Automatic control method for canal lining construction of water conservancy project

Abstract

The invention relates to the technical field of data processing for supervision, in particular to a water conservancy project canal lining construction automatic control method, which comprises the following steps of: in a water conservancy project canal lining construction process, acquiring multi-dimensional data and elevation data of each monitoring point in a canal in real time; based on the elevation data, determining whether a channel lining quality problem occurs at the current moment; under the condition that the canal lining quality problem occurs at the current moment, target reason information of the canal lining quality problem is determined based on the multi-dimensional data; executing a corresponding target control instruction based on the target reason information; according to the automatic control method for the canal lining construction of the water conservancy project, the cause of the problem can be accurately and efficiently found out, targeted adjustment and control are carried out, constructors are helped to rapidly position and solve the problem, and more importantly, the efficiency of the automatic canal lining construction of the water conservancy project is effectively guaranteed.

Description

Technical Field

[0001] The invention relates to the technical field of data processing for supervision, and in particular to an automatic control method for channel lining construction of a water conservancy project. Background Art

[0002] The automated control method for channel lining construction of water conservancy projects refers to the use of modern information technology, automation technology and mechanical equipment to improve the efficiency, quality and safety of channel lining construction. Currently, the use of channel lining trolleys for trapezoidal channel construction has extremely high construction efficiency, greatly reducing labor input and construction costs.

[0003] During the channel lining construction of water conservancy projects, there are many reasons for the quality problems of the channel lining, including inadequate preparation before construction, such as defects in the material feeding quality; equipment failure during construction, external factors during construction, etc., and each cause of channel lining quality problems requires a different solution. When encountering channel lining quality problems, it is generally necessary to conduct a comprehensive manual inspection directly, which seriously affects construction efficiency. Summary of the invention

[0004] In order to solve the technical problem that when encountering channel lining quality problems, the direct manual detection method seriously affects the construction efficiency of water conservancy project channel lining, the purpose of the present invention is to provide a water conservancy project channel lining construction automation control method, the technical scheme adopted is as follows: The present invention provides an automated control method for channel lining construction of a water conservancy project, the method comprising: During the construction of water conservancy project channel lining, real-time collection of multi-dimensional data and elevation data of each monitoring point in the channel; Based on the elevation data, determining whether a channel lining quality problem occurs at the current moment; In the case where a channel lining quality problem occurs at the current moment, determining target cause information of the channel lining quality problem based on the multi-dimensional data; Based on the target reason information, executing a corresponding target control instruction; Among them, the multi-dimensional data includes vibration data, humidity data and wind speed data; the elevation data represents the distance value from the monitoring point in the channel to the uppermost surface of the channel; the target cause information includes construction equipment failure, external factors and material feeding quality; the target control instructions include deceleration instructions, shutdown instructions and alarm instructions.

[0005] Furthermore, the elevation data includes: a target elevation data sequence composed of elevation data of a plurality of monitoring points evenly distributed along the channel width direction at the current moment; The step of determining whether a channel lining quality problem occurs at the current moment based on the elevation data comprises: Comparing the target elevation data sequence with the standard elevation data sequence in terms of single corresponding data to determine problematic data in the target elevation data sequence; Based on the problem data, determining the degree of the channel lining quality problem at the current moment; According to the degree of the channel lining quality problem, it is determined whether there is a channel lining quality problem at the current moment.

[0006] Further, based on the problem data, the step of determining the degree of the channel lining quality problem at the current moment includes: determining a problem degree, a first quantity, and a second quantity of total data in a target elevation data sequence of the problem data; Determine a sequence segment formed by adjacent problem data sequences in the target elevation data sequence, and determine a maximum length value in the sequence segment; The problem degree of the channel lining quality at the current moment is calculated using the problem degree, the first quantity, the second quantity and the maximum length value.

[0007] Further, the vibration data includes a traveling vibration signal of the construction equipment when it moves forward; The step of determining target cause information of the channel lining quality problem based on the multi-dimensional data comprises: Determine the vibration data sequence of each vibrator on the construction equipment; determining the traveling vibration signal based on the vibration data sequence; Calculating the influence degree of external factors based on the traveling vibration signal, the humidity data and the wind speed data; According to the influence degree of the external factors, it is determined whether the target cause information of the channel lining quality problem is affected by the external factors.

[0008] Further, based on the vibration data sequence, the step of determining the traveling vibration signal comprises: Decomposing the vibration data sequence into a plurality of eigenmode function components by empirical mode decomposition; Divide the eigenmode function components of two adjacent vibrators into component groups to obtain a plurality of non-repeating component groups; Based on the eigenmode function components of the two vibrators in each component group, the dynamic time warping set of all component groups is calculated; Take any data in each dynamic time warping set and obtain multiple update sets in a full permutation manner; Calculate the sum of each update set to determine the target set with the minimum sum; Based on the eigenmode function components respectively corresponding to each data in the target set, a traveling vibration signal corresponding to each vibrator is obtained.

[0009] Furthermore, based on the eigenmode function components of the two vibrators in the component group, the dynamic time warping set of all component groups is calculated, including: Take any eigenmode function component of each of the two vibrators in the component group, and calculate the dynamic time warping distance between the two eigenmode function components; The dynamic time warping distance between any two eigenmode function components from different vibrators in the same group is calculated without repetition to obtain the dynamic time warping set of all component groups.

[0010] Further, the step of calculating the influence degree of external factors based on the traveling vibration signal, the humidity data and the wind speed data comprises: determining peaks and troughs of each of the travel vibration signal, the humidity data, and the wind speed data; Based on the respective peaks and troughs, respectively determine the relative maximum vibration of the traveling vibration signal, the degree of humidity drop of the humidity data, and the degree of wind speed increase of the wind speed data; The maximum mutation degree is calculated by using the relative maximum vibration, humidity drop degree and wind speed increase degree; Determine the time nodes corresponding to the relative maximum vibration, humidity drop and wind speed increase, and determine the time difference from each time node to the current moment; The influence of external factors is calculated using the maximum mutation degree, time node and time difference.

[0011] Further, the step of determining target cause information of the channel lining quality problem based on the multi-dimensional data includes: removing the traveling vibration signal from all the eigenmode function components corresponding to the vibration data sequence to obtain the remaining eigenmode function components; Reconstructing the remaining eigenmode function components into an updated vibration data sequence through empirical mode decomposition; Determining a corresponding fitting fluctuation curve based on the peaks and troughs in the updated vibration data sequence; The possibility of failure at the current moment is calculated by using the influence of external factors, the fitting fluctuation curve and the number of vibrators; Based on the fault possibility, it is determined whether the target cause information of the channel lining quality problem is a construction equipment failure.

[0012] Further, the step of determining the corresponding fitting fluctuation curve based on the peaks and troughs in the updated vibration data sequence includes: Dividing the updated vibration data sequence into a plurality of vibration fluctuations based on the peaks and troughs therein, and obtaining the amplitude and vibration period of each vibration fluctuation; The instability value of the vibration fluctuation is calculated by using the amplitude and vibration period of the vibration fluctuation and the amplitude and vibration period of the adjacent vibration fluctuation; The least square method is used to fit the fluctuation curve of all the instability values ​​of vibration fluctuations to obtain the fitting fluctuation curve.

[0013] Furthermore, based on the target reason information, the step of executing the corresponding target control instruction includes: When the influence of the external factors is greater than the external influence threshold, execute the corresponding deceleration instruction; or When the degree of influence of external factors is less than or equal to the external influence threshold and the possibility of failure is greater than the possible failure threshold, execute the shutdown command and equipment failure alarm command; or When the influence degree of external factors is less than or equal to the external influence threshold and the possibility of fault is less than or equal to the possible fault threshold, the shutdown command and the feeding problem alarm command are executed.

[0014] The present invention has the following beneficial effects: The method comprises the following steps: during the construction of the channel lining of the water conservancy project, real-time collection of multi-dimensional data and elevation data of each monitoring point in the channel; determining whether a quality problem of the channel lining occurs at the current moment based on the elevation data; and determining target cause information of the quality problem of the channel lining based on the multi-dimensional data when a quality problem of the channel lining occurs at the current moment. Based on the target cause information, the corresponding target control instruction is executed. The present invention can accurately determine whether there is a quality problem of the channel lining based on the analysis of the elevation data of each monitoring point, and is based on the analysis of multi-dimensional data including the external environment and construction equipment, so that when there is a quality problem of the channel lining, the cause of the problem can be accurately and efficiently found, and targeted adjustment and control can be carried out, which not only helps construction personnel to quickly locate and solve the problem, but more importantly, effectively guarantees the efficiency of the automation of the channel lining construction of water conservancy projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] 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 embodiments or the prior art descriptions are briefly introduced below. 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 creative work.

[0016] Figure 1A flowchart of the steps of an automated control method for channel lining construction of a water conservancy project provided by one embodiment of the present invention; Figure 2 A detailed flow chart of step S3 in a method for automated control of channel lining construction of a water conservancy project provided by one embodiment of the present invention; Figure 3 A detailed flow chart of step S31 in a method for automated control of channel lining construction of a water conservancy project provided by one embodiment of the present invention; Figure 4 A detailed flow chart of step S32 in a method for automated control of channel lining construction of a water conservancy project provided by one embodiment of the present invention; Figure 5 Another detailed flow chart of step S3 in a method for automated control of channel lining construction of a water conservancy project provided by one embodiment of the present invention; Figure 6 A detailed flow chart of step S4 in a method for automated control of channel lining construction of a water conservancy project provided by one embodiment of the present invention; Figure 7 It is a structural schematic diagram of the hardware operating environment of the water conservancy project channel lining construction automation control equipment involved in the embodiment of the present invention; Figure 8 It is a schematic diagram of the framework structure of the automatic control device for channel lining construction of a water conservancy project involved in the embodiment of the present invention; Fig. 9 A schematic diagram of elevation data measurement in an automated control method for channel lining construction of a water conservancy project provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a hydraulic engineering channel lining construction automation control method proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0018] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0019] The specific scheme of the automatic control method for channel lining construction of a water conservancy project provided by the present invention is described in detail below with reference to the accompanying drawings.

[0020] Embodiment 1: For the automatic control method for channel lining construction of a water conservancy project provided by the present invention, please refer to Figure 1 , which shows a flow chart of steps of an automated control method for channel lining construction of a water conservancy project provided by an embodiment of the present invention.

[0021] Among them, the multi-dimensional data in the following embodiments include vibration data, humidity data and wind speed data; the elevation data represents the distance value from the monitoring point in the channel to the top surface of the channel; the target cause information includes construction equipment failure, external factors and material feeding quality; the target control instructions include deceleration instructions, shutdown instructions and alarm instructions.

[0022] The method comprises: Step S1, during the construction of the channel lining of the water conservancy project, real-time collection of multi-dimensional data and elevation data of each monitoring point in the channel; In this embodiment, the process of channel lining construction of the water conservancy project here mainly refers to the process in which the construction equipment (generally the lining trolley) performs operations such as concrete pouring, vibration, and screeding in the channel base. Real-time here means that the corresponding sensors can be used to collect the above-mentioned multiple dimensional data at a certain collection frequency, for example, the collection frequency can be once per second. Sensors generally include vibration sensors to collect vibration data, humidity sensors to collect humidity data, and wind speed sensors to collect wind speed data. More specifically, the vibration data here can include the vibration vibration data of each vibrator itself, the traveling vibration data of the vibrator, and the vibration superposition data (the signal superposition of the vibration vibration and the traveling vibration). Humidity data and wind speed data can refer to the temperature and wind speed of the environment surrounding the construction equipment. The data of each dimension can be standardized and unified in dimension.

[0023] Among them, the vibrators in the lining trolley can be evenly distributed along the width of the channel, that is, evenly arranged in the direction perpendicular to the channel (the lining trolley in this embodiment can be a small device, so multiple vibrators can be in only one row, and for large equipment, there can also be multiple rows). This arrangement helps to ensure that the concrete is evenly vibrated in the cross-section of the channel.

[0024] During the lining trolley operation, laser radar can also be used to collect elevation data of each monitoring point evenly distributed on a line along the width of the channel after the concrete surface is leveled.

[0025] As the lining trolley moves forward, the elevation data of each monitoring point is collected at a preset interval (e.g. 1 cm) along the direction of the channel. Each collection corresponds to a moment. Each collection is to collect the elevation data of each monitoring point at equal intervals on a line along the width direction of the channel. The elevation data is the distance from each monitoring point to the top of the channel. Please refer to Fig. 9 's instructions for understanding.

[0026] Step S2, determining whether there is a channel lining quality problem at the current moment based on the elevation data; Comparing the collected elevation data with the corresponding standard elevation data during normal construction without channel lining quality problems can reflect the presence or absence of channel lining quality problems and the degree of quality problems, thereby determining whether channel lining quality problems exist at the current moment. The standard elevation data here can be obtained in the following ways: In the design drawing of the channel, the standard elevation data of each monitoring point can be obtained according to the design standards of the channel (i.e. the length, width, height, inclination angles of the two slopes, etc. of the channel).

[0027] In a preferred embodiment, the elevation data includes: a target elevation data sequence composed of elevation data of a plurality of monitoring points evenly distributed along the channel width direction at the current moment; The step S2 comprises: Comparing the target elevation data sequence with the standard elevation data sequence in terms of single corresponding data to determine problematic data in the target elevation data sequence; Based on the problem data, determining the degree of the channel lining quality problem at the current moment; According to the degree of the channel lining quality problem, it is determined whether there is a channel lining quality problem at the current moment.

[0028] As for how to compare the elevation data collected up to the current moment with the standard elevation data, in this embodiment, first, the target elevation data sequence corresponding to each moment can be obtained based on the elevation data of each monitoring point evenly distributed on a line along the width direction of the channel collected each time, that is, a sequence composed of the elevation data of all monitoring points along the width direction of the channel from one side of the channel to the other side, and the target elevation data sequence and the standard elevation data sequence are compared between single corresponding data, for example, the first data of the target elevation data sequence is compared with the first data in the standard elevation data sequence, and the second data of each is compared separately, and so on.

[0029] After comparison, if the difference between any two data involved in the comparison exceeds a certain limit (which can be set as needed), the corresponding data in the target elevation data sequence can be considered as problematic data. Then, all problematic data can be found, and combined with the deviation, quantity and distribution of these problematic data, the degree of channel lining quality problems at the current moment can be determined more comprehensively, effectively and accurately.

[0030] Generally speaking, the greater the difference between the elevation data collected at the monitoring point and the standard elevation data, and the more and more continuous the problematic monitoring points and problematic data are, the greater the quality problem of the channel lining at this time, that is, the greater or more serious the degree of the channel lining quality problem. When the degree of the problem exceeds a certain limit (which can be set as needed), it can be considered that there is a channel lining quality problem, otherwise it does not exist, thereby determining the channel lining quality at each moment.

[0031] In a preferred embodiment, the step of determining the degree of the channel lining quality problem at the current moment based on the problem data specifically includes: determining a problem degree, a first quantity, and a second quantity of total data in a target elevation data sequence of the problem data; Determine a sequence segment formed by adjacent problem data sequences in the target elevation data sequence, and determine a maximum length value in the sequence segment; The problem degree of the channel lining quality at the current moment is calculated using the problem degree, the first quantity, the second quantity and the maximum length value.

[0032] In this embodiment, the above steps can be represented as the following data processing process: In the target elevation data sequence corresponding to the jth moment, the normalized value of the absolute value of the difference between each elevation data and its corresponding standard elevation data is calculated, that is, ,in and are the i-th elevation data and its corresponding standard elevation data, is a linear normalization function, normalized to (0, 1), as the problem degree of each elevation data.

[0033] The threshold can be set to 0.6, and elevation data with a problem degree greater than 0.6 can be recorded as problematic data.

[0034] At this time, the degree of channel lining quality problems at the jth moment The acquisition process is: At the jth moment, obtain the ratio of the number of problem data in the target elevation data sequence (i.e., the first number) to the number of all data in the target elevation data sequence (i.e., the second number) as the first ratio; obtain the ratio of the maximum value (i.e., the maximum length value, which reflects the continuity of the problem data) in the length of the sequence segment composed of adjacent problem data in the target elevation data sequence to the number of all data in the target elevation data sequence (i.e., the second number) as the second ratio; obtain the sum of the problem levels of all elevation data in the target elevation data sequence; normalize the product of the sum, the first ratio, and the second ratio to obtain a normalized value, and use the normalized value as the channel lining quality problem level at the jth moment. In this embodiment, using The linear normalization function normalizes the product to obtain the degree of channel lining quality problems.

[0035] when When it is greater than 0.6, it is determined that there is a channel lining quality problem at the jth moment.

[0036] During the forward operation of the lining trolley, if there is a quality problem with the channel lining at the current moment, it is necessary to analyze the data of the historical moments before the current moment to determine the cause of the problem.

[0037] Step S3, when a channel lining quality problem occurs at the current moment, determining target cause information of the channel lining quality problem based on the multi-dimensional data; When it is determined that there is a quality problem with the channel lining at the current moment, the multiple dimensional data mentioned above can be combined to further determine the target cause information of the channel lining quality problem. For example, vibration data, humidity data and wind speed data can be combined to determine whether the cause of the channel lining quality problem is the influence of external factors. If external factors can be ruled out, it can be further analyzed whether there is a failure in the construction equipment, especially whether the vibrator has a failure.

[0038] In order to understand this step, it is necessary to further explain: Before the lining trolley is operated, two tracks need to be laid first, the trolley is lifted and placed on the pre-leveled tracks, and then construction is carried out on the tracks.

[0039] Regarding the influence of external factors, during the operation of the lining trolley, the quality problems of channel lining caused by external factors are mainly the vibration of the lining trolley when it moves forward (dust, sand, debris, etc. that float into the track during the construction process cause the lining trolley to vibrate when it moves forward, resulting in poor leveling effect) and sudden changes in environmental conditions.

[0040] Since the location of channel lining construction of water conservancy projects is often near rivers and lakes, the humidity and wind speed in this environment change greatly and quickly, while the temperature changes less. This is because the temperature of water changes slowly due to its large heat capacity, while the temperature of land changes quickly. This temperature difference will cause air flow, forming the so-called "lake breeze" phenomenon, and the evaporation and condensation of water will affect humidity changes. A sudden drop in humidity and a sudden increase in wind speed will cause the moisture on the concrete surface to evaporate rapidly, which may cause surface drying and the formation of microcracks.

[0041] Therefore, before obtaining the current moment when the channel lining quality problem occurs, it is necessary to collect the vibration data sequence of each vibrator of the lining trolley, as well as the humidity data sequence and wind speed data sequence to comprehensively, effectively and accurately determine whether the occurrence of the quality problem is caused by external factors.

[0042] In addition, the main reasons affecting the quality of channel lining include vibrator failure in construction equipment failure, which leads to poor discharge of air bubbles inside the concrete, resulting in poor compactness of the concrete, leading to quality problems in the channel lining, and problems with feeding the lining trolley (i.e., concrete quality problems in the preparation work, leading to quality problems in the channel lining).

[0043] After eliminating the influence of external factors, the vibration data sequence can be further combined to determine whether the cause of the channel lining quality problem is a vibrator failure, and further determine that the cause of the channel lining quality problem may be related to the material feeding quality.

[0044] In a preferred embodiment, the vibration data includes a traveling vibration signal of the construction equipment when it is moving forward; Please refer to Figure 2 , the step S3 comprises: Step S30, determining the vibration data sequence of each vibrator on the construction equipment; Step S31, determining the traveling vibration signal based on the vibration data sequence; Each vibration data sequence is affected by the vibration of the lining trolley when it moves forward, that is, the traveling vibration signal of the lining trolley when it moves forward will be superimposed on the total vibration signal of each vibrator, that is, the vibration signal (vibration data sequence) collected from the vibrator during the construction process includes both the vibration vibration signal of the vibrator and the traveling vibration signal of the lining trolley superimposed on the vibrator when it moves forward. In order to determine whether the quality problem of the channel lining is related to external factors such as dust, sand, and debris floating into the track that cause the lining trolley to move forward and vibrate, it is necessary to separate the two vibration signals from the vibration data sequence, determine the traveling vibration signal, and then analyze based on the traveling vibration signal.

[0045] In a preferred embodiment, please refer to Figure 3 ; The step S31 specifically comprises: Step S310, decomposing the vibration data sequence into a plurality of eigenmode function components through empirical mode decomposition; Step S311, dividing the intrinsic mode function components of two adjacent vibrators into component groups to obtain a plurality of non-repeating component groups; Step S312, based on the intrinsic mode function components of the two vibrators in the component group, a dynamic time warping set of all component groups is calculated; Step S313, randomly select any data in each dynamic time warping set to obtain multiple update sets in a full permutation manner; Step S314, calculating the sum values ​​in each update set to determine the target set with the minimum sum value; Step S315: obtaining a traveling vibration signal corresponding to each vibrator based on the intrinsic mode function components corresponding to each data in the target set.

[0046] Wherein, the step S312 specifically includes: Take any eigenmode function component of each of the two vibrators in the component group, and calculate the dynamic time warping distance between the two eigenmode function components; The dynamic time warping distance between any two eigenmode function components from different vibrators in the same group is calculated without repetition to obtain the dynamic time warping set of all component groups.

[0047] In this embodiment, each vibration data sequence is decomposed into several IMF (Intrinsic Mode Function) components using EMD (Empirical Mode Decomposition) decomposition (a well-known technique). One of the IMF components should be the traveling vibration signal of the lining trolley when it moves forward.

[0048] By grouping two adjacent vibrators, several non-repetitive groups can be obtained.

[0049] For example, vibrators A, B, C, and D give component groups (A, B) and (C, D).

[0050] In any group (C, D), take any IMF component in C and any IMF component in D, and calculate the DTW (Dynamic Time Warping) distance between the two IMF components (DTW is a well-known technology. The smaller the DTW distance, the more similar the two IMF components are). In this way, the DTW distance of any two IMF components is calculated without repetition to obtain the DTW set consisting of all DTW distances in the group (C, D).

[0051] It should be pointed out that, by way of example, the non-repetitive calculations here refer to: Assume C: {1, 2}; D: {5, 6}.

[0052] The DTW set is: {15, 16, 25, 26}.

[0053] That is, there is no such repetitive pattern as 15 and 51.

[0054] This is only for illustrative purposes and does not represent the actual DTW distance.

[0055] Similarly, obtain the DTW sets of all component groups.

[0056] In all groups, any data of the DTW set of each group is taken to form an update set, thereby using a full permutation method to obtain several different update sets.

[0057] For example, the DTW sets {1, 2} and {3, 4} can form the update sets {1, 3}, {1, 4}, {2, 3}, and {2, 4}.

[0058] The sum of all data in each update set is calculated as the vibration signal similarity of each update set.

[0059] The updated set of minimum vibration signal similarity is used as the target set.

[0060] An IMF component of each vibrator corresponding to all the data in the target set is obtained as a traveling vibration signal of the lining trolley corresponding to each vibrator when it moves forward.

[0061] To make it easier to understand the above process, for example: Assume: vibrators A, B, C, D IMF components corresponding to A: A1, A2 BCD IMF component form analogy A The DTW set of AB is A1B1, A1B2, A2B1, A2B2 The DTW set of CD is C1D1, C1D2, C2D1, C2D2 Assume that the update set with the smallest sum is A1B1 and C1D1, and use it as the target set Therefore, the IMF components A1, B1, C1, and D1 in the target set are the traveling vibration signals of the lining trolleys of vibrators A, B, C, and D when they move forward.

[0062] Assuming that the target set is A1B2 and C2D1, it can be seen that there will be a component of vibrators A, B, C, and D as the traveling vibration signal when the lining trolley moves forward.

[0063] Step S32, calculating the influence degree of external factors based on the traveling vibration signal, the humidity data and the wind speed data; A comprehensive analysis combining the travel vibration signal, humidity data and wind speed data can more comprehensively cover the external factors that affect the construction and further determine the extent of the impact brought by the external factors.

[0064] In a preferred embodiment, please refer to Figure 4 The step S32 comprises: Step S320, determining the peaks and troughs of the traveling vibration signal, the humidity data, and the wind speed data; Step S321, determining the relative maximum vibration of the traveling vibration signal, the humidity drop degree of the humidity data, and the wind speed increase degree of the wind speed data respectively based on the respective peaks and troughs; Step S322, using the relative maximum vibration, the degree of humidity drop and the degree of wind speed increase, the maximum mutation degree is calculated; Step S323, determining the time nodes corresponding to the relative maximum vibration, humidity drop and wind speed increase, and determining the time difference from each time node to the current moment; Step S324, using the maximum mutation degree, time node and time difference, calculate the influence degree of external factors.

[0065] For the traveling vibration signal: The mean sequence of the traveling vibration signals of the lining trolley corresponding to all vibrators when it moves forward, that is, the traveling vibration data sequence of each vibrator is added and the mean value is taken, which is recorded as the final vibration signal F when the lining trolley moves forward.

[0066] If a vibration sensor is directly installed on the lining trolley to collect the vibration generated when the lining trolley is moving, it will be affected by the vibration of the vibrator when it is working. Therefore, this embodiment uses the above method to obtain the travel vibration signal generated when the lining trolley is moving, so as to more effectively separate the above travel vibration signal and the vibration vibration signal of each vibrator.

[0067] Dust, sand and debris floating in the track will only cause the vibration amplitude of F to increase. The larger the vibration amplitude, the greater the impact on the quality of concrete smoothing.

[0068] Therefore, we obtain the peaks and valleys in F, calculate the absolute value of the difference between adjacent peaks and valleys, and convert , as the relative maximum vibration E in F, where is the maximum absolute value of the difference, is the minimum absolute value of the difference. The time of the corresponding wave peak is recorded as the maximum vibration time node.

[0069] For humidity data: In the humidity data series, the difference between each peak and its adjacent trough, as well as the time difference, are calculated in chronological order. , as the humidity drop degree G, where is the maximum difference, for The corresponding time difference will be The corresponding trough time is recorded as the humidity drop time. If there is no trough after the last peak, the last data is taken as the trough.

[0070] For wind speed data: In the wind speed data sequence, the absolute value of the difference between each trough and its adjacent peak, as well as the time difference, are calculated in chronological order. , as the wind speed sudden increase degree H, where is the maximum absolute value of the difference, for The corresponding time difference will be The time of the corresponding peak is recorded as the wind speed surge time. If there is no peak after the last trough, the last data is taken as the peak.

[0071] From this we can know the maximum mutation degree of external factors The larger K is, the more likely the quality problem is caused by external factors.

[0072] Therefore, the process of obtaining the influence degree Q of external factors at the current moment is: Get the time difference between the maximum vibration time node, humidity drop time node, wind speed increase time node and the current time , and The mean of the time node of maximum vibration, the time node of humidity drop, and the time node of wind speed increase are obtained, and the variance V of the time node of maximum vibration, humidity drop, and wind speed increase is calculated. , and The product of the mean and variance V is inversely normalized to obtain the inversely normalized value. The maximum mutation degree of the function to the inverse proportional normalized value and external factors The product of is normalized, and the obtained normalized value is recorded as the external factor influence degree Q at the current moment. To perform inverse normalization, and use The linear normalization function is used for normalization. Among them, the variance of the maximum vibration time node, the humidity drop time node, and the wind speed increase time node The smaller it is, the more uniform the appearance time of various mutation factors is, and the time difference is , and The smaller the mean value of , the closer the mutation time of external factors is to the current moment, so the inverse proportional normalization value is used to adjust K. The larger the Q, the more likely it is that the larger P (the degree of channel lining quality problems at the current moment) is caused by external factors.

[0073] Step S33: Determine whether the target cause information of the channel lining quality problem is affected by external factors according to the degree of influence of the external factors.

[0074] You can set the external influence threshold as needed, for example, 0.7. Then: When Q is greater than 0.7, it is determined that the channel lining quality problem is caused by a sudden change in external factors and is affected by external factors.

[0075] When Q is less than or equal to 0.7, further analyze the cause of the problem, and the smaller Q is, the greater the possibility of other reasons.

[0076] In addition, in another preferred embodiment, please refer to Figure 5 ; The step S3 further comprises: Step S300, removing the traveling vibration signal from all the intrinsic mode function components corresponding to the vibration data sequence to obtain the remaining intrinsic mode function components; Step S301, reconstructing the remaining intrinsic mode function components into an updated vibration data sequence through empirical mode decomposition; Step S302, determining a corresponding fitting fluctuation curve based on the peaks and troughs in the updated vibration data sequence; Step S303, using the influence degree of external factors, the fitting fluctuation curve and the number of vibrators, the fault possibility at the current moment is calculated; Step S304: determining whether the target cause information of the channel lining quality problem is a construction equipment failure based on the fault possibility.

[0077] Wherein, the step S302 specifically includes: Dividing the updated vibration data sequence into a plurality of vibration fluctuations based on the peaks and troughs therein, and obtaining the amplitude and vibration period of each vibration fluctuation; The instability value of the vibration fluctuation is calculated by using the amplitude and vibration period of the vibration fluctuation and the amplitude and vibration period of the adjacent vibration fluctuation; The least square method is used to fit the fluctuation curve of all the instability values ​​of vibration fluctuations to obtain the fitting fluctuation curve.

[0078] In this embodiment, the traveling vibration signal of the lining trolley when moving forward is removed from all IMF components of the vibration data sequence corresponding to each vibrator, and the remaining IMF components are used to perform EMD reconstruction to obtain an updated vibration data sequence corresponding to each vibrator.

[0079] This eliminates the vibration effects of the lining trolley as it moves forward.

[0080] The vibrator of the lining trolley is inserted into the concrete poured in the channel to work. At the beginning, there are air bubbles inside the concrete, which makes the concrete uneven, causing the vibration frequency and amplitude of the vibrator to be unstable. As the air bubbles are discharged, the concrete gradually becomes uniform, and the vibration frequency and amplitude of the vibrator will tend to be stable. Then, as the lining trolley moves forward, new concrete is continuously poured into the channel, and the vibrator performs this repetitive operation.

[0081] Since all vibrators work synchronously, the changing trends of the vibration frequencies and amplitudes from unstable to stable for all vibrators should be similar, and the stable states should be similar (this is due to the similar internal uniformity of the concrete after vibration).

[0082] The updated vibration data sequence is divided into a number of vibration fluctuations based on the troughs in the updated vibration data sequence, and the amplitude (maximum value minus minimum value in the vibration fluctuation) and the vibration period (duration of the vibration fluctuation) of each vibration fluctuation are obtained.

[0083] The instability of the tth vibration fluctuation is thus The acquisition process is: The mean of the absolute values ​​of the differences between the amplitude of the t-th vibration fluctuation and the amplitudes of the t-1th and t+1th vibration fluctuations is obtained as the first mean; the mean of the absolute values ​​of the differences between the vibration period of the t-th vibration fluctuation and the vibration period of the t-1th and t+1th vibration fluctuations is obtained as the second mean; the product of the first mean and the second mean is normalized to obtain a normalized value, and the normalized value is used as the instability of the t-th vibration fluctuation. In this embodiment, using The linear normalization function normalizes the product. The greater the difference between the amplitude and vibration period of adjacent vibration fluctuations, the more unstable it is.

[0084] The least square method is used to fit the instability of all vibration fluctuations in each updated vibration data sequence to obtain a fitting fluctuation curve.

[0085] Therefore, the process of obtaining the fault probability U at the current moment is: The Pearson correlation coefficient of the fitting fluctuation curves corresponding to any two vibrators is obtained, the mean of the Pearson correlation coefficients of the fitting fluctuation curves corresponding to all any two vibrators is calculated, and then the difference between the value 1 and the mean is calculated, and the product of the difference, the inverse proportional value of the external factor influence degree Q at the current moment, and the variance W of all peaks and valleys in all fitting fluctuation curves is normalized to obtain a normalized value, and the normalized value is used as the fault probability U at the current moment. In this embodiment, the inverse proportional value of Q is 1-Q, and the product is normalized using the norm linear normalization function.

[0086] Among them, the smaller the influence degree Q of the external factors at the current moment is, the more likely it is a non-external factor. The Pearson correlation coefficient is a well-known technology. The closer its value is to 1, the more positively correlated the two curves are. When there is no fault, it should be close to 1. And when there is no fault, the results after concrete vibration should be similar, so the stable vibration fluctuations should be similar, and the variance should be close to 0. Therefore, the larger U is, the more likely it is a fault.

[0087] Here you can set the possible fault threshold as needed, for example, 0.6. Then: When U is greater than 0.6, it is determined that the channel lining quality problem is caused by equipment failure.

[0088] When U is less than or equal to 0.6, it can be further determined as a feed quality problem in the preparation work.

[0089] Based on the above steps and links, it is determined whether the target cause information of the channel lining quality problem is a construction equipment failure or a material delivery quality problem.

[0090] Step S4, executing the corresponding target control instruction based on the target reason information; For the above three types of target cause information, after determining the cause, different target control instructions are executed respectively, so as to solve the channel lining quality problems in a timely and effective manner, greatly reduce the workload of manual comprehensive inspection, improve construction efficiency and ensure production.

[0091] In a preferred embodiment, please refer to Figure 6 ; The step S4 comprises: Step S40, when the influence degree of the external factors is greater than the external influence threshold, executing the corresponding deceleration instruction; or Step S41, when the influence degree of the external factors is less than or equal to the external influence threshold and the possibility of the fault is greater than the possible fault threshold, executing the shutdown instruction and the equipment fault alarm instruction; or Step S42, when the influence degree of external factors is less than or equal to the external influence threshold and the fault possibility is less than or equal to the fault possibility threshold, execute the shutdown command and the material feeding problem alarm command.

[0092] Based on the above embodiments, Q and U are used as input reference data of a PID (PID control system) controller: For example, the external factor impact Q is 0.7 and the possible fault threshold U is 0.6.

[0093] When Q is greater than or equal to 0.7, the PID controller outputs a deceleration command to slow down the lining trolley. The larger the Q, the slower the speed, so that more time is used to better adapt to the sudden changes in the external environment and ensure construction quality.

[0094] When Q is less than 0.7 and U is greater than 0.6, the PID controller outputs a shutdown command and issues an equipment failure alarm.

[0095] When Q is less than 0.7 and U is less than or equal to 0.6, the PID controller outputs a shutdown command and issues a feeding problem alarm.

[0096] In this way, automatic control of channel lining construction of water conservancy projects is achieved according to the different causes of channel lining quality problems.

[0097] The present invention can accurately determine whether there is a quality problem with the channel lining based on the analysis of the elevation data of each monitoring point, and is based on the analysis of multi-dimensional data including the external environment and construction equipment. Therefore, when there is a quality problem with the channel lining, the cause of the problem can be accurately and efficiently found out, and targeted adjustment and control can be carried out. This not only helps construction personnel to quickly locate and solve problems, but more importantly, effectively guarantees the efficiency of the automation of channel lining construction in water conservancy projects.

[0098] Embodiment 2: The embodiment of the present invention also provides an automatic control device for the construction of a water conservancy project channel lining. The automatic control device for the construction of a water conservancy project channel lining can be a lining trolley.

[0099] like Figure 7 As shown, Figure 7 It is a structural schematic diagram of the hardware operating environment of the water conservancy project channel lining construction automation control equipment involved in the embodiment of the present invention.

[0100] like Figure 7 As shown, the automatic control device for channel lining construction of water conservancy projects may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display (Display), an input unit such as a control panel, and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WIFI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001. The memory 1005 as a computer storage medium may include a channel lining construction automatic control program.

[0101] Those skilled in the art will understand that Figure 7 The hardware structure shown in the figure does not constitute a limitation of the device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0102] Continue to refer to Figure 7 , Figure 7The memory 1005 as a computer-readable storage medium may include an operating system, a user interface module, a network communication module, and a channel lining construction automation control program.

[0103] exist Figure 7 In the embodiment, the network communication module is mainly used to connect to the server and can communicate data with the server; and the processor 1001 can call the channel lining construction automation control program stored in the memory 1005 and execute the steps in the above embodiments.

[0104] The hardware structure of the above-mentioned automatic control equipment for construction of channel lining of water conservancy project is used to implement various embodiments of the automatic control of construction of channel lining of water conservancy project of the present invention.

[0105] In addition, the present invention also provides an automatic control device for channel lining construction of a water conservancy project, please refer to Figure 8 The automatic control device for channel lining construction of water conservancy project comprises: Data acquisition module A10 is used to collect multi-dimensional data and elevation data of each monitoring point in the channel in real time during the construction of the channel lining of the water conservancy project; The quality determination module A20 is used to determine whether there is a channel lining quality problem at the current moment based on the elevation data; A problem analysis module A30, for determining target cause information of the channel lining quality problem based on the multi-dimensional data when a channel lining quality problem occurs at the current moment; The adjustment control module A40 is used to execute the corresponding target control instruction based on the target reason information.

[0106] Furthermore, the quality determination module A20 is also used for: Comparing the target elevation data sequence with the standard elevation data sequence in terms of single corresponding data to determine problematic data in the target elevation data sequence; Based on the problem data, determining the degree of the channel lining quality problem at the current moment; According to the degree of the channel lining quality problem, it is determined whether there is a channel lining quality problem at the current moment.

[0107] Furthermore, the quality determination module A20 is also used for: determining a problem degree, a first quantity, and a second quantity of total data in a target elevation data sequence of the problem data; Determine a sequence segment formed by adjacent problem data sequences in the target elevation data sequence, and determine a maximum length value in the sequence segment; The problem degree of the channel lining quality at the current moment is calculated using the problem degree, the first quantity, the second quantity and the maximum length value.

[0108] Furthermore, the problem analysis module A30 is also used to: Determine the vibration data sequence of each vibrator on the construction equipment; determining the traveling vibration signal based on the vibration data sequence; Calculating the influence degree of external factors based on the traveling vibration signal, the humidity data and the wind speed data; According to the influence degree of the external factors, it is determined whether the target cause information of the channel lining quality problem is affected by the external factors.

[0109] Furthermore, the problem analysis module A30 is also used to: Decomposing the vibration data sequence into a plurality of eigenmode function components by empirical mode decomposition; Divide the eigenmode function components of two adjacent vibrators into component groups to obtain a plurality of non-repeating component groups; Based on the eigenmode function components of the two vibrators in each component group, the dynamic time warping set of all component groups is calculated; Take any data in each dynamic time warping set and obtain multiple update sets in a full permutation manner; Calculate the sum of each update set to determine the target set with the minimum sum; Based on the eigenmode function components respectively corresponding to each data in the target set, a traveling vibration signal corresponding to each vibrator is obtained.

[0110] Furthermore, the problem analysis module A30 is also used to: Take any eigenmode function component of each of the two vibrators in the component group, and calculate the dynamic time warping distance between the two eigenmode function components; The dynamic time warping distance between any two eigenmode function components from different vibrators in the same group is calculated without repetition to obtain the dynamic time warping set of all component groups.

[0111] Furthermore, the problem analysis module A30 is also used to: determining peaks and troughs of each of the travel vibration signal, the humidity data, and the wind speed data; Based on the respective peaks and troughs, respectively determine the relative maximum vibration of the traveling vibration signal, the degree of humidity drop of the humidity data, and the degree of wind speed increase of the wind speed data; The maximum mutation degree is calculated by using the relative maximum vibration, humidity drop degree and wind speed increase degree; Determine the time nodes corresponding to the relative maximum vibration, humidity drop and wind speed increase, and determine the time difference from each time node to the current moment; The influence of external factors is calculated using the maximum mutation degree, time node and time difference.

[0112] Furthermore, the problem analysis module A30 is also used to: removing the traveling vibration signal from all the eigenmode function components corresponding to the vibration data sequence to obtain the remaining eigenmode function components; Reconstructing the remaining eigenmode function components into an updated vibration data sequence through empirical mode decomposition; Determining a corresponding fitting fluctuation curve based on the peaks and troughs in the updated vibration data sequence; The possibility of failure at the current moment is calculated by using the influence of external factors, the fitting fluctuation curve and the number of vibrators; Based on the fault possibility, it is determined whether the target cause information of the channel lining quality problem is a construction equipment failure.

[0113] Furthermore, the problem analysis module A30 is also used to: Dividing the updated vibration data sequence into a plurality of vibration fluctuations based on the peaks and troughs therein, and obtaining the amplitude and vibration period of each vibration fluctuation; The instability value of the vibration fluctuation is calculated by using the amplitude and vibration period of the vibration fluctuation and the amplitude and vibration period of the adjacent vibration fluctuation; The least square method is used to fit the fluctuation curve of all the instability values ​​of vibration fluctuations to obtain the fitting fluctuation curve.

[0114] Furthermore, the regulation control module A40 is also used for: When the influence of the external factors is greater than the external influence threshold, execute the corresponding deceleration instruction; or When the degree of influence of external factors is less than or equal to the external influence threshold and the possibility of failure is greater than the possible failure threshold, execute the shutdown command and equipment failure alarm command; or When the influence degree of external factors is less than or equal to the external influence threshold and the possibility of fault is less than or equal to the possible fault threshold, the shutdown command and the feeding problem alarm command are executed.

[0115] The specific implementation of the automatic control device for channel lining construction of a water conservancy project of the present invention is basically the same as the embodiments of the automatic control method for channel lining construction of a water conservancy project described above, and will not be described in detail here.

[0116] In addition, the present invention also provides a computer-readable storage medium. The computer-readable storage medium of the present invention stores a channel lining construction automation control program, wherein when the channel lining construction automation control program is executed by a processor, the steps of the water conservancy project channel lining construction automation control method as described above are implemented.

[0117] Among them, the method implemented when the channel lining construction automation control program is executed can refer to the various embodiments of the water conservancy project channel lining construction automation control method of the present invention, and will not be repeated here.

[0118] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0119] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0120] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0122] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0124] Although preferred embodiments of the present invention have been described, additional changes and modifications may occur to these embodiments once those skilled in the art are aware of the basic inventive concepts.

[0125] The above description is only a preferred embodiment of the present invention, and does not limit the protection scope of the present invention. All equivalent structural changes made by using the contents of the present invention specification and drawings under the inventive concept of the present invention, or directly / indirectly applied in other related technical fields are included in the protection scope of the present invention.

Claims

1. A method for automatic control of channel lining construction of a water conservancy project, characterized in that: The method comprises: During the construction of water conservancy project channel lining, real-time collection of multi-dimensional data and elevation data of each monitoring point in the channel; Based on the elevation data, determining whether a channel lining quality problem occurs at the current moment; In the case where a channel lining quality problem occurs at the current moment, determining target cause information of the channel lining quality problem based on the multi-dimensional data; Based on the target reason information, executing a corresponding target control instruction; Among them, the multi-dimensional data includes vibration data, humidity data and wind speed data; the elevation data represents the distance value from the monitoring point in the channel to the uppermost surface of the channel; the target cause information includes construction equipment failure, external factors and material feeding quality; the target control instructions include deceleration instructions, shutdown instructions and alarm instructions.

2. The automatic control method for channel lining construction of a water conservancy project according to claim 1 is characterized in that: The elevation data includes: a target elevation data sequence composed of elevation data of a plurality of monitoring points evenly distributed along the channel width direction at the current moment; The step of determining whether a channel lining quality problem occurs at the current moment based on the elevation data comprises: Comparing the target elevation data sequence with the standard elevation data sequence in terms of single corresponding data to determine problematic data in the target elevation data sequence; Based on the problem data, determining the degree of the channel lining quality problem at the current moment; According to the degree of the channel lining quality problem, it is determined whether there is a channel lining quality problem at the current moment.

3. The automatic control method for channel lining construction of a water conservancy project according to claim 2 is characterized in that: Based on the problem data, the step of determining the degree of the channel lining quality problem at the current moment comprises: determining a problem degree, a first quantity, and a second quantity of total data in a target elevation data sequence of the problem data; Determine a sequence segment formed by adjacent problem data sequences in the target elevation data sequence, and determine a maximum length value in the sequence segment; The problem degree of the channel lining quality at the current moment is calculated using the problem degree, the first quantity, the second quantity and the maximum length value.

4. The automatic control method for channel lining construction of a water conservancy project according to claim 1 is characterized in that: The vibration data includes a traveling vibration signal of the construction equipment when it moves forward; The step of determining target cause information of the channel lining quality problem based on the multi-dimensional data comprises: Determine the vibration data sequence of each vibrator on the construction equipment; determining the traveling vibration signal based on the vibration data sequence; Calculating the influence degree of external factors based on the traveling vibration signal, the humidity data and the wind speed data; According to the influence degree of the external factors, it is determined whether the target cause information of the channel lining quality problem is affected by the external factors.

5. The automatic control method for channel lining construction of a water conservancy project according to claim 4 is characterized in that: Based on the vibration data sequence, the step of determining the traveling vibration signal comprises: Decomposing the vibration data sequence into a plurality of eigenmode function components by empirical mode decomposition; Divide the eigenmode function components of two adjacent vibrators into component groups to obtain a plurality of non-repeating component groups; Based on the eigenmode function components of the two vibrators in each component group, the dynamic time warping set of all component groups is calculated; Take any data in each dynamic time warping set and obtain multiple update sets in a full permutation manner; Calculate the sum of each update set to determine the target set with the minimum sum; Based on the eigenmode function components respectively corresponding to each data in the target set, a traveling vibration signal corresponding to each vibrator is obtained.

6. The automatic control method for channel lining construction of a water conservancy project according to claim 5 is characterized in that: Based on the eigenmode function components of the two vibrators in the component group, the dynamic time warping set of all component groups is calculated, including: Take any eigenmode function component of each of the two vibrators in the component group, and calculate the dynamic time warping distance between the two eigenmode function components; The dynamic time warping distance between any two eigenmode function components from different vibrators in the same group is calculated without repetition to obtain the dynamic time warping set of all component groups.

7. The automatic control method for channel lining construction of a water conservancy project according to claim 6 is characterized in that: The step of calculating the influence degree of external factors based on the traveling vibration signal, the humidity data and the wind speed data comprises: determining peaks and troughs of each of the travel vibration signal, the humidity data, and the wind speed data; Based on the respective peaks and troughs, respectively determine the relative maximum vibration of the traveling vibration signal, the degree of humidity drop of the humidity data, and the degree of wind speed increase of the wind speed data; The maximum mutation degree is calculated by using the relative maximum vibration, humidity drop degree and wind speed increase degree; Determine the time nodes corresponding to the relative maximum vibration, humidity drop and wind speed increase, and determine the time difference from each time node to the current moment; The influence of external factors is calculated using the maximum mutation degree, time node and time difference.

8. The automatic control method for channel lining construction of a water conservancy project according to claim 7 is characterized in that: The step of determining target cause information of the channel lining quality problem based on the multi-dimensional data also includes: removing the traveling vibration signal from all the eigenmode function components corresponding to the vibration data sequence to obtain the remaining eigenmode function components; Reconstructing the remaining eigenmode function components into an updated vibration data sequence through empirical mode decomposition; Determining a corresponding fitting fluctuation curve based on the peaks and troughs in the updated vibration data sequence; The possibility of failure at the current moment is calculated by using the influence of external factors, the fitting fluctuation curve and the number of vibrators; Based on the fault possibility, it is determined whether the target cause information of the channel lining quality problem is a construction equipment failure.

9. The automatic control method for channel lining construction of a water conservancy project according to claim 8 is characterized in that: The step of determining a corresponding fitting fluctuation curve based on the peaks and troughs in the updated vibration data sequence comprises: Dividing the updated vibration data sequence into a plurality of vibration fluctuations based on the peaks and troughs therein, and obtaining the amplitude and vibration period of each vibration fluctuation; The instability value of the vibration fluctuation is calculated by using the amplitude and vibration period of the vibration fluctuation and the amplitude and vibration period of the adjacent vibration fluctuation; The least square method is used to fit the fluctuation curve of all the instability values ​​of the vibration fluctuations to obtain the fitting fluctuation curve.

10. The automatic control method for channel lining construction of a water conservancy project according to claim 1, characterized in that: The step of executing a corresponding target control instruction based on the target reason information includes: When the influence of the external factors is greater than the external influence threshold, execute the corresponding deceleration instruction; or When the degree of influence of external factors is less than or equal to the external influence threshold and the possibility of failure is greater than the possible failure threshold, execute the shutdown command and equipment failure alarm command; or When the influence degree of external factors is less than or equal to the external influence threshold and the possibility of fault is less than or equal to the possible fault threshold, the shutdown command and the feeding problem alarm command are executed.

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