Dynamic compaction monitoring system based on sensor

Abstract

The invention provides a dynamic compaction monitoring system based on a sensor, and relates to the technical field of dynamic compaction monitoring, and the system comprises a sensor module which is used for collecting the working state of a dynamic compaction machine; the Beidou positioning antenna is installed on the dynamic compaction machine and used for collecting the compaction position of the dynamic compaction machine; and the main control module is in communication connection with the sensor module and the positioning module and is used for sending the working state and the tamping position of the dynamic compactor to the display module to be displayed. The real-time data of the working state and the tamping position are transmitted to the main control module and are displayed in a centralized manner, so that a manager can monitor the construction progress more efficiently and make a reasonable decision. Compared with traditional manual supervision, the management efficiency can be greatly improved through automatic data processing and real-time display, and meanwhile data support is provided for subsequent construction adjustment and optimization.

Description

Technical Field

[0001] This invention relates to the field of dynamic compaction monitoring technology, and in particular to a sensor-based dynamic compaction monitoring system. Background Technology

[0002] Dynamic compaction, as a deep foundation treatment technology, is widely used to improve the bearing capacity of foundations and accelerate foundation consolidation, especially in complex or soft foundation environments, where its technical and economic advantages are widely recognized in the industry. According to the "Technical Specification for Dynamic Compaction Foundation Treatment" (CECS279-2010), the quality inspection and acceptance of dynamic compaction foundation treatment is divided into key control items and general items. Key control items mainly include post-construction testing indicators such as foundation strength (or compaction degree), compression modulus, foundation bearing capacity, and effective reinforcement depth, reflecting the final state of the overall construction quality and foundation bearing capacity. General items mainly involve key construction parameters during dynamic compaction, such as hammer drop height, hammer weight, number and sequence of compaction passes, spacing between compaction points, compaction range, and interval between consecutive passes.

[0003] In traditional dynamic compaction construction, especially during the inspection of general projects, the construction process often relies on manual control by supervisors and construction personnel. This is easily affected by human factors, such as non-standard operation, inaccurate recording, and imprecise parameter control, leading to unstable construction quality. This manual management method suffers from data loss and inconsistent records, and it is difficult to effectively achieve precise control and monitoring of the dynamic compaction process. Furthermore, since key control item inspections are generally conducted after construction is completed, and this process is time-consuming, there is a significant time lag between the inspection results and the actual construction process. Once quality defects are found, feedback and adjustments cannot be made immediately, posing a significant challenge to timely remediation of construction quality issues. Summary of the Invention

[0004] To address the aforementioned problems, the purpose of this invention is to provide a sensor-based dynamic compaction monitoring system.

[0005] A sensor-based dynamic compaction monitoring system includes:

[0006] The sensor module is used to collect the working status of the dynamic compaction machine;

[0007] The Beidou positioning antenna is installed on the dynamic compaction machine to collect the impact position of the machine.

[0008] The main control module communicates with the sensor module and the positioning module respectively, and is used to send the working status and impact position of the dynamic compaction machine to the display module for display.

[0009] Preferably, the sensor module includes: a drop distance sensor and a tension sensor; the drop distance sensor is installed on the main winch of the dynamic compaction machine and is used to measure the lifting height, drop distance and impact settlement of the hammer; the tension sensor is used to record the number of impacts.

[0010] Preferably, in the display module, a color-coded distribution map of the number of tamping blows at each point is used, or the points are labeled with numbers; in the display module, a color-coded distribution map of the hammer lifting height at each point is also used.

[0011] Preferably, the main control module includes:

[0012] The signal decomposition module is used to adaptively decompose the raw operating state signal collected by the sensor module to obtain IMF components of different frequencies.

[0013] The signal filtering module is used to filter IMF components of different frequencies to obtain noise IMF components and effective IMF components.

[0014] The signal denoising module is used to denoise the noise IMF components to obtain the denoised IMF components;

[0015] The signal reconstruction module is used to reconstruct the denoised IMF components and the effective IMF components to obtain the denoised working status signal, and to perform analog-to-digital conversion on the denoised working status signal to obtain the hammer lifting height, drop distance, impact settlement and number of impacts.

[0016] Preferably, the signal decomposition module includes:

[0017] The signal acquisition unit is used to construct a signal to be processed based on the original operating state signal; wherein, the signal to be processed is:

[0018]

[0019] in, This is the original working status signal. The signal to be processed. For the first addition of the Gaussian noise standard deviation, To use the first IMF component of Empirical Mode Decomposition, For the i-th group of Gaussian noise added, For noise amplitude parameters, This is the standard deviation estimation function;

[0020] An initial decomposition unit is used to decompose the working state signal to obtain initial IMF components;

[0021] The iterative calculation unit is used to calculate the next IMF component based on the initial IMF component until the decomposition is completed and IMF components of different frequencies are obtained.

[0022] Preferably, in the iterative calculation unit, the formula for calculating the k-th IMF component is:

[0023]

[0024] in, Let k be the k-th IMF component, and k be greater than 1. , For the k-th order residual, Let M be the standard deviation of the Gaussian noise added for the (k-1)th time, and M represent the local mean of the signal. For the number of iterations, This is the k-th IMF component using Empirical Mode Decomposition.

[0025] Preferably, the signal denoising module includes:

[0026] Wavelet decomposition unit is used to perform wavelet decomposition on the noise IMF component to obtain multiple wavelet coefficients;

[0027] The threshold calculation unit is used to calculate the threshold based on the median of the wavelet coefficients.

[0028] A denoising function construction unit is used to construct a wavelet coefficient denoising function using the threshold.

[0029] The wavelet coefficient processing unit is used to process all wavelet coefficients using the wavelet coefficient denoising function to obtain denoised wavelet coefficients.

[0030] The inverse wavelet transform unit is used to perform inverse wavelet transform on the denoised wavelet coefficients to obtain the denoised IMF components.

[0031] Preferably, in the threshold calculation unit, the threshold calculation formula is:

[0032]

[0033] in, For the threshold, For noise intensity parameters, The length of the IMF signal. This represents the median of all wavelet coefficients at the first-level decomposition scale.

[0034] Preferably, in the denoising function construction unit, the following formula is used:

[0035]

[0036] Construct a wavelet coefficient denoising function; where, Represents the wavelet coefficients after denoising. This represents the k-th wavelet coefficient at the j-th decomposition scale. , Indicates the threshold. This represents the adjustment coefficient. Represents a symbolic function.

[0037] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0038] This invention relates to a sensor-based dynamic compaction monitoring system. Compared with existing technologies, this invention transmits real-time data on the working status and compaction position to the main control module for centralized display, enabling managers to monitor construction progress more efficiently and make informed decisions. Compared with traditional manual supervision, automated data processing and real-time display can significantly improve management efficiency and provide data support for subsequent construction adjustments and optimizations.

[0039] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic diagram of a sensor-based dynamic compaction monitoring system provided in this invention;

[0042] Figure 2 This is an interface diagram showing the number of impacts provided in this invention;

[0043] Figure 3 This is a diagram showing the lifting height interface provided in this invention;

[0044] Figure 4 This is a diagram showing the final impact settlement amount provided in this invention. Detailed Implementation

[0045] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0046] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0047] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0048] like Figure 1 As shown, this embodiment provides a sensor-based dynamic compaction monitoring system, including:

[0049] The sensor module is used to collect the working status of the dynamic compaction machine;

[0050] The Beidou positioning antenna is installed on the dynamic compaction machine to collect the impact position of the machine.

[0051] The main control module communicates with the sensor module and the positioning module respectively, and is used to send the working status and impact position of the dynamic compaction machine to the display module for display.

[0052] The sensor module includes a drop distance sensor and a tension sensor. The drop distance sensor is installed on the main winch of the dynamic compaction machine and is used to measure the lifting height, drop distance, and impact settlement of the hammer. The tension sensor is used to record the number of impacts.

[0053] The Beidou antenna module consists of two Beidou antennas and cables. Beidou antenna 1 is mounted on the top of the boom of the dynamic compaction machine; Beidou antenna 2 is mounted on the boom pulley bracket. The Beidou antenna module can determine the azimuth, direction, center position of the boom's rotating shaft, and surface elevation of the dynamic compaction machine through the precise positioning of the two antennas.

[0054] The drop distance sensor, consisting of a distance sensor and its cable, is installed near the main winch of the dynamic compaction machine. Its main function is to measure the lifting height and drop distance of the hammer, as well as the settlement amount per impact.

[0055] The tensioning sensor, by installing RFID cards and sensors on the machine, records each instance of lifting and loosening the hammer.

[0056] The display module consists of an industrial-grade tablet computer and its cables. Installed in the cab of the dynamic compaction machine, the display module provides the operator with real-time information on the compaction point layout, guiding the compaction position, number of impacts, real-time hammer lifting height, compaction settlement, and dynamic planning to guide construction.

[0057] The power module is installed in the cab of the dynamic compaction machine, connected to the power supply, and the power supply is regulated and transformed before supplying power to each module.

[0058] Main control module: The main control module is installed in the cab of the dynamic compaction machine. Its function is to receive and process sensor data, store and send it to the tablet display, and at the same time send the construction data to the cloud service for processing via 4G antenna.

[0059] The communication module supports multiple methods such as 4G, WIFI, and radio. It is installed in the cab of the dynamic compaction machine and its function is to transmit construction data to the cloud service for processing in real time.

[0060] It should be noted that the main control module plays a crucial role in the sensor-based dynamic compaction monitoring system, as it directly affects the accuracy, reliability, and real-time performance of the entire monitoring system's data.

[0061] The main control module, through multiple functional modules including signal decomposition, filtering, denoising, and reconstruction, ensures the extraction of effective and accurate working status data from the raw signals acquired by the sensors. This process is crucial for handling signals in complex environments (such as those affected by vibration, temperature differences, dust, and other interference). The dynamic compaction construction environment itself is full of noise and interference, and the raw signals often contain a large amount of noise; relying solely on the raw signals cannot accurately reflect the actual construction situation. The main control module in this invention includes:

[0062] The signal decomposition module is used to adaptively decompose the raw operating state signal collected by the sensor module to obtain IMF components of different frequencies.

[0063] The signal decomposition module includes:

[0064] The signal acquisition unit is used to construct a signal to be processed based on the original operating state signal; wherein, the signal to be processed is:

[0065]

[0066] in, This is the original working status signal. The signal to be processed. For the first addition of the Gaussian noise standard deviation, To use the first IMF component of Empirical Mode Decomposition, For the i-th group of Gaussian noise added, For noise amplitude parameters, This is the standard deviation estimation function;

[0067] An initial decomposition unit is used to decompose the working state signal to obtain initial IMF components;

[0068] The iterative calculation unit is used to calculate the next IMF component based on the initial IMF component until the decomposition is completed and IMF components of different frequencies are obtained.

[0069] In the iterative calculation unit, the formula for calculating the k-th IMF component is:

[0070]

[0071] in, Let k be the k-th IMF component, and k be greater than 1. , For the k-th order residual, Let M be the standard deviation of the Gaussian noise added for the (k-1)th time, and M represent the local mean of the signal. For the number of iterations, This is the k-th IMF component using Empirical Mode Decomposition.

[0072] The signal filtering module is used to filter IMF components of different frequencies to obtain noise IMF components and effective IMF components.

[0073] In this invention, the sample entropy of IMF components at different frequencies is calculated. Sample entropy primarily measures the complexity of a time series by the probability of new patterns emerging in the signal. The higher the sample entropy, the greater the probability of new patterns emerging, and the greater the complexity of the sequence. Therefore, a larger sample entropy value for an IMF component indicates higher complexity and dominance by noise. Conversely, a smaller sample entropy value indicates higher self-similarity and dominance by valid information. IMF components with entropy values ​​outside the set range are considered noise IMF components.

[0074] The signal denoising module is used to denoise the noise IMF components to obtain the denoised IMF components;

[0075] The signal denoising module includes:

[0076] Wavelet decomposition unit is used to perform wavelet decomposition on the noise IMF component to obtain multiple wavelet coefficients;

[0077] The threshold calculation unit is used to calculate the threshold based on the median of the wavelet coefficients.

[0078] In the threshold calculation unit, the threshold calculation formula is:

[0079]

[0080] in, For the threshold, For noise intensity parameters, The length of the IMF signal. This represents the median of all wavelet coefficients at the first-level decomposition scale.

[0081] A denoising function construction unit is used to construct a wavelet coefficient denoising function using the threshold.

[0082] In the denoising function construction unit, the following formula is used:

[0083]

[0084] Construct a wavelet coefficient denoising function; where, Represents the wavelet coefficients after denoising. This represents the k-th wavelet coefficient at the j-th decomposition scale. , Indicates the threshold. This represents the adjustment coefficient. Represents a symbolic function.

[0085] In this invention, the convergence point is adjusted. The wavelet coefficient denoising function can be adaptively adjusted to determine the convergence degree of the threshold function, so that the wavelet coefficient denoising function can make comprehensive use of both soft and hard threshold functions. This solves the problems of discontinuity at the threshold of the hard threshold function and certain deviations in the soft threshold function, retains more useful signals, and improves the performance of the denoising function.

[0086] The wavelet coefficient processing unit is used to process all wavelet coefficients using the wavelet coefficient denoising function to obtain denoised wavelet coefficients.

[0087] The inverse wavelet transform unit is used to perform inverse wavelet transform on the denoised wavelet coefficients to obtain the denoised IMF components.

[0088] The signal reconstruction module is used to reconstruct the denoised IMF components and the effective IMF components to obtain the denoised working status signal, and to perform analog-to-digital conversion on the denoised working status signal to obtain the hammer lifting height, drop distance, impact settlement and number of impacts.

[0089] Sensors transmit collected construction data to front-end equipment, allowing machinery operators to monitor the current construction status in real time. Simultaneously, a positioning antenna is installed on top of the machinery, interacting with a GNSS positioning base station installed on-site via a 4G / 5G network. The GNSS base station determines the equipment's location using a satellite positioning system, and the vehicle-mounted positioning antenna receives this location information and transmits it to the front-end equipment via wired transmission. The front-end equipment then sends the location information, construction records, and other construction data to a cloud computing server in real time via the 4G / 5G network. Upon receiving the data, the server analyzes and renders it to create a visualized construction record, which managers can view in real time via PC or mobile devices to manage the on-site construction progress.

[0090] The industrial tablet's software interface displays the equipment's operating status in real time on the display module; it graphically shows the pre-set design compaction point locations, construction standards, and areas to be compacted, as well as real-time information such as the actual number of compactions, hammer lifting height, and compaction settlement, guiding the compaction machinery to operate according to construction standards; it also allows for understanding the actual compaction situation and avoiding missed hammer blows. The monitoring terminal can mainly record the following information:

[0091] (1) Number of tamping blows: Displays a distribution map of the number of tamping blows at each point, distinguished by color or marked with numbers;

[0092] (2) Lifting hammer height: Displays the distribution map of lifting hammer height at each point, distinguished by color;

[0093] (3) Settlement: Real-time recording of the settlement value for each tamping blow and the total settlement.

[0094] In addition to recording information such as the number of tamping blows, hammer lifting height, and settlement amount, the front-end monitoring terminal also has the following functions to facilitate operators' understanding of the construction situation and to ensure data security and timely transmission:

[0095] (1) Task Acquisition: Acquire and graphically display the current construction planning area boundary;

[0096] (2) Parameter display: can display the location of construction vehicles, the location of tamping points, the number of tamping blows, the amount of settlement, etc.

[0097] (3) Construction guidance: The number of tamping blows is calculated in real time and drawn into graphics according to different colors to facilitate on-site construction by construction personnel;

[0098] (4) Data storage: Stores local construction data;

[0099] (5) Data feedback: Real-time feedback of construction data.

[0100] The system software platform leverages computer technology, the Internet of Things, cloud computing, big data, artificial intelligence, VR & AR, and other technologies to provide advanced technical means for engineering project management. It constructs an intelligent monitoring and digital control system for construction sites, overcoming the shortcomings of traditional methods in supervision, and ultimately achieving comprehensive real-time monitoring of personnel, machinery, materials, methods, and environment. The platform's comprehensive engineering dashboard provides a clear overview of project information, including progress, personnel management, equipment status, and construction maps, allowing users to have a comprehensive understanding of the overall construction situation.

[0101] The main functions include, but are not limited to, the following: electronic map display, personnel management, vehicle management, electronic perimeter management for non-stop construction, construction area perimeter alarm system and site monitoring system, earthwork and foundation treatment subsystems (including intelligent compaction system, dynamic compaction digital construction monitoring system, and pile driver digital construction monitoring system), online monitoring system for mixing plants, paving and compaction monitoring system (including water-stabilized layer paving digital construction monitoring system and compaction monitoring system), and platform reserved interfaces including investment management, progress management, data management, knowledge base management, and duty management, connecting to a digital integrated management platform. The system is built on a microservice architecture, adopts a B / S structure, supports PC Web terminals and Android App applications, enabling unified access, information sharing, collaborative work, and process control.

[0102] The software system mainly consists of a front-end digital construction management and control platform and a back-end database. The back-end database is deployed on a highly secure server and is primarily used to store and process construction data sent from the front-end equipment. The front-end digital construction management and control platform is mainly used to display construction data, equipment operating status, and to establish the construction work area.

[0103] The main functions and interface of the front-end digital construction management and control platform are as follows:

[0104] (1) Cockpit Interface

[0105] The cockpit interface mainly reflects the overall construction status, including the number of operating dynamic compaction equipment, the number of work areas, construction method warnings, and closure warnings.

[0106] (2) Construction monitoring interface

[0107] The monitoring interface mainly consists of three modules: a tools module, a construction status query module, and an equipment information module. The tools module includes functions such as box selection query, distance measurement, and area measurement. The construction status query module is used to view current and historical construction data. By selecting the contract section, dynamic compaction method, work area, and construction monitoring indicators, the dynamic compaction construction data can be viewed. The equipment information module clearly displays the total number of dynamic compaction machines and the number of currently online machines. The monitoring effect is as follows: Figure 2-4 As shown in the illustrations, the tamping effect can be clearly seen by referring to the diagrams.

[0108] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A sensor-based dynamic compaction monitoring system, characterized in that, include: The sensor module is used to collect the working status of the dynamic compaction machine; The Beidou positioning antenna is installed on the dynamic compaction machine to collect the impact position of the machine. The main control module communicates with the sensor module and the positioning module respectively, and is used to send the working status and impact position of the dynamic compaction machine to the display module for display.

2. The sensor-based dynamic compaction monitoring system according to claim 1, characterized in that, The sensor module includes a drop distance sensor and a tension sensor; the drop distance sensor is installed on the main winch of the dynamic compaction machine and is used to measure the lifting height, drop distance and impact settlement of the hammer; the tension sensor is used to record the number of impacts.

3. The sensor-based dynamic compaction monitoring system according to claim 1, characterized in that, In the display module, the distribution of the number of tamping blows at each point is distinguished by color or by numbers; in the display module, the distribution of the hammer lifting height at each point is distinguished by color.

4. The sensor-based dynamic compaction monitoring system according to claim 1, characterized in that, The main control module includes: The signal decomposition module is used to adaptively decompose the raw operating state signal collected by the sensor module to obtain IMF components of different frequencies. The signal filtering module is used to filter IMF components of different frequencies to obtain noise IMF components and effective IMF components. The signal denoising module is used to denoise the noise IMF components to obtain the denoised IMF components; The signal reconstruction module is used to reconstruct the denoised IMF components and the effective IMF components to obtain the denoised working status signal, and to perform analog-to-digital conversion on the denoised working status signal to obtain the hammer lifting height, drop distance, impact settlement and number of impacts.

5. The sensor-based dynamic compaction monitoring system according to claim 4, characterized in that, The signal decomposition module includes: The signal acquisition unit is used to construct a signal to be processed based on the original operating state signal; wherein, the signal to be processed is: in, This is the original working status signal. The signal to be processed. For the first addition of the Gaussian noise standard deviation, To use the first IMF component of Empirical Mode Decomposition, For the i-th group of Gaussian noise added, For noise amplitude parameters, This is the standard deviation estimation function; An initial decomposition unit is used to decompose the working state signal to obtain initial IMF components; The iterative calculation unit is used to calculate the next IMF component based on the initial IMF component until the decomposition is completed and IMF components of different frequencies are obtained.

6. The sensor-based dynamic compaction monitoring system according to claim 5, characterized in that, In the iterative calculation unit, the formula for calculating the k-th IMF component is: in, Let k be the k-th IMF component, and k be greater than 1. , For the k-th order residual, Let M be the standard deviation of the Gaussian noise added for the (k-1)th time, and M represent the local mean of the signal. For the number of iterations, This is the k-th IMF component using Empirical Mode Decomposition.

7. A sensor-based dynamic compaction monitoring system according to claim 6, characterized in that, The signal denoising module includes: Wavelet decomposition unit is used to perform wavelet decomposition on the noise IMF component to obtain multiple wavelet coefficients; The threshold calculation unit is used to calculate the threshold based on the median of the wavelet coefficients. A denoising function construction unit is used to construct a wavelet coefficient denoising function using the threshold. The wavelet coefficient processing unit is used to process all wavelet coefficients using the wavelet coefficient denoising function to obtain denoised wavelet coefficients. The inverse wavelet transform unit is used to perform inverse wavelet transform on the denoised wavelet coefficients to obtain the denoised IMF components.

8. A sensor-based dynamic compaction monitoring system according to claim 7, characterized in that, In the threshold calculation unit, the threshold calculation formula is: in, For the threshold, For noise intensity parameters, The length of the IMF signal. This represents the median of all wavelet coefficients at the first-level decomposition scale.

9. A sensor-based dynamic compaction monitoring system according to claim 8, characterized in that, In the denoising function construction unit, the following formula is used: Construct a wavelet coefficient denoising function; where, Represents the wavelet coefficients after denoising. This represents the k-th wavelet coefficient at the j-th decomposition scale. , Indicates the threshold. This represents the adjustment coefficient. Represents a symbolic function.

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