Ecological cycle treatment method and system for river and lake bottom mud

Abstract

The invention relates to the technical field of ecological circulation, and discloses an ecological circulation treatment method and system for river and lake sediment, and the method comprises the steps: determining a centrifugal rotating speed according to a target moisture content and a centrifugal rotating speed model, obtaining a real-time image set of a plurality of to-be-monitored areas, judging whether scale exists or not according to the real-time image set, and if yes, judging whether the scale exists or not. When it is judged that incrustation exists, a real-time image set is deleted, an incrustation image set is determined according to a deletion result, all incrustation pixel points are divided according to a clustering center point, an incrustation score value is determined based on a division result, and a determination mode of a rotating speed adjustment coefficient is determined based on the incrustation score value. The centrifugal rotating speed is adjusted according to the first rotating speed adjusting coefficient or the second rotating speed adjusting coefficient, and the river and lake bottom mud to be treated is dehydrated according to the adjusted centrifugal rotating speed. Good dynamic control is achieved, the requirement for the dehydration process is met, and the utilization rate of the river and lake bottom mud is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of ecological cycle, and in particular, to an ecological cycle treatment method and system for river and lake sediment. Background Art

[0002] In the river and lake ecosystem, pollutants in the river and lake are continuously deposited and finally form river and lake sediment. The excessive accumulation of river and lake sediment not only seriously threatens the water quality, causing a series of ecological problems such as eutrophication and black and odorous water bodies, but also hinders river flood discharge, increases the risk of flood disasters, and has an adverse impact on shipping safety and efficiency. Making "sludge cement" by treating river and lake sediment through incineration is an effective way to achieve ecological cycle. However, due to the existence of a large amount of water in river and lake sediment, if high-moisture-content river and lake sediment is incinerated, not only sludge cement cannot be obtained, but also a large amount of fuel needs to be supplemented to complete the incineration. During the dehydration process of high-moisture-content river and lake sediment, the centrifugal speed of the centrifuge often depends on the experience of technicians for setting. Moreover, due to the long-term dehydration of the centrifuge, as the water evaporates or the temperature of the river and lake sediment changes, calcium, magnesium and other ions in the water will precipitate in the form of carbonates, sulfates, etc., and adhere to the internal channels of the centrifuge to form scale, resulting in the centrifugal speed not meeting the requirements of the dehydration process, and thus the utilization rate of river and lake sediment is insufficient.

[0003] Therefore, it is necessary to design an ecological cycle treatment method and system for river and lake sediment to solve the problems existing in the current technology. Summary of the Invention

[0004] In view of this, the present invention provides an ecological cycle treatment method and system for river and lake sediment, aiming to solve the problems that the centrifugal speed of the centrifuge often depends on the experience of technicians for setting, and due to the evaporation of water or the change of the temperature of the river and lake sediment, calcium, magnesium and other ions in the water will precipitate in the form of carbonates, sulfates, etc., and adhere to the internal channels of the centrifuge to form scale, resulting in the centrifugal speed not meeting the requirements of the dehydration process, and thus the utilization rate of river and lake sediment is insufficient.

[0005] On the one hand, the present invention provides an ecological cycle treatment method for river and lake sediment, including: Obtaining the moisture contents of the river and lake sediment to be treated for several times, determining the target moisture content of the river and lake sediment to be treated based on the several moisture contents, and determining the centrifugal speed according to the target moisture content and the centrifugal speed model; Dividing the centrifugal channel of the centrifuge into several monitoring areas to be monitored, obtaining a real-time image set of the several monitoring areas to be monitored, judging whether there is scale according to the real-time image set, when it is determined that there is scale, deleting the real-time image set, and determining a scale image set according to the deletion result; Obtain all the scale pixel points of the scale image set, and determine the clustering center points of the scale image set. Divide all the scale pixel points according to the clustering center points, determine the scale score value based on the division result, and determine the method for determining the rotation speed adjustment coefficient based on the scale score value. The rotation speed adjustment coefficient includes a first rotation speed adjustment coefficient and a second rotation speed adjustment coefficient; Adjust the centrifugal rotation speed according to the first rotation speed adjustment coefficient or the second rotation speed adjustment coefficient, and dehydrate the to-be-treated river and lake bottom mud according to the adjusted centrifugal rotation speed.

[0006] Further, when determining the target moisture content of the to-be-treated river and lake bottom mud based on several moisture contents and determining the centrifugal rotation speed according to the target moisture content and the centrifugal rotation speed model, it includes: The target moisture content is the average value of several moisture contents; Obtain a river and lake bottom mud data set, and divide the river and lake bottom mud data set into a training set and a test set; Use the training set to train an artificial neural network model, use the test set to test the trained artificial neural network model, and finally determine a centrifugal rotation speed model with the target moisture content as the input and the centrifugal rotation speed as the output; The artificial neural network model includes a BP neural network model or an RBF neural network model.

[0007] Further, when judging whether there is scale according to the real-time image set, and when it is determined that there is scale, deleting the real-time image set, and determining the scale image set according to the deletion result, it includes: Preprocess the real-time image set, and the preprocessing includes image denoising and contrast adjustment; Use a preset image algorithm to determine the image features of the preprocessed real-time image set, and determine the standard image features of the standard real-time image set; When the image features are equal to the standard image features, it is determined that there is no scale in the real-time image set, and dehydrate the to-be-treated river and lake bottom mud at the centrifugal rotation speed; When the image features are not equal to the standard image features, it is determined that there is scale in the real-time image set, delete the real-time images without scale, and construct the remaining real-time images into the scale image set.

[0008] Further, when dividing all the scale pixel points according to the clustering center points and determining the scale score value based on the division result, it includes: Determine the clustering distance between each scale pixel and the clustering center point, and preset a first preset clustering distance and a second preset clustering distance, where the first preset clustering distance is greater than the second preset clustering distance; When the clustering distance is greater than the first preset clustering distance, divide the scale pixel into the first scale set; When the clustering distance is less than or equal to the first preset clustering distance and greater than or equal to the second preset clustering distance, divide the scale pixel into the second scale set; When the clustering distance is less than the second preset clustering distance, divide the scale pixel into the third scale set; Determine the scale score value based on the first scale set, the second scale set, and the third scale set.

[0009] Further, when determining the scale score value based on the first scale set, the second scale set, and the third scale set, it includes: Count the first quantity of scale pixels in the first scale set, count the second quantity of scale pixels in the second scale set, and count the third quantity of scale pixels in the third scale set; Obtain the first maximum clustering distance and the first minimum clustering distance in the first scale set, obtain the second maximum clustering distance and the second minimum clustering distance in the second scale set, and obtain the third maximum clustering distance and the third minimum clustering distance in the third scale set; Obtain the first difference between the first maximum clustering distance and the first minimum clustering distance, obtain the second difference between the second maximum clustering distance and the second minimum clustering distance, and obtain the third difference between the third maximum clustering distance and the third minimum clustering distance; Determine the scale score value according to the first quantity, the second quantity, the third quantity, the first difference, the second difference, and the third difference.

[0010] Further, when determining the determination method of the rotation speed adjustment coefficient based on the scale score value, it includes: Compare the scale score value with the scale score threshold, and determine the determination method of the rotation speed adjustment coefficient according to the comparison result; When the scale score value is greater than the scale score threshold, determine the first rotation speed adjustment coefficient according to the historical data set; When the scale score value is less than or equal to the scale score threshold, determine the second rotation speed adjustment coefficient based on the scale score value.

[0011] Further, when determining the first rotation speed adjustment coefficient according to the historical data set, it includes: The historical data set includes a number of historical scale deposit score values and a number of historical first rotational speed adjustment coefficients, and each historical scale deposit score value corresponds to a historical first rotational speed adjustment coefficient; When there is a historical scale deposit score value in the historical data set that is the same as the scale deposit score value, the historical first rotational speed adjustment coefficient corresponding to the historical scale deposit score value is used as the first rotational speed adjustment coefficient; When there is no historical scale deposit score value in the historical data set that is the same as the scale deposit score value, an adjustment data set is constructed based on the number of historical first rotational speed adjustment coefficients, a rotational speed adjustment model is determined according to the adjustment data set, and the first rotational speed adjustment coefficient is determined based on the rotational speed adjustment model.

[0012] Further, when determining the second rotational speed adjustment coefficient based on the scale deposit score value, it includes: A first preset scale deposit score value and a second preset scale deposit score value are preset, and the first preset scale deposit score value is greater than the second preset scale deposit score value; A first preset rotational speed adjustment coefficient, a second preset rotational speed adjustment coefficient, and a third preset rotational speed adjustment coefficient are preset, the first preset rotational speed adjustment coefficient is greater than the second preset rotational speed adjustment coefficient, and the second preset rotational speed adjustment coefficient is greater than the third preset rotational speed adjustment coefficient; When the scale deposit score value is greater than or equal to the first preset scale deposit score value, the first preset rotational speed adjustment coefficient is used as the second rotational speed adjustment coefficient; When the scale deposit score value is less than the first preset scale deposit score value and greater than the second preset scale deposit score value, the second preset rotational speed adjustment coefficient is used as the second rotational speed adjustment coefficient; When the scale deposit score value is less than or equal to the second preset scale deposit score value, the third preset rotational speed adjustment coefficient is used as the second rotational speed adjustment coefficient.

[0013] Further, when adjusting the centrifugal rotational speed according to the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, it includes: The centrifugal rotational speed is positively correlated with the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: By obtaining the moisture content multiple times to determine the target moisture content and combining with the centrifugal speed model to set the centrifugal speed, the actual water content of the river and lake bottom mud can be fully considered, so as to accurately match the centrifugal speed required for dehydration, avoid excessive dehydration time or energy waste caused by unreasonable speed, reduce the interference of human factors, and ensure the stability of the dehydration process. Once scale is detected, by processing and analyzing the image to determine the scale score value and determining the method for determining the speed adjustment coefficient based on this value, it effectively makes up for the insufficient dehydration efficiency caused by the influence of scale, ensures that the river and lake bottom mud can be effectively dehydrated, avoids affecting the efficiency of manufacturing "sludge cement" due to insufficient dehydration, thereby improving the stability of the ecological cycle of the river and lake bottom mud, reducing resource waste caused by improper centrifugal speed, realizing the resource conversion of the river and lake bottom mud, and ensuring the stability of the ecological cycle.

[0015] On the other hand, the present application also provides an ecological cycle treatment system for river and lake bottom mud. Applied to the above ecological cycle treatment system for river and lake bottom mud, it includes: A first analysis unit, configured to obtain the moisture content of the river and lake bottom mud to be treated multiple times, determine the target moisture content of the river and lake bottom mud to be treated based on the multiple moisture contents, and determine the centrifugal speed according to the target moisture content and the centrifugal speed model; A second analysis unit, configured to divide the centrifugal channel of the centrifuge into several monitoring areas to be monitored, obtain a real-time image set of the several monitoring areas to be monitored, determine whether there is scale according to the real-time image set, and when it is determined that there is scale, delete the real-time image set, and determine the scale image set according to the deletion result; An adjustment analysis unit, configured to obtain all the scale pixel points of the scale image set, determine the clustering center point of the scale image set, divide all the scale pixel points according to the clustering center point, determine the scale score value based on the division result, and determine the method for determining the speed adjustment coefficient based on the scale score value. The speed adjustment coefficient includes a first speed adjustment coefficient and a second speed adjustment coefficient; An adjustment processing unit, configured to adjust the centrifugal speed according to the first speed adjustment coefficient or the second speed adjustment coefficient, and dehydrate the river and lake bottom mud to be treated according to the adjusted centrifugal speed.

[0016] It can be understood that the above ecological cycle treatment method and system for river and lake bottom mud have the same beneficial effects, which will not be elaborated here. Description of the Drawings

[0017] Upon reading the following detailed description of the preferred embodiments, various other advantages and benefits will become apparent to those of ordinary skill in the art. The accompanying drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Also, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings: Figure 1 FIG. is a flowchart of an ecological cycle treatment method for river and lake bottom mud provided by an embodiment of the present invention; Figure 2 FIG. is a functional block diagram of an ecological cycle treatment system for river and lake bottom mud provided by an embodiment of the present invention. Detailed Embodiments

[0018] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. Hereinafter, the present invention will be described in detail with reference to the drawings and in combination with the embodiments.

[0019] Refer to Figure 1 As shown, in some embodiments of the present application, an ecological cycle treatment method for river and lake bottom mud includes: S100: Obtain several moisture contents of the river and lake bottom mud to be treated, determine the target moisture content of the river and lake bottom mud to be treated based on the several moisture contents, and determine the centrifugal speed according to the target moisture content and the centrifugal speed model.

[0020] S200: Divide the centrifugal channel of the centrifuge into several areas to be monitored, obtain a real-time image set of the several areas to be monitored, determine whether there is scale according to the real-time image set, and when it is determined that there is scale, delete the real-time image set, and determine the scale image set according to the deletion result.

[0021] S300: Obtain all the scale pixel points of the scale image set, and determine the clustering center point of the scale image set, divide all the scale pixel points according to the clustering center point, determine the scale score value based on the division result, and determine the determination method of the speed adjustment coefficient based on the scale score value. The speed adjustment coefficient includes a first speed adjustment coefficient and a second speed adjustment coefficient.

[0022] S400: Adjust the centrifugal speed according to the first speed adjustment coefficient or the second speed adjustment coefficient, and dehydrate the river and lake bottom mud to be treated according to the adjusted centrifugal speed.

[0023] Specifically, in the utilization of river and lake sediment, a cutter suction dredger is used to suck the slurry water with a certain moisture content from the river and lake bottom. Through pipeline transportation operations, it is transported to the sediment treatment site, where relatively large fibers and gravel are filtered out. Then, it flows into the biological homogenization tank by gravity and is injected into the biological homogenization reaction tank by a metering pump. A push-flow aerator is used to remove some organic matter in the sediment, achieving the purpose of degradation and deodorization, and at the same time facilitating the dehydration of the sediment. Through the dehydration treatment of the river and lake sediment, the moisture content of the river and lake sediment is reduced. A part of the river and lake sediment with a lower moisture content is transported to the landfill site and incineration site for landscaping or building material sintering, and a part is sent to the sludge storage bin for building filling, thus achieving the multi-level utilization of the river and lake sediment.

[0024] Specifically, the moisture content of river and lake sediment is an important factor affecting the dehydration effect. By obtaining the moisture content of the river and lake sediment to be treated several times and analyzing and processing these several moisture contents, the overall moisture condition of the river and lake sediment can be grasped more accurately, and then the target moisture content can be determined. The process of obtaining the moisture content is redundant and mature, so it will not be described in detail here. The several moisture contents are at least five times to avoid errors caused by accidental data. The centrifugal speed is determined according to the target moisture content and the centrifugal speed model, avoiding the deviation of manual experience setting, which can not only ensure the dehydration efficiency but also avoid energy waste or insufficient dehydration caused by improper speed, improving the utilization rate of the ecological cycle of river and lake sediment. The centrifuge in this embodiment is not specifically limited, and the centrifugal channel refers to the channel (such as the hopper, barrel, etc.) where the centrifuge actually places the river and lake sediment. During the long-term use of the centrifuge, a certain amount of scale will be generated in the centrifugal channel, and the scale will affect the dehydration efficiency and the performance of the centrifuge. Moreover, since the centrifuge for treating river and lake sediment is relatively large in size, it is impossible to remove the scale every time during dehydration. Therefore, the centrifugal channel is divided into several areas to be monitored. When dividing, the centrifugal channel is evenly divided to ensure the consistency of each area to be monitored. Infrared and other image acquisition devices are used to obtain a real-time image set, which includes the real-time images of all areas to be monitored. Image recognition is used to judge whether there is scale. When it is determined that there is scale, the real-time image set is trimmed to remove irrelevant images, and the images related to the scale are retained to form a scale image set, which is helpful for subsequent accurate analysis.

[0025] It can be understood that by obtaining all the scale pixel points of the scale image set and determining the clustering center points, the characteristics such as the distribution, area, and density of the scale can be analyzed through the division of the scale pixel points. Based on the division results, a scale score value is determined. The higher the scale score value, the greater the impact of the scale on the performance of the centrifuge. Determining the speed adjustment coefficient according to different situations of the scale score value takes into account the different degrees of influence of the scale on the centrifuge performance. Adjusting the centrifugal speed according to the determined speed adjustment coefficient enables the adjusted centrifugal speed to meet the requirements of the dehydration process, promotes the evaporation of water in the river-lake sediment, and thus improves the utilization rate of the river-lake sediment.

[0026] In some embodiments of the present application, when determining the target moisture content of the river-lake sediment to be processed based on several moisture contents and determining the centrifugal speed according to the target moisture content and the centrifugal speed model, it includes: the target moisture content is the average value of several moisture contents. Obtain the river-lake sediment data set, and divide the river-lake sediment data set into a training set and a test set. Use the training set to train the artificial neural network model, and use the test set to test the trained artificial neural network model. Finally, determine the centrifugal speed model with the target moisture content as the input and the centrifugal speed as the output. The artificial neural network model includes a BP neural network model or an RBF neural network model.

[0027] Specifically, determining the average value of several moisture contents as the target moisture content can comprehensively consider the actual water content situation of the river-lake sediment and avoid deviations in the overall moisture judgment of the river-lake sediment caused by errors or fluctuations in single moisture content measurement. Establishing the association between the target moisture content and the centrifugal speed through the artificial neural network model can fully learn the complex relationship between the two. The river-lake sediment data set includes key data such as the target moisture content, particle size distribution, pH value, and activity at different times. Divide the river-lake sediment data set into a training set and a test set, which are respectively used for model training and testing. The BP neural network model or the RBF neural network model has self-learning and adaptive capabilities. The training set enables the model to learn the rules and characteristics in the data, and the test set tests the generalization ability of the model to avoid overfitting of the model, so that it can better handle river-lake sediment from different sources and with different characteristics. Regardless of how the composition and properties of the sediment change, the finally obtained centrifugal speed model can output the centrifugal speed, making the centrifugal speed consistent with the dehydration requirements of the river-lake sediment, ensuring the stability and consistency of the dehydration effect of the river-lake sediment, and effectively avoiding human errors caused by the setting of human experience.

[0028] In some embodiments of the present application, when determining whether there is scale based on the real-time image set, and when it is determined that there is scale, the real-time image set is pruned, and when determining the scale image set according to the pruning result, it includes: preprocessing the real-time image set, and the preprocessing includes image denoising and contrast adjustment. The preprocessed real-time image set is used to determine the image features by a preset image algorithm, and the standard image features of the standard real-time image set are determined. When the image features are equal to the standard image features, it is determined that there is no scale in the real-time image set, and the lake and river bottom mud to be processed is dehydrated at the centrifugal speed. When the image features are not equal to the standard image features, it is determined that there is scale in the real-time image set, and the real-time images without scale are pruned, and the remaining real-time images are constructed into a scale image set.

[0029] Specifically, the preprocessing operations of image denoising and contrast adjustment on the real-time image set can remove the noise interference in the real-time images, improve the image clarity, and make the detail features in the images more obvious. This lays a foundation for subsequent determination of whether there is scale. The preset image algorithms include SIFT (Scale-Invariant Feature Transform), Gray-Level Co-Occurrence Matrix (GLCM), and Local Binary Pattern (LBP), etc. Through the preset image algorithms, all the image features of the real-time image set can be accurately captured. The standard image features of the standard real-time image set are obtained when there is no scale in the centrifuge (or it has not been used once). Based on whether the two are equal, it is determined whether there is scale, and the real-time images different from the standard real-time image set can be accurately identified. When it is determined that there is scale in the real-time image set, the real-time images without scale are pruned and the remaining real-time images are constructed into a scale image set, avoiding the ineffective processing of a large number of irrelevant images, so as to conduct targeted analysis and processing of the scale situation. If no scale is found, the lake and river bottom mud to be processed is directly dehydrated at the centrifugal speed. Once scale is found, the centrifugal speed needs to be adjusted to make up for the problem of the decrease in the centrifuge speed caused by the scale, so as to ensure that the lake and river bottom mud reaches the required dehydration degree and avoid affecting the stability of the ecological cycle of the lake and river bottom mud due to insufficient dehydration.

[0030] In some embodiments of the present application, when dividing all scale pixel points according to the clustering center points and determining the scale score value based on the division result, it includes: determining the clustering distance between each scale pixel point and the clustering center point, presetting a first preset clustering distance and a second preset clustering distance, where the first preset clustering distance is greater than the second preset clustering distance. When the clustering distance is greater than the first preset clustering distance, dividing the scale pixel point into the first scale set; when the clustering distance is less than or equal to the first preset clustering distance and greater than or equal to the second preset clustering distance, dividing the scale pixel point into the second scale set; when the clustering distance is less than the second preset clustering distance, dividing the scale pixel point into the third scale set, and determining the scale score value based on the first scale set, the second scale set, and the third scale set.

[0031] In some embodiments of the present application, when determining the scale score value based on the first scale set, the second scale set, and the third scale set, it includes: counting the first quantity of scale pixel points in the first scale set, counting the second quantity of scale pixel points in the second scale set, counting the third quantity of scale pixel points in the third scale set, obtaining the first maximum clustering distance and the first minimum clustering distance in the first scale set, obtaining the second maximum clustering distance and the second minimum clustering distance in the second scale set, obtaining the third maximum clustering distance and the third minimum clustering distance in the third scale set, obtaining the first difference between the first maximum clustering distance and the first minimum clustering distance, obtaining the second difference between the second maximum clustering distance and the second minimum clustering distance, obtaining the third difference between the third maximum clustering distance and the third minimum clustering distance, and determining the scale score value according to the first quantity, the second quantity, the third quantity, the first difference, the second difference, and the third difference.

[0032] Specifically, the clustering center point can be determined by one of the K-means algorithm, hierarchical clustering algorithm, and spectral clustering algorithm, which is not limited herein. The method for determining the clustering distance is long and mature and will not be specifically described herein. The first preset clustering distance and the second preset clustering distance are set according to the determined clustering distance, which is also not limited herein. Constructing the first scale set, the second scale set, and the third scale set lays a foundation for determining the scale score value, and the scale score value is determined according to the following formula: ; where U represents the scale score value, K1 represents the first difference, K2 represents the second difference, K3 represents the third difference, S1 represents the first quantity, S2 represents the second quantity, and S3 represents the third quantity.

[0033] In some embodiments of the present application, when determining the determination method of the rotation speed adjustment coefficient based on the scale score value, it includes: comparing the scale score value with the scale score threshold, and determining the determination method of the rotation speed adjustment coefficient according to the comparison result. When the scale score value is greater than the scale score threshold, the first rotation speed adjustment coefficient is determined according to the historical data set. When the scale score value is less than or equal to the scale score threshold, the second rotation speed adjustment coefficient is determined based on the scale score value.

[0034] Specifically, after comparing the scale score value with the scale score threshold and determining the rotation speed adjustment coefficient according to different situations, the centrifugal rotation speed can be accurately controlled. The rotation speed adjustment coefficient includes the first rotation speed adjustment coefficient and the second rotation speed adjustment coefficient. When the scale score value is greater than the scale score threshold, the first rotation speed adjustment coefficient is determined using the historical data set. This is because at this time, the scale has a greater impact on the performance of the centrifuge. Referring to historical data can integrate past experience, quickly and reasonably adjust the centrifugal rotation speed, ensure that the centrifugal rotation speed meets the dehydration requirements, and guarantee the dehydration effect of the river and lake bottom mud. When the scale score value is less than or equal to the scale score threshold, the second rotation speed adjustment coefficient is determined based on the scale score value, which can finely adjust the centrifugal rotation speed according to the actual situation of the current scale. While ensuring the dehydration effect, it avoids unnecessary losses caused by excessive adjustment, improves the adjustment adaptability and flexibility in different degrees of scale situations, and guarantees the stability of the ecological cycle of the river and lake bottom mud.

[0035] In some embodiments of the present application, when determining the first rotation speed adjustment coefficient according to the historical data set, it includes: the historical data set includes a number of historical scale score values and a number of historical first rotation speed adjustment coefficients, and each historical scale score value corresponds to a historical first rotation speed adjustment coefficient. When there is a historical scale score value in the historical data set that is the same as the scale score value, the historical first rotation speed adjustment coefficient corresponding to the historical scale score value is used as the first rotation speed adjustment coefficient. When there is no historical scale score value in the historical data set that is the same as the scale score value, an adjustment data set is constructed based on the number of historical first rotation speed adjustment coefficients, a rotation speed adjustment model is determined according to the adjustment data set, and the first rotation speed adjustment coefficient is determined based on the rotation speed adjustment model.

[0036] Specifically, when there is a historical scale rating value in the historical dataset that is the same as the current scale rating value, the historical first rotational speed adjustment coefficient in the historical experience can be directly used as the current first rotational speed adjustment coefficient to ensure the consistency of the dehydration effect. When there is no such same historical scale rating value in the historical dataset, the first rotational speed adjustment coefficient is determined by constructing an adjustment dataset and determining a rotational speed adjustment model. The rotational speed adjustment model is obtained based on a random forest model, and the training and testing processes are consistent with those of the centrifugal rotational speed model, which will not be repeated here. By exploring the potential relationships and patterns between data, it is no longer limited to a specific historical data, but integrates multiple historical data, enabling accurate response to complex and unknown scale conditions, improving the flexibility and accuracy of adjusting the centrifugal rotational speed in various situations, thereby enhancing the efficiency and quality of treating river and lake bottom mud, and ensuring the stability of the ecological cycle.

[0037] In some embodiments of the present application, when determining the second rotational speed adjustment coefficient based on the scale rating value, it includes: presetting a first preset scale rating value and a second preset scale rating value, where the first preset scale rating value is greater than the second preset scale rating value; presetting a first preset rotational speed adjustment coefficient, a second preset rotational speed adjustment coefficient, and a third preset rotational speed adjustment coefficient, where the first preset rotational speed adjustment coefficient is greater than the second preset rotational speed adjustment coefficient, and the second preset rotational speed adjustment coefficient is greater than the third preset rotational speed adjustment coefficient. When the scale rating value is greater than or equal to the first preset scale rating value, the first preset rotational speed adjustment coefficient is used as the second rotational speed adjustment coefficient; when the scale rating value is less than the first preset scale rating value and greater than the second preset scale rating value, the second preset rotational speed adjustment coefficient is used as the second rotational speed adjustment coefficient; when the scale rating value is less than or equal to the second preset scale rating value, the third preset rotational speed adjustment coefficient is used as the second rotational speed adjustment coefficient.

[0038] Specifically, by presetting different preset scale rating values to select the corresponding preset rotational speed adjustment coefficients, the stability and flexibility of the adjustment are improved. For example, when the scale rating value is relatively high (greater than or equal to the first preset scale rating value), it indicates that the scale has a greater impact. At this time, the larger first preset rotational speed adjustment coefficient is used to adjust the centrifugal rotational speed to make up for the decrease in dehydration efficiency caused by the scale, ensuring the centrifugal requirements during the dehydration process of river and lake bottom mud, thereby improving the dehydration efficiency and quality, and further ensuring the stability of the ecological cycle.

[0039] In some embodiments of the present application, when adjusting the centrifugal rotational speed according to the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, it includes: the centrifugal rotational speed is positively correlated with the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient.

[0040] Specifically, since the centrifugal speed is positively correlated with the first speed adjustment coefficient or the second speed adjustment coefficient, the centrifugal speed can be increased according to the first speed adjustment coefficient or the second speed adjustment coefficient, thereby accelerating the dehydration speed of the river and lake bottom mud. This ensures that even when the dehydration efficiency of the river and lake bottom mud is reduced due to the influence of water scale, a high-efficiency dehydration process can still be maintained, improving the reliability of the ecological cycle and ensuring the stability of the dehydration treatment of the river and lake bottom mud.

[0041] In summary, the beneficial effects of the present invention are as follows: By obtaining the moisture content multiple times to determine the target moisture content and combining with the centrifugal speed model to set the centrifugal speed, the actual water content of the river and lake bottom mud can be fully considered, so as to accurately match the centrifugal speed required for dehydration, avoid excessive dehydration time or energy waste caused by unreasonable speed, reduce the interference of human factors, and ensure the stability of the dehydration process. Once water scale is detected, by processing and analyzing the image to determine the water scale score value and determining the method for determining the speed adjustment coefficient based on this value, the insufficient dehydration efficiency caused by the influence of water scale is effectively compensated, ensuring that the river and lake bottom mud can be effectively dehydrated, avoiding the impact on the efficiency of manufacturing "sludge cement" due to insufficient dehydration, thereby improving the stability of the ecological cycle of the river and lake bottom mud, reducing resource waste caused by inappropriate centrifugal speed, realizing the resource conversion of the river and lake bottom mud, and ensuring the stability of the ecological cycle.

[0042] In another preferred embodiment based on the above embodiments, refer to Figure 2 As shown, this embodiment provides an ecological cycle treatment system for river and lake bottom mud, which is applied to the above-mentioned ecological cycle treatment method for river and lake bottom mud, and includes: A first analysis unit, configured to obtain the moisture content of the river and lake bottom mud to be treated multiple times, determine the target moisture content of the river and lake bottom mud to be treated based on the multiple moisture contents, and determine the centrifugal speed according to the target moisture content and the centrifugal speed model.

[0043] A second analysis unit, configured to divide the centrifugal channel of the centrifuge into several monitoring areas to be monitored, obtain a real-time image set of the several monitoring areas to be monitored, determine whether there is water scale according to the real-time image set, and when it is determined that there is water scale, delete the real-time image set and determine the water scale image set according to the deletion result.

[0044] An adjustment analysis unit, configured to obtain all the water scale pixel points of the water scale image set, determine the clustering center point of the water scale image set, divide all the water scale pixel points according to the clustering center point, determine the water scale score value based on the division result, and when the water scale score value is less than or equal to the water scale score value, determine the method for determining the speed adjustment coefficient based on the water scale score value. The speed adjustment coefficient includes a first speed adjustment coefficient and a second speed adjustment coefficient.

[0045] The adjustment processing unit is configured to adjust the centrifugal speed according to the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, and dehydrate the to-be-treated river and lake bottom mud according to the adjusted centrifugal speed.

[0046] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0047] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of multiple blocks.

[0048] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of multiple blocks.

[0049] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of multiple blocks.

[0050] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: it is still possible to modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. An ecological cycle treatment method for river and lake bottom mud, characterized in that, Including: Obtain the moisture contents of the river and lake sediment to be processed for several times, determine the target moisture content of the river and lake sediment to be processed based on the several moisture contents, and determine the centrifugal speed according to the target moisture content and the centrifugal speed model; Divide the centrifugal channel of the centrifuge into several areas to be monitored, obtain the real-time image sets of the several areas to be monitored, judge whether there is scale according to the real-time image sets, when it is determined that there is scale, delete the real-time image sets, and determine the scale image set according to the deletion result; Obtain all the scale pixel points of the scale image set, and determine the clustering center point of the scale image set, divide all the scale pixel points according to the clustering center point, determine the scale score value based on the division result, and determine the determination method of the speed adjustment coefficient based on the scale score value, where the speed adjustment coefficient includes a first speed adjustment coefficient and a second speed adjustment coefficient; Adjust the centrifugal speed according to the first speed adjustment coefficient or the second speed adjustment coefficient, and dehydrate the river and lake sediment to be processed according to the adjusted centrifugal speed.

2. The ecological cycle treatment method for river and lake bottom mud according to claim 1, wherein When determining the target moisture content of the river and lake sediment to be processed based on the several moisture contents and determining the centrifugal speed according to the target moisture content and the centrifugal speed model, it includes: The target moisture content is the average value of the several moisture contents; Obtain the river and lake sediment data set, and divide the river and lake sediment data set into a training set and a test set; Use the training set to train the artificial neural network model, use the test set to test the trained artificial neural network model, and finally determine the centrifugal speed model with the target moisture content as the input and the centrifugal speed as the output; The artificial neural network model includes a BP neural network model or an RBF neural network model.

3. The ecological cycle treatment method for river and lake bottom sludge according to claim 2, characterized in that When judging whether there is scale according to the real-time image set, when it is determined that there is scale, delete the real-time image set, and determine the scale image set according to the deletion result, it includes: Preprocess the real-time image set, and the preprocessing includes image noise reduction and contrast adjustment; Use a preset image algorithm to determine the image features of the preprocessed real-time image set, and determine the standard image features of the standard real-time image set; When the image features are equal to the standard image features, it is determined that there is no scale in the real-time image set, and the river and lake sediment to be processed is dehydrated at the centrifugal speed; When the image features are not equal to the standard image features, it is determined that there is scale in the real-time image set, delete the real-time images without scale, and construct the remaining real-time images into the scale image set.

4. The ecological cycle treatment method for river and lake bottom mud according to claim 3, characterized in that, When dividing all the scale pixel points according to the clustering center point and determining the scale score value based on the division result, it includes: Determine the clustering distance between each scale pixel point and the clustering center point, and preset a first preset clustering distance and a second preset clustering distance, where the first preset clustering distance is greater than the second preset clustering distance; When the clustering distance is greater than the first preset clustering distance, divide the scale pixel point into the first scale set; When the clustering distance is less than or equal to the first preset clustering distance and greater than or equal to the second preset clustering distance, divide the scale pixel point into the second scale set; When the clustering distance is less than the second preset clustering distance, divide the scale pixel point into the third scale set; Determine the scale score value based on the first scale set, the second scale set, and the third scale set.

5. The ecological cycle treatment method for river and lake bottom mud according to claim 4, wherein, When determining the scale score value based on the first scale set, the second scale set, and the third scale set, it includes: Count the first quantity of scale pixel points in the first scale set, count the second quantity of scale pixel points in the second scale set, and count the third quantity of scale pixel points in the third scale set; Obtain the first maximum clustering distance and the first minimum clustering distance in the first scale set, obtain the second maximum clustering distance and the second minimum clustering distance in the second scale set, and obtain the third maximum clustering distance and the third minimum clustering distance in the third scale set; Obtain the first difference between the first maximum clustering distance and the first minimum clustering distance, obtain the second difference between the second maximum clustering distance and the second minimum clustering distance, and obtain the third difference between the third maximum clustering distance and the third minimum clustering distance; Determine the scale score value according to the first quantity, the second quantity, the third quantity, the first difference, the second difference, and the third difference.

6. The ecological cycle treatment method for river and lake bottom mud according to claim 5, characterized in that When determining the determination method of the rotation speed adjustment coefficient based on the scale score value, it includes: Compare the scale score value with the scale score threshold, and determine the determination method of the rotation speed adjustment coefficient according to the comparison result; When the scale score value is greater than the scale score threshold, determine the first rotation speed adjustment coefficient according to the historical data set; When the scale score value is less than or equal to the scale score threshold, determine the second rotation speed adjustment coefficient based on the scale score value.

7. The ecological cycle treatment method for river and lake bottom mud according to claim 6, characterized in that, When determining the first rotation speed adjustment coefficient according to the historical data set, it includes: The historical data set includes a number of historical scale score values and a number of historical first rotation speed adjustment coefficients, and each historical scale score value corresponds to a historical first rotation speed adjustment coefficient; When there is a historical scale score value in the historical data set that is the same as the scale score value, use the historical first rotation speed adjustment coefficient corresponding to the historical scale score value as the first rotation speed adjustment coefficient; When there is no historical scale score value in the historical data set that is the same as the scale score value, construct an adjustment data set based on a number of the historical first rotation speed adjustment coefficients, determine a rotation speed adjustment model according to the adjustment data set, and determine the first rotation speed adjustment coefficient based on the rotation speed adjustment model.

8. The ecological cycle treatment method for river and lake bottom mud according to claim 7, characterized in that, When determining the second rotation speed adjustment coefficient based on the scale score value, it includes: Preset a first preset scale score value and a second preset scale score value, and the first preset scale score value is greater than the second preset scale score value; Preset a first preset rotational speed adjustment coefficient, a second preset rotational speed adjustment coefficient, and a third preset rotational speed adjustment coefficient, where the first preset rotational speed adjustment coefficient is greater than the second preset rotational speed adjustment coefficient, and the second preset rotational speed adjustment coefficient is greater than the third preset rotational speed adjustment coefficient; When the scale score value is greater than or equal to the first preset scale score value, use the first preset rotational speed adjustment coefficient as the second rotational speed adjustment coefficient; When the scale score value is less than the first preset scale score value and greater than the second preset scale score value, use the second preset rotational speed adjustment coefficient as the second rotational speed adjustment coefficient; When the scale score value is less than or equal to the second preset scale score value, use the third preset rotational speed adjustment coefficient as the second rotational speed adjustment coefficient.

9. The ecological cycle treatment method for river and lake bottom mud according to claim 8, characterized in that When adjusting the centrifugal rotational speed according to the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, it includes: The centrifugal rotational speed is positively correlated with the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient.

10. An ecological cycle treatment system for river and lake bottom mud, which is applied to the ecological cycle treatment method for river and lake bottom mud as described in any one of claims 1-9, and is characterized in that, It includes: A first analysis unit configured to obtain several moisture contents of the to-be-treated river and lake bottom mud, determine the target moisture content of the to-be-treated river and lake bottom mud based on the several moisture contents, and determine the centrifugal rotational speed according to the target moisture content and the centrifugal rotational speed model; A second analysis unit configured to divide the centrifugal channel of the centrifuge into several regions to be monitored, obtain a real-time image set of the several regions to be monitored, determine whether there is scale according to the real-time image set, and when it is determined that there is scale, delete part of the real-time image set, and determine the scale image set according to the deletion result; An adjustment analysis unit configured to obtain all the scale pixel points of the scale image set, determine the clustering center point of the scale image set, divide all the scale pixel points according to the clustering center point, determine the scale score value based on the division result, and determine the determination method of the rotational speed adjustment coefficient based on the scale score value, where the rotational speed adjustment coefficient includes a first rotational speed adjustment coefficient and a second rotational speed adjustment coefficient; An adjustment processing unit configured to adjust the centrifugal rotational speed according to the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, and dehydrate the to-be-treated river and lake bottom mud according to the adjusted centrifugal rotational speed.

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