CN116693163A

CN116693163A - Control method, terminal and system of sludge drying system

Info

Publication number: CN116693163A
Application number: CN202310906183.2A
Authority: CN
Inventors: 冯耀忠; 冯梓睿; 陈锦标
Original assignee: Yaochangrong Phase Change Materials Technology Guangdong Co ltd
Current assignee: Yaochangrong Phase Change Materials Technology Guangdong Co ltd
Priority date: 2023-07-21
Filing date: 2023-07-21
Publication date: 2023-09-05
Anticipated expiration: 2043-07-21
Also published as: CN116693163B

Abstract

The invention provides a control method, a terminal and a system of a sludge drying system, wherein the control method of the sludge drying system comprises the following steps: before the sludge enters the dehydrator, invoking a pre-trained dehydration pattern matching model to analyze and process the sludge information, determining a dehydration pattern corresponding to the sludge information, and controlling the dehydrator to dehydrate the sludge according to the dehydration pattern; the dewatered sludge is conveyed to the input end of the conveying device, the conveying device is controlled to rotate, the second circulating pump is controlled to drive heat energy of the energy storage tank to circularly flow in the heat exchange tube so as to heat the sludge on the conveying device to obtain target sludge, the water content sensor is controlled to detect the water content of the target sludge, when the water content of the target sludge is judged to be lower than the preset water content, the target sludge is output, the sludge is dried by solar energy, environmental pollution is reduced, and the water content of the sludge is ensured to reach the standard and be output.

Description

Control method, terminal and system of sludge drying system

Technical Field

The invention relates to the technical field of sludge drying, in particular to a control method, a terminal and a system of a sludge drying system.

Background

The sludge is used as the residual product of municipal sewage treatment plants in the sewage treatment process, has higher water content, huge volume, easy decay and odor malodor, and can be accompanied with toxic and harmful substances such as heavy metals, germs and the like. If the sludge is directly discharged to the external environment without treatment, the sludge can cause great harm to surface water, underground water, soil and air, and finally the adverse effect on the human health and the whole environment is brought. Therefore, it is important to perform reduction, stabilization and harmless treatment on the sludge.

Sludge drying refers to heating sludge by using heat energy, and reducing the water content in the sludge. The existing sludge drying system generally utilizes methane heat energy, waste and sludge incineration waste heat generated in the anaerobic digestion process of sludge, waste heat of a power plant or other waste heat as a heat source for sludge drying treatment, so that the environmental pollution is large, the water content of dried sludge is difficult to ensure to reach the standard, and the sludge drying effect is poor.

In the technical scheme with the application number of CN202210901801.X, although the water content, the sludge conveying flow and the hydrophobic capacity of the sludge before and after entering the sludge drier can be utilized for measurement, the measurement result is only used for judging whether the sludge drier works normally or not, and the water content of the sludge cannot be ensured to reach the standard.

Disclosure of Invention

The invention provides a control method, a terminal and a system of a sludge drying system, which are used for drying sludge by using a clean heat source, reducing environmental pollution and ensuring that the water content of the sludge reaches the standard.

In order to solve the problems, the invention adopts the following technical scheme:

the invention provides a control method of a sludge drying system, which is applied to a control center of the sludge drying system, wherein the sludge drying system further comprises an energy storage tank, a first circulating pump, a second circulating pump, a solar heat collector, a dehydrator, a heat exchange tube, a waste heat recovery device, a conveying device and a sensor, wherein the input end of the energy storage tank is connected with the output end of the solar heat collector, the first circulating pump is further connected between the energy storage tank and the solar heat collector, the output end of the energy storage tank is connected with the heat exchange tube through the second circulating pump, the heat exchange tube is positioned below the conveying device, the input end of the conveying device is adjacent to the output end of the dehydrator, the control center is respectively and electrically connected with the first circulating pump, the second circulating pump, the solar heat collector, the dehydrator, the conveying device and the sensor, the solar heat collector is used for converting solar energy into heat energy by utilizing solar radiation energy, the energy storage tank is used for storing the heat energy, the first circulating pump is used for driving the solar energy to flow into the heat energy, and the heat energy flows into the heat exchange tube through the second circulating pump; the control method of the sludge drying system comprises the following steps:

Before sludge enters a dehydrator, receiving sludge information of the sludge acquired by a sensor, calling a pre-trained dehydration pattern matching model to analyze and process the sludge information, determining a dehydration pattern corresponding to the sludge information, controlling the dehydrator to dehydrate the sludge according to the dehydration pattern, and conveying the dehydrated sludge to an input end of a conveying device; the sludge information comprises initial water content, solid particle size, solid particle concentration, density and viscosity, the sensor comprises a water content sensor, a particle size sensor, a concentration sensor, a density sensor and a viscosity sensor, and the dehydration pattern matching model is a neural network model and is used for matching corresponding dehydration patterns according to different sludge information;

controlling the conveying device to rotate, and controlling the second circulating pump to drive heat energy of the energy storage tank to circularly flow in the heat exchange tube so as to heat sludge on the conveying device to obtain target sludge; the conveying device comprises a plurality of conveying belts, each conveying belt is arranged at equal intervals from top to bottom, and the input end of the conveying belt positioned below is protruded from the output end of the conveying belt positioned above and adjacent to the conveying belt;

And controlling a water content sensor to detect the water content of the target sludge, and outputting the target sludge when the water content of the target sludge is judged to be lower than a preset water content.

Preferably, the sludge drying system further comprises a condenser and an evaporator, wherein the output end of the heat exchange tube is respectively connected with the input end of the energy storage tank and one input end of the condenser, the other input end of the condenser is connected with the output end of the energy storage tank, the output end of the condenser is connected with the input end of the evaporator through an expansion valve or a compressor, the output end of the evaporator is communicated with the reservoir through a pipeline, the condenser is used for cooling gas or steam and converting the gas or steam into liquid, and the evaporator is used for converting the liquid into steam or gas.

Further, before the step of calling the pre-trained dehydration pattern matching model to analyze and process the sludge information and determining the dehydration pattern corresponding to the sludge information, the method further comprises the following steps:

acquiring a training sample data set; the training sample data set comprises a plurality of training samples, and each training sample comprises a group of sludge information samples and a corresponding standard dehydration mode;

Dividing the training sample data set into a plurality of sub-data sets; wherein each sub-data set contains at least two training samples;

randomly extracting a training sample from each sub-data set to serve as a target training sample, and obtaining K target training samples; wherein K is a positive integer greater than 1;

randomly selecting the K target training samples to obtain N groups of training sets; wherein, N is a positive integer greater than 1, each group of training sets comprises a plurality of target training samples, and the number of the target training samples of each group of training sets is the same but not repeated;

training the N groups of training sets according to a preset decision tree algorithm to obtain N trained classification models, and respectively calculating the loss value of each trained classification model by utilizing a multi-classification cross entropy loss function;

comparing the loss value of each trained classification model with a target loss value respectively, screening classification models with loss values lower than the target loss value, and obtaining a plurality of first classification models;

sorting the plurality of first classification models according to the sequence from the low loss value to the high loss value to obtain a sorting result;

and screening the first classification model arranged in the front M bits according to the sorting result to obtain at least two target classification models, and combining at least two target classification models to obtain a dehydration pattern matching model.

Preferably, the step of dividing the training sample data set into a plurality of sub-data sets comprises:

randomly selecting a plurality of training samples from the training sample data set to obtain a plurality of reference training samples;

taking each reference training sample as a clustering center, and taking the rest training samples which are not selected as training samples to be distributed;

determining labels of the reference training samples in each cluster center, obtaining the reference labels of each cluster center, and determining the labels of each training sample to be distributed;

converting the reference label of each clustering center into a vector by utilizing single-hot coding to obtain a plurality of reference vectors;

converting the label of each training sample to be distributed into vectors by utilizing the single-hot coding to obtain a plurality of vectors;

calculating the cosine distance between each vector and each reference vector, determining the reference vector with the maximum cosine distance between each vector, and distributing training samples to be distributed corresponding to each vector to the clustering center corresponding to the reference vector with the maximum cosine distance to obtain a plurality of sub-data sets; wherein each sub-data set contains a set of similar training samples.

Preferably, the step of calling a pre-trained dehydration pattern matching model to analyze and process the sludge information and determining a dehydration pattern corresponding to the sludge information includes:

Setting a target water content of the sludge;

invoking a pre-trained dehydration pattern matching model to determine at least one parameter affecting the target water content, and constructing an initial function formula according to at least one parameter; wherein the parameters comprise the rotating speed of the dehydrator and the dehydration time length;

setting an initial value of each parameter, substituting the initial value of each parameter into the initial function formula, and carrying out iterative calculation for at least one parameter for preset times on the basis of the initial value by utilizing a parallel genetic algorithm; wherein, the value of any at least one parameter is adjusted during each iteration, and the initial function formula is adjusted according to the value of each parameter after each iteration;

inputting the sludge information into an adjusted initial function formula to calculate a first water content after each iteration, and judging whether the first water content is lower than the target water content;

when the first water content is determined to be lower than the target water content, outputting the numerical value of each parameter after the last iteration, taking the numerical value of each parameter after the last iteration as a target numerical value, and formulating a dehydration mode according to the target numerical value of each parameter; wherein, the dehydration mode comprises the optimal rotation speed and the optimal dehydration time length of the dehydrator;

And when the first water content is not lower than the target water content, returning to execute the step of carrying out iterative computation on at least one parameter for preset times on the basis of the initial value by using a parallel genetic algorithm until the first water content is lower than the target water content or the iterative times reach the preset times.

Preferably, the step of performing iterative computation of at least one of the parameters for a preset number of times based on the initial values using a parallel genetic algorithm includes:

encoding the numerical value of each parameter during each iteration to obtain a plurality of target codes;

performing crossover and/or mutation operations on the plurality of target codes;

acquiring adjustment values of the parameters after the crossover and/or mutation operation;

and adjusting the initial function formula according to the adjustment value of each parameter after the crossover and/or mutation operation.

invoking a pre-trained dehydration pattern matching model to convert the sludge information into a matrix to obtain a standard matrix;

Randomly initializing two matrixes by using a Gaussian distribution function to obtain a first initial matrix and a second initial matrix;

judging whether the product of the first initial matrix and the second initial matrix is equal to the standard matrix or not;

when the product of the first initial matrix and the second initial matrix is not equal to the standard matrix, continuously updating the first initial matrix and the second initial matrix according to a method for minimizing reconstruction errors until the product of the first initial matrix and the second initial matrix is equal to the standard matrix, and obtaining a first target matrix and a second target matrix;

converting the first target matrix and the second target matrix into low-dimensional characteristic representations by using a principal component analysis method to obtain sludge characteristics of the sludge information;

and analyzing and processing the sludge characteristics to determine a dehydration mode corresponding to the sludge characteristics.

Further, after the step of detecting the water content of the target sludge by the water content control sensor, the method further comprises:

when the water content of the target sludge is not lower than the preset water content, calculating a difference value between the preset water content and the water content;

controlling a cutting device to cut the target sludge into a plurality of target sludge blocks on average;

Estimating the drying time length required by each target sludge block according to the difference value, and adjusting the rotating speed of a conveyor belt in the conveyor according to the drying time length to obtain a target rotating speed;

and re-conveying the multi-item standard sludge blocks to the input end of the conveying device, and drying the multi-item standard sludge blocks according to the target rotating speed until the water content of the target sludge is lower than the preset water content.

The invention provides a terminal comprising a memory and a processor, wherein the memory stores computer readable instructions which, when executed by the processor, cause the processor to execute the steps of the method for controlling a sludge drying system as described in any one of the above.

The invention also provides a sludge drying system, which comprises a control center, an energy storage tank, a first circulating pump, a second circulating pump, a solar heat collector, a dehydrator, a heat exchange tube, a waste heat recovery device, a conveying device and a sensor, wherein the input end of the energy storage tank is connected with the output end of the solar heat collector; the control center comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the control method of the sludge drying system according to any one of the above.

Compared with the prior art, the technical scheme of the invention has at least the following advantages:

according to the control method, the terminal and the system of the sludge drying system, before sludge enters the dehydrator, the sludge information acquired by the sensor is received, the pre-trained dehydration pattern matching model is called to analyze and process the sludge information, the dehydration pattern corresponding to the sludge information is determined, the dehydrator is controlled to dehydrate the sludge according to the dehydration pattern, so that the proper dehydration pattern is automatically matched in an artificial intelligent mode according to different sludge information, the dehydration effect of the sludge is improved, and the subsequent sludge drying burden is reduced; the dehydrated sludge is conveyed to the input end of the conveying device, the conveying device is controlled to rotate, the second circulating pump is controlled to drive heat energy of the energy storage tank to circularly flow in the heat exchange tube so as to heat the sludge on the conveying device to obtain target sludge, the conveying device, the heat exchange tube and the output end of the dehydrator are sealed in the cavity through a plurality of sealing walls so as to avoid heat energy loss, and at least one sealing wall is provided with a through hole which is communicated with the cavity and the waste heat recovery device so as to recycle waste heat in the cavity, thereby saving resources; in addition, conveyer includes many conveyer belts, every conveyer belt is equidistant setting from top to bottom, and the input of conveyer belt that is located the below is more than the output that is located the top and adjacent conveyer belt protrusion, in order to ensure that the mud above can accurately fall into below and adjacent conveyer belt, the moisture content of control moisture sensor detects the moisture content of target sludge at last, when judging that the moisture content of target sludge is less than the preset moisture content, output the target sludge, in order to utilize this clean heat source desiccation mud of solar energy, reduce environmental pollution, and detect the moisture content of the target sludge after the desiccation through the moisture content sensor, ensure that the moisture content of mud reaches standard and just output.

Drawings

FIG. 1 is a block flow diagram of one embodiment of a method for controlling a sludge drying system of the present invention;

FIG. 2 is a block diagram of an embodiment of a sludge drying system of the present invention;

FIG. 3 is a block diagram of one embodiment of a control device for a sludge drying system in accordance with the present invention;

fig. 4 is a block diagram illustrating an internal structure of a terminal according to an embodiment of the present invention.

Detailed Description

In order to enable those skilled in the art to better understand the present invention, the following description will make clear and complete descriptions of the technical solutions according to the embodiments of the present invention with reference to the accompanying drawings.

In some of the flows described in the specification and claims of the present invention and in the foregoing figures, a plurality of operations appearing in a particular order are included, but it should be clearly understood that the operations may be performed in other than the order in which they appear herein or in parallel, the sequence numbers of the operations such as S11, S12, etc. are merely used to distinguish between the various operations, and the sequence numbers themselves do not represent any order of execution. In addition, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first" and "second" herein are used to distinguish different messages, devices, modules, etc., and do not represent a sequence, and are not limited to the "first" and the "second" being different types.

As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless expressly stated otherwise, as understood by one of ordinary skill in the art. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. The term "and/or" as used herein includes all or any element and all combination of one or more of the associated listed items.

It will be understood by those of ordinary skill in the art that unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to fall within the scope of the invention.

Referring to fig. 1, in combination with fig. 2, the present invention provides a control method of a sludge drying system, which is applied to a control center (not shown in fig. 2) of the sludge drying system, wherein the control center may be a computer device, a server or a server cluster, the sludge drying system further includes an energy storage tank 1, a first circulation pump 2, a second circulation pump 3, a solar heat collector 4, a dehydrator 5, a heat exchange tube 6, a waste heat recovery device 7, a transmission device 8 and a sensor, one input end of the energy storage tank 1 is connected with an output end of the solar heat collector 4, one output end of the energy storage tank 1 is connected with an input end of the solar heat collector 4, the first circulation pump 2 is further connected between the energy storage tank 1 and the solar heat collector 4, the output end of the energy storage tank 1 is connected with the heat exchange tube 6 through the second circulating pump 3, the heat exchange tube 6 is positioned below the conveying device, the input end of the conveying device is bordered with the output end of the dehydrator 5 and is used for receiving sludge falling into the conveying device 8, the control center is respectively and electrically connected with the first circulating pump 2, the second circulating pump 3, the solar heat collector 4, the dehydrator 5, the conveying device 8 and a sensor, the sensor is used for collecting sludge information of the sludge, the solar heat collector 4 is used for converting solar energy into heat energy by utilizing solar radiation energy, the heat energy is stored or transmitted in a heat conducting medium form, the heat conducting medium comprises water or oil, the energy storage tank 1 is used for storing the heat energy, the first circulating pump 2 is used for driving the heat energy of the solar heat collector 4 to flow into the energy storage tank 1, the second circulating pump 3 is used for driving the heat energy of the energy storage tank 1 to flow in the heat exchange tube 6 so as to heat the sludge on the conveyor belt and dry the sludge.

The waste heat recovery device 7 is a device for recovering and reutilizing waste heat generated in an industrial process or heat energy in flue gas. It can help to improve the energy utilization efficiency and reduce the energy consumption and environmental pollution. The method specifically comprises the following structures:

heat exchanger: the heat exchanger is the core component of the waste heat recovery device 7 for effecting the transfer of thermal energy. Through the heat exchanger, the heat energy in the waste heat or flue gas can be transferred to other media (such as water, air or steam) for use in heating, hot water or other heat energy demands.

Flue gas purifying equipment: in the waste heat recovery device 7, the flue gas cleaning apparatus is used for treating solid particulate matters, harmful gases and other pollutants in the waste flue gas, so as to ensure that the recovered heat energy does not pollute the environment.

A heat storage device: the heat storage device is used for storing the recovered heat energy so as to supply heat when needed. It may be in the form of a hot water storage tank, a heat medium storage tank, etc. for balancing the time difference between supply and demand.

Piping and valve systems: for connecting heat exchangers, flue gas cleaning equipment, heat storage devices and other components to form a complete thermal energy transfer path.

The heat exchange tube 6 is a kind of pipe for transferring heat, and is generally used in a heat exchanger or a heat exchange apparatus. Its main function is to transfer heat from one medium to another, realizing transfer and utilization of heat energy. The heat exchange tube 6 is generally made of a metal material such as copper, stainless steel, or the like to have good heat conductivity and corrosion resistance. The heat exchange tubes 6 often transfer heat internally by a fluid. In a heat exchanger, the heat source medium flows through a pipe on one side, and the medium to be heated or cooled flows through a pipe on the other side. Heat can be transferred from the heat source medium to the medium being heated or cooled by conduction and convection through the walls of the heat exchange tubes 6.

The control method of the sludge drying system comprises the following steps:

s11, before sludge enters a dehydrator, receiving sludge information of the sludge acquired by a sensor, calling a pre-trained dehydration pattern matching model to analyze and process the sludge information, determining a dehydration pattern corresponding to the sludge information, controlling the dehydrator to dehydrate the sludge according to the dehydration pattern, and conveying the dehydrated sludge to an input end of a conveying device; the sludge information comprises initial water content, solid particle size, solid particle concentration, density and viscosity, the sensor comprises a water content sensor, a particle size sensor, a concentration sensor, a density sensor and a viscosity sensor, and the dehydration pattern matching model is a neural network model and is used for matching corresponding dehydration patterns according to different sludge information;

S12, controlling the conveying device to rotate, and controlling the second circulating pump to drive heat energy of the energy storage tank to circularly flow in the heat exchange tube so as to heat sludge on the conveying device to obtain target sludge; the conveying device comprises a plurality of conveying belts, each conveying belt is arranged at equal intervals from top to bottom, and the input end of the conveying belt positioned below is protruded from the output end of the conveying belt positioned above and adjacent to the conveying belt;

s13, controlling a water content sensor to detect the water content of the target sludge, and outputting the target sludge when the water content of the target sludge is judged to be lower than a preset water content.

As described in the above step S11, before the sludge enters the dehydrator 5, the sensor first detects the sludge to obtain sludge information, and sends the sludge information to the control center, and the control center receives the sludge information of the sludge collected by the sensor, and analyzes and processes the sludge information according to a preset algorithm or model. Based on the characteristics of the sludge, the system can determine a corresponding dewatering pattern. Sludge information may include, but is not limited to, the following:

Initial water content: the proportion of water in the sludge.

Solid particle size: the size range of the solid particles in the sludge.

Concentration of solid particles: concentration of solid particles in the sludge.

pH value: acid-base of sludge.

Organic matter content: organic matter content in the sludge.

Content of suspended matter: the content of suspended particles in the sludge.

Specific gravity: density of sludge.

Viscosity: the degree of sludge thickening.

The sensor may include, but is not limited to, the following:

a water content sensor: the device is used for measuring the moisture content in the sludge and comprises a resistance type sensor, a microwave sensor, an infrared sensor and the like.

Concentration sensor: the device is used for measuring the concentration of solid particles in sludge and comprises a suspended matter concentration sensor, a turbidity sensor, a laser scattering sensor and the like.

pH sensor: is used for measuring the acid-base property of the sludge. The pH sensor can provide pH value information of the sludge and is used for judging condition adjustment and control in the dehydration process.

Temperature sensor: for measuring the temperature of the sludge. The temperature sensor can provide temperature information of the sludge and is used for controlling the operation of the dewatering equipment and optimizing the dewatering effect.

Particle size sensor: the method is used for measuring the size of solid particles in the sludge and comprises a laser particle analyzer, an image analyzer, an ultrasonic sensor and the like.

Gas sensor: is used for detecting the gas component in the sludge. For example, gas sensors may be used to measure the oxygen, ammonia, etc. gas content in the sludge to understand the gas characteristics of the sludge.

A density sensor: for measuring the density of sludge, i.e. the mass per unit volume, including pressure sensors, vibrating tube densitometers, radiodensitometers, etc.

Viscosity sensor: for measuring the viscosity of sludge, i.e. the viscosity of a fluid, including rotary viscometers, oscillating viscometers, pressure drop viscometers, and the like.

In this embodiment, a pre-trained dehydration pattern matching model is called to analyze and process sludge information, a dehydration pattern corresponding to the sludge information is determined, the dehydrator 5 is controlled to dehydrate sludge according to the dehydration pattern, the dehydrated sludge is conveyed to the input end of the conveying device 8, and in the sludge dehydration process, the control center can automatically adjust the rotation speed of the dehydrator 5 according to the dehydration pattern, and in particular, the rotation speed adjustment can be realized by adjusting the output frequency of a motor or controlling the opening and closing of a valve. In addition, the operation state and the dewatering effect of the dewatering machine 5 can be continuously monitored. If the dewatering effect is found to be undesirable, the control center automatically adjusts the rotational speed or other parameters to optimize the dewatering effect.

For example, assume that the collected sludge information shows a higher water content, smaller solid particles, and lower concentration. According to the analysis processing of the dehydration pattern matching model, the control center judges that a higher rotating speed is required to realize effective dehydration, automatically adjusts the rotating speed of the dehydrator 5, and continuously optimizes the rotating speed in real-time monitoring to achieve the optimal dehydration effect.

As described in the above steps S12-S13, the output ends of the conveying device 8, the heat exchange tube 6 and the dehydrator 5 are sealed in the cavity by a plurality of packaging walls, the packaging walls include a heat insulation layer to avoid heat dissipation, and at least one packaging wall is provided with a through hole for communicating the cavity with the waste heat recovery device 7 to recover and utilize the waste heat in the cavity.

The conveyor 8 comprises a plurality of conveyor belts, each conveyor belt is arranged at equal intervals from top to bottom, and the input end of the conveyor belt positioned below is protruded from the output end of the conveyor belt positioned above and adjacent to the conveyor belt, so that the sludge heated above can accurately fall into the input end of the conveyor belt positioned below, and the sludge is continuously heated until being output from the output end of the conveyor belt positioned below.

The control center of the present embodiment controls the rotation of the conveyor 8, and the rotation directions of the adjacent two conveyor belts are different, for example, assuming that the rotation direction of the uppermost conveyor belt is clockwise, the rotation direction of the second upper conveyor belt is counterclockwise, and so on.

The control center controls the second circulating pump 3 to drive the heat energy of the energy storage tank 1 to circularly flow in the heat exchange tube 6 so as to heat the sludge on the conveying device 8, dry the sludge and obtain target sludge, controls the water content sensor to detect the water content of the target sludge, and outputs the target sludge when the water content of the target sludge is judged to be lower than the preset water content, so that the sludge with the water content reaching the standard is obtained. The preset water content can be set in a self-defined manner, for example, 10%.

According to the control method of the sludge drying system, before sludge enters the dehydrator 5, the sludge information acquired by the sensor is received, the pre-trained dehydration mode matching model is called to analyze and process the sludge information, the dehydration mode corresponding to the sludge information is determined, the dehydrator 5 is controlled to dehydrate the sludge according to the dehydration mode, so that the proper dehydration mode is automatically matched in an artificial intelligent mode according to different sludge information, the dehydration effect of the sludge is improved, and the subsequent sludge drying burden is reduced; the dehydrated sludge is conveyed to the input end of a conveying device 8, the conveying device 8 is controlled to rotate, the second circulating pump 3 is controlled to drive heat energy of the energy storage tank 1 to circularly flow in the heat exchange tube 6 so as to heat the sludge on the conveying device 8 to obtain target sludge, the conveying device 8, the heat exchange tube 6 and the output end of the dehydrator 5 are sealed in a cavity through a plurality of sealing walls so as to avoid heat energy loss, and at least one sealing wall is provided with a through hole for communicating the cavity with the waste heat recovery device 7 so as to recycle waste heat in the cavity, thereby saving resources; in addition, the conveying device 8 comprises a plurality of conveying belts, each conveying belt is arranged at equal intervals from top to bottom, the input end of the conveying belt positioned below is protruded from the output end of the conveying belt positioned above and adjacent to each other, so that the sludge above can accurately fall into the conveying belt below and adjacent to each other, the water content sensor is finally controlled to detect the water content of the target sludge, when the water content of the target sludge is judged to be lower than the preset water content, the target sludge is output, the solar energy is utilized as a clean heat source for drying the sludge, the environmental pollution is reduced, the water content of the dried target sludge is detected through the water content sensor, and the water content of the sludge is ensured to reach the standard and be output.

In one embodiment, the sludge drying system further comprises a plurality of valves, a condenser 9 and an evaporator 12, wherein each valve can be installed on a pipeline according to the requirement and is used for adjusting the flow direction of a heat conducting medium, the output end of the heat exchange tube 6 is respectively connected with the input end of the energy storage tank 1 and one input end of the condenser 9, the other input end of the condenser 9 is connected with the output end of the energy storage tank 1 so as to discharge the redundant heat energy of the energy storage tank 1, the output end of the condenser 9 is connected with the input end of the evaporator 12 through an expansion valve 10 or a compressor 11, the output end of the evaporator 12 is communicated with a reservoir or a drainage canal through a pipeline, a third circulating pump 13 is installed on a communicating pipeline between the evaporator 12 and the reservoir, the condenser 9 is used for cooling and converting gas or steam into liquid, and the evaporator 12 is used for converting the liquid into steam or gas.

The condenser 9 is a device for cooling and converting a gas or a vapor into a liquid, among others. It extracts heat from the gas or vapor by a heat transfer process, which cools it to a temperature at saturation or supersaturation, thereby condensing the gas or vapor into a liquid.

The condenser 9 is typically composed of piping, heat exchange tubes 6 bundles and a cooling medium. In operation, gas or steam flows through the tubes or heat exchange tubes 6 of the condenser 9, and a cooling medium (such as cold water or cooling air) flows outside the tubes or tube bundles, removing heat from the gas or steam by heat transfer.

The principle of operation of the condenser 9 is based on the principles of heat transfer and convective heat transfer. By contact with the cooling medium, heat is transferred from the gas or vapor to the cooling medium, and heat is carried away by convective heat transfer. As heat is lost, the temperature of the gas or vapor gradually decreases until a saturated or supersaturated state is reached, and condensation occurs to form a liquid.

The evaporator 12 is a device for converting a liquid into a vapor or gas. It heats the liquid by providing heat, causing it to evaporate into a vapor or gaseous state. The evaporator 12 is generally comprised of a heated surface, an evaporation chamber, and an evaporation medium. The liquid flows or sprays through the heated surfaces of the evaporator 12 and is subjected to the heat provided by the heated surfaces, thereby warming and gradually evaporating. An evaporating medium (e.g., air or other gas) flows through the evaporating chamber, contacting the liquid and removing heat and vapor released during evaporation.

The principle of operation of the evaporator 12 is based on the principle of evaporation of the liquid and heat transfer. When the liquid contacts the heating surface, heat is transferred from the heating surface to the liquid, causing its temperature to rise. As the temperature increases, the molecular energy of the liquid increases and a portion of the liquid molecules will break away from the liquid surface, forming a vapor or gas. The vapor or gas contacts and mixes with the evaporating medium, eventually forming a mixture of vapor or gas.

The expansion valve 10 is a device for controlling the flow of refrigerant in a refrigeration system. It is typically installed between the evaporator 12 and the condenser 9 of the refrigeration system, and serves to regulate the flow of refrigerant. The main function of the expansion valve 10 is to control the flow of refrigerant by regulating the pressure differential in the refrigeration system. When high pressure refrigerant flows from the condenser 9 into the expansion valve 10, the valve adjusts the size of the passage according to the system demand, thereby controlling the flow rate of the refrigerant. By the control of the expansion valve 10, the refrigerant can expand and evaporate in the evaporator 12, absorb heat and reduce temperature, achieving a refrigerating effect.

The compressor 11 is a device for compressing gas or vapor to a high pressure. It compresses a gas or vapor from a low pressure state to a high pressure state by providing mechanical energy for processing or utilization in a subsequent process. The compressor 11 is typically composed of an electric motor, a compressor 11 head, a control system, and the like. The motor provides mechanical energy to drive the compressor 11 head to compress the gas or vapor. The compressor 11 head includes a compression chamber, a cylinder, a piston, and the like, gradually compresses gas or vapor by reciprocating motion, and pushes it into a high-pressure gas tank or other apparatus.

In one embodiment, before the step of calling the pre-trained dehydration pattern matching model to analyze and process the sludge information and determining the dehydration pattern corresponding to the sludge information, the method further includes:

In the embodiment, the neural network model is trained by using the training sample, so as to obtain the dehydration pattern matching model. Specifically, the control center firstly acquires a training sample data set, the more the data volume of the training sample data set is, the better the training effect of the neural network model is, the training sample data set comprises a plurality of training samples, each training sample comprises a group of sludge information samples and a corresponding standard dehydration mode, the sludge information samples can comprise water content, solid particle size, solid particle concentration and the like, and the standard dehydration mode comprises the optimal dehydration rotating speed and the optimal dehydration duration of the dehydrator 5.

The training sample data set is divided into a plurality of sub-data sets, each sub-data set comprising at least two training samples, e.g. the training sample data set is divided into three sub-data sets, the first sub-data set comprising two training samples, the second sub-data set comprising three training samples, the third sub-data set comprising three training samples, and the training samples of each sub-data set are not repeated. Then randomly extracting a training sample from each sub-data set as a target training sample to obtain K target training samples, for example, extracting a training sample A from the first sub-data set as a target training sample, extracting a training sample B from the second sub-data set as a target training sample, extracting a training sample C from the third sub-data set as a target training sample, and extracting a training sample D from the fourth sub-data set as a target training sample to obtain four target training samples A, B, C, D.

The K target training samples are randomly selected to obtain N sets of training sets, where each set of training sets includes a plurality of target training samples, and the number of target training samples in each set of training sets is the same but not repeated, for example, the target training samples A, B may be selected to form a set of training sets, and the target training samples C, D may be selected to form a set of training sets, so as to obtain two sets of training sets.

Training N groups of training sets according to a preset decision tree algorithm to obtain N trained classification models, calculating the loss value of each trained classification model by utilizing a multi-classification cross entropy loss function, comparing the loss value of each trained classification model with a target loss value, and screening classification models with loss values lower than the target loss value to obtain a plurality of first classification models.

The decision tree algorithm is a supervised learning algorithm and is used for solving the problems of classification and regression. It predicts or classifies new input data by constructing a tree structure to represent the decision rules of the data. The decision tree is composed of nodes and edges, wherein the nodes represent features or attributes, and the edges represent branches of feature values or attributes. The root node represents the most important feature, the internal node represents the intermediate feature, and the leaf node represents the final prediction result or class label.

The multi-class cross entropy loss function is a loss function that is used to solve the multi-class classification problem. The method is used for measuring the difference between the model prediction result and the real label and is used as an optimization target to adjust the model parameters.

And finally, sorting the plurality of first classification models according to the sequence of the loss values from small to large to obtain a sorting result, screening the first classification models ranked in the previous M bits according to the sorting result to obtain at least two target classification models, and combining at least two target classification models to obtain a dehydration pattern matching model so as to improve the training effect of the dehydration pattern matching model. For example, the first classification model with the loss value arranged in the first two positions can be selected from the plurality of first classification models to serve as a target classification model, and after the two target classification models are spliced, a dehydration mode matching model is obtained and is used for automatically matching a proper dehydration mode according to sludge information, so that the dehydration effect is improved.

In one embodiment, the step of dividing the training sample data set into a plurality of sub-data sets comprises:

In this embodiment, a plurality of training samples are randomly selected from a training sample data set to obtain a plurality of reference training samples, each reference training sample is used as a clustering center, and the remaining training samples which are not selected are used as training samples to be distributed. And then determining the label of the reference training sample in each clustering center, obtaining the reference label of each clustering center, and determining the label of each training sample to be distributed, wherein the label can be high in water content, high in solid particle or high in solid particle concentration.

The control center converts the reference label of each cluster center into a vector by utilizing the single thermal coding to obtain a plurality of reference vectors, and converts the label of each training sample to be distributed into the vector by utilizing the single thermal coding to obtain a plurality of vectors.

The single-hot coding is a data coding technology, and is used for converting discrete characteristics into numerical representations which can be processed by a machine learning algorithm.

In one-hot encoding, discrete features with S different values are encoded into a binary vector of length S. In the binary vector, only the element at the position corresponding to the feature value is 1, and the elements at the other positions are all 0.

For example, assume that there is a discrete feature "color", with possible values of red, blue and green. The process of converting these values into binary vectors using one-hot encoding is as follows:

the red code is [1, 0]

Blue code is [0,1,0]

The green code is [0, 1]

By single-hot encoding, each discrete feature will be represented as a vector with only one element being 1 and the remaining elements being 0. Such an encoding scheme facilitates machine learning algorithms to better understand and process discrete features.

And finally, calculating the cosine distance between each vector and each reference vector, determining the reference vector with the maximum cosine distance between each vector, distributing the training samples to be distributed corresponding to each vector to the clustering center corresponding to the reference vector with the maximum cosine distance, and obtaining a plurality of sub-data sets, wherein each sub-data set comprises a group of similar training samples so as to distribute the similar training samples to the same data set, thereby improving the subsequent training effect. For example, if the reference vector having the largest cosine distance from the vector A1 is A1, determining that the reference vector is a cluster center Q1 corresponding to A1, and distributing the training sample to be distributed corresponding to the vector A1 to the cluster center Q1 corresponding to the reference vector A1; if the reference vector with the largest cosine distance from the vector A2 is A2, determining that the reference vector is a clustering center Q2 corresponding to the A2, and distributing training samples to be distributed, corresponding to the vector A2, to the clustering center Q2 corresponding to the reference vector A2.

In one embodiment, the step of calling a pre-trained dehydration pattern matching model to analyze and process the sludge information and determining a dehydration pattern corresponding to the sludge information includes:

setting a target water content of the sludge;

invoking a pre-trained dehydration pattern matching model to determine at least one parameter affecting the target water content, and constructing an initial function formula according to at least one parameter; wherein the parameters comprise the rotating speed of the dehydrator 5 and the dehydration time period;

when the first water content is determined to be lower than the target water content, outputting the numerical value of each parameter after the last iteration, taking the numerical value of each parameter after the last iteration as a target numerical value, and formulating a dehydration mode according to the target numerical value of each parameter; wherein, the dehydration mode comprises the optimal rotation speed and the optimal dehydration time length of the dehydrator 5;

In this embodiment, the target water content of the sludge may be set to 10%, for example, and then a pre-trained dehydration pattern matching model is invoked to obtain parameters affecting the target water content in a centralized manner, and an initial function formula is constructed according to at least one of the parameters, for example, the rotation speed, the dehydration duration, etc. of the dehydrator 5, where the initial function formula may beWherein P is the first water content, r is the rotation speed of the dehydrator 5, h is the dehydration duration, and c and f are constants which can be dynamically adjusted.

The initial value of each parameter is randomly set, such as setting the rotating speed to 2000 revolutions per minute, setting the dehydration time to 1 hour, then substituting the initial value of each parameter into an initial function formula, and performing iterative calculation on a plurality of parameters on the basis of the initial values by using a parallel genetic algorithm.

The parallel genetic algorithm is an optimization method based on the genetic algorithm, and the search and optimization process is accelerated by utilizing parallel computing resources. Genetic algorithms are optimization algorithms that simulate the natural evolution process, searching for optimal solutions by simulating genetic operations (e.g., selection, crossover, and mutation). Genetic algorithms, however, may require significant computational resources and time in handling complex problems. In order to accelerate the search process of genetic algorithms, the concept of parallel computation is introduced to process multiple individuals or sub-populations simultaneously, thereby improving the efficiency and performance of the algorithm.

In parallel genetic algorithms, parallel computation may be performed by:

group parallelization: the population is divided into sub-populations, each sub-population undergoing genetic manipulation, such as selection, crossover and mutation, on separate processing units. Each sub-population evolves independently and periodically communicates and synchronizes information.

Task parallelism: different tasks of the genetic algorithm are allocated to multiple processing units for parallel execution. For example, tasks such as selection, interleaving, and mutation may be assigned to different processing units and data exchange and synchronization may be performed through messaging or shared memory.

Island model parallelism: the population is divided into a plurality of islands, each island having its own population and evolutionary process. Each island evolves independently and population migration occurs periodically, i.e., some individuals migrate from one island to another.

The parallel genetic algorithm can fully utilize computing resources such as a multi-core processor, a distributed computing platform and a parallel computing platform, accelerate searching and optimizing processes, and improve the efficiency and performance of the algorithm.

And then, based on the numerical value of each parameter after each iteration, adjusting an initial function formula, wherein the initial function formula is used for calculating the first water content of the sludge information, inputting the sludge information into the adjusted initial function formula to calculate the first water content after each iteration, judging whether the first water content is lower than the target water content, when the target water content is determined to be lower than the target water content, indicating that the numerical value of each current parameter is reasonably set, outputting the numerical value of each parameter after the last iteration, taking the numerical value of each parameter after the last iteration as a target numerical value, and formulating a dehydration mode according to the target numerical value, such as the optimal rotation speed and the optimal dehydration duration of the dehydrator 5, so as to reduce the subsequent dehydration times and obtain the optimal dehydration mode.

And when the first water content is not lower than the target water content, adjusting the value of the parameter, and returning to execute the step of carrying out iterative computation on at least one parameter for preset times on the basis of the initial value by using the parallel genetic algorithm according to the value after the parameter is adjusted until the first water content is lower than the target water content or the iterative times reach the preset times.

In one embodiment, the step of performing iterative computation of at least one of the parameters for a preset number of times based on the initial values using a parallel genetic algorithm includes:

The present embodiment may encode the value of each parameter to obtain a plurality of target codes, for example, 0-1 codes may be used when the value of the parameter is small, and octal or hexadecimal codes may be used when the value of the parameter is large.

And then distributing the plurality of coded target codes into corresponding computers to perform crossover and/or mutation operation, acquiring adjustment values of parameters after each crossover and/or mutation operation of each computer, and adjusting an initial function formula according to the adjustment values of the parameters after each crossover and/or mutation operation of each computer, so as to gradually approximate to the target function formula and corresponding target values thereof, and reducing operation time and improving operation efficiency by simultaneously operating by virtue of the plurality of computers.

In this embodiment, the method of converting the sludge information into a matrix by invoking a pre-trained dehydration pattern matching model depends on the data type and structure of the sludge information. As for numeric data, the matrix can be constructed directly using the raw data. Each sample may be represented as a row in a matrix and each feature may be represented as a column in the matrix. For example, if the sludge information has m samples and n features, a matrix of size m×n can be constructed. For text data, feature extraction or vectorization is typically required and then converted to a matrix representation. Text vectorization methods include bag of words model, TF-IDF vectorization, word embedding, etc. These methods convert text data into sparse or dense matrix representations. For image data, the numerical value of each pixel may be taken as an element in a matrix, thereby representing the image as a matrix. The gray-scale image may be represented as a two-dimensional matrix and the color image may be represented as a three-dimensional matrix (height×width×number of channels). For category type data, one-Hot Encoding (One-Hot Encoding) may be used to convert it into a binary matrix form. Each class may be represented as a column in the matrix, with the corresponding sample having a value of 1 on that column and 0 on the other columns. For time series data, the observed value at each time point can be taken as an element in a matrix, thereby obtaining a matrix of time x features.

Given a standard matrix V, our goal is to find two non-negative matrices W and H such that v≡wh. Specifically, two matrixes can be randomly initialized by using a gaussian distribution function to obtain a first initial matrix W and a second initial matrix H, whether the product of the first initial matrix and the second initial matrix is equal to a standard matrix is firstly judged, and when the product of the first initial matrix and the second initial matrix is not equal to the standard matrix, the first initial matrix W and the second initial matrix H are updated by a method of minimizing reconstruction errors.

The method for minimizing the reconstruction error comprises gradient descent, multiplication updating rule and the like until the product of a first initial matrix and a second initial matrix is equal to a standard matrix to obtain a first target matrix and a second target matrix, respectively extracting features of the first target matrix and the second target matrix through a principal component analysis method, extracting more useful information from the features, further obtaining sludge features of sludge information, analyzing the sludge features, and determining a dehydration mode corresponding to the sludge features.

The principal component analysis method can convert a high-dimensional matrix into a low-dimensional characteristic representation, so that principal component characteristic information of sludge information is obtained, and redundant information and noise are reduced. A gaussian distribution is a continuous probability distribution, also known as a normal distribution. It is presented in the form of a bell curve with one peak and two symmetrical tails.

Minimizing reconstruction errors is an unsupervised learning method for dimension reduction or feature extraction of data. Its goal is to reconstruct the original data into a low-dimensional representation such that the result of the reconstruction is as close as possible to the original data.

In one embodiment, after the step of detecting the water content of the target sludge by the water content control sensor, the method further includes:

estimating the drying time length required by each target sludge block according to the difference value, and adjusting the rotating speed of a conveyor belt in the conveyor device 8 according to the drying time length to obtain a target rotating speed;

and re-conveying the multi-item standard sludge blocks to the input end of the conveying device 8, and drying the multi-item standard sludge blocks according to the target rotating speed until the water content of the target sludge is lower than the preset water content.

In this embodiment, when it is determined that the water content of the target sludge is not lower than the preset water content, a difference between the preset water content and the water content is calculated, the cutting device is controlled to cut the target sludge into a plurality of target sludge blocks with similar shapes and sizes on average, and then the drying time required by each target sludge block is estimated according to the difference, wherein the larger the difference between the preset water content and the water content is, the longer the drying time is.

And finally, regulating the rotation speed of a conveyor belt in the conveyor device 8 according to the drying time length to obtain a target rotation speed, conveying the multi-item target sludge blocks to the input end of the conveyor device 8 again, and drying the multi-item target sludge blocks again according to the target rotation speed until the water content of the target sludge is lower than the preset water content. Wherein the drying time period is inversely proportional to the target rotational speed, and when the drying time period is longer, the target rotational speed of the conveying device 8 is slower to ensure drying of the sludge.

Referring to fig. 3, an embodiment of the present invention further provides a control device for a sludge drying system, including:

the receiving module 31 is configured to receive sludge information of the sludge acquired by the sensor before the sludge enters the dehydrator 5, call a pre-trained dehydration pattern matching model to analyze and process the sludge information, determine a dehydration pattern corresponding to the sludge information, control the dehydrator 5 to dehydrate the sludge according to the dehydration pattern, and convey the dehydrated sludge to an input end of the conveying device 8; the sludge information comprises initial water content, solid particle size, solid particle concentration, density and viscosity, the sensor comprises a water content sensor, a particle size sensor, a concentration sensor, a density sensor and a viscosity sensor, and the dehydration pattern matching model is a neural network model and is used for matching corresponding dehydration patterns according to different sludge information;

The control module 32 is used for controlling the conveying device 8 to rotate and controlling the second circulating pump 3 to drive the heat energy of the energy storage tank 1 to circularly flow in the heat exchange tube 6 so as to heat the sludge on the conveying device 8 and obtain target sludge; the output ends of the conveying device 8, the heat exchange tube 6 and the dehydrator 5 are sealed in the cavity through a plurality of packaging walls, at least one packaging wall is provided with a through hole for communicating the cavity with the waste heat recovery device 7 so as to recycle waste heat in the cavity, the conveying device 8 comprises a plurality of conveying belts, each conveying belt is arranged at equal intervals from top to bottom, and the input end of the conveying belt positioned below is protruded from the output end of the conveying belt positioned above and adjacent to the conveying belt;

and the judging module 33 is used for controlling the water content sensor to detect the water content of the target sludge, and outputting the target sludge when judging that the water content of the target sludge is lower than the preset water content.

The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.

The terminal provided by the invention comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, enable the processor to execute the steps of the control method of the sludge drying system.

In an embodiment, referring to fig. 4, the terminal provided in an embodiment of the present application may be a computer device, and the internal structure of the terminal may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the computer is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing relevant data of a control method of the sludge drying system. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements the method for controlling the sludge drying system described in the above embodiment.

In one embodiment, the application further provides a sludge drying system, which comprises a control center, an energy storage tank 1, a first circulating pump 2, a second circulating pump 3, a solar heat collector 4, a dehydrator 5, a heat exchange tube 6, a waste heat recovery device 7, a conveying device 8 and a sensor, wherein the input end of the energy storage tank 1 is connected with the output end of the solar heat collector 4, the first circulating pump 2 is further connected between the energy storage tank 1 and the solar heat collector 4, the output end of the energy storage tank 1 is connected with the heat exchange tube 6 through the second circulating pump 3, the heat exchange tube 6 is positioned below the conveying device 8, the input end of the conveying device 8 is connected with the output end of the dehydrator 5, the control center is respectively electrically connected with the first circulating pump 2, the second circulating pump 3, the solar heat collector 4, the dehydrator 5, the conveying device 8 and the sensor, the solar heat collector 4 is used for converting solar energy into heat energy by utilizing solar radiation, the energy storage tank 1 is used for driving the heat energy storage tank 1, and the heat energy storage tank 1 flows into the heat exchange tube 4; the control center comprises a memory and a processor, wherein the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the control method of the sludge drying system according to any one of the above.

In one embodiment, the invention also provides a storage medium storing computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the method of controlling a sludge drying system as described above. Wherein the storage medium may be ROM, random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, etc.

Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program stored in a storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).

As can be seen from the above embodiments, the present invention has the following advantages:

according to the control method, the terminal and the system of the sludge drying system, before sludge enters the dehydrator 5, the sludge information acquired by the sensor is received, the pre-trained dehydration pattern matching model is called to analyze and process the sludge information, the dehydration pattern corresponding to the sludge information is determined, the dehydrator 5 is controlled to dehydrate the sludge according to the dehydration pattern, so that the proper dehydration pattern is automatically matched in an artificial intelligent mode according to different sludge information, the dehydration effect of the sludge is improved, and the subsequent sludge drying burden is reduced; the dehydrated sludge is conveyed to the input end of a conveying device 8, the conveying device 8 is controlled to rotate, the second circulating pump 3 is controlled to drive heat energy of the energy storage tank 1 to circularly flow in the heat exchange tube 6 so as to heat the sludge on the conveying device 8 to obtain target sludge, the conveying device 8, the heat exchange tube 6 and the output end of the dehydrator 5 are sealed in a cavity through a plurality of sealing walls so as to avoid heat energy loss, and at least one sealing wall is provided with a through hole for communicating the cavity with the waste heat recovery device 7 so as to recycle waste heat in the cavity, thereby saving resources; in addition, the conveying device 8 comprises a plurality of conveying belts, each conveying belt is arranged at equal intervals from top to bottom, the input end of the conveying belt positioned below is protruded from the output end of the conveying belt positioned above and adjacent to each other, so that the sludge above can accurately fall into the conveying belt below and adjacent to each other, the water content sensor is finally controlled to detect the water content of the target sludge, when the water content of the target sludge is judged to be lower than the preset water content, the target sludge is output, the solar energy is utilized as a clean heat source for drying the sludge, the environmental pollution is reduced, the water content of the dried target sludge is detected through the water content sensor, and the water content of the sludge is ensured to reach the standard and be output.

The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.

Claims

1. The control method of the sludge drying system is characterized by being applied to a control center of the sludge drying system, the sludge drying system further comprises an energy storage tank (1), a first circulating pump (2), a second circulating pump (3), a solar heat collector (4), a dehydrator (5), a heat exchange tube (6), a waste heat recovery device (7), a conveying device (8) and a sensor, wherein the input end of the energy storage tank (1) is connected with the output end of the solar heat collector (4), the first circulating pump (2) is further connected between the energy storage tank (1) and the solar heat collector (4), the output end of the energy storage tank (1) is connected with the heat exchange tube (6) through the second circulating pump (3), the heat exchange tube (6) is positioned below the conveying device (8), the input end of the conveying device (8) is connected with the output end of the dehydrator, the control center is respectively connected with the first circulating pump (2), the second circulating pump (3), the solar heat collector (4), the solar heat collector (5) and the solar heat energy collector (4) by means of the heat energy storage tank (1) and the solar heat collector (4) for converting heat energy into electric energy, the first circulating pump (2) is used for driving heat energy of the solar heat collector (4) to flow into the energy storage tank (1), and the second circulating pump (3) is used for driving heat energy of the energy storage tank (1) to flow in the heat exchange tube (6); the control method of the sludge drying system comprises the following steps:

Before sludge enters a dehydrator (5), receiving sludge information of the sludge acquired by a sensor, calling a pre-trained dehydration pattern matching model to analyze and process the sludge information, determining a dehydration pattern corresponding to the sludge information, controlling the dehydrator (5) to dehydrate the sludge according to the dehydration pattern, and conveying the dehydrated sludge to an input end of a conveying device (8); the sludge information comprises initial water content, solid particle size, solid particle concentration, density and viscosity, the sensor comprises a water content sensor, a particle size sensor, a concentration sensor, a density sensor and a viscosity sensor, and the dehydration pattern matching model is a neural network model and is used for matching corresponding dehydration patterns according to different sludge information;

controlling the conveying device (8) to rotate, and controlling the second circulating pump (3) to drive heat energy of the energy storage tank (1) to circularly flow in the heat exchange tube (6) so as to heat sludge on the conveying device (8) to obtain target sludge; the conveying device (8), the heat exchange tube (6) and the output end of the dehydrator (5) are sealed in the cavity through a plurality of packaging walls, at least one packaging wall is provided with a through hole for communicating the cavity with the waste heat recovery device (7) so as to recycle waste heat in the cavity, the conveying device (8) comprises a plurality of conveying belts, each conveying belt is arranged at equal intervals from top to bottom, and the input end of the conveying belt positioned below is protruded from the output end of the conveying belt positioned above and adjacent to the conveying belt;

2. The method for controlling the sludge drying system according to claim 1, further comprising a condenser (9) and an evaporator (12), wherein the output end of the heat exchange tube (6) is respectively connected with the input end of the energy storage tank (1) and one input end of the condenser (9), the other input end of the condenser (9) is connected with the output end of the energy storage tank (1), the output end of the condenser (9) is connected with the input end of the evaporator (12) through an expansion valve (10) or a compressor (11), the output end of the evaporator (12) is communicated with a reservoir through a pipeline, the condenser (9) is used for cooling gas or steam and converting the gas into liquid, and the evaporator (12) is used for converting the liquid into steam or gas.

3. The method for controlling a sludge drying system according to claim 1, wherein the step of calling a pre-trained dehydration pattern matching model to analyze and process the sludge information and determining a dehydration pattern corresponding to the sludge information further comprises:

4. A method of controlling a sludge drying system as claimed in claim 3 wherein the step of dividing the training sample data set into a plurality of sub-data sets comprises:

5. The method for controlling a sludge drying system according to claim 1, wherein the step of calling a pre-trained dehydration pattern matching model to analyze and process the sludge information and determining a dehydration pattern corresponding to the sludge information comprises the steps of:

setting a target water content of the sludge;

invoking a pre-trained dehydration pattern matching model to determine at least one parameter affecting the target water content, and constructing an initial function formula according to at least one parameter; wherein the parameters comprise the rotating speed of the dehydrator (5) and the dehydration time length;

when the first water content is determined to be lower than the target water content, outputting the numerical value of each parameter after the last iteration, taking the numerical value of each parameter after the last iteration as a target numerical value, and formulating a dehydration mode according to the target numerical value of each parameter; wherein the dehydration mode comprises the optimal rotation speed and the optimal dehydration duration of the dehydrator (5);

6. The method according to claim 5, wherein the step of performing iterative calculation of at least one of the parameters for a preset number of times based on the initial values using a parallel genetic algorithm comprises:

7. The method for controlling a sludge drying system according to claim 1, wherein the step of calling a pre-trained dehydration pattern matching model to analyze and process the sludge information and determining a dehydration pattern corresponding to the sludge information comprises the steps of:

8. The method for controlling a sludge drying system according to claim 1, further comprising, after the step of detecting the water content of the target sludge by the water content control sensor:

estimating the drying time length required by each target sludge block according to the difference value, and adjusting the rotating speed of a conveyor belt in the conveyor device (8) according to the drying time length to obtain a target rotating speed;

and re-conveying the multi-item standard sludge blocks to the input end of the conveying device (8), and drying the multi-item standard sludge blocks according to the target rotating speed until the water content of the target sludge is lower than the preset water content.

9. A terminal comprising a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the method of controlling a sludge drying system as claimed in any one of claims 1 to 8.

10. The utility model provides a sludge drying system, its characterized in that includes control center, energy storage tank (1), first circulating pump (2), second circulating pump (3), solar collector (4), hydroextractor (5), heat transfer pipe (6), waste heat recovery device (7), conveyer (8) and sensor, the input of energy storage tank (1) with the output of solar collector (4) is connected, energy storage tank (1) with still be connected with first circulating pump (2) between solar collector (4), the output of energy storage tank (1) is passed through second circulating pump (3) with heat transfer pipe (6) are connected, heat transfer pipe (6) are located the below of conveyer (8), the input of conveyer (8) with the output of hydroextractor (5) is in contact, control center respectively with first circulating pump (2), second circulating pump (3), solar collector (4), hydroextractor (5) and conveyer (8) and sensor are used for energy storage tank (4) are used for heat energy conversion, solar energy (4) are used for heat energy storage tank (1) is heat energy conversion, solar collector (4) are used for heat energy storage tank (1), the second circulating pump (3) is used for driving heat energy of the energy storage tank (1) to flow in the heat exchange tube (6); wherein the control center comprises a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the steps of the method of controlling a sludge drying system as claimed in any one of claims 1 to 8.