Pipeline robot autonomous charging and energy management method and system

Abstract

The invention relates to the technical field of data processing, and discloses a pipeline robot autonomous charging and energy management method and system.The system comprises a battery unit and a central control module, and the central control module comprises a collecting module, a charging module, a processing module and an adjusting module; the acquisition module determines an interface position coordinate of the pipeline robot based on all target voiceprint signals, and the charging module judges whether to charge the pipeline robot according to the interface position coordinate, the interface target position coordinate and the residual electric quantity of the battery unit, and determines a charging node of the battery unit based on a battery attenuation model; the processing module determines an output voltage adjusting factor of the battery subunit based on the pipeline inflection point, the adjusting module adjusts the output voltage based on the output voltage adjusting factor, and when the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again. According to the invention, the charging autonomy and the energy management efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to an autonomous charging and energy management method and system for a pipeline robot. Background Art

[0002] As an important infrastructure for transporting gas, oil, water and other media, the real-time safety status of pipelines is directly related to the normal operation of industrial production and social life. Pipeline robots are usually used for internal detection of pipelines.

[0003] However, the detection distance of traditional wired pipeline robots is limited due to the length of the power supply cable. In addition, the traditional cable-free pipeline robots increase the weight of the robot itself due to the large-capacity battery, which affects the maneuverability. Once the battery is insufficient, the pipeline robot needs to be disassembled at the pipeline, which is time-consuming and there is a risk of pipeline leakage. Secondly, the continuous full-load operation of the drive wheels will lead to energy waste, and there is a lack of adaptive adjustment of the battery in complex working conditions (curve turning points).

[0004] Therefore, it is necessary to design a pipeline robot autonomous charging and energy management method and system to solve the problems existing in current technology. Summary of the invention

[0005] In view of this, the present invention proposes an autonomous charging and energy management method and system for a pipeline robot, aiming to solve the problem that once the power is insufficient, the pipeline robot needs to be disassembled at the pipeline, which is time-consuming and there is a risk of pipeline leakage, and there is a lack of adaptive adjustment of the battery in complex working conditions (curve turning points).

[0006] In one aspect, the present invention provides an autonomous charging and energy management system for a pipeline robot, comprising: A battery unit and a central control module, wherein the central control module is electrically connected to the battery unit, and the central control module includes a collection module, a charging module, a processing module and an adjustment module; The acquisition module is configured to acquire initial voiceprint signals of at least three voiceprint sensors uniformly deployed on the pipeline robot, preprocess each initial voiceprint signal, determine all target voiceprint signals according to the preprocessing result, determine the interface position coordinates of the pipeline robot based on all target voiceprint signals, and acquire the interface target position coordinates of the wireless power supply device; The charging module is configured to determine whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, and when it is determined that the pipeline robot is to be charged, determine the charging node of the battery unit based on the battery attenuation model; The processing module is configured to acquire multiple pipeline images of the pipeline and perform image processing on the multiple pipeline images to obtain a pipeline merged image of the pipeline when the charging module completes charging based on the charging node or drives based on the remaining power, the battery unit includes a plurality of battery subunits, the output voltage of each battery subunit is determined based on the pipeline merged image, and when the pipeline has a pipeline inflection point and a battery subunit reaches the pipeline inflection point, the output voltage adjustment factor of the battery subunit is determined based on the pipeline inflection point; The adjustment module is configured to adjust the output voltage based on the output voltage adjustment factor, drive the pipeline robot forward according to the adjusted output voltage, and adjust the adjusted output voltage again when the battery subunit leaves the pipeline inflection point.

[0007] Furthermore, when each initial voiceprint signal is preprocessed and all target voiceprint signals are determined according to the preprocessing result, it includes: The acquisition module removes the signal noise of each initial voiceprint signal based on the first preset algorithm of the signal, and performs time-frequency conversion on each initial voiceprint signal after removing the signal noise using the second preset algorithm of the signal; Each initial voiceprint signal after time-frequency conversion is preprocessed, and the preprocessing includes signal compression and signal standardization.

[0008] Furthermore, when determining the interface position coordinates of the pipeline robot based on all target voiceprint signals and acquiring the interface target position coordinates of the wireless power supply device, it includes: The acquisition module establishes a pipeline coordinate system with the center of the pipeline robot as the origin, and determines the interface position coordinates based on triangulation. The interface position coordinates are obtained by the following formula: ; in, represents the position coordinates of the first voiceprint sensor, represents the position coordinates of the second voiceprint sensor, Indicates the location coordinates of the third voiceprint sensor, Indicates the interface position coordinates, Indicates the distance difference between the interface location and the first voiceprint sensor and the second voiceprint sensor. Indicates the distance difference between the interface location and the first voiceprint sensor and the third voiceprint sensor; The interface target position coordinates are determined based on the pipeline coordinate system: .

[0009] Further, when judging whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, it includes: The charging module pre-sets a remaining power threshold and a deviation distance threshold; When the remaining power of the battery unit is greater than the remaining power threshold, determining not to charge the pipeline robot; When the remaining power of the battery unit is less than or equal to the remaining power threshold, determining a deviation distance based on the interface position coordinates and the interface target position coordinates, comparing the deviation distance with the deviation distance threshold, and judging whether to charge the pipeline robot according to the comparison result; The deviation distance is obtained by the following formula: ; in, Indicates the deviation distance, Indicates the interface target location coordinates, Indicates the interface position coordinates; When the deviation distance is less than or equal to the deviation distance threshold, it is determined that the pipeline robot is to be charged; When the deviation distance is greater than the deviation distance threshold, it is determined that the pipeline robot is adjusted based on the interface target position coordinates, and the pipeline robot is charged according to the adjusted interface position coordinates.

[0010] Further, when it is determined that the pipeline robot is to be charged, the charging node of the battery unit is determined based on the battery attenuation model, including: The charging module acquires historical charging data, and constructs a model data set according to the historical charging data, samples the model data set according to a preset ratio to obtain a training set and a test set, uses a grid search to find the establishment parameters of the random forest model, and establishes the random forest model; Fitting the random forest model using the training set, substituting the test set into the random forest model and evaluating it, and obtaining the battery degradation model when the evaluation value reaches a preset evaluation value threshold; Substitute the remaining power of the battery cell into the battery degradation model to determine the charging node of the battery cell.

[0011] Furthermore, when acquiring multiple pipeline images of a pipeline and performing image processing on the multiple pipeline images to obtain a pipeline merged image of the pipeline, it includes: The processing module performs image processing on the multiple pipeline images, wherein the image processing includes geometric correction and adjustment of image contrast; Feature points are extracted from the multiple pipeline images after image processing, and association information between the images is determined according to the RANSAC algorithm, wherein the association information includes relative position and rotation relationship. Based on the association information, the multiple pipeline images after image processing are registered, and the multiple registered pipeline images are merged according to the weighted mean to obtain the pipeline merged image.

[0012] Further, when determining the output voltage of each battery subunit based on the pipeline merged image, it includes: The processing module analyzes the pipeline merged image to determine the inner diameter of the pipeline, and determines the output voltage of each battery subunit according to the inner diameter of the pipeline; The output voltage is given by the following formula: ; in, Indicates the output voltage, and represents the weight coefficient, and , Indicates the inner diameter of the pipe. Represents the friction coefficient between the driving wheels of the pipeline robot and the pipeline.

[0013] Furthermore, when the pipeline has a pipeline inflection point and a battery subunit reaches the pipeline inflection point, determining the output voltage adjustment factor of the battery subunit based on the pipeline inflection point includes: The processing module determines an inflection point image of the inflection point of the pipeline, analyzes the inflection point image, determines a bending radius and a bending angle of the pipeline, and determines an output voltage adjustment factor of the battery subunit according to the bending radius and the bending angle; The output voltage adjustment factor is obtained according to the following formula: ; in, represents the output voltage adjustment factor, represents the bending angle, Indicates the bending radius.

[0014] Further, the output voltage is adjusted based on the output voltage adjustment factor, and the pipeline robot is driven forward according to the adjusted output voltage. When the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again, including: The adjustment module determines a target output voltage according to the output voltage and the output voltage adjustment factor, wherein the target output voltage is a product value of the output voltage and the output voltage adjustment factor; When the battery subunit leaves the pipeline inflection point, the adjustment module restores the target output voltage of the battery subunit to the output voltage.

[0015] Compared with the prior art, the beneficial effects of the present invention are: by obtaining the initial voiceprint signal through multiple voiceprint sensors and determining the target voiceprint signal by preprocessing, the interface position coordinates of the pipeline robot and the interface target position coordinates of the wireless power supply device can be accurately located, thereby improving the accuracy of the charging process. Dynamically determine whether to charge, and combine the battery attenuation model to obtain the charging node, thereby optimizing the charging time and charging efficiency, thereby extending the battery life, while ensuring that the pipeline robot obtains energy, improving autonomy and intelligence, and by obtaining the pipeline image and obtaining the pipeline merged image, the pipeline environment and pipeline inflection point can be accurately determined, thereby adjusting the output voltage of the battery subunit in real time to cope with the energy requirements in different pipeline environments, avoiding the risk of being unable to pass due to insufficient energy, and through secondary adjustments after leaving the pipeline inflection point, further ensuring the efficient operation of the pipeline robot, effectively improving the robot's operating stability and energy management efficiency in a complex pipeline environment.

[0016] On the other hand, the present application also provides a pipeline robot autonomous charging and energy management method, which is applied to the above-mentioned pipeline robot autonomous charging and energy management system, including: Acquire initial voiceprint signals of at least three voiceprint sensors uniformly deployed on the pipeline robot, preprocess each initial voiceprint signal, determine all target voiceprint signals according to the preprocessing result, determine the interface position coordinates of the pipeline robot based on all target voiceprint signals, and acquire the interface target position coordinates of the wireless power supply device; Determining whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, and when it is determined that the pipeline robot is to be charged, determining the charging node of the battery unit based on the battery attenuation model; When charging is completed based on the charging node or driving is performed based on the remaining power, a plurality of pipeline images of the pipeline are acquired, and image processing is performed on the plurality of pipeline images to obtain a pipeline merged image of the pipeline, and an output voltage of each battery subunit is determined based on the pipeline merged image, and when a pipeline inflection point exists in the pipeline and a battery subunit reaches the pipeline inflection point, an output voltage adjustment factor of the battery subunit is determined based on the pipeline inflection point; The output voltage is adjusted based on the output voltage adjustment factor, and the pipeline robot is driven forward according to the adjusted output voltage. When the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again.

[0017] It is understandable that the above-mentioned pipeline robot autonomous charging and energy management method and system have the same beneficial effects, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings: Figure 1 A schematic diagram of the structure of an autonomous charging and energy management system for a pipeline robot provided by an embodiment of the present invention; Figure 2 A flow chart of a pipeline robot autonomous charging and energy management method provided by an embodiment of the present invention; Figure 3 A schematic diagram of the structure of a pipeline robot provided by an embodiment of the present invention; Figure 4 A top view of a pipeline robot provided by an embodiment of the present invention; Figure 5 A three-dimensional schematic diagram of a pipeline robot provided in an embodiment of the present invention.

[0019] In the figure, 1. Robot body; 2. Voiceprint sensor; 3. Interface; 4. Camera; 5. Driving wheel; 6. Central control module; 7. Battery subunit; 10. Front connecting arm; 11. Rear connecting arm. DETAILED DESCRIPTION

[0020] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0021] In some embodiments of the present application, see Figure 1 As shown, a pipeline robot autonomous charging and energy management system includes: The battery unit and the central control module are electrically connected to the battery unit, and the central control module includes a collection module, a charging module, a processing module and an adjustment module.

[0022] The acquisition module is configured to obtain the initial voiceprint signals of at least three voiceprint sensors evenly deployed on the pipeline robot, and preprocess each initial voiceprint signal, determine all target voiceprint signals according to the preprocessing results, determine the interface position coordinates of the pipeline robot based on all target voiceprint signals, and obtain the interface target position coordinates of the wireless power supply device.

[0023] The charging module is configured to determine whether to charge the pipeline robot based on the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit. When it is determined to charge the pipeline robot, the charging node of the battery unit is determined based on the battery attenuation model.

[0024] The processing module is configured to obtain multiple pipeline images of the pipeline and perform image processing on the multiple pipeline images to obtain a pipeline merged image of the pipeline when the charging module completes charging based on the charging node or drives based on the remaining power. The battery unit includes a plurality of battery sub-units. The output voltage of each battery sub-unit is determined based on the pipeline merged image. When there is a pipeline inflection point in the pipeline and a battery sub-unit reaches the pipeline inflection point, the output voltage adjustment factor of the battery sub-unit is determined based on the pipeline inflection point.

[0025] The adjustment module is configured to adjust the output voltage based on the output voltage adjustment factor, drive the pipeline robot forward according to the adjusted output voltage, and adjust the adjusted output voltage again when the battery subunit leaves the pipeline inflection point.

[0026] Specifically, the acquisition module collects the initial voiceprint signal by installing at least three voiceprint sensors on the pipeline robot. The voiceprint sensor can locate the interface position of the pipeline robot by the reflection time of the signal. In the process of acquiring the initial voiceprint signal, some environmental noise or internal noise of the pipeline will interfere with the initial voiceprint signal. After preprocessing each initial voiceprint signal, the interference of noise and other factors can be eliminated, thereby ensuring the accuracy of the target voiceprint signal, and using the target voiceprint signal to calculate the interface position coordinates of the pipeline robot, and then obtain the interface target position coordinates of the wireless power supply device. By determining the interface position coordinates and interface target position coordinates of the pipeline robot, accurate positioning data can be provided for the subsequent charging process. The charging module determines whether the pipeline robot needs to be charged based on the interface position coordinates, interface target position coordinates and the remaining power of the battery unit. If the remaining power does not meet the subsequent drive, it is determined that the pipeline robot needs to be charged, and the charging node of the battery unit is determined based on the battery attenuation model. When charging is completed or the pipeline robot is driven based on the remaining power, the processing module uses a camera to obtain multiple pipeline images in the pipeline and performs image processing to obtain a pipeline merged image of the pipeline. Combined with the pipeline merged image, the processing module will evaluate the spatial structure of the pipeline to calculate the output voltage of each battery subunit (the remaining power of the battery unit represents the sum of the remaining power of each battery subunit). The output voltage of the battery subunit needs to be adjusted according to the geometric structure of the pipeline, especially when there is a pipeline inflection point in the pipeline. The situation of the pipeline inflection point is more complicated than that of a straight pipeline, and the motion load requirement of the pipeline robot is higher. If one of the battery subunits reaches the pipeline inflection point, the processing module determines the output voltage adjustment factor of the battery subunit according to the characteristics of the pipeline inflection point to ensure that the battery subunit stably supplies energy in the area of ​​the pipeline inflection point, thereby meeting the motion load of the pipeline robot. The adjustment module accurately adjusts the output voltage of the battery subunit according to the obtained output voltage adjustment factor, ensuring that the pipeline robot can flexibly adjust at the pipeline inflection point according to the actual situation, which not only ensures the smooth passage at the pipeline inflection point, but also optimizes the energy utilization efficiency. When the battery subunit leaves the inflection point of the pipeline, the adjustment module will adjust the adjusted output voltage again to ensure the stable movement of the pipeline robot.

[0027] It is understandable that through the combination of voiceprint sensors and cameras, the pipeline robot can accurately obtain the environmental information of the pipeline, locate the interface position and wireless power supply device of the pipeline robot, and independently determine whether to charge the pipeline robot, so that the pipeline robot can independently complete tasks in complex pipeline environments, reduce human intervention and improve the operation efficiency of the pipeline robot. According to the remaining power of the battery unit and the interface position coordinates, the charging node of the battery unit is dynamically determined. The intelligent charging strategy ensures the charging of the pipeline robot and avoids overcharging and attenuation of the service life of the battery unit. At the same time, it also reduces energy waste. By precisely controlling the output voltage of each battery subunit, the system can achieve efficient energy management, thereby improving the adaptability and operation efficiency of the pipeline robot in complex environments.

[0028] In some embodiments of the present application, when preprocessing each initial voiceprint signal and determining all target voiceprint signals based on the preprocessing results, it includes: the acquisition module removes the signal noise of each initial voiceprint signal based on a first preset algorithm for the signal, performs time-frequency conversion on each initial voiceprint signal after the signal noise is removed using a second preset algorithm for the signal, and preprocesses each initial voiceprint signal after the time-frequency conversion, and the preprocessing includes signal compression and signal standardization.

[0029] Specifically, the first preset algorithm of the signal includes Wiener filtering or wavelet transform, and one of them can be selected according to the actual environment of the pipeline. The first preset algorithm of the signal can remove the signal noise of each initial voiceprint signal, improve the signal-to-noise ratio of the signal, and reduce the impact of external factors on the initial voiceprint signal. The second preset algorithm includes Fourier transform and Hilbert transform, and one of them can be selected according to the actual environment of the pipeline. The time-frequency conversion can reveal the frequency characteristics of the initial voiceprint signal changing with time, thereby capturing details and instantaneous changes, which is helpful to extract key information from the signal. Secondly, the use of signal compression helps to reduce the amount of information in the signal while retaining the effective information of the signal. Especially during the long-term operation of the pipeline robot, the compressed signal can be quickly transmitted and processed accordingly. Signal standardization eliminates the processing error caused by the difference in signal amplitude, so that signals collected from different sources can be compared and analyzed under the same processing framework, which improves the accuracy and reliability of the target voiceprint signal and lays the foundation for the subsequent determination of the interface position coordinates.

[0030] In some embodiments of the present application, when determining the interface position coordinates of the pipeline robot based on all target voiceprint signals and obtaining the interface target position coordinates of the wireless power supply device, the acquisition module establishes a pipeline coordinate system with the center of the pipeline robot as the origin, and determines the interface position coordinates based on triangulation positioning, and the interface position coordinates are obtained by the following formula: ; in, represents the position coordinates of the first voiceprint sensor, represents the position coordinates of the second voiceprint sensor, Indicates the location coordinates of the third voiceprint sensor, Indicates the interface position coordinates, Indicates the distance difference between the interface location and the first voiceprint sensor and the second voiceprint sensor. Indicates the distance difference between the interface position and the first voiceprint sensor and the third voiceprint sensor. The coordinates of the interface target position are determined based on the pipeline coordinate system: .

[0031] Specifically, a pipeline coordinate system is established with the center of the pipeline robot as the origin. Through triangulation and combining at least three voiceprint sensors, the accuracy and efficiency of determining the interface position coordinates are improved. Since the wireless power supply device is fixed in the pipeline, the interface position coordinates can also be directly determined when determining the interface position coordinates. The traditional positioning method uses a large amount of data such as point clouds for positioning. Although it can also achieve accurate positioning, it is necessary to simplify and accurately determine the interface position coordinates for pipeline robots that already have a large amount of motion data. In contrast, triangulation positioning uses the time difference and distance difference between voiceprint sensors. There is no need to process a large amount of positioning data, which reduces the reliance on human experience. At the same time, it can quickly and accurately locate the interface position coordinates, thereby improving the efficiency of autonomous charging management.

[0032] In some embodiments of the present application, when judging whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, it includes: the charging module pre-sets the remaining power threshold and the deviation distance threshold, when the remaining power of the battery unit is greater than the remaining power threshold, it is determined not to charge the pipeline robot, when the remaining power of the battery unit is less than or equal to the remaining power threshold, the deviation distance is determined based on the interface position coordinates and the interface target position coordinates, the deviation distance is compared with the deviation distance threshold, and whether to charge the pipeline robot is judged according to the comparison result, and the deviation distance is obtained by the following formula: ; in, Indicates the deviation distance, Indicates the interface target location coordinates, It represents the interface position coordinates. When the deviation distance is less than or equal to the deviation distance threshold, it is determined to charge the pipeline robot. When the deviation distance is greater than the deviation distance threshold, it is determined to adjust the pipeline robot based on the interface target position coordinates, and charge the pipeline robot according to the adjusted interface position coordinates.

[0033] Specifically, the charging module intelligently judges the remaining power of the battery unit and the interface position coordinates to ensure the autonomy of the pipeline robot's charging process. There is no need to manually disassemble the pipeline robot to avoid the risk of leakage caused by damaging the pipeline. At the same time, the intelligent charging process saves the energy and time of manual operation, ensuring the autonomy and reliability of the charging process. When the deviation distance is greater than the deviation distance threshold, the pipeline robot needs to be charged, but there is a deviation between the interface position coordinates and the interface target position coordinates, and they cannot be effectively aligned. The pipeline robot is adjusted according to the interface target position coordinates, thereby reducing the deviation distance to meet the charging needs, thereby improving the intelligence and automation of charging.

[0034] In some embodiments of the present application, when it is determined that the pipeline robot is to be charged, the charging node of the battery unit is determined based on the battery attenuation model, including: the charging module obtains historical charging data, and constructs a model data set based on the historical charging data, samples the model data set according to a preset ratio to obtain a training set and a test set, uses grid search to find the establishment parameters of the random forest model, establishes a random forest model, uses the training set to fit the random forest model, substitutes the test set into the random forest model and evaluates it, when the evaluation value reaches the preset evaluation value threshold, obtains the battery attenuation model, substitutes the remaining power of the battery unit into the battery attenuation model, and determines the charging node of the battery unit.

[0035] Specifically, the historical charging data includes the various charging states, charging times, and required charging amounts of the pipeline robot in different periods. A model data set is constructed based on the historical charging data, and the model data set is sampled according to a preset ratio to obtain a training set and a test set, usually 70-80% as a training set and the rest as a test set. The training set is used to train the random forest model, and the test set is used to evaluate the performance of the trained model. A grid search is used to exhaustively search the range of hyperparameter values ​​of the random forest model and find the best hyperparameter combination to establish a random forest model, thereby improving the model's predictive ability. The random forest model contains multiple decision trees, tree depth, and the number of leaf nodes, etc., which aims to capture the complex relationships in the data. Fitting the random forest model reduces the overfitting ability of the random forest model. At the same time, it tries to learn the patterns and relationships in the data in the training set to improve its prediction or classification ability. The test set is substituted into the random forest model and evaluated. The evaluation indicators include accuracy, loss function value and recall rate, which are used to measure the comprehensive performance of the model. When the evaluation value reaches the preset evaluation value threshold, it is considered that the model can stably approach the global optimal solution, so the model is determined as a battery attenuation model. The charging node is determined according to the remaining power of the battery cell. This charging node includes the energy proportion charged to (the battery cell itself has its own attenuation during actual charging, so it cannot be charged to 100%) and the actual charging time, etc., which improves the work efficiency of the subsequent pipeline robot.

[0036] In some embodiments of the present application, when acquiring multiple pipeline images of a pipeline and performing image processing on the multiple pipeline images to obtain a pipeline merged image of the pipeline, it includes: a processing module performs image processing on the multiple pipeline images, the image processing includes geometric correction and adjustment of image contrast, feature points are extracted from the multiple pipeline images after image processing, and correlation information between images is determined according to the RANSAC algorithm, the correlation information includes relative position and rotation relationship, based on the correlation information, the multiple pipeline images after image processing are aligned, and the aligned multiple pipeline images are merged according to the weighted mean to obtain the pipeline merged image.

[0037] Specifically, when the charging module completes charging according to the charging node or drives based on the remaining power, the processing module uses the camera to shoot the pipeline to determine the environmental information of the pipeline. A single pipeline image may not be able to fully reflect the actual situation of the pipeline. Therefore, multiple pipeline images are obtained to obtain the pipeline environment. The details and features of the pipeline image are enhanced by geometric correction and adjustment of image contrast, thereby improving the image quality. Feature points of the multiple pipeline images after image processing are extracted, and the correlation information between images is determined according to the RANSAC algorithm. The relative position and rotation relationship between the images can be accurately obtained. The multiple pipeline images after image processing are aligned according to affine transformation and perspective transformation, etc., to eliminate the translation, rotation and deformation caused by different shooting angles between images, thereby achieving precise alignment between images. The multiple aligned pipeline images are merged according to the weighted mean, which improves the overall image effect and stitching quality of the pipeline merged image, and lays a reliable foundation for the subsequent determination of the output voltage of each battery subunit and energy management.

[0038] In some embodiments of the present application, when determining the output voltage of each battery subunit based on the pipeline merged image, the process includes: a processing module analyzes the pipeline merged image, determines the inner diameter of the pipeline, and determines the output voltage of each battery subunit according to the inner diameter of the pipeline, and the output voltage is obtained according to the following formula: ; in, Indicates the output voltage, and represents the weight coefficient, and , Indicates the inner diameter of the pipe. Represents the friction coefficient between the driving wheels of the pipeline robot and the pipeline.

[0039] In some embodiments of the present application, when there is a pipeline inflection point in the pipeline and a battery subunit reaches the pipeline inflection point, the output voltage adjustment factor of the battery subunit is determined based on the pipeline inflection point, including: a processing module determines an inflection point image of the pipeline inflection point, and analyzes the inflection point image to determine the bending radius and bending angle of the pipeline, and determines the output voltage adjustment factor of the battery subunit according to the bending radius and bending angle, and the output voltage adjustment factor is obtained according to the following formula: ; in, represents the output voltage adjustment factor, represents the bending angle, Indicates the bending radius.

[0040] In some embodiments of the present application, the output voltage is adjusted based on the output voltage adjustment factor, and the pipeline robot is driven forward according to the adjusted output voltage. When the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again, including: an adjustment module determines a target output voltage according to the output voltage and the output voltage adjustment factor, the target output voltage being the product of the output voltage and the output voltage adjustment factor, and when the battery subunit leaves the pipeline inflection point, the adjustment module restores the target output voltage of the battery subunit to the output voltage.

[0041] Specifically, the output voltage is determined by the inner diameter of the pipeline and the friction coefficient between the driving wheel of the pipeline robot and the pipeline, so that each battery subunit can intelligently adapt to pipelines of different sizes, reducing unnecessary power consumption and thus improving endurance. For example: Select 0.3, Select 0.7, The friction coefficient between the driving wheel of the pipeline robot and the pipeline is determined to be 10 cm after image analysis. is 0.6 (here the material of the pipe is set to iron and the driving wheel is set to rubber), the output voltage for , =244V, the output voltage of each battery subunit is dynamically determined according to the pipeline environment, avoiding energy waste caused by simple output, and when any battery subunit reaches the inflection point of the pipeline, the inflection point image is obtained (the camera and image processing are also used, which will not be repeated here), and the bending radius and bending angle are determined. The output voltage adjustment factor of the battery subunit is determined according to the bending radius and bending angle, for example: the bending angle For six , bending radius For 25cm, the output voltage adjustment factor The output voltage is 1.18, and the target output voltage is determined by the output voltage and the output voltage adjustment factor, which can ensure that each battery subunit makes corresponding adjustments at the inflection point of the pipeline, so as to smoothly pass through the area at the inflection point, prevent slipping or inability to pass due to energy mismatch at the inflection point of the curve, and adaptively adjust the output voltage to reduce the problem of over-energy supply or insufficient energy supply, effectively deal with the bending angle and bending radius of the pipeline, so that the pipeline robot can operate stably in a variety of scenarios, and make adjustments for each battery subunit when it reaches a specific inflection point of the curve, reducing the energy consumption of blind driving, thereby ensuring the operation stability of the pipeline robot, and when the arriving battery subunit leaves the inflection point of the pipeline, the adjustment module restores the target output voltage of the battery subunit to the output voltage, avoiding excessive energy consumption, improving the efficiency of energy management and the utilization rate of the battery subunit, and thus ensuring the autonomy and intelligence level of the pipeline robot.

[0042] In summary, the beneficial effects of the present invention are: by acquiring the initial voiceprint signal through multiple voiceprint sensors and determining the target voiceprint signal by preprocessing, the interface position coordinates of the pipeline robot and the interface target position coordinates of the wireless power supply device can be accurately located, thereby improving the accuracy of the charging process. Dynamically determine whether to charge, and combine the battery attenuation model to obtain the charging node, thereby optimizing the charging time and charging efficiency, thereby extending the battery life, while ensuring that the pipeline robot obtains energy, improving autonomy and intelligence, and by acquiring the pipeline image and obtaining the pipeline merged image, the pipeline environment and pipeline inflection point can be accurately determined, thereby adjusting the output voltage of the battery subunit in real time to cope with the energy requirements in different pipeline environments, avoiding the risk of being unable to pass due to insufficient energy, and through secondary adjustments after leaving the pipeline inflection point, further ensuring the efficient operation of the pipeline robot, effectively improving the robot's operating stability and energy management efficiency in a complex pipeline environment.

[0043] In another preferred embodiment based on the above embodiment, refer to Figure 2 As shown, this embodiment provides a pipeline robot autonomous charging and energy management method, which is applied to the above pipeline robot autonomous charging and energy management system, including: S100: Obtain initial voiceprint signals from at least three voiceprint sensors evenly deployed on the pipeline robot, preprocess each initial voiceprint signal, determine all target voiceprint signals according to the preprocessing results, determine the interface position coordinates of the pipeline robot based on all target voiceprint signals, and obtain the interface target position coordinates of the wireless power supply device.

[0044] S200: Determine whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit. When it is determined that the pipeline robot is to be charged, determine the charging node of the battery unit based on the battery attenuation model.

[0045] S300: When charging is completed based on the charging node or driving is performed based on the remaining power, multiple pipeline images of the pipeline are acquired, and image processing is performed on the multiple pipeline images to obtain a pipeline merged image of the pipeline, and the output voltage of each battery subunit is determined based on the pipeline merged image. When there is a pipeline inflection point in the pipeline and a battery subunit reaches the pipeline inflection point, the output voltage adjustment factor of the battery subunit is determined based on the pipeline inflection point.

[0046] S400: adjusting the output voltage based on the output voltage adjustment factor, driving the pipeline robot forward according to the adjusted output voltage, and adjusting the adjusted output voltage again when the battery subunit leaves the pipeline inflection point.

[0047] Specifically, by evenly deploying at least three voiceprint sensors on the pipeline robot, the initial voiceprint signals in the pipeline can be obtained in real time, and these signals are preprocessed to improve the signal quality, and the target voiceprint signals are obtained. The interface position coordinates of the pipeline robot are determined based on the target voiceprint signals, which improves the positioning accuracy and ensures the stability of the charging process. By judging the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, it is decided whether to charge the pipeline robot. If it is determined that charging is required, the charging node will be determined according to the battery attenuation model. According to the energy state of the pipeline robot, intelligent decisions are made to ensure the efficiency of the battery unit, the reliability of the charging process, and the unnecessary charging waste, thereby extending the life of the battery unit and improving the efficiency of energy management. When charging is completed or the remaining power is sufficient, multiple pipeline images of the pipeline are obtained and image processing is performed to dynamically determine the output voltage of each battery subunit, thereby improving the stability of energy management. When there is a pipeline inflection point in the pipeline and the battery subunit reaches the pipeline inflection point, the output voltage adjustment factor of the battery subunit is dynamically determined based on the pipeline inflection point, thereby ensuring that the pipeline robot can perform corresponding movements at the inflection point of the curve, avoiding the problem of mismatch in the output voltage of the battery subunit, and improving the adaptability of the pipeline robot and the reliability of energy management. When the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again to ensure the continuous movement and stable energy supply of the pipeline robot. It can not only ensure the stable operation of the pipeline robot in a complex environment, but also optimize the efficiency of the battery subunit, reduce energy waste, and thus improve the autonomous ability and the intelligent level of management.

[0048] See also Figure 3-5As shown, the pipeline robot includes a robot body 1, and the robot body 1 includes a front connecting arm 10 and a rear connecting arm 11. The tail of the front connecting arm 10 is connected to the head of the rear connecting arm 11, and the tops of the front connecting arm 10 and the rear connecting arm 11 are fixedly connected to the voiceprint sensor 2. The top of the front connecting arm 10 is fixedly connected to the central control module 6, and the top of the front connecting arm 10 is provided with an interface 3. The head of the front connecting arm 10 is installed with a camera 4, and the top of the rear connecting arm 11 is provided with an interface 3. The front connecting arm 10 is installed with three driving wheels 5, and the rear connecting arm 11 is installed with three driving wheels 5, and each driving wheel 5 contains a battery subunit 7.

[0049] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0050] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0051] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0052] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An autonomous charging and energy management system for a pipeline robot, characterized in that: include: A battery unit and a central control module, wherein the central control module is electrically connected to the battery unit, and the central control module includes a collection module, a charging module, a processing module and an adjustment module; The acquisition module is configured to acquire initial voiceprint signals of at least three voiceprint sensors uniformly deployed on the pipeline robot, preprocess each initial voiceprint signal, determine all target voiceprint signals according to the preprocessing result, determine the interface position coordinates of the pipeline robot based on all target voiceprint signals, and acquire the interface target position coordinates of the wireless power supply device; The charging module is configured to determine whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, and when it is determined that the pipeline robot is to be charged, determine the charging node of the battery unit based on the battery attenuation model; The processing module is configured to acquire multiple pipeline images of the pipeline and perform image processing on the multiple pipeline images to obtain a pipeline merged image of the pipeline when the charging module completes charging based on the charging node or drives based on the remaining power, the battery unit includes a plurality of battery subunits, the output voltage of each battery subunit is determined based on the pipeline merged image, and when the pipeline has a pipeline inflection point and a battery subunit reaches the pipeline inflection point, the output voltage adjustment factor of the battery subunit is determined based on the pipeline inflection point; The adjustment module is configured to adjust the output voltage based on the output voltage adjustment factor, drive the pipeline robot forward according to the adjusted output voltage, and adjust the adjusted output voltage again when the battery subunit leaves the pipeline inflection point.

2. The pipeline robot autonomous charging and energy management system according to claim 1 is characterized in that: When preprocessing each initial voiceprint signal and determining all target voiceprint signals according to the preprocessing result, it includes: The acquisition module removes the signal noise of each initial voiceprint signal based on the first preset algorithm of the signal, and performs time-frequency conversion on each initial voiceprint signal after removing the signal noise using the second preset algorithm of the signal; Each initial voiceprint signal after time-frequency conversion is preprocessed, and the preprocessing includes signal compression and signal standardization.

3. The pipeline robot autonomous charging and energy management system according to claim 2 is characterized in that: When determining the interface position coordinates of the pipeline robot based on all target voiceprint signals and acquiring the interface target position coordinates of the wireless power supply device, it includes: The acquisition module establishes a pipeline coordinate system with the center of the pipeline robot as the origin, and determines the interface position coordinates based on triangulation. The interface position coordinates are obtained by the following formula: ； in, represents the position coordinates of the first voiceprint sensor, represents the position coordinates of the second voiceprint sensor, Indicates the location coordinates of the third voiceprint sensor, Indicates the interface position coordinates, Indicates the distance difference between the interface location and the first voiceprint sensor and the second voiceprint sensor. Indicates the distance difference between the interface location and the first voiceprint sensor and the third voiceprint sensor; The interface target position coordinates are determined based on the pipeline coordinate system: .

4. The pipeline robot autonomous charging and energy management system according to claim 3 is characterized in that: When judging whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, it includes: The charging module pre-sets a remaining power threshold and a deviation distance threshold; When the remaining power of the battery unit is greater than the remaining power threshold, determining not to charge the pipeline robot; When the remaining power of the battery unit is less than or equal to the remaining power threshold, determining a deviation distance based on the interface position coordinates and the interface target position coordinates, comparing the deviation distance with the deviation distance threshold, and judging whether to charge the pipeline robot according to the comparison result; The deviation distance is obtained by the following formula: ； in, Indicates the deviation distance, Indicates the interface target location coordinates, Indicates the interface position coordinates; When the deviation distance is less than or equal to the deviation distance threshold, it is determined that the pipeline robot is to be charged; When the deviation distance is greater than the deviation distance threshold, it is determined that the pipeline robot is adjusted based on the interface target position coordinates, and the pipeline robot is charged according to the adjusted interface position coordinates.

5. The pipeline robot autonomous charging and energy management system according to claim 4 is characterized in that: When it is determined that the pipeline robot is to be charged, the charging node of the battery unit is determined based on the battery attenuation model, including: The charging module acquires historical charging data, and constructs a model data set according to the historical charging data, samples the model data set according to a preset ratio to obtain a training set and a test set, uses a grid search to find the establishment parameters of the random forest model, and establishes the random forest model; Fitting the random forest model using the training set, substituting the test set into the random forest model and evaluating it, and obtaining the battery degradation model when the evaluation value reaches a preset evaluation value threshold; Substitute the remaining power of the battery cell into the battery degradation model to determine the charging node of the battery cell.

6. The pipeline robot autonomous charging and energy management system according to claim 5 is characterized in that: When a plurality of pipeline images of a pipeline are acquired and image processing is performed on the plurality of pipeline images to obtain a pipeline merged image of the pipeline, the method includes: The processing module performs image processing on the multiple pipeline images, wherein the image processing includes geometric correction and adjustment of image contrast; Feature points are extracted from the multiple pipeline images after image processing, and association information between the images is determined according to the RANSAC algorithm, wherein the association information includes relative position and rotation relationship. Based on the association information, the multiple pipeline images after image processing are registered, and the multiple registered pipeline images are merged according to the weighted mean to obtain the pipeline merged image.

7. The pipeline robot autonomous charging and energy management system according to claim 6, characterized in that: When determining the output voltage of each battery subunit based on the pipeline merged image, the method includes: The processing module analyzes the pipeline merged image to determine the inner diameter of the pipeline, and determines the output voltage of each battery subunit according to the inner diameter of the pipeline; The output voltage is given by the following formula: ； in, Indicates the output voltage, and represents the weight coefficient, and , Indicates the inner diameter of the pipe. Represents the friction coefficient between the driving wheels of the pipeline robot and the pipeline.

8. The pipeline robot autonomous charging and energy management system according to claim 7 is characterized in that: When the pipeline has a pipeline inflection point and a battery subunit reaches the pipeline inflection point, determining the output voltage adjustment factor of the battery subunit based on the pipeline inflection point includes: The processing module determines an inflection point image of the inflection point of the pipeline, analyzes the inflection point image, determines a bending radius and a bending angle of the pipeline, and determines an output voltage adjustment factor of the battery subunit according to the bending radius and the bending angle; The output voltage adjustment factor is obtained according to the following formula: ； in, represents the output voltage adjustment factor, represents the bending angle, Indicates the bending radius.

9. The pipeline robot autonomous charging and energy management system according to claim 8, characterized in that: The output voltage is adjusted based on the output voltage adjustment factor, and the pipeline robot is driven forward according to the adjusted output voltage. When the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again, including: The adjustment module determines a target output voltage according to the output voltage and the output voltage adjustment factor, wherein the target output voltage is a product value of the output voltage and the output voltage adjustment factor; When the battery subunit leaves the pipeline inflection point, the adjustment module restores the target output voltage of the battery subunit to the output voltage.

10. A pipeline robot autonomous charging and energy management method, applied to the pipeline robot autonomous charging and energy management system according to any one of claims 1 to 9, characterized in that: include: Acquire initial voiceprint signals of at least three voiceprint sensors uniformly deployed on the pipeline robot, preprocess each initial voiceprint signal, determine all target voiceprint signals according to the preprocessing result, determine the interface position coordinates of the pipeline robot based on all target voiceprint signals, and acquire the interface target position coordinates of the wireless power supply device; Determining whether to charge the pipeline robot according to the interface position coordinates, the interface target position coordinates and the remaining power of the battery unit, and when it is determined that the pipeline robot is to be charged, determining the charging node of the battery unit based on the battery attenuation model; When charging is completed based on the charging node or driving is performed based on the remaining power, a plurality of pipeline images of the pipeline are acquired, and image processing is performed on the plurality of pipeline images to obtain a pipeline merged image of the pipeline, and an output voltage of each battery subunit is determined based on the pipeline merged image, and when a pipeline inflection point exists in the pipeline and a battery subunit reaches the pipeline inflection point, an output voltage adjustment factor of the battery subunit is determined based on the pipeline inflection point; The output voltage is adjusted based on the output voltage adjustment factor, and the pipeline robot is driven forward according to the adjusted output voltage. When the battery subunit leaves the pipeline inflection point, the adjusted output voltage is adjusted again.

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