th future moment.;

[0017] In addition, in this embodiment, the calculation processes of the upper slope and the lower slope of the construction data points are well-known calculations, so they will not be described in detail in this embodiment.

[0018] In this embodiment, the upper axis of the first threshold range is the sum of the ordinate value of the construction data point corresponding to the current moment and the preset initial threshold value, the lower axis of the first threshold range is the result of subtracting the preset initial threshold value from the ordinate value of the construction data point corresponding to the current moment, the upper axis of the second threshold range is the sum of the ordinate value of the construction data point corresponding to the b-th future moment and the first adjusted threshold value, the lower axis of the first threshold range is the result of subtracting the first adjusted threshold value from the ordinate value of the construction data point corresponding to the b-th future moment, the upper axis of the third threshold range is the sum of the ordinate value of the construction data point corresponding to the c-th future moment and the second adjusted threshold value, and the lower axis of the third threshold range is the result of subtracting the second adjusted threshold value from the ordinate value of the construction data point corresponding to the c-th future moment.

[0019] In this embodiment, the specific process of adjusting the preset initial threshold value according to the first sequence and the first inflection point to obtain the first adjusted threshold value is as follows: according to the extreme points in the first sequence and the differences between adjacent construction data points in the first sequence, the fluctuation trend characteristic value corresponding to the first sequence is obtained; the first construction data point in the first sequence is denoted as the adjacent inflection point of the first inflection point, and according to the vertical coordinate difference between the last construction data point in the first sequence and the first inflection point and the change rate between the adjacent inflection point of the first inflection point and the first inflection point, the first inflection point trend change characterization value is obtained; the vertical coordinate mean value of all construction data points collected during the time period from the start of construction to the first inflection point is denoted as the comprehensive mean value corresponding to the first inflection point, and the vertical coordinate mean value of all construction data points in the first sequence is denoted as the local mean value corresponding to the first inflection point. According to the difference between the comprehensive mean value corresponding to the first inflection point and the vertical coordinate of the first inflection point and the difference between the local mean value corresponding to the first inflection point and the vertical coordinate of the first inflection point, the first inflection point trend deviation characterization value is obtained; according to the fluctuation trend characteristic value corresponding to the first sequence, the first inflection point trend change characterization value, and the first inflection point trend deviation characterization value, the adjustment degree characterization value of the preset initial threshold value is obtained, and the product of the adjustment degree characterization value of the first adjusted threshold value and the preset initial threshold value is denoted as the first adjusted threshold value.

[0020] In this embodiment, the specific process of the fluctuation trend characteristic value corresponding to the first sequence is as follows: the normalized value of the ratio of the total number of extreme points in the first sequence to the total number of construction data points in the first sequence is denoted as the first index value, the adjacent difference sequence corresponding to the first sequence is obtained, and the normalized value of the mean value of the adjacent difference sequence is denoted as the second index value. The z-th adjacent difference in the adjacent difference sequence is the absolute value of the vertical coordinate difference between the (z + 1)-th construction data point and the z-th construction data point in the first sequence. The mean value of the first index value and the second index value is denoted as the fluctuation trend characteristic value corresponding to the first sequence.

[0021] The specific process of obtaining the first inflection point trend change characterization value is as follows: the result of subtracting the vertical coordinate of the last construction data point in the first sequence from the vertical coordinate value of the first inflection point is denoted as the first difference, the result of subtracting the horizontal coordinate of the last construction data point in the first sequence from the horizontal coordinate value of the first inflection point is denoted as the second difference, the ratio of the first difference to the second difference is denoted as the first ratio, and the mean value of the hyperbolic tangent value of the first difference and the hyperbolic tangent value of the second difference is denoted as the first inflection point trend change characterization value.

[0022] Method for obtaining adjustment degree characterization value of preset initial threshold value, including: recording the mean value of the first inflection point trend change characterization value and the first inflection point trend deviation characterization value as the first characteristic mean value, and determining whether the weighted sum result of the first characteristic mean value and the fluctuation trend characteristic value corresponding to the first sequence is greater than the preset adjustment direction determination threshold. If so, taking the constant -1 as the adjustment direction parameter of the preset initial threshold value; otherwise, taking the constant 1 as the adjustment direction parameter of the preset initial threshold value; taking the weighted sum result of the normalized value of the first characteristic mean value and the fluctuation trend characteristic value corresponding to the first sequence as the adjustment degree parameter of the preset initial threshold value; recording the result of multiplying the adjustment direction parameter of the preset initial threshold value by the adjustment degree parameter of the preset initial threshold value and then adding the preset first constant as the adjustment degree characterization value of the preset initial threshold value.

[0023] In this embodiment, the specific process of adjusting the first adjustment threshold value to obtain the second adjustment threshold value according to the second sequence and the second inflection point is as follows: obtaining the fluctuation trend characteristic value corresponding to the second sequence; recording the first inflection point as the neighboring inflection point of the second inflection point, and obtaining the second inflection point trend change characterization value according to the ordinate difference between the last construction data point in the second sequence and the second inflection point and the change rate between the neighboring inflection point of the second inflection point and the second inflection point; recording the ordinate mean value of all construction data points collected during the time period from the start of construction to the second inflection point as the comprehensive mean value corresponding to the second inflection point, and recording the ordinate mean value of all construction data points in the second sequence as the local mean value corresponding to the second inflection point, and obtaining the second inflection point trend deviation characterization value according to the difference between the comprehensive mean value corresponding to the second inflection point and the ordinate of the second inflection point and the difference between the local mean value corresponding to the second inflection point and the ordinate of the second inflection point; the methods for obtaining the fluctuation trend characteristic value corresponding to the second sequence, the second inflection point trend change characterization value, and the second inflection point trend deviation characterization value are the same as those for obtaining the fluctuation trend characteristic value corresponding to the first sequence, the first inflection point trend change characterization value, and the first inflection point trend deviation characterization value, so no detailed description will be given here. According to the fluctuation trend characteristic value corresponding to the second sequence, the second inflection point trend change characterization value, and the second inflection point trend deviation characterization value, obtaining the adjustment degree characterization value of the first adjustment threshold value, and recording the product of the first adjustment threshold value and the first adjustment threshold value of the first adjustment threshold value as the second adjustment threshold value; and the method for obtaining the adjustment degree characterization value of the first adjustment threshold value is the same as the method for obtaining the adjustment degree characterization value of the preset initial threshold value, so no detailed description will be given here.

[0024] So far, this embodiment has completed the compression process of the construction data collected in real time during the construction of the water conservancy project, and in the construction of the water conservancy project, the process of real-time compression of the construction data collected by any configured sensor is the same as the above process.

[0025] In summary, in this embodiment, during the construction process of a water conservancy project, the construction data points corresponding to the current moment and the preset initial threshold value are obtained, and the first threshold range is obtained according to the preset initial threshold value; then, if it is determined that the construction data points corresponding to the first future moment to the b-th future moment are within the first threshold range, and the upper slope of the construction data points corresponding to the first future moment to the b-th future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (b + 1)-th future moment is not within the first threshold range or the upper slope of the construction data point corresponding to the (b + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (b + 1)-th future moment, then the construction data points corresponding to the current moment and the b-th future moment are archived, and the data point sequence formed by the construction data points corresponding to the current moment to the b-th future moment is recorded as the first sequence, and the construction data point corresponding to the (b + 1)-th future moment is recorded as the first inflection point; according to the first sequence and the first inflection point, the preset initial threshold value is adjusted to obtain the first adjusted threshold value, and the second threshold range is obtained according to the first adjusted threshold value. If it is continuously determined that the construction data points corresponding to the (b + 1)-th future moment to the c-th future moment are within the second threshold range, and the slope of the construction data points corresponding to the (b + 1)-th future moment to the c-th future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (c + 1)-th future moment is not within the second threshold range or the upper slope of the construction data point corresponding to the (c + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (c + 1)-th future moment, then the construction data point corresponding to the c-th future moment is archived, and the traversal of the future moments is continued until the construction of the water conservancy project ends, and all the construction data points archived during the traversal are used as compressed data. The first future moment is the next moment of the current moment. And through the adjustment of the threshold value in this embodiment, the compression effect of real-time compression of water conservancy construction data can be achieved.

[0026] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A water conservancy project construction information collection and processing system based on big data, including a processor and a memory, characterized in that, The processor executes the computer program stored in the memory to implement the following steps: During the construction of a water conservancy project, obtain the construction data point corresponding to the current moment and a preset initial threshold value, and obtain a first threshold range according to the preset initial threshold value; If it is determined that the construction data points corresponding to the 1st future moment to the bth future moment are within the first threshold range, and the upper slope of the construction data points corresponding to the 1st future moment to the bth future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (b + 1)th future moment is not within the first threshold range or the upper slope of the construction data point corresponding to the (b + 1)th future moment is not less than the lower slope of the construction data point corresponding to the (b + 1)th future moment, then archive the construction data points corresponding to the current moment and the bth future moment, and record the data point sequence formed by the construction data points corresponding to the current moment to the bth future moment as the first sequence, and record the construction data point corresponding to the (b + 1)th future moment as the first inflection point; according to the first sequence and the first inflection point, adjust the preset initial threshold value to obtain the 1st adjusted threshold value, and obtain a second threshold range according to the 1st adjusted threshold value. If it is continuously determined that the construction data points corresponding to the (b + 1)th future moment to the cth future moment are within the second threshold range, and the slope of the construction data points corresponding to the (b + 1)th future moment to the cth future moment is less than the lower slope of the corresponding construction data points, and the construction data point corresponding to the (c + 1)th future moment is not within the second threshold range or the upper slope of the construction data point corresponding to the (c + 1)th future moment is not less than the lower slope of the construction data point corresponding to the (c + 1)th future moment, then archive the construction data point corresponding to the cth future moment, continue to traverse the future moments until the construction of the water conservancy project ends, and use all the archived construction data points during the traversal as compressed data. The 1st future moment is the next moment of the current moment.

2. The water conservancy project construction information acquisition and processing system based on big data according to claim 1, characterized in that The construction data point corresponding to any moment consists of the corresponding moment and the construction data collected at the corresponding moment.

3. The water conservancy project construction information acquisition and processing system based on big data according to claim 2, characterized in that The upper axis of the first threshold range is the sum of the ordinate value of the construction data point corresponding to the current moment and the preset initial threshold value, the lower axis of the first threshold range is the result of subtracting the preset initial threshold value from the ordinate value of the construction data point corresponding to the current moment, the upper axis of the second threshold range is the sum of the ordinate value of the construction data point corresponding to the bth future moment and the 1st adjusted threshold value, and the lower axis of the second threshold range is the result of subtracting the 1st adjusted threshold value from the ordinate value of the construction data point corresponding to the bth future moment.

4. The water conservancy project construction information acquisition and processing system based on big data according to claim 1, characterized in that, The method for adjusting the preset initial threshold value to obtain the 1st adjusted threshold value according to the first sequence and the first inflection point includes: Obtain the fluctuation trend characteristic value corresponding to the first sequence according to the extreme points in the first sequence and the differences between adjacent construction data points in the first sequence; Denote the first construction data point in the first sequence as the neighboring inflection point of the first inflection point, and obtain the first inflection point trend change characterization value according to the vertical coordinate difference between the last construction data point in the first sequence and the first inflection point and the change rate between the neighboring inflection point of the first inflection point and the first inflection point; Denote the average value of the vertical coordinates of all construction data points collected during the time period from the start of construction to the first inflection point as the comprehensive average value corresponding to the first inflection point, and denote the average value of the vertical coordinates of all construction data points in the first sequence as the local average value corresponding to the first inflection point. Obtain the first inflection point trend deviation characterization value according to the difference between the comprehensive average value corresponding to the first inflection point and the vertical coordinate of the first inflection point and the difference between the local average value corresponding to the first inflection point and the vertical coordinate of the first inflection point; Obtain the adjustment degree characterization value of the preset initial threshold according to the fluctuation trend characteristic value, the first inflection point trend change characterization value, and the first inflection point trend deviation characterization value corresponding to the first sequence. Denote the product of the adjustment degree characterization value of the first adjustment threshold and the preset initial threshold as the first adjustment threshold.

5. The water conservancy project construction information acquisition and processing system based on big data according to claim 4, characterized in that, The method for obtaining the fluctuation trend characteristic value corresponding to the first sequence includes: Denote the normalized value of the ratio of the total number of extreme points in the first sequence to the total number of construction data points in the first sequence as the first index value. Obtain the adjacent difference sequence corresponding to the first sequence, and denote the normalized value of the average value of the adjacent difference sequence as the second index value. The z-th adjacent difference in the adjacent difference sequence is the absolute value of the vertical coordinate difference between the (z + 1)-th construction data point and the z-th construction data point in the first sequence. Denote the average value of the first index value and the second index value as the fluctuation trend characteristic value corresponding to the first sequence.

6. The water conservancy project construction information acquisition and processing system based on big data according to claim 4, characterized in that, The method for obtaining the first inflection point trend change characterization value includes: Denote the result of subtracting the vertical coordinate of the last construction data point in the first sequence from the vertical coordinate value of the first inflection point as the first difference, denote the result of subtracting the horizontal coordinate of the last construction data point in the first sequence from the horizontal coordinate value of the first inflection point as the second difference, denote the ratio of the first difference to the second difference as the first ratio, and denote the average value of the hyperbolic tangent value of the first difference and the hyperbolic tangent value of the second difference as the first inflection point trend change characterization value.

7. The water conservancy project construction information acquisition and processing system based on big data according to claim 4, characterized in that The method for obtaining the first inflection point trend deviation characterization value includes: Denote the result of subtracting the local average value corresponding to the first inflection point from the vertical coordinate value of the first inflection point as the third difference, denote the result of subtracting the comprehensive average value corresponding to the first inflection point from the vertical coordinate value of the first inflection point as the fourth difference, and denote the hyperbolic tangent value of the result obtained by adding the third difference and the fourth difference as the first inflection point trend deviation characterization value.

8. The water conservancy project construction information acquisition and processing system based on big data according to claim 7, characterized in that, The method for obtaining the adjustment degree characterization value of the preset initial threshold includes: Denote the mean of the first inflection point trend transformation characterization value and the first inflection point trend deviation characterization value as the first feature mean. Determine whether the weighted sum result of the first feature mean and the fluctuation trend feature value corresponding to the first sequence is greater than the preset adjustment direction determination threshold. If so, use the constant -1 as the adjustment direction parameter of the preset initial threshold value; otherwise, use the constant 1 as the adjustment direction parameter of the preset initial threshold value. Take the weighted sum result of the normalized value of the first feature mean and the fluctuation trend feature value corresponding to the first sequence as the adjustment degree parameter of the preset initial threshold value. Denote the result of multiplying the adjustment direction parameter of the preset initial threshold value by the adjustment degree parameter of the preset initial threshold value and then adding a preset first constant as the adjustment degree characterization value of the preset initial threshold value.

9. The water conservancy project construction information acquisition and processing system based on big data according to claim 8, characterized in that, After archiving the construction data point corresponding to the c-th future moment, the following steps are further included: Denote the data point sequence formed by the construction data points corresponding to the b-th future moment to the c-th future moment as the second sequence, and denote the construction data point corresponding to the (c + 1)-th future moment as the second inflection point. Adjust the first adjustment threshold value according to the second sequence and the second inflection point to obtain the second adjustment threshold value, and obtain the third threshold range according to the second adjustment threshold value. If it is continuously determined that the construction data points corresponding to the (c + 1)-th future moment to the d-th future moment are within the third threshold range, and the slope of the construction data points corresponding to the (c + 1)-th future moment to the d-th future moment is less than the lower slope of the corresponding construction data points, the construction data point corresponding to the (d + 1)-th future moment is not within the third threshold range, or the upper slope of the construction data point corresponding to the (d + 1)-th future moment is not less than the lower slope of the construction data point corresponding to the (d + 1)-th future moment, then archive the construction data point corresponding to the d-th future moment. The method of adjusting the first adjustment threshold value to obtain the second adjustment threshold value and obtaining the third threshold range according to the second adjustment threshold value is the same as the method of adjusting the preset initial threshold value to obtain the first adjustment threshold value and obtaining the second threshold range according to the first adjustment threshold value. The d-th future moment is behind the c-th future moment, and the c-th future moment is behind the b-th future moment.

10. The water conservancy project construction information acquisition and processing system based on big data according to claim 9, characterized in that, The method of adjusting the first adjustment threshold value to obtain the second adjustment threshold value according to the second sequence and the second inflection point includes: Obtain the fluctuation trend eigenvalue corresponding to the second sequence; Denote the first inflection point as the neighboring inflection point of the second inflection point, and obtain the second inflection point trend change characterization value according to the vertical coordinate difference between the last construction data point in the second sequence and the second inflection point and the change rate between the neighboring inflection point of the second inflection point and the second inflection point; Denote the average value of the vertical coordinates of all construction data points collected during the time period from the start of construction to the second inflection point as the comprehensive average value corresponding to the second inflection point, and denote the average value of the vertical coordinates of all construction data points in the second sequence as the local average value corresponding to the second inflection point, and obtain the second inflection point trend deviation characterization value according to the difference between the comprehensive average value corresponding to the second inflection point and the vertical coordinate of the second inflection point and the difference between the local average value corresponding to the second inflection point and the vertical coordinate of the second inflection point; The methods for obtaining the fluctuation trend eigenvalue corresponding to the second sequence, the second inflection point trend change characterization value, and the second inflection point trend deviation characterization value are the same as the methods for obtaining the fluctuation trend eigenvalue corresponding to the first sequence, the first inflection point trend change characterization value, and the first inflection point trend deviation characterization value; According to the fluctuation trend eigenvalue corresponding to the second sequence, the second inflection point trend change characterization value, and the second inflection point trend deviation characterization value, obtain the adjustment degree characterization value of the first adjustment threshold, and denote the product of the first adjustment threshold of the first adjustment threshold and the first adjustment threshold as the second adjustment threshold; The method for obtaining the adjustment degree characterization value of the first adjustment threshold is the same as the method for obtaining the adjustment degree characterization value of the preset initial threshold.

Images