CN114850184B - Safe automatic disassembling system for environmentally-friendly recycling of waste power batteries and disassembling method thereof - Google Patents
Safe automatic disassembling system for environmentally-friendly recycling of waste power batteries and disassembling method thereof Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B09—DISPOSAL OF SOLID WASTE; RECLAMATION OF CONTAMINATED SOIL
- B09B—DISPOSAL OF SOLID WASTE NOT OTHERWISE PROVIDED FOR
- B09B3/00—Destroying solid waste or transforming solid waste into something useful or harmless
- B09B3/30—Destroying solid waste or transforming solid waste into something useful or harmless involving mechanical treatment
- B09B3/35—Shredding, crushing or cutting
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07B—SEPARATING SOLIDS FROM SOLIDS BY SIEVING, SCREENING, SIFTING OR BY USING GAS CURRENTS; SEPARATING BY OTHER DRY METHODS APPLICABLE TO BULK MATERIAL, e.g. LOOSE ARTICLES FIT TO BE HANDLED LIKE BULK MATERIAL
- B07B15/00—Combinations of apparatus for separating solids from solids by dry methods applicable to bulk material, e.g. loose articles fit to be handled like bulk material
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- B09B3/00—Destroying solid waste or transforming solid waste into something useful or harmless
- B09B3/30—Destroying solid waste or transforming solid waste into something useful or harmless involving mechanical treatment
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B09—DISPOSAL OF SOLID WASTE; RECLAMATION OF CONTAMINATED SOIL
- B09B—DISPOSAL OF SOLID WASTE NOT OTHERWISE PROVIDED FOR
- B09B3/00—Destroying solid waste or transforming solid waste into something useful or harmless
- B09B3/70—Chemical treatment, e.g. pH adjustment or oxidation
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- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/05—Accumulators with non-aqueous electrolyte
- H01M10/052—Li-accumulators
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- H—ELECTRICITY
- H01—ELECTRIC ELEMENTS
- H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
- H01M10/00—Secondary cells; Manufacture thereof
- H01M10/54—Reclaiming serviceable parts of waste accumulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B09—DISPOSAL OF SOLID WASTE; RECLAMATION OF CONTAMINATED SOIL
- B09B—DISPOSAL OF SOLID WASTE NOT OTHERWISE PROVIDED FOR
- B09B2101/00—Type of solid waste
- B09B2101/15—Electronic waste
- B09B2101/16—Batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
- Y02W30/00—Technologies for solid waste management
- Y02W30/50—Reuse, recycling or recovery technologies
- Y02W30/84—Recycling of batteries or fuel cells
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Abstract
The invention discloses a safe automatic disassembly system for environmentally-friendly recovery of waste power batteries and a disassembly method thereof, wherein a battery fault detection module is used for detecting by using an algorithm and then classifying by using a waste battery classification cell module, an ending interface of the waste battery classification cell module is matched with a starting interface of a battery cutting module, an ending interface of the battery cutting module is matched with a starting interface of a shell crushing module, the ending interface of the shell crushing module is respectively matched with starting interfaces of a harmful substance decomposition module and a harmful impurity recovery module, one side of the ending interface of the recoverable substance classification module is matched with the starting interface of the recovery cell module, and simultaneously is matched with the starting interfaces of the harmful substance decomposition module and the harmful impurity recovery module again.
Description
Technical Field
The invention relates to the field of battery disassembly, in particular to a safe automatic disassembly system for environmentally friendly recovery of waste power batteries and a disassembly method thereof.
Background
With the increasing weight of the energy crisis, new energy is rapidly applied and developed. As the demand of batteries is increasing, the production of waste batteries is also increasing. In the process of disassembling and recycling the waste batteries, a large amount of toxic and harmful gases can be generated, and if the gases are not treated and directly discharged, the environment can be seriously polluted, and the health of human beings is influenced. In order to realize sustainable development of waste battery dismantling and recycling, the problem of waste gas pollution generated in the waste battery dismantling process needs to be solved urgently.
Patent No. CN110787547A discloses a waste gas treatment system and method for dismantling waste lithium batteries, and the system comprises: the system comprises a cloth bag dust removal device, a three-stage washing device and RTO heat storage combustion equipment, wherein the input end of the cloth bag dust removal device is used as the system input end and is externally connected with waste lithium battery dismantling waste gas to be treated; the output end of the cloth bag dust removal device is connected with the input end of the three-stage washing device, and the output end of the three-stage washing device is connected with the RTO heat storage combustion equipment. The treatment method comprises (1) removing dust from waste gas generated by dismantling the waste lithium battery to be treated; (2) Carrying out multi-stage washing on the waste gas generated by disassembling the waste lithium battery after dust removal to remove corrosive components in the waste gas; (3) And (3) treating the waste gas by adopting an RTO heat storage combustion process, so that the waste gas generated by disassembling the waste lithium battery is subjected to oxidation reaction at high temperature to generate CO2 and H2O. This scheme realizes that greatly reduced energy consumption and reduction waste gas are to treatment facility's corruption when the waste gas is disassembled to the useless lithium cell of effective treatment.
In the prior art, the batteries are not fully detected and classified before the battery disassembling process, so that the batteries are disassembled according to a uniform disassembling flow, and the full detection before the disassembling process is an important link.
Disclosure of Invention
In order to overcome the defects and shortcomings of the prior art, the invention provides a safe automatic disassembling system for environment-friendly recovery of waste power batteries and a disassembling method thereof.
The technical scheme adopted by the invention is that,
the system comprises a battery fault detection module, a waste battery classification pool module, a battery cutting module, a shell crushing module, a harmful substance decomposition module, a harmful impurity recovery module, a recyclable substance classification module, an impurity degradation module, a recovery pool module and a man-machine interaction module;
the battery fault detection module detects a battery signal by using a neural network algorithm, and after the detection is finished, the battery signal is classified by using a waste battery classification pool module, an ending interface of the waste battery classification pool module is matched with a starting interface of a battery cutting module, an ending interface of the battery cutting module is matched with a starting interface of a shell crushing module, an ending interface of the shell crushing module is respectively matched with starting interfaces of a harmful substance decomposition module and a harmful impurity recovery module, the ending interfaces of the harmful substance decomposition module and the harmful impurity recovery module are both matched with the starting interface of a recyclable substance classification module, one side of the ending interface of the recyclable substance classification module is matched with the starting interface of the recovery pool module, and the ending interface of the recyclable substance classification module is simultaneously matched with the starting interfaces of the harmful substance decomposition module and the harmful impurity recovery module again;
the starting interface of the impurity degradation module is matched with the harmful substance decomposition module and the harmful impurity recovery module, impurities generated by chemical reaction degradation are utilized, the man-machine interaction module is used for setting parameters of each module in the disassembly process, generating a detailed disassembly report and residual data of harmful substances and harmful impurities, and displaying the detailed disassembly report and the residual data on a screen in a chart form;
the battery cutting module comprises a cutting blade and a pneumatic cylinder, one end of the cutting blade is fixedly matched with the tail part of the rotating clamp opposite to the stainless steel baffle, and the pneumatic cylinder is fixedly matched with the other end of the cutting blade and corresponds to the stainless steel baffle;
the man-machine interaction module is including control display screen, infrared scanner, a plurality of position sensor, a plurality of energy consumption sensor and a plurality of ray radiation sensor, the control display screen carries out the parameter setting to each module of disassembling the in-process, infrared scanner sets up the interface the place ahead that begins at the battery cutting module, position sensor and energy consumption sensor set up respectively on battery cutting module, shell crushing module, harmful substance decompose module, harmful impurity recovery module and impurity degradation module, ray radiation sensor sets up on harmful substance decomposes module and impurity degradation module.
Further, categorised pond module of waste battery includes the rotatory clamp and puts the battery, the inboard fixed matching of rotatory clamp has the multiunit stainless steel baffle, the multiunit stainless steel baffle all matches through wire and the positive negative conductor of putting the battery, still be provided with the battery cutting module that is used for fixed waste battery on the rotatory clamp.
Further, the recyclable substance classification module primarily classifies substances into metals and non-metals according to different weights, and then classifies the metals into general metals and precious metals according to density.
Further, the impurity degradation module carries out the channel connection with the module is smashed to the shell, harmful substance decomposes module and harmful impurity recovery module respectively, and the connecting channel is mutual noninterference.
A safe automatic disassembling system for environmental-friendly recovery of waste power batteries and a disassembling method thereof are characterized by comprising the following steps:
step S1: the method comprises the steps that a battery fault detection module is used for detecting a battery signal by using a neural network algorithm, a waste battery classification pool module is used for classifying after detection is finished, waste power batteries are input into a battery cutting module in the waste battery classification pool module, an infrared scanner is used for detecting before the waste power batteries are in good condition, when the waste power batteries enter the battery cutting module, an electrode part of the waste power batteries is in contact with a stainless steel baffle plate in a rotating clamp and is tightly abutted against the stainless steel baffle plate under the extrusion of a pneumatic cylinder and a cutting blade, and full discharging is carried out in a discharging pool;
step S2: the waste power battery after full discharge enters a shell crushing module, is crushed into particles with uniform diameter and then is divided into two piles of substances, and the substances enter a harmful substance decomposition module and a harmful impurity recovery module respectively for treatment, the residues after treatment at the two sides enter a recoverable substance classification module to preliminarily classify the substances into metal and nonmetal according to different weights, then the metal is classified into common metal and precious metal according to density, and the metals enter a recovery tank module after being qualified by sorting;
and step S3: the impurity degradation module collects the shell respectively and smashes the module, the impurity that produces in harmful substance decomposition module and the harmful impurity recovery module, at first utilize solid powder and piece washing liquid to cool down and wash, utilize classifying screen to separate solid powder and piece, impurity after the separation gets into the molecular sieve filter tower afterwards, adsorb the moisture in the impurity by the molecular sieve filter tower, impurity after the drying gets into condensing equipment, make the organic solvent condensation in the impurity separate out, impurity uses two-stage alkali lye absorption and active carbon adsorption at last, alkali lye is sodium hydroxide or calcium hydroxide ground paste, reach the standard after, impurity discharges via the impurity discharge port, if do not reach the standard, then continue through active carbon adsorption, until reaching standard.
Further, the model for detecting the battery signal by using the neural network algorithm in the step S1 is as follows:
wherein A is b (c (n) ) The method comprises the steps of representing the total number of fault types of the waste power battery, b representing the charging and discharging times of the waste power battery, n representing the residual capacity of the waste power battery, c representing the type of the waste power battery, D representing the probability of the fault of the waste power battery, m representing the service life of the waste power battery, and f representing the fault characteristics of the waste power battery.
Further, after the detection model is established, the data of the waste power battery is specifically calculated, and the calculation formula is as follows:
l (m) ＝p(O l s (m-1) +Z l l (m) +y l )
q (m) ＝tanr(O q s (m-1) +Z q l (m) +y q )
wherein l represents the voltage capacity of the waste power battery, p represents the charge-discharge proportionality coefficient of the waste power battery, O represents the residual voltage of the waste power battery, s represents the internal resistance of the waste power battery, Z represents the residual length of the carbon core of the waste power battery, y represents the shell integrity of the waste power battery, q represents the current capacity of the waste power battery, and r represents the average value of the charge-discharge proportionality coefficients of different waste power batteries.
Further, the output result of the neural network algorithm is utilized to detect the fault diagnosis signal of the battery, and when the neurons in the intelligent neural network are activated, the neurons are subjected to algorithm processing, wherein the specific implementation formula is as follows:
t (m) ＝p(O t s (m-1) +Z t l (m) +y t )
wherein t represents the service life of the waste power battery.
Further, the time sequence data of the battery input layer is segmented and calculated by using a neural network algorithm, and the formula of the aging output value is as follows:
x (m) ＝p(O x s (m-1) +Z x l (m) +y x )
where x represents the aged output value of the waste power battery.
Further, the final output result is obtained as follows:
where V denotes a detection result of the waste power battery, and u denotes a weighted average of a voltage capacity, a current capacity, a battery use time, and an aging output value of the waste power battery.
The invention has the beneficial effects that: the invention provides a method for detecting a battery by using a neural network algorithm before the battery is disassembled, fully knowing the fault reason of the battery, and classifying the battery, thereby improving the battery disassembling efficiency.
Drawings
FIG. 1 is a block diagram of the system of the present invention;
FIG. 2 is a diagram of a battery cutting module according to the present invention;
FIG. 3 is a block diagram of a recyclable material module according to the present invention;
FIG. 4 is a diagram of a human-computer interaction module according to the present invention;
FIG. 5 is a flow chart of the overall method steps of the present invention;
FIG. 6 is a diagram of a neural network detection algorithm of the present invention.
Detailed Description
It should be noted that, in the present application, the embodiments and features of the embodiments may be combined with each other without conflict, and the present application will be further described in detail with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, an automatic disassembling system for safely recycling waste power batteries in an environmental protection manner and a disassembling method thereof comprise a battery fault detection module, a waste battery classification pool module, a battery cutting module, a shell crushing module, a harmful substance decomposition module, a harmful impurity recycling module, a recyclable substance classification module, an impurity degradation module, a recycling pool module and a man-machine interaction module;
the battery fault detection module and the ending interface of the waste battery classification pool module are matched with the starting interface of the battery cutting module, the ending interface of the battery cutting module is matched with the starting interface of the shell crushing module, the ending interface of the shell crushing module is respectively matched with the starting interfaces of the harmful substance decomposition module and the harmful impurity recovery module, the ending interfaces of the harmful substance decomposition module and the harmful impurity recovery module are matched with the starting interface of the recyclable substance classification module, one side of the ending interface of the recyclable substance classification module is matched with the starting interface of the recovery pool module, and meanwhile, the ending interfaces of the recyclable substance classification module are matched with the starting interfaces of the harmful substance decomposition module and the harmful impurity recovery module again;
the starting interface of the impurity degradation module is matched with the harmful substance decomposition module and the harmful impurity recovery module, impurities generated by chemical reaction degradation are utilized, the man-machine interaction module carries out parameter setting on each module in the disassembly process, a detailed disassembly report and residual data of harmful substances and harmful impurities are generated, and the residual data are displayed on a screen in a chart form.
As shown in fig. 2, the battery cutting module includes a cutting blade having one end fixedly mated with the end of the rotating clamp opposite the stainless steel barrier, and a pneumatic cylinder fixedly mated with the other end of the cutting blade and corresponding to the stainless steel barrier.
As shown in fig. 3, the recyclable substance classifying module primarily classifies substances into metals and non-metals according to different weights, and then classifies metals into general metals and precious metals according to density.
The impurity degradation module carries out the channel connection with the crushing module of shell, harmful substance decomposition module and harmful impurity recovery module respectively, and every connecting tube sets up alone.
As shown in fig. 4, the human-computer interaction module comprises a control display screen, an infrared scanner, a plurality of position sensors, a plurality of energy consumption sensors and a plurality of ray radiation sensors, the control display screen performs parameter setting on each module in the disassembly process, the infrared scanner is arranged in front of a starting interface of the battery cutting module, the position sensors and the energy consumption sensors are respectively arranged on the battery cutting module, the shell crushing module, the harmful substance decomposition module, the harmful impurity recovery module and the impurity degradation module, and the ray radiation sensors are arranged on the harmful substance decomposition module and the impurity degradation module; the infrared scanner is a camera based on machine vision, surface defects of the waste power battery, such as impact, scratch, dirt, perforation and the like, are identified through an intelligent machine learning algorithm, and if the risk of electrolyte leakage is detected, an alarm is given in time through a control display screen; the working temperature, the internal impurity components and the working pressure of each device are detected in real time through various sensors, and when the working parameters of the devices exceed the set warning values, the display screen is timely and overcontrolled to give an alarm.
As shown in fig. 5, a method for safely recycling and disassembling a waste battery includes the following steps:
step S1: the method comprises the steps that a battery fault detection module is used for detecting a battery signal by using a neural network algorithm, a waste battery classification pool module is used for classifying after detection is finished, waste power batteries are input into a battery cutting module in the waste battery classification pool module, an infrared scanner is used for detecting before the waste power batteries are in good condition, when the waste power batteries enter the battery cutting module, an electrode part of the waste power batteries is in contact with a stainless steel baffle plate in a rotating clamp and is tightly abutted against the stainless steel baffle plate under the extrusion of a pneumatic cylinder and a cutting blade, and full discharging is carried out in a discharging pool;
step S2: the waste power battery after full discharge enters a shell crushing module, is crushed into particles with uniform diameter and then is divided into two piles of substances, and the substances enter a harmful substance decomposition module and a harmful impurity recovery module respectively for treatment, the residues after treatment at the two sides enter a recoverable substance classification module to preliminarily classify the substances into metal and nonmetal according to different weights, then the metal is classified into common metal and precious metal according to density, and the metals enter a recovery tank module after being qualified by sorting;
and step S3: the impurity degradation module collects the shell respectively and smashes the module, the impurity that produces in harmful substance decomposition module and the harmful impurity recovery module, at first utilize solid powder and piece washing liquid to cool down and wash, utilize classifying screen to separate solid powder and piece, impurity after the separation gets into the molecular sieve filter tower afterwards, adsorb the moisture in the impurity by the molecular sieve filter tower, impurity after the drying gets into condensing equipment, make the organic solvent condensation in the impurity separate out, impurity uses two-stage alkali lye absorption and active carbon adsorption at last, alkali lye is sodium hydroxide or calcium hydroxide ground paste, reach the standard after, impurity discharges via the impurity discharge port, if do not reach the standard, then continue through active carbon adsorption, until reaching standard.
The problem that the battery has the highest frequency is the electric leakage phenomenon of the battery, and the battery faults can be divided into two types, namely a full-charge fault of the battery and an internal circuit problem. For full-charge faults, the power consumption of the battery shows a nonlinear trend of faults along with the increase of the number of days for placing; the line connection condition shows that the battery has no fault, but the electric quantity of the battery is sharply reduced along with the increase of the charging and discharging times, so that the electric leakage phenomenon is generated, the power supply of the whole battery is insufficient, and the use of the battery is influenced.
As shown in fig. 6, the model for detecting the battery signal by using the neural network algorithm in step S1 is:
wherein A is b (c (n) ) The method comprises the steps of representing the total number of fault types of the waste power battery, b representing the charging and discharging times of the waste power battery, n representing the residual capacity of the waste power battery, c representing the type of the waste power battery, D representing the probability of the fault of the waste power battery, m representing the service life of the waste power battery, and f representing the fault characteristics of the waste power battery.
After a detection model is established, the data of the waste power battery is specifically calculated, and the calculation formula is as follows:
l (m) ＝p(O l s (m-1) +Z l l (m) +y l )
q (m) ＝tanr(O q s (m-1) +Z q l (m) +y q )
wherein l represents the voltage capacity of the waste power battery, p represents the charge-discharge proportionality coefficient of the waste power battery, O represents the residual voltage of the waste power battery, s represents the internal resistance of the waste power battery, Z represents the residual length of the carbon core of the waste power battery, y represents the shell integrity of the waste power battery, q represents the current capacity of the waste power battery, and r represents the average value of the charge-discharge proportionality coefficients of different waste power batteries.
The output result of the neural network algorithm is utilized to detect the fault diagnosis signal of the battery, and when the neurons in the intelligent neural network are activated, the neurons are subjected to algorithm processing, wherein the specific implementation formula is as follows:
t (m) ＝p(O t s (m-1) +Z t l (m) +y t )
wherein t represents the service life of the waste power battery.
The time sequence data of the battery input layer is divided and calculated by using a neural network algorithm, and the formula of the aging output value is as follows:
x (m) ＝p(O x s (m-1) +Z x l (m) +y x )
where x represents the aged output value of the waste power battery.
The final output results are obtained as follows:
where V denotes a detection result of the waste power battery, and u denotes a weighted average of a voltage capacity, a current capacity, a battery use time, and an aging output value of the waste power battery.
The invention has the beneficial effects that: the invention provides that the neural network algorithm is used for detecting the battery before the battery is disassembled, the fault reason of the battery is fully known, and then the battery is classified, so that the battery disassembling efficiency is improved.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," "matched," and "fixed" are to be construed broadly, e.g., as fixed, removably matched, or integrally matched; can be mechanically matched or electrically matched; they may be connected directly or indirectly through intervening media, or they may be connected internally between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made herein without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.
Claims (5)
1. A safe automatic disassembly system for environmentally-friendly recovery of waste power batteries is characterized by comprising a battery fault detection module, a waste battery classification pool module, a battery cutting module, a shell crushing module, a harmful substance decomposition module, a harmful impurity recovery module, a recyclable substance classification module, an impurity degradation module, a recovery pool module and a man-machine interaction module;
the battery fault detection module detects a battery signal by using a neural network algorithm, and after the detection is finished, the battery signal is classified by using a waste battery classification pool module, an ending interface of the waste battery classification pool module is matched with a starting interface of a battery cutting module, an ending interface of the battery cutting module is matched with a starting interface of a shell crushing module, an ending interface of the shell crushing module is respectively matched with starting interfaces of a harmful substance decomposition module and a harmful impurity recovery module, the ending interfaces of the harmful substance decomposition module and the harmful impurity recovery module are both matched with the starting interface of a recyclable substance classification module, one side of the ending interface of the recyclable substance classification module is matched with the starting interface of the recovery pool module, and the ending interface of the recyclable substance classification module is simultaneously matched with the starting interfaces of the harmful substance decomposition module and the harmful impurity recovery module again;
the starting interface of the impurity degradation module is matched with the harmful substance decomposition module and the harmful impurity recovery module, impurities generated by chemical reaction degradation are utilized, the man-machine interaction module carries out parameter setting on each module in the disassembly process, generates a detailed disassembly report and residual data of harmful substances and harmful impurities, and displays the data on a screen in a chart form;
the battery cutting module comprises a cutting blade and a pneumatic cylinder, one end of the cutting blade is fixedly matched with the tail part of the rotating clamp opposite to the stainless steel baffle, and the pneumatic cylinder is fixedly matched with the other end of the cutting blade and corresponds to the stainless steel baffle;
the man-machine interaction module is including control display screen, infrared scanner, a plurality of position sensor, a plurality of energy consumption sensor and a plurality of ray radiation sensor, the control display screen carries out parameter setting to each module of disassembling the in-process, infrared scanner sets up the interface the place ahead that begins at the battery cutting module, position sensor and energy consumption sensor set up respectively on battery cutting module, shell crushing module, harmful substance decompose module, harmful impurity recovery module and impurity degradation module, ray radiation sensor sets up on harmful substance decomposes module and impurity degradation module.
2. The system of claim 1, wherein the waste battery classification cell module comprises a rotating clamp and a battery, a plurality of stainless steel baffles are fixedly matched on the inner side of the rotating clamp, the stainless steel baffles are matched with positive and negative wires of the battery, and a battery cutting module for fixing the waste battery is further arranged on the rotating clamp.
3. The system of claim 2, wherein the recyclable substance classification module primarily classifies substances into metals and non-metals according to different weights, and further classifies metals into general metals and precious metals according to density.
4. The system of claim 3, wherein the impurity degradation module is in channel connection with the housing crushing module, the harmful substance decomposition module and the harmful impurity recovery module respectively, and the connection channels are not interfered with each other.
5. The disassembly method of the safe automatic disassembly system for the environmental-friendly recovery of waste power batteries according to claim 4 is characterized by comprising the following steps:
step S1: the method comprises the steps that a battery fault detection module is used for detecting a battery signal by using a neural network algorithm, a waste battery classification pool module is used for classifying after detection is finished, waste power batteries are input into a battery cutting module in the waste battery classification pool module, an infrared scanner is used for detecting before the waste power batteries are in good condition, when the waste power batteries enter the battery cutting module, an electrode part of the waste power batteries is in contact with a stainless steel baffle plate in a rotating clamp and is tightly abutted against the stainless steel baffle plate under the extrusion of a pneumatic cylinder and a cutting blade, and full discharging is carried out in a discharging pool;
step S2: the waste power battery after full discharge enters a shell crushing module, is crushed into particles with uniform diameter and then is divided into two piles of substances, and the substances enter a harmful substance decomposition module and a harmful impurity recovery module respectively for treatment, the residues after treatment at the two sides enter a recoverable substance classification module to preliminarily classify the substances into metal and nonmetal according to different weights, then the metal is classified into common metal and precious metal according to density, and the metals enter a recovery tank module after being qualified by sorting;
and step S3: the impurity degradation module collects the shell respectively and smashes the module, the impurity that produces in harmful substance decomposition module and the harmful impurity recovery module, at first utilize solid powder and piece washing of cooling down, utilize classifying screen to separate solid powder and piece, the impurity after the separation gets into the molecular sieve filter tower afterwards, adsorb the moisture in the impurity by the molecular sieve filter tower, impurity after the drying gets into condensing equipment, make the organic solvent condensation in the impurity precipitate, impurity uses two-stage alkali lye absorption and active carbon adsorption at last, alkali lye is sodium hydroxide or calcium hydroxide ground paste, reach the standard after, impurity is discharged via the impurity discharge port, if do not reach the standard, then continue through active carbon adsorption, until reaching standard.
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| CN118398942B (en) * | 2024-05-20 | 2024-10-29 | 常州厚德再生资源科技有限公司 | Chain type power battery disassembly and recovery system and method |
| CN118983558A (en) * | 2024-08-01 | 2024-11-19 | 常州厚丰新能源有限公司 | A recycling method and recycling system for waste battery negative electrode waste |
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