Method and device for monitoring water content of pipeline sludge and electronic equipment

Abstract

The invention provides a monitoring method and device for the water content of pipeline sludge and electronic equipment, and relates to the field of data processing. The method comprises the following steps: acquiring capacitance tomography data and ultrasonic tomography data for a target pipeline; analyzing the capacitance tomography data and the ultrasonic tomography data by adopting a linear back projection algorithm to obtain a moisture content distribution matrix for a target section of the target pipeline; constructing a three-dimensional moisture field model according to the moisture content distribution matrixes corresponding to the target sections; based on the three-dimensional moisture field model, a target abnormal point location is determined, and the target abnormal point location is a point location which does not meet the sludge moisture content index in a plurality of point locations included in the target pipeline; and according to the target abnormal point location, a water supplementing strategy of the climbing robot is determined, and the climbing robot is installed on the target pipeline. By implementing the technical scheme provided by the invention, the water content of the sludge in the pipeline can be conveniently monitored in real time, so that the water distribution of the sludge in the conveying pipeline can be accurately mastered, and effective regulation and control can be implemented.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular to a method, device and electronic equipment for monitoring the moisture content of pipeline sludge. Background Art

[0002] In sludge incineration systems at wastewater treatment plants and sewage treatment stations, sludge moisture content is a key parameter affecting incineration efficiency and energy consumption. Excessively high moisture content can lead to a drop in furnace temperature and incomplete combustion, while excessively low moisture content can easily cause furnace overheating, slagging, and even equipment damage. Therefore, to ensure stable operation of the incineration system, it is necessary to monitor the moisture content of the sludge in the pipelines.

[0003] Currently, most related technologies rely on single-point sampling and testing, online weighing specific humidity, microwave detection and other means, which can only obtain the average moisture content data at the pipeline inlet, and cannot achieve a global perception of the distributed and dynamic moisture status of the sludge during transportation. This coarse-grained monitoring method easily leads to the neglect of abnormal conditions such as local uneven dryness and wetness, thereby causing fluctuating interference to the reaction process in the furnace. In addition, existing solutions generally lack closed-loop control methods for precise regulation based on monitoring results. Usually, water replenishment can only be achieved through manual or extensive pipe spraying, which is both inefficient and unable to accurately deliver water to actual water-scarce areas.

[0004] Therefore, how to accurately grasp the moisture distribution of sludge in the transportation pipeline and implement effective regulation is an urgent problem that needs to be solved. Summary of the Invention

[0005] The present application provides a method, device and electronic equipment for monitoring the moisture content of pipeline sludge, which facilitates real-time monitoring of the moisture content of pipeline sludge, so as to accurately grasp the moisture distribution of sludge in the transportation pipeline and implement effective regulation.

[0006] In a first aspect of the present application, a method for monitoring the moisture content of pipeline sludge is provided, the method comprising: obtaining capacitance tomography data and ultrasonic tomography data for a target pipeline; using a linear back-projection algorithm to analyze the capacitance tomography data and the ultrasonic tomography data to obtain a moisture content distribution matrix for a target section of the target pipeline; constructing a three-dimensional moisture field model based on the moisture content distribution matrices corresponding to a plurality of target sections; determining a target abnormal point based on the three-dimensional moisture field model, the target abnormal point being a point among a plurality of points included in the target pipeline that does not meet the sludge moisture content index; and determining a water replenishment strategy for a climbing robot based on the target abnormal point, the climbing robot being installed on the target pipeline.

[0007] By employing the aforementioned technical solution, integrating electrical capacitance tomography (ECT) and ultrasonic tomography (UTT), the system achieves the joint sensing and spatial distribution of moisture content across multiple sections within a sludge conveying pipeline. This effectively overcomes the difficulty of traditional single-point measurement and average assessment in capturing the spatially heterogeneous nature of sludge moisture content. By analyzing and reconstructing the imaging data using a linear back-projection algorithm, not only does it improve measurement accuracy and resolution, but it also enables a visual representation of the moisture content distribution in matrix form. This allows the construction of a three-dimensional moisture field model with practical engineering significance based on the multi-section data, providing the foundation for subsequent accurate identification of abnormally dry areas. Furthermore, based on this model, the system automatically determines which points do not meet the set moisture content threshold and generates the optimal water replenishment path and strategy accordingly. This enables the efficient and precise operation of a climbing robot mounted on the outer wall of the pipeline, achieving integrated closed-loop control. This facilitates real-time monitoring of the sludge moisture content within the pipeline, enabling precise understanding and effective regulation of the sludge moisture distribution within the conveying pipeline. This significantly enhances the automation, intelligence, and operational stability of the incineration system.

[0008] Optionally, acquiring capacitance tomography data and ultrasonic tomography data for the target pipeline specifically includes: controlling a high-frequency electrode arranged in a ring outside the target pipeline to excite the target pipeline with a capacitance signal; receiving an echo signal of the target pipeline after the capacitance signal excitation; determining a change in dielectric constant based on the echo signal; and performing two-dimensional image inversion on the change in dielectric constant using an iterative optimization algorithm with regularization to obtain the capacitance tomography data.

[0009] By adopting the above technical solution, the sludge medium is stimulated by non-contact capacitance signals through a high-frequency electrode array arranged in a ring outside the target pipeline, thereby obtaining its internal dielectric characteristic response, which has good adaptability and feasibility. As a non-destructive testing technology based on the change of dielectric constant to reflect the internal structural differences of the material, capacitance imaging can achieve real-time online monitoring without destroying the pipeline structure or interfering with the normal transportation of sludge. By receiving the capacitance echo signal after excitation and further extracting the dielectric constant change information closely related to the water content, the physical property differences between water and other solid components in the sludge can be accurately identified. The image inversion processing of the dielectric constant change value combined with the regularized iterative optimization algorithm can effectively suppress the common artifacts and noise interference in the traditional inversion process, enhance the stability and resolution of image reconstruction, and thus obtain high-quality, engineering-oriented capacitance tomography image data.

[0010] Optionally, the acquiring of capacitance tomography data and ultrasonic tomography data for the target pipeline further includes: controlling an ultrasonic transducer array installed outside the target pipeline to transmit a broadband ultrasonic pulse signal to the target pipeline; receiving a reflected signal of the target pipeline after being irradiated by the broadband ultrasonic pulse signal; determining a regional sound velocity and an attenuation value corresponding to the reflected signal; and based on the multiphase medium propagation characteristics of the sludge in the target pipeline, combining the regional sound velocity and the attenuation value, imaging the radial and axial distribution of water in the target pipeline to obtain the ultrasonic tomography data.

[0011] By employing the above-mentioned technical solution, an ultrasonic transducer array is positioned outside the target pipeline and controlled to emit broadband ultrasonic pulse signals, enabling non-destructive acoustic testing of sludge inside the pipeline with high penetration and resolution accuracy. As broadband ultrasonic pulses pass through sludge, a typical multiphase medium, their propagation velocity and energy attenuation are significantly affected by the distribution of moisture, solid particles, and bubbles within the medium. Therefore, by receiving and analyzing the reflected signals, the sound velocity and attenuation characteristic parameters of different regions can be accurately determined. Since increased moisture content typically leads to a decrease in regional sound velocity and increased attenuation, this technology establishes a physical correlation model based on the acoustic propagation characteristics of the sludge medium. Combined with the sound velocity and attenuation values ​​extracted from the reflected signals, this technology can perform spatial inversion imaging of the radial and axial distribution of moisture within the pipeline cross-section, generating physically meaningful ultrasonic tomographic data. Compared to traditional single-point or average-value monitoring methods, this method not only offers the advantages of non-contact, strong real-time performance, and high imaging accuracy, but also effectively identifies localized areas of abnormal moisture content, enabling early detection and precise identification of uneven moisture content during transportation.

[0012] Optionally, the linear back-projection algorithm is used to analyze the capacitance tomography data and the ultrasonic tomography data to obtain a water content distribution matrix for a target cross section of the target pipeline, specifically comprising: scanning the target pipeline using a scanning device to generate a pipeline cross-section geometric model; calibrating the geometric positions and sensitivity weights of the high-frequency electrode and the ultrasonic transducer array on the pipeline cross-section geometric model; determining a geometric weight based on the geometric positions and the sensitivity weights; determining a capacitance excitation signal strength and a corresponding received signal strength of a target frame, as well as an ultrasonic transmission signal amplitude and a corresponding received signal amplitude of the target frame based on the capacitance tomography data and the ultrasonic tomography data, wherein the target frame is any identical frame of the capacitance tomography data and the ultrasonic tomography data; based on the capacitance excitation signal strength and the corresponding received signal strength of the target frame, as well as the ultrasonic transmission signal amplitude and the corresponding received signal amplitude of the target frame, back-projecting the target channel result onto the corresponding target cross section according to a preset ratio using the geometric weight; and accumulating multiple target channel results and performing normalization processing to obtain a water content distribution matrix for the target cross section of the target pipeline.

[0013] By employing this technical solution, a geometric model of the target pipeline cross section is established using a scanning device. The geometric positions and sensitivity weights of the high-frequency electrodes and ultrasonic transducer array are precisely calibrated on this model, providing a geometric basis and weighting parameters for subsequent signal backprojection. Subsequently, the capacitive excitation signal strength, received signal strength, and ultrasonic transmit and receive signal amplitudes at specific frames are simultaneously acquired in a unified coordinate system to ensure temporal and spatial consistency of the imaging data. Using these geometric weights, the fused signal is backprojected onto the corresponding cross section at a preset ratio, effectively mapping the one-dimensional projection data into a two-dimensional spatial distribution map, significantly improving information restoration and local feature resolution. By accumulating and normalizing the results from multiple projection channels, a high-resolution distribution matrix representing the moisture content of the sludge in the target pipeline is ultimately obtained. This method achieves physically consistent fusion of multi-source data while maintaining computational efficiency, enabling clear visualization of localized dry-wet anomalies. This method provides a precise data foundation and reliable spatial support for subsequent three-dimensional moisture field construction and water replenishment strategy formulation, effectively addressing the shortcomings of existing technologies in spatial recognition, data alignment, and image restoration.

[0014] Optionally, determining the target abnormal point based on the three-dimensional moisture field model specifically includes: determining a plurality of voxels according to the three-dimensional moisture field model; obtaining the moisture value corresponding to each of the voxels; traversing from the plurality of the voxels to determine the target voxel whose moisture value exceeds the moisture range corresponding to the sludge moisture content index; determining the target abnormal point according to the coordinate position of the target voxel in the three-dimensional moisture field model, the target abnormal point including the pipeline segment number and the cross-sectional angle position.

[0015] By employing the aforementioned technical solution, this technology divides the entire pipeline interior into multiple small volume units (voxels) and obtains the moisture value corresponding to each voxel, resulting in a granular, digital representation of moisture distribution in three-dimensional space. This avoids the omission of critical areas or ambiguity in positioning caused by data averaging or local sampling in traditional methods. Furthermore, the system compares the moisture value voxel by voxel against the allowable range of the sludge moisture content indicator, automatically identifying target voxels that exceed the preset threshold (either too dry or too wet), ensuring comprehensive and sensitive anomaly identification. Furthermore, by combining the precise coordinates of each target voxel in the 3D model, anomalies can be precisely pinpointed to specific pipeline segment numbers and cross-sectional angles, achieving an efficient closed-loop process from "problem discovery" to "precise location." This method provides a clear target and path for developing targeted control strategies for subsequent water replenishment devices (such as crawling robots), significantly improving the accuracy and efficiency of intelligent water replenishment. It also provides deeper and more valuable spatial perception capabilities for remote system monitoring, trend warnings, and maintenance planning.

[0016] Optionally, the water replenishment strategy of the climbing robot is determined according to the target abnormal point, specifically including: based on the pipeline segment number and the cross-sectional angle position, controlling the climbing robot to go to the target abnormal point in an odometer plus magnetic encoder driving mode and / or a crawler crawling mode; determining the volume of the abnormal voxel group corresponding to the target abnormal point according to the three-dimensional moisture field model; determining the water replenishment amount according to the abnormal voxel group volume, and generating a water replenishment strategy; controlling the microfluidic injector of the climbing robot to inject the water replenishment amount into the target abnormal point according to the water replenishment strategy.

[0017] By employing this technical solution, a dynamic response system with autonomous navigation and precise water replenishment capabilities was constructed by integrating anomaly points identified in a three-dimensional moisture field model with an intelligent climbing robot. This significantly improves the efficiency of water balance control during sludge transportation. Specifically, based on the identified pipeline segment number and cross-sectional angular position, the system drives the climbing robot to the target anomaly point using either an odometer and magnetic encoder or crawler-type motion. This ensures stable movement within complex, curved, or slippery pipelines while maintaining accurate motion paths and environmental adaptability, overcoming the limitations of traditional manual or fixed devices in positioning response and flexible execution. The system then quantifies the amount of water required based on the volume of the anomaly voxel cluster at the target point, enabling a personalized water replenishment strategy to ensure neither over- nor under-replenishment, further improving resource utilization efficiency and control accuracy. By controlling the robot's integrated microfluidic injector to perform water replenishment operations, the system can deliver high-precision, small-dose, targeted injections at specific locations, effectively addressing the uneven coverage and significant side effects of conventional spraying and humidification methods.

[0018] Optionally, the method also includes: during the process of water injection of the climbing robot, obtaining real-time humidity change data sent by a near-infrared small moisture sensor located on the climbing robot; determining the moisture adjustment value of the target abnormal point after water injection based on the real-time humidity change data; if it is determined that the moisture adjustment value meets the sludge moisture content index, controlling the climbing robot to stop water injection.

[0019] By adopting this technical solution, the near-infrared moisture sensor boasts advantages such as small size, fast response, non-contact operation, and high sensitivity. It continuously collects humidity change data near the target point during the water injection process and transmits this data in real time to the central control unit. Based on the dynamic data stream provided by the sensor, the system quickly determines whether the current water injection has achieved the desired adjustment effect, namely, whether the moisture content in the target area has reached the established sludge moisture index. By analyzing the moisture change trend before and after water injection, the system can instantly calculate the moisture adjustment value. If the adjustment value meets the index requirement, the control command is automatically triggered, instructing the robot to stop the water injection operation, effectively avoiding the "over-injection" or "under-injection" problems that exist in traditional quantitative water injection methods.

[0020] In a second aspect of the present application, a monitoring device for the moisture content of pipeline sludge is provided, the monitoring device including an acquisition module and a processing module, wherein the acquisition module is used to acquire capacitance tomography data and ultrasonic tomography data for a target pipeline; the processing module is used to analyze the capacitance tomography data and the ultrasonic tomography data using a linear back-projection algorithm to obtain a moisture content distribution matrix for a target section of the target pipeline; the processing module is also used to construct a three-dimensional moisture field model based on the moisture content distribution matrices corresponding to multiple target sections; the processing module is also used to determine a target abnormal point based on the three-dimensional moisture field model, the target abnormal point being a point among multiple points included in the target pipeline that does not meet the sludge moisture content index; the processing module is also used to determine a water replenishment strategy for a climbing robot based on the target abnormal point, wherein the climbing robot is installed on the target pipeline.

[0021] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device performs the method described above.

[0022] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions. When the instructions are executed, the method described above is executed.

[0023] In summary, one or more technical solutions provided in this application have at least the following technical effects or advantages: By integrating electrical capacitance tomography (ECT) and ultrasonic tomography (UTT), the system achieves joint sensing and spatial distribution of moisture content across multiple sections within a sludge conveying pipeline. This effectively overcomes the difficulty of traditional single-point measurement and average assessment in capturing the spatially heterogeneous nature of sludge moisture content. By analyzing and reconstructing the imaging data using a linear back-projection algorithm, not only does it improve measurement accuracy and resolution, but it also enables a visual representation of the moisture content distribution in matrix form. This allows for the construction of a three-dimensional moisture field model with practical engineering significance based on the multi-section data, providing the foundation for subsequent accurate identification of abnormally dry areas. Furthermore, based on this model, the system automatically determines which points do not meet a set moisture content threshold and generates optimal water replenishment paths and strategies accordingly. This system then drives a climbing robot mounted on the outer wall of the pipeline to operate efficiently and accurately, achieving integrated closed-loop control. This facilitates real-time monitoring of pipeline sludge moisture content, enabling precise understanding and effective regulation of sludge moisture distribution within the pipeline, significantly enhancing the automation, intelligence, and operational stability of the incineration system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 A flow chart of a method for monitoring the water content of pipeline sludge provided in an embodiment of the present application; Figure 2 Another schematic flow chart of a method for monitoring the moisture content of pipeline sludge provided in an embodiment of the present application; Figure 3 A schematic diagram of a module of a device for monitoring the moisture content of pipeline sludge provided in an embodiment of the present application; Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0025] Explanation of the reference numerals: 31, acquisition module; 32, processing module; 41, processor; 42, communication bus; 43, user interface; 44, network interface; 45, memory. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0027] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0028] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0029] In systems involving sludge incineration, such as waste treatment plants and sewage treatment stations, sludge moisture content is a critical parameter affecting incineration efficiency, calorific value utilization, and energy consumption control. High sludge moisture content not only leads to a drop in incinerator temperature and reduced combustion efficiency, but can also cause incomplete combustion and increased flue gas treatment pressure. Low moisture content, on the other hand, can lead to excessively high furnace temperatures, further causing slagging, corrosion, and even damage to incineration equipment. Therefore, to ensure the efficient, stable, and safe operation of incineration systems, real-time and accurate monitoring and control of the sludge moisture content within the delivery pipeline is crucial.

[0030] However, the currently widely used technical means, such as single-point sampling and testing, online weighing specific humidity or microwave detection, are mostly limited to obtaining the overall average moisture content value at the pipeline inlet, and cannot reflect the dynamic changes in the spatial distribution of sludge along the pipeline during the entire transportation process. This coarse-grained, single-point monitoring mode makes it difficult to capture local dry-wet differences, and it is very easy to cause areas with uneven moisture content to be ignored, making the state of sludge entering the incinerator unstable, and thus causing fluctuations in the combustion process. At the same time, most current systems are still at the stage of manual experience adjustment or overall water spraying in the control link. They lack a response mechanism for monitoring results and intelligent closed-loop control capabilities, and cannot achieve targeted water replenishment or adjustment, resulting in waste of resources and low control efficiency.

[0031] Therefore, there is an urgent need for a technical solution that can achieve high-precision, distributed monitoring of the moisture content of sludge in the transportation pipeline, and can intelligently identify abnormal areas based on the detection results and implement refined regulation, so as to fundamentally improve the safety, controllability and operational efficiency of the incineration process.

[0032] In order to solve the above technical problems, this application provides a method for monitoring the water content of pipeline sludge, referring to Figure 1 , Figure 1 This is a flow chart of a method for monitoring the water content of pipeline sludge provided in an embodiment of the present application. The monitoring method is applied to a server and includes steps S110 to S150, which are as follows: S110 : Acquire capacitance tomography data and ultrasonic tomography data for the target pipeline.

[0033] Specifically, the server, acting as a central control and processing unit, acquires two key types of data reflecting the moisture status of the sludge within the pipeline from a variety of sensor devices deployed outside the pipeline: electrical capacitance tomography (ECT) data and ultrasonic tomography (UTT) data. ECT is a non-contact imaging method that reflects moisture differences based on changes in the dielectric constant distribution within the pipeline. It is suitable for detecting changes in the dielectric properties of sludge at different locations, thereby indirectly inferring its moisture distribution. Ultrasonic tomography, on the other hand, acquires information on the internal structure and moisture distribution of the sludge by transmitting ultrasonic waves into the pipeline and receiving the echo characteristics (such as changes in sound velocity and attenuation intensity) after propagation through a multiphase medium. By collecting and integrating these two types of data, the server provides the raw supporting data for subsequent moisture content calculations and three-dimensional reconstruction.

[0034] In one possible embodiment, obtaining capacitance tomography data and ultrasonic tomography data for a target pipeline specifically includes: controlling a high-frequency electrode arranged in a ring outside the target pipeline to excite the target pipeline with a capacitance signal; receiving an echo signal from the target pipeline after the capacitance signal excitation; determining a change in dielectric constant based on the echo signal; and performing two-dimensional image inversion of the change in dielectric constant using an iterative optimization algorithm with regularization to obtain capacitance tomography data.

[0035] Specifically, the server controls a ring-shaped high-frequency electrode array positioned outside the target pipeline, transmitting capacitance signals into the pipe through these electrodes. Upon contact with the sludge within the pipe, the capacitance signal changes based on the sludge's dielectric constant (closely related to moisture content). This change affects the signal's echo intensity and characteristics. The server then receives the echo signal from the pipe after the capacitance signal passes through the sludge and calculates the change in the sludge's dielectric constant based on these echo signals. Using these changes, the server converts them into a two-dimensional image using an iterative optimization algorithm with regularization, generating capacitance tomography data that displays moisture distribution in different areas within the pipe.

[0036] For example, in a sewage treatment plant, the moisture content of the sludge in the conveying pipeline needs to be precisely controlled. In this case, a ring-shaped high-frequency electrode array is installed on the outer wall of the pipeline. After the electrode transmits a capacitance signal, the echo signal generated by the interaction between the signal and the moisture in the sludge is received and analyzed. The server calculates the change in the signal echo to obtain the change in the dielectric constant of the sludge, which reflects the amount of moisture in the sludge. These change values ​​are then processed using a regularized iterative optimization algorithm to generate a two-dimensional capacitance tomography image, which helps operators visualize the moisture distribution in various areas of the pipeline. This method can monitor the moisture status of the sludge in real time, ensuring that the server can make precise adjustments based on actual conditions.

[0037] In one possible embodiment, obtaining capacitance tomography data and ultrasonic tomography data for a target pipeline specifically includes: controlling an ultrasonic transducer array installed outside the target pipeline to transmit a broadband ultrasonic pulse signal to the target pipeline; receiving a reflected signal from the target pipeline after being irradiated by the broadband ultrasonic pulse signal; determining a regional sound velocity and attenuation value corresponding to the reflected signal; and imaging the radial and axial distribution of water in the target pipeline based on the multiphase medium propagation characteristics of the sludge in the target pipeline in combination with the regional sound velocity and attenuation value to obtain ultrasonic tomography data.

[0038] Specifically, the server first controls an ultrasonic transducer array installed outside the pipeline. These transducer arrays are responsible for emitting broadband ultrasonic pulse signals into the pipeline. As they pass through the pipeline and sludge, the ultrasonic pulse signals are affected by the different media, particularly the sludge's moisture content, density, and internal structure. These signals are reflected by the sludge. After receiving these reflected signals, the server further analyzes the regional sound velocity (i.e., the speed at which sound waves propagate through the medium) and attenuation (i.e., the degree of signal attenuation) contained in the reflected signals. By analyzing these parameters, combined with the propagation characteristics of sludge as a multiphase medium, the server can accurately determine the radial and axial distribution of moisture within the pipeline, thereby obtaining ultrasonic tomographic imaging data that demonstrates the spatial distribution of moisture within the pipeline.

[0039] For example, in a sludge treatment process, sludge is transported to an incinerator through a long pipeline. To ensure uniform moisture content in the sludge and prevent excessively high or low moisture levels from affecting the incineration process, an ultrasonic transducer array is installed on the outside of the pipeline, periodically emitting broadband ultrasonic pulse signals. After penetrating the sludge, these signals are reflected back by different moisture areas inside the pipeline. The server analyzes the sound velocity and attenuation characteristics of the reflected signals to obtain the sound velocity and attenuation values ​​for each area, and based on this information, accurately maps the moisture distribution of the sludge. This ultrasonic imaging technology can provide a detailed distribution of the moisture status inside the pipeline, helping operators monitor and adjust the moisture status in real time to ensure optimal sludge treatment throughout the incineration process.

[0040] S120. Analyze the capacitance tomography data and the ultrasonic tomography data using a linear back-projection algorithm to obtain a moisture content distribution matrix for a target cross section of the target pipeline.

[0041] Specifically, first, capacitance tomography and ultrasonic tomography provide raw data on the moisture content of sludge in the pipeline, including the dielectric constant and acoustic properties of the sludge, such as sound velocity and attenuation values. The server processes this data using a linear back-projection algorithm, which is a mathematical method for back-projecting the signal to the target area. Through this method, the system can reconstruct a two-dimensional or three-dimensional moisture distribution map from the signal reflection data of multiple acquisition points, which specifically reflects the moisture content at different locations in the pipeline cross-section. Finally, these back-projection data are integrated into a moisture content distribution matrix of the target cross-section, which can clearly show the moisture status of each location in the pipeline.

[0042] In one possible embodiment, a linear back-projection algorithm is used to analyze capacitance tomography data and ultrasonic tomography data to obtain a water content distribution matrix for a target cross section of a target pipeline. The method specifically includes: scanning the target pipeline using a scanning device to generate a pipeline cross-section geometric model; calibrating the geometric positions and sensitivity weights of the high-frequency electrodes and ultrasonic transducer array on the pipeline cross-section geometric model; determining a geometric weight based on the geometric positions and sensitivity weights; determining the capacitance excitation signal strength and the corresponding received signal strength of a target frame, as well as the ultrasonic transmission signal amplitude and the corresponding received signal amplitude of the target frame based on the capacitance tomography data and the ultrasonic tomography data, where the target frame is any identical frame in the capacitance tomography data and the ultrasonic tomography data; back-projecting the capacitance excitation signal strength and the corresponding received signal strength of the target frame, as well as the ultrasonic transmission signal amplitude and the corresponding received signal amplitude of the target frame, onto the corresponding target cross section according to a preset ratio using the geometric weights to obtain a target channel result; and accumulating multiple target channel results and performing normalization processing to obtain a water content distribution matrix for the target cross section of the target pipeline.

[0043] Specifically, the scanning device first scans the target pipe, acquiring data on its geometry and generating a precise geometric model of the pipe's cross-section. This step determines the pipe's shape and dimensions, which are crucial for subsequent analysis. For example, suppose the target pipe is circular and transports sludge. The scanning device can use laser scanning or CT technology to generate the pipe's detailed geometry, including information such as diameter, wall thickness, and bends.

[0044] Next, the positions of the high-frequency electrodes and ultrasonic transducer arrays need to be calibrated on this geometric model. Each electrode and ultrasonic transducer may be located differently on the pipeline, so their geometric positions need to be precisely calibrated. Furthermore, the sensitivity weight of each device—that is, its ability to respond to signals—must be considered. Different devices may have different response sensitivities at different locations, so calibrating the sensitivity weights is a key step in ensuring data accuracy. For example, several high-frequency electrodes and ultrasonic transducer arrays are installed outside the pipeline. These devices emit capacitance signals and ultrasonic pulse signals, respectively. After propagating through the sludge, the signals are received. Each electrode and ultrasonic transducer has different sensitivities, and calibration is required to quantify their sensitivity to the signal. For example, a transducer may receive a stronger echo signal on the outside of the pipeline, while a transducer near the center of the pipeline may receive a weaker signal. Calibrated sensitivity weights help correctly decode the signals.

[0045] After acquiring the signal, the server analyzes the capacitance excitation signal strength and received signal strength, as well as the ultrasonic transmission signal amplitude and received signal amplitude, for each target frame. When capacitance and ultrasonic signals propagate through the pipeline, their strength is affected by the moisture content, and the signal strength can reflect changes in moisture content within the pipeline. Geometric weights are determined based on the aforementioned calibration information and the propagation characteristics of the signal to compensate for differences in signals at different locations, thereby ensuring the accuracy of the back-projection algorithm. For example, if the capacitance signal intensity at a certain location is very high, it indicates that the moisture content at that location may be high. Conversely, if the signal intensity is low, it may indicate that the moisture content at that location is low. In this way, the approximate moisture distribution can be inferred. Geometric weights help correct errors caused by factors such as signal attenuation and reflection during signal transmission.

[0046] Next, the capacitance and ultrasonic signal data are back-projected onto the pipe cross section using a linear back-projection algorithm. This is an image reconstruction process, in which the linear back-projection algorithm maps the influence of each signal point onto the target pipe cross section based on signal strength and geometric position. In this way, the moisture information in the signal is "reconstructed" into a moisture distribution map for the pipe cross section. These results mapped onto the pipe cross section are then accumulated and normalized to ultimately produce a moisture distribution matrix. For example, if the capacitance signal intensity is higher at a certain location, the linear back-projection algorithm will distribute the influence of this signal to the corresponding area of ​​the target cross section, thereby inferring the moisture content in that area. This process not only calculates the influence of a single signal but also comprehensively considers the contributions of multiple samples and multiple signals, ultimately resulting in a complete moisture distribution matrix representing the moisture content at each location in the pipe.

[0047] This method not only allows the server to obtain moisture information from multiple signal sources but also accurately calculates the moisture content of each area across the pipe cross section. This is crucial for precise pipeline monitoring and moisture regulation, especially in applications such as incineration where strict moisture control is required. It effectively prevents incineration efficiency degradation and equipment damage caused by uneven moisture content.

[0048] S130. Construct a three-dimensional moisture field model according to the moisture content distribution matrices corresponding to the multiple target sections.

[0049] Specifically, the process involves integrating the moisture distribution matrices at multiple target sections (cross sections at different locations in the pipeline) to construct a complete three-dimensional moisture field model. First, the server uses the moisture distribution matrix data for multiple sections. The moisture information for each section is obtained from electrical capacitance tomography and ultrasonic tomography data. By integrating and analyzing this data, a three-dimensional model is constructed that reflects the moisture distribution at different locations throughout the pipeline. This 3D model accurately displays changes in moisture content within the pipeline, helping to monitor the transportation status of sludge in the pipeline and providing accurate data support for subsequent moisture regulation and control.

[0050] For example, suppose the target pipeline has different moisture contents at different locations (such as different sections or cross-sections of the pipeline). By analyzing the capacitance and ultrasonic data at these locations, a moisture distribution matrix is ​​obtained for each cross-section. For example, the moisture content may be higher at the pipeline inlet and lower in the middle section. By combining the moisture content matrices of these cross-sections, the server can construct a complete moisture field model in three-dimensional space. This means that the operator not only knows the moisture content at each location, but can also see how these moisture contents are distributed along the radial and axial directions of the pipeline. This helps to further analyze and adjust the moisture status of the entire pipeline, thereby improving the efficiency of sludge transportation and the stability of the incineration system.

[0051] S140 . Determine a target abnormal point based on the three-dimensional moisture field model. The target abnormal point is a point that does not meet the sludge moisture content index among multiple points included in the target pipeline.

[0052] Specifically, the server locates abnormal points in the pipeline where the sludge moisture content does not meet the standard requirements by analyzing the constructed three-dimensional moisture field model. Specifically, the three-dimensional moisture field model provides the moisture distribution at different locations throughout the pipeline. By analyzing this model, the server filters out points where the moisture content does not meet the preset standards. These points are the so-called target abnormal points. Target abnormal points are usually areas where the moisture content is too high or too low. Such areas may affect incineration efficiency, cause energy waste, or even cause damage to equipment. Therefore, by locating these abnormal points, the moisture status in the pipeline can be adjusted in a timely manner, thereby ensuring the efficiency and safety of the entire sludge treatment process.

[0053] In a possible implementation, based on a three-dimensional moisture field model, a target abnormal point is determined, specifically including: determining a plurality of voxels according to the three-dimensional moisture field model; obtaining the moisture value corresponding to each voxel; traversing from the plurality of voxels to determine a target voxel whose moisture value exceeds the moisture range corresponding to the sludge moisture content index; and determining the target abnormal point according to the coordinate position of the target voxel in the three-dimensional moisture field model, the target abnormal point including the pipeline segment number and the cross-sectional angle position.

[0054] Specifically, first, the three-dimensional moisture field model is divided into multiple voxels, each voxel corresponds to a small area inside the pipe, and the moisture content of the area is recorded. The server traverses these voxels and checks whether the moisture value of each voxel exceeds the preset sludge moisture content standard range (for example, the set moisture range is 40% to 60%). If the moisture values ​​of some voxels do not meet the standards, these voxels will be marked as target voxels. Finally, based on the coordinate information of the target voxels in the model (including the pipeline segment number and cross-sectional angle position), the server can accurately determine these non-standard abnormal points and provide data support for the subsequent water replenishment strategy formulation.

[0055] For example, suppose the pipeline is divided into multiple sections, and each section is further divided into many voxels. For each voxel, the server will obtain the moisture value of the area. For example, if the moisture value of a voxel is 35%, which is outside the normal range of 40% to 60%, the server will mark this voxel as a target voxel. The server will then find all target voxels that do not meet the standards and record their locations in the 3D model, such as the third section of the pipeline, where the cross-sectional angle is 45 degrees. Through this coordinate information, the server can accurately locate the specific locations in the pipeline where problems exist, making it easier to take targeted control measures (such as water replenishment or drainage).

[0056] S150. Determine a water replenishment strategy for the climbing robot based on the target abnormal point, and install the climbing robot on the target pipeline.

[0057] Specifically, the server analyzes information about the target abnormal points, including the pipeline's segment number, cross-sectional angle, and abnormal moisture values, to determine how much water is needed to replenish these abnormal points. The water replenishment strategy must not only be based on the water requirements of each abnormal point, but also consider the feasibility of actual operations, such as precise control of the water replenishment volume, the water replenishment method (such as a microfluidic syringe), and the time window for water replenishment. In this way, the server can provide the climbing robot with precise action instructions to ensure that water is replenished to the correct location, maintaining the optimal moisture level of the sludge in the pipeline, thereby avoiding incineration efficiency issues or equipment damage caused by excessive or insufficient water.

[0058] In one possible embodiment, the water replenishment strategy of the climbing robot is determined according to the target abnormal point, specifically including: based on the pipeline segment number and cross-sectional angle position, controlling the climbing robot to go to the target abnormal point by odometer plus magnetic encoder driving mode and / or track crawling mode; determining the volume of the abnormal voxel group corresponding to the target abnormal point according to the three-dimensional moisture field model; determining the water replenishment amount according to the abnormal voxel group volume, and generating a water replenishment strategy; controlling the microfluidic injector of the climbing robot to inject the water replenishment amount to the target abnormal point according to the water replenishment strategy.

[0059] Specifically, the server first instructs the climbing robot to proceed to the target location using a specific drive method (such as an odometer plus magnetic encoder or crawler-type propulsion) based on the pipeline segment number and cross-sectional angle information provided by the target anomaly. The odometer plus magnetic encoder drive method enables precise movement within the pipeline, while the crawler-type propulsion method is suitable for stable movement in complex environments. Using these methods, the climbing robot reaches the target anomaly location, ensuring precise positioning and preparation for the water replenishment mission.

[0060] Next, based on the 3D moisture field model, the server calculates the volume of the abnormal voxel cluster at the target anomaly point. These voxels represent areas with abnormal moisture content. Using this volume data, the server accurately calculates the amount of water required for replenishment. Once the replenishment amount is determined, the server generates a replenishment strategy, instructing the climbing robot to use its microfluidic syringe to precisely inject water into the target point.

[0061] For example, if the moisture content is too low at a 30-degree section in the second section of a pipe, the server will direct the robot to that exact location and inject a preset amount of water, such as 10 ml, into the abnormal area using a syringe. This precise water replenishment strategy ensures that the sludge moisture content reaches the optimal level, preventing the incineration effect from being affected by excessive or insufficient moisture.

[0062] Therefore, by integrating electrical capacitance tomography and ultrasonic tomography, two physical detection methods, a joint sensing and spatial distribution of moisture content across multiple sections within the sludge conveying pipeline is achieved. This effectively overcomes the problem that traditional single-point measurement and average assessment methods fail to reflect the spatially heterogeneous nature of sludge moisture status. By analyzing and reconstructing the imaging data using a linear back-projection algorithm, not only does measurement accuracy and resolution improve, but it also enables a visual representation of the moisture content distribution in matrix form. This allows for the construction of a three-dimensional moisture field model with practical engineering significance based on the multi-section data, providing the foundation for subsequent accurate identification of abnormally dry areas. Furthermore, based on this model, the server automatically determines which points do not meet the set moisture content threshold and generates the optimal water replenishment path and strategy accordingly. This drives the efficient and precise operation of a climbing robot mounted on the outer wall of the pipeline, achieving integrated closed-loop control and facilitating real-time monitoring of pipeline sludge moisture content. This allows for precise understanding and effective regulation of the sludge moisture distribution within the conveying pipeline, significantly enhancing the automation, intelligence, and operational stability of the incineration server.

[0063] In one possible implementation, refer to Figure 2 , Figure 2 Another flow chart of a method for monitoring the moisture content of pipeline sludge provided in an embodiment of the present application includes steps S210 to S230, and the above steps are as follows: S210, during the process of water injection by the climbing robot, obtaining real-time humidity change data sent by a small near-infrared moisture sensor located on the climbing robot; S220, based on the real-time humidity change data, determining the moisture adjustment value of the target abnormal point after water injection; S230, if it is determined that the moisture adjustment value meets the sludge moisture content index, controlling the climbing robot to stop water injection.

[0064] Specifically, while the climbing robot is performing water injection, it is equipped with a small near-infrared moisture sensor that can detect humidity changes at target abnormal points in real time. The near-infrared sensor uses near-infrared light to penetrate the sludge sample and detect changes in moisture content based on changes in reflected light. The sensor continuously monitors humidity changes and transmits this data to a server or control server. Based on this real-time humidity change data, the server can adjust the water injection volume and frequency in real time to ensure that the water injection operation is carried out within the precise moisture range.

[0065] For example, suppose the humidity at a certain section of the target pipeline is detected to be too low, requiring water replenishment. The climbing robot begins injecting water, while the near-infrared sensor continuously provides feedback on humidity changes. When the humidity at the target point increases to approach the required sludge moisture content, the control server calculates the moisture adjustment value based on real-time data and determines whether the target humidity has been met. If the humidity has reached or exceeded the required level, the server instructs the robot to stop injecting water, thereby avoiding overinjection and ensuring the server's accuracy and efficiency. This real-time adjustment mechanism makes the moisture control process more precise, effectively avoiding errors caused by manual adjustments, and improving the intelligence level of the entire sludge treatment process.

[0066] This application also provides a monitoring device for the water content of pipeline sludge, referring to Figure 3 , Figure 3 A schematic diagram of a module for monitoring the moisture content of sludge in a pipeline provided in an embodiment of the present application. The monitoring device is a server, which includes an acquisition module 31 and a processing module 32. The acquisition module 31 acquires capacitance tomography data and ultrasonic tomography data for a target pipeline; the processing module 32 uses a linear back-projection algorithm to analyze the capacitance tomography data and ultrasonic tomography data to obtain a moisture content distribution matrix for a target cross-section of the target pipeline; the processing module 32 constructs a three-dimensional moisture field model based on the moisture content distribution matrices corresponding to multiple target cross-sections; the processing module 32 determines target abnormal points based on the three-dimensional moisture field model, where the target abnormal points are points in the target pipeline that do not meet the sludge moisture content index; the processing module 32 determines a water replenishment strategy for a climbing robot based on the target abnormal points, and the climbing robot is installed on the target pipeline.

[0067] In one possible embodiment, the acquisition module 31 acquires capacitance tomography data and ultrasonic tomography data for the target pipeline, specifically including: the processing module 32 controls the high-frequency electrodes arranged in a ring outside the target pipeline to excite the target pipeline with a capacitance signal; the acquisition module 31 receives the echo signal of the target pipeline after the capacitance signal excitation; the processing module 32 determines the dielectric constant change value based on the echo signal; the processing module 32 performs two-dimensional image inversion on the dielectric constant change value through an iterative optimization algorithm with regularization to obtain capacitance tomography data.

[0068] In one possible embodiment, the acquisition module 31 acquires capacitance tomography data and ultrasonic tomography data for the target pipeline, and specifically also includes: the processing module 32 controls the ultrasonic transducer array installed outside the target pipeline to transmit a broadband ultrasonic pulse signal to the target pipeline; the acquisition module 31 receives the reflected signal of the target pipeline after being irradiated by the broadband ultrasonic pulse signal; the processing module 32 determines the regional sound velocity and attenuation value corresponding to the reflected signal; the processing module 32 images the radial and axial distribution of water in the target pipeline based on the multi-phase medium propagation characteristics of the sludge in the target pipeline, combined with the regional sound velocity and attenuation value, to obtain ultrasonic tomography data.

[0069] In one possible implementation, the processing module 32 uses a linear back-projection algorithm to analyze the capacitance tomography data and the ultrasonic tomography data to obtain a moisture content distribution matrix for the target cross section of the target pipe, specifically including: the processing module 32 scans the target pipe through a scanning device to generate a pipe cross-section geometric model; the processing module 32 calibrates the geometric position and sensitivity weight of the high-frequency electrode and the ultrasonic transducer array on the pipe cross-section geometric model; the processing module 32 determines the geometric weight according to the geometric position and sensitivity weight; the processing module 32 determines the target frame based on the capacitance tomography data and the ultrasonic tomography data. The capacitance excitation signal strength and the corresponding receiving signal strength, as well as the ultrasonic transmission signal amplitude and the corresponding receiving signal amplitude of the target frame, the target frame being any identical frame in the capacitance tomography data and the ultrasonic tomography data; the processing module 32 back-projects the capacitance excitation signal strength and the corresponding receiving signal strength of the target frame, as well as the ultrasonic transmission signal amplitude and the corresponding receiving signal amplitude of the target frame, onto the corresponding target section according to a preset proportion through geometric weights to obtain a target channel result; the processing module 32 accumulates multiple target channel results and performs normalization processing to obtain a water content distribution matrix for the target section of the target pipe.

[0070] In a possible embodiment, the processing module 32 determines the target abnormal point based on the three-dimensional moisture field model, specifically including: the processing module 32 determines multiple voxels according to the three-dimensional moisture field model; the acquisition module 31 obtains the moisture value corresponding to each voxel; the processing module 32 traverses from the multiple voxels to determine the target voxel whose moisture value exceeds the moisture range corresponding to the sludge moisture content index; the processing module 32 determines the target abnormal point according to the coordinate position of the target voxel in the three-dimensional moisture field model, and the target abnormal point includes the pipeline segment number and the cross-sectional angle position.

[0071] In one possible embodiment, the processing module 32 determines the water replenishment strategy of the climbing robot according to the target abnormal point, specifically including: the processing module 32 controls the climbing robot to go to the target abnormal point by odometer plus magnetic encoder driving mode and / or track crawling mode based on the pipeline segment number and cross-sectional angle position; the processing module 32 determines the volume of the abnormal voxel group corresponding to the target abnormal point according to the three-dimensional moisture field model; the processing module 32 determines the water replenishment amount according to the abnormal voxel group volume and generates a water replenishment strategy; the processing module 32 controls the microfluidic injector of the climbing robot to inject the water replenishment amount into the target abnormal point according to the water replenishment strategy.

[0072] In one possible embodiment, during the water injection process of the climbing robot, the acquisition module 31 obtains the real-time humidity change data sent by the near-infrared small moisture sensor located on the climbing robot; the processing module 32 determines the moisture adjustment value of the target abnormal point after water injection based on the real-time humidity change data; if the processing module 32 determines that the moisture adjustment value meets the sludge moisture content index, it controls the climbing robot to stop injecting water.

[0073] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0074] This application also provides an electronic device, referring to Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include: at least one processor 41, at least one network interface 44, a user interface 43, a memory 45, and at least one communication bus 42.

[0075] The communication bus 42 is used to realize the connection and communication between these components.

[0076] The user interface 43 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 43 may also include a standard wired interface and a wireless interface.

[0077] The network interface 44 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0078] The processor 41 may include one or more processing cores. Using various interfaces and circuits, the processor 41 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 45, as well as accesses data stored in the memory 45, to perform various server functions and process data. Optionally, the processor 41 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 41 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may also be implemented as a separate chip, rather than integrated into the processor 41.

[0079] Among them, the memory 45 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 45 includes a non-transitory computer-readable storage medium. The memory 45 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 45 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 45 may also be optionally at least one storage device located away from the aforementioned processor 41. As Figure 4 As shown, the memory 45 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a method for monitoring the water content of pipeline sludge.

[0080] exist Figure 4In the electronic device shown, the user interface 43 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 41 can be used to call an application program stored in the memory 45 for a method for monitoring the moisture content of pipeline sludge. When executed by one or more processors, the electronic device executes one or more methods in the above-mentioned embodiments.

[0081] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0082] The present application also provides a computer-readable storage medium storing instructions, which, when executed by one or more processors, enable an electronic device to execute one or more of the methods described in the above embodiments.

[0083] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0085] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0086] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0087] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0088] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art that are not recorded in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for monitoring the water content of pipeline sludge, characterized in that: The method comprises: Acquiring electrical capacitance tomography data and ultrasonic tomography data for a target pipeline; Using a linear back-projection algorithm, the electrical capacitance tomography data and the ultrasonic tomography data are analyzed to obtain a moisture content distribution matrix for a target cross section of the target pipeline; constructing a three-dimensional moisture field model according to the moisture content distribution matrices corresponding to the plurality of target sections; Determining a target abnormal point based on the three-dimensional moisture field model, where the target abnormal point is a point that does not meet the sludge moisture content index among multiple points included in the target pipeline; According to the target abnormal point, a water replenishment strategy of a climbing robot is determined, and the climbing robot is installed on the target pipeline.

2. The method for monitoring the water content of pipeline sludge according to claim 1, characterized in that: The acquiring of capacitance tomography data and ultrasonic tomography data for the target pipeline specifically includes: controlling a high-frequency electrode arranged in an annular manner outside the target pipeline to perform capacitive signal excitation on the target pipeline; receiving an echo signal of the target pipeline after being excited by the capacitance signal; determining a dielectric constant change value according to the echo signal; The capacitance tomography data is obtained by performing two-dimensional image inversion on the dielectric constant change value through an iterative optimization algorithm with regularization.

3. The method for monitoring the water content of pipeline sludge according to claim 2, characterized in that: The acquiring of capacitance tomography data and ultrasonic tomography data for the target pipeline specifically further includes: controlling an ultrasonic transducer array installed outside the target pipeline to transmit a broadband ultrasonic pulse signal toward the target pipeline; receiving a reflection signal of the target pipe after being irradiated by the broadband ultrasonic pulse signal; Determining the regional sound velocity and attenuation value corresponding to the reflected signal; Based on the multiphase medium propagation characteristics of the sludge in the target pipeline, combined with the regional sound velocity and the attenuation value, the distribution of water in the target pipeline is imaged in the radial and axial directions to obtain the ultrasonic tomography data.

4. The method for monitoring the water content of pipeline sludge according to claim 3, characterized in that: The linear back-projection algorithm is used to analyze the capacitance tomography data and the ultrasonic tomography data to obtain a moisture content distribution matrix for a target cross section of the target pipeline, specifically including: Scanning the target pipeline by a scanning device to generate a pipeline cross-section geometric model; Calibrate the geometric positions and sensitivity weights of the high-frequency electrode and the ultrasonic transducer array on the pipeline cross-section geometric model; determining a geometric weight according to the geometric position and the sensitivity weight; Determining, based on the electrical capacitance tomography data and the ultrasonic tomography data, a capacitance excitation signal strength and a corresponding received signal strength of a target frame, as well as an ultrasonic transmit signal amplitude and a corresponding received signal amplitude of the target frame, the target frame being any identical frame of the electrical capacitance tomography data and the ultrasonic tomography data; Based on the capacitance excitation signal strength and the corresponding received signal strength of the target frame, as well as the ultrasound transmission signal amplitude and the corresponding received signal amplitude of the target frame, back-projecting them onto the corresponding target cross section according to a preset ratio through the geometric weight to obtain a target channel result; The results of the plurality of target channels are accumulated and normalized to obtain a moisture content distribution matrix for the target cross section of the target pipeline.

5. The method for monitoring the water content of pipeline sludge according to claim 1, characterized in that: The determining of target abnormal points based on the three-dimensional moisture field model specifically includes: determining a plurality of voxels according to the three-dimensional moisture field model; Obtaining the moisture value corresponding to each voxel; traversing and determining, from the plurality of voxels, a target voxel whose moisture value exceeds a moisture range corresponding to the sludge moisture content index; The target abnormal point position is determined according to the coordinate position of the target voxel in the three-dimensional moisture field model, and the target abnormal point position includes a pipeline segment number and a cross-sectional angle position.

6. The method for monitoring the water content of pipeline sludge according to claim 5, characterized in that: The determining of the water replenishment strategy of the climbing robot according to the target abnormal point specifically includes: Based on the pipeline segment number and the cross-sectional angle position, the climbing robot is controlled to move toward the target abnormal point in an odometer plus magnetic encoder driving mode and / or a crawler crawling mode; Determining the volume of the abnormal voxel group corresponding to the target abnormal point according to the three-dimensional moisture field model; determining a water replenishment amount according to the volume of the abnormal voxel group and generating a water replenishment strategy; The microfluidic injector of the climbing robot is controlled to inject the replenishing amount of water into the target abnormal point according to the replenishing strategy.

7. The method for monitoring the water content of pipeline sludge according to claim 5, characterized in that: The method further comprises: During the process of injecting water into the climbing robot, real-time humidity change data transmitted by a small near-infrared moisture sensor located on the climbing robot is obtained; Determining the moisture adjustment value of the target abnormal point after water injection based on the real-time humidity change data; If it is determined that the moisture adjustment value meets the sludge moisture content index, the climbing robot is controlled to stop water injection.

8. A monitoring device for the water content of pipeline sludge, characterized in that: The monitoring device comprises an acquisition module (31) and a processing module (32), wherein: The acquisition module (31) is used to acquire capacitance tomography data and ultrasonic tomography data for the target pipeline; The processing module (32) is used to analyze the capacitance tomography data and the ultrasonic tomography data using a linear back-projection algorithm to obtain a water content distribution matrix for a target cross section of the target pipeline; The processing module (32) is further configured to construct a three-dimensional moisture field model based on the moisture content distribution matrices corresponding to the plurality of target sections; The processing module (32) is further configured to determine a target abnormal point based on the three-dimensional moisture field model, wherein the target abnormal point is a point that does not meet the sludge moisture content index among the multiple points included in the target pipeline; The processing module (32) is further used to determine a water replenishment strategy for a climbing robot based on the target abnormal point, wherein the climbing robot is installed on the target pipeline.

9. An electronic device, characterized in that: The electronic device comprises a processor (41), a memory (45), a user interface (43) and a network interface (44), wherein the memory (45) is used to store instructions, the user interface (43) and the network interface (44) are both used to communicate with other devices, and the processor (41) is used to execute the instructions stored in the memory (45) so that the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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