An ecological cycle treatment method and system for river and lake bottom sediment

Abstract

The present invention relates to the field of ecological cycle technology, and discloses an ecological cycle treatment method and system for river and lake bottom mud. The method includes: determining the centrifugal speed according to the target moisture content and the centrifugal speed model, obtaining the real-time image sets of a number of areas to be monitored, judging whether there is scale according to the real-time image sets, when it is determined that there is scale, deleting the real-time image sets, determining the scale image set according to the deletion result, dividing all scale pixel points according to the clustering center points, determining the scale score value based on the division result, determining the determination method of the speed adjustment coefficient based on the scale score value, adjusting the centrifugal speed according to the first speed adjustment coefficient or the second speed adjustment coefficient, and dehydrating the river and lake bottom mud to be treated according to the adjusted centrifugal speed. The good dynamic control of the present invention ensures the requirements of the dehydration process and improves the utilization rate of river and lake bottom mud.

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 the flood discharge of the river course, increasing the risk of flood disasters. At the same time, it 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 can't sludge cement 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., attaching 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., attaching 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:

[0006] 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;

[0007] Divide the centrifugal channels of the centrifuge into several areas to be monitored, obtain real-time image sets of several of the areas to be monitored, determine whether there is scale based on the real-time image sets, and when it is determined that there is scale, delete the real-time image sets, and determine a scale image set according to the deletion results;

[0008] 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 a scale score value based on the division results, and determine the determination method of 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;

[0009] 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.

[0010] Further, when determining the target water content rate of the to-be-treated river and lake bottom mud based on several water content rates and determining the centrifugal rotation speed according to the target water content rate and the centrifugal rotation speed model, it includes:

[0011] The target water content rate is the average value of several water content rates;

[0012] 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;

[0013] 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 water content rate as the input and the centrifugal rotation speed as the output;

[0014] The artificial neural network model includes a BP neural network model or an RBF neural network model.

[0015] Further, when determining whether there is scale based on the real-time image set, and when it is determined that there is scale, deleting the real-time image set and determining a scale image set according to the deletion results, it includes:

[0016] Preprocess the real-time image set, and the preprocessing includes image noise reduction and contrast adjustment;

[0017] 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;

[0018] 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;

[0019] 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 the scale are deleted, and the remaining real-time images are constructed into the scale image set.

[0020] Further, when dividing all scale pixel points according to the clustering center point and determining the scale score value based on the division result, it includes:

[0021] 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;

[0022] When the clustering distance is greater than the first preset clustering distance, divide the scale pixel point into the first scale set;

[0023] 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;

[0024] When the clustering distance is less than the second preset clustering distance, divide the scale pixel point into the third scale set;

[0025] Determine the scale score value based on the first scale set, the second scale set, and the third scale set.

[0026] Further, when determining the scale score value based on the first scale set, the second scale set, and the third scale set, it includes:

[0027] 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;

[0028] 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;

[0029] 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;

[0030] 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.

[0031] Further, when determining the method for determining the rotational speed adjustment coefficient based on the scale rating value, it includes:

[0032] Compare the scale rating value with the scale rating threshold, and determine the method for determining the rotational speed adjustment coefficient according to the comparison result;

[0033] When the scale rating value is greater than the scale rating threshold, determine the first rotational speed adjustment coefficient according to the historical data set;

[0034] When the scale rating value is less than or equal to the scale rating threshold, determine the second rotational speed adjustment coefficient based on the scale rating value.

[0035] Further, when determining the first rotational speed adjustment coefficient according to the historical data set, it includes:

[0036] The historical data set includes a number of historical scale rating values and a number of historical first rotational speed adjustment coefficients, and each historical scale rating value corresponds to a historical first rotational speed adjustment coefficient;

[0037] When there is a historical scale rating value in the historical data set that is the same as the scale rating value, then use the historical first rotational speed adjustment coefficient corresponding to this historical scale rating value as the first rotational speed adjustment coefficient;

[0038] When there is no historical scale rating value in the historical data set that is the same as the scale rating value, construct an adjustment data set based on the number of historical first rotational speed adjustment coefficients, determine a rotational speed adjustment model according to the adjustment data set, and determine the first rotational speed adjustment coefficient based on the rotational speed adjustment model.

[0039] Further, when determining the second rotational speed adjustment coefficient based on the scale rating value, it includes:

[0040] Preset 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;

[0041] 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;

[0042] When the scale rating value is greater than or equal to the first preset scale rating value, use the first preset rotational speed adjustment coefficient as the second rotational speed adjustment coefficient;

[0043] 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 speed adjustment coefficient is taken as the second speed adjustment coefficient;

[0044] When the scale rating value is less than or equal to the second preset scale rating value, the third preset speed adjustment coefficient is taken as the second speed adjustment coefficient.

[0045] Further, when adjusting the centrifugal speed according to the first speed adjustment coefficient or the second speed adjustment coefficient, it includes:

[0046] The centrifugal speed is positively correlated with the first speed adjustment coefficient or the second speed adjustment coefficient.

[0047] 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 moisture 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, the scale rating value is determined through the processing and analysis of the image, and the determination method of the speed adjustment coefficient is determined based on this value, effectively making up for the insufficient dehydration efficiency caused by the influence of scale, ensuring that the river and lake bottom mud can be effectively dehydrated, avoiding 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.

[0048] 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:

[0049] 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;

[0050] A second analysis unit, configured to 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;

[0051] An adjustment analysis unit, configured to obtain all the scale pixel points of the scale image set, determine the clustering center points of the scale image set, divide all the scale pixel points according to the clustering center points, determine a scale score value based on the division result, and determine a determination method for a rotation speed adjustment coefficient based on the scale score value, where the rotation speed adjustment coefficient includes a first rotation speed adjustment coefficient and a second rotation speed adjustment coefficient;

[0052] An adjustment processing unit, configured to 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.

[0053] It can be understood that the above-mentioned 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

[0054] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0055] Figure 1 is a flowchart of an ecological cycle treatment method for river and lake bottom mud provided by an embodiment of the present invention;

[0056] Figure 2 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

[0057] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the 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 fully 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.

[0058] 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:

[0059] S100: Obtain the water content of the to-be-treated river and lake bottom mud several times, determine the target water content of the to-be-treated river and lake bottom mud based on the several times of water content, and determine the centrifugal rotation speed according to the target water content and the centrifugal rotation speed model.

[0060] S200: Divide the centrifugal channels 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. 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.

[0061] S300: 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 determination method of the rotational speed adjustment coefficient based on the scale score value. The rotational speed adjustment coefficient includes a first rotational speed adjustment coefficient and a second rotational speed adjustment coefficient.

[0062] S400: 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-lake sediment according to the adjusted centrifugal rotational speed.

[0063] Specifically, in the utilization of river-lake sediment, use a cutter suction dredger to suck the slurry water of the river-lake with a certain water content, transport it through pipeline transportation operations to the sludge treatment site, filter out relatively thick fibers and gravel, and then flow into the biological homogenization tank by gravity. Inject it into the biological homogenization reaction tank with a metering pump, and use a push-flow aerator to remove part of the organic matter in the sediment to achieve the purpose of degradation and deodorization, and at the same time facilitate the dehydration of the sediment. Through the dehydration treatment of the river-lake sediment, the water content of the river-lake sediment is reduced. Part of the river-lake sediment with a lower water content is transported to the landfill site and the incineration site for landscaping purposes or building material sintering, and part is sent to the sludge storage bin for building filling, so as to achieve the multi-level utilization of the river-lake sediment.

[0064] 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 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 elaborated here. The number of moisture contents is at least five times to avoid subsequent errors caused by accidental data. Determining the centrifugal speed according to the target moisture content and the centrifugal speed model avoids the deviation caused by manual empirical setting, which can not only ensure the dehydration efficiency but also avoid energy waste or insufficient dehydration due to 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 river and lake sediment is actually placed in the centrifuge. 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 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 determine whether there is scale. When it is determined that there is scale, the real-time image set is pruned 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.

[0065] It can be understood that all the scale pixel points of the scale image set are obtained, and the clustering center point is determined. By dividing the scale pixel points, the characteristics such as the distribution, area, and density of the scale can be analyzed. Based on the division result, 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 performance of the centrifuge. Adjusting the centrifugal speed according to the determined speed adjustment coefficient enables the adjusted centrifugal speed to adapt to the requirements of the dehydration process, promoting the evaporation of water in the river and lake sediment, thereby improving the utilization rate of the river and lake sediment.

[0066] In some embodiments of the present application, when determining the target moisture content of the river and lake sediment to be treated 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. A river and lake sediment data set is obtained and divided into a training set and a test set. The artificial neural network model is trained using the training set, and the trained artificial neural network model is tested using the test set. Finally, a centrifugal speed model with the target moisture content as the input and the centrifugal speed as the output is determined. The artificial neural network model includes a BP neural network model or an RBF neural network model.

[0067] Specifically, determining the average value of the moisture content over several times as the target moisture content can comprehensively consider the actual moisture content of the river and lake bottom mud, avoiding deviations in the overall moisture judgment of the river and lake bottom mud caused by errors or fluctuations in single moisture content measurements. Establishing the correlation between the target moisture content and the centrifugal speed through an artificial neural network model can fully learn the complex relationship between the two. The river and lake bottom mud dataset includes key data such as the target moisture content, particle size distribution, pH value, and activity at different times. The river and lake bottom mud dataset is divided into a training set and a test set, which are used for model training and testing respectively. The BP neural network model or the RBF neural network model has the ability of self-learning and self-adaptation. 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, enabling it to better handle river and lake bottom mud from different sources and with different characteristics. Regardless of how the composition and properties of the bottom mud change, the finally obtained centrifugal speed model can output the centrifugal speed, making the centrifugal speed consistent with the dehydration requirements of the river and lake bottom mud, ensuring the stability and consistency of the dehydration effect of the river and lake bottom mud, and effectively avoiding human errors caused by the setting of human experience.

[0068] In some embodiments of the present application, when determining whether there is scale according to the real-time image set, and when it is determined that there is scale, when deleting the real-time image set and determining the scale image set according to the deletion result, it includes: preprocessing the real-time image set, and the preprocessing includes image noise reduction and contrast adjustment; determining the image features of the preprocessed real-time image set by using a preset image algorithm, and determining the standard image features of the standard real-time image set; when the image features are equal to the standard image features, determining that the real-time image set does not have scale, and dehydrating the river and lake bottom mud to be processed at the centrifugal speed; when the image features are not equal to the standard image features, determining that the real-time image set has scale, deleting the real-time images without scale, and constructing the remaining real-time images into a scale image set.

[0069] Specifically, preprocessing operations such as image denoising and contrast adjustment on the real-time image set can remove noise interference in the real-time images, improve image clarity, and make the detailed features in the images more obvious. This lays a foundation for subsequent judgment of the existence of 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 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 (or the centrifuge has not been used once). Based on whether they are equal, it is determined whether there is scale. Real-time images different from the standard real-time image set can be accurately identified. When it is determined that the real-time image set has scale, the real-time images without scale are deleted, and the remaining real-time images are constructed into a scale image set, avoiding 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 river-lake bottom mud to be processed is directly dehydrated according to the centrifugal speed. Once scale is found, the centrifugal speed needs to be adjusted to make up for the problem that the rotation speed of the centrifuge decreases due to scale, so as to ensure that the river-lake bottom mud reaches the required dehydration degree and avoid affecting the stability of the ecological cycle of the river-lake bottom mud due to insufficient dehydration.

[0070] In some embodiments of the present application, when dividing all scale pixel points according to the clustering center point 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, the first preset clustering distance being greater than the second preset clustering distance. When the clustering distance is greater than the first preset clustering distance, the scale pixel point is divided 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, the scale pixel point is divided into the second scale set. When the clustering distance is less than the second preset clustering distance, the scale pixel point is divided into the third scale set. The scale score value is determined based on the first scale set, the second scale set, and the third scale set.

[0071] In some embodiments of the present application, when determining the scale deposit score value based on the first scale deposit set, the second scale deposit set, and the third scale deposit set, it includes: counting the first quantity of scale deposit pixel points in the first scale deposit set, counting the second quantity of scale deposit pixel points in the second scale deposit set, counting the third quantity of scale deposit pixel points in the third scale deposit set, obtaining the first maximum clustering distance and the first minimum clustering distance in the first scale deposit set, obtaining the second maximum clustering distance and the second minimum clustering distance in the second scale deposit set, obtaining the third maximum clustering distance and the third minimum clustering distance in the third scale deposit 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 deposit score value according to the first quantity, the second quantity, the third quantity, the first difference, the second difference, and the third difference.

[0072] Specifically, the clustering center point can be determined by one of the K-means algorithm, the hierarchical clustering algorithm, and the spectral clustering algorithm, which is not limited herein. The method for determining the clustering distance is long and mature, and will not be described in detail 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 deposit set, the second scale deposit set, and the third scale deposit set lays a foundation for determining the scale deposit score value, and the scale deposit score value is determined according to the following formula:

[0073] ;

[0074] wherein, U represents the scale deposit 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.

[0075] In some embodiments of the present application, when determining the determination method of the rotation speed adjustment coefficient based on the scale deposit score value, it includes: comparing the scale deposit score value with the scale deposit score threshold, and determining the determination method of the rotation speed adjustment coefficient according to the comparison result. When the scale deposit score value is greater than the scale deposit score threshold, determining the first rotation speed adjustment coefficient according to the historical data set. When the scale deposit score value is less than or equal to the scale deposit score threshold, determining the second rotation speed adjustment coefficient based on the scale deposit score value.

[0076] Specifically, after comparing the scale deposit score value with the scale deposit score threshold, the rotational speed adjustment coefficient is determined according to different situations, which can accurately control the centrifugal rotational speed. The rotational speed adjustment coefficient includes a first rotational speed adjustment coefficient and a second rotational speed adjustment coefficient. When the scale deposit score value is greater than the scale deposit score threshold, the first rotational speed adjustment coefficient is determined using the historical data set. This is because at this time, the scale deposit has a greater impact on the performance of the centrifuge. Referring to the historical data can integrate past experience, quickly and reasonably adjust the centrifugal rotational speed, ensure that the centrifugal rotational speed meets the dehydration requirements, and guarantee the dehydration effect of the river and lake bottom mud. When the scale deposit score value is less than or equal to the scale deposit score threshold, the second rotational speed adjustment coefficient is determined based on the scale deposit score value, which can finely adjust the centrifugal rotational speed according to the actual situation of the current scale deposit. While ensuring the dehydration effect, it avoids unnecessary losses caused by over-adjustment, improves the adjustment adaptability and flexibility in different degrees of scale deposit situations, and guarantees the stability of the ecological cycle of the river and lake bottom mud.

[0077] In some embodiments of the present application, when determining the first rotational 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 this 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, a regulation data set is constructed based on a number of historical first rotational speed adjustment coefficients, a rotational speed adjustment model is determined according to the regulation data set, and the first rotational speed adjustment coefficient is determined based on the rotational speed adjustment model.

[0078] Specifically, when there is a historical scale deposit score value in the historical data set that is the same as the current scale deposit score 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 same historical scale deposit score value in the historical data set, the first rotational speed adjustment coefficient is determined by constructing a regulation data set and determining a rotational speed adjustment model. The rotational speed adjustment model is obtained based on the random forest model, and the training and testing processes are the same as those of the centrifugal rotational speed model, which will not be repeated here. By exploring the potential relationships and rules between data, it is no longer limited to a specific historical data, but integrates multiple historical data, can accurately handle complex and unknown scale deposit conditions, improves the flexibility and accuracy of adjusting the centrifugal rotational speed in various situations, thereby improving the efficiency and quality of treating the river and lake bottom mud, and ensuring the stability of the ecological cycle.

[0079] In some embodiments of the present application, when determining the second rotational speed adjustment coefficient based on the scale deposit score value, it includes: presetting a first preset scale deposit score value and a second preset scale deposit score value, where the first preset scale deposit score value is greater than the second preset scale deposit score 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 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.

[0080] Specifically, by presetting different preset scale deposit score values to select the corresponding preset rotational speed adjustment coefficients, the stability and flexibility of the adjustment are improved. For example: when the scale deposit score value is relatively high (greater than or equal to the first preset scale deposit score value), it indicates that the scale deposit 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 deposit, ensuring the centrifugal requirements during the dehydration process of river and lake bottom mud, thereby improving the dehydration efficiency and dehydration quality, and further ensuring the stability of the ecological cycle.

[0081] 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.

[0082] Specifically, since the centrifugal rotational speed is positively correlated with the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, the centrifugal rotational speed can be increased according to the first rotational speed adjustment coefficient or the second rotational speed adjustment coefficient, thereby accelerating the dehydration speed of the river and lake bottom mud. Ensure that the river and lake bottom mud can still maintain an efficient dehydration process under the condition that the dehydration efficiency is reduced due to the influence of scale deposit, improve the reliability of the ecological cycle, and ensure the stability of the dehydration treatment of the river and lake bottom mud.

[0083] 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 moisture 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, the scale score value is determined through the processing and analysis of the image, and the determination method of the speed adjustment coefficient is determined based on this value, effectively making up for the insufficient dehydration efficiency caused by the influence of scale, 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 improper centrifugal speed, realizing the resource conversion of the river and lake bottom mud, and ensuring the stability of the ecological cycle.

[0084] 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 ecological cycle treatment method for river and lake bottom mud, and includes:

[0085] The first analysis unit is 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.

[0086] The second analysis unit is configured to divide the centrifugal channel of the centrifuge into several monitoring areas to be monitored, obtain the 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.

[0087] The adjustment analysis unit is 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 when the scale score value is less than or equal to the scale score value, determine the determination method of the speed adjustment coefficient based on the scale score value. The speed adjustment coefficient includes the first speed adjustment coefficient and the second speed adjustment coefficient.

[0088] The adjustment processing unit is 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.

[0089] 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 take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can 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.) that contain computer-usable program code.

[0090] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of processes 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 means for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0091] 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 instruction means, and the instruction means implement the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0092] 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 thus the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not 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: still can modify the specific implementation manners of the present invention or make equivalent replacements, and any modification or equivalent replacement without departing 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 sediment, characterized in that, Including: Obtaining the moisture contents of the river and lake sediment to be processed for several times, 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; Dividing the centrifugal channel of the centrifuge into several areas to be monitored, obtaining the real-time image sets of the several areas to be monitored, judging whether there is scale according to the real-time image sets, when it is determined that there is scale, deleting the real-time image sets, and determining the scale image sets according to the deletion results; Obtaining all the scale pixel points of the scale image sets, and determining the clustering center points of the scale image sets, dividing all the scale pixel points according to the clustering center points, determining the scale score value based on the division results, and determining 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; Adjusting the centrifugal speed according to the first speed adjustment coefficient or the second speed adjustment coefficient, and dehydrating 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, characterized in that 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, including: The target moisture content is the average value of the several moisture contents; Obtaining a river and lake sediment data set, and dividing the river and lake sediment data set into a training set and a test set; Training an artificial neural network model with the training set, testing the trained artificial neural network model with the test set, and finally determining a 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 sets, when it is determined that there is scale, deleting the real-time image sets, and determining the scale image sets according to the deletion results, including: Preprocessing the real-time image sets, the preprocessing includes image noise reduction and contrast adjustment; Determining the image features of the preprocessed real-time image sets by using a preset image algorithm, and determining the standard image features of the standard real-time image sets; When the image features are equal to the standard image features, it is determined that there is no scale in the real-time image sets, 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 sets, deleting the real-time images without scale, and constructing the remaining real-time images into the scale image sets.

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 points and determining the scale score value based on the division results, including: 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, 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, classify the scale pixel point into the second scale set; When the clustering distance is less than the second preset clustering distance, classify 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, characterized in that, 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 sludge according to claim 6, wherein 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 according to any one of claims 1-9, and is characterized in that, It includes: A first analysis unit configured to obtain the water content of the to-be-treated river and lake sediment several times, determine the target water content of the to-be-treated river and lake sediment based on the several water contents, and determine the centrifugal rotational speed according to the target water content and the centrifugal rotational speed model; A second analysis unit configured to 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, judge 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; 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, determine the determination method of the rotational speed adjustment coefficient based on the scale score value, and 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 sediment according to the adjusted centrifugal rotational speed.

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