CN106500114B - The environment-friendly disposal system of medical waste - Google Patents
The environment-friendly disposal system of medical waste Download PDFInfo
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- CN106500114B CN106500114B CN201710021812.8A CN201710021812A CN106500114B CN 106500114 B CN106500114 B CN 106500114B CN 201710021812 A CN201710021812 A CN 201710021812A CN 106500114 B CN106500114 B CN 106500114B
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Classifications
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G7/00—Incinerators or other apparatus for consuming industrial waste, e.g. chemicals
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23J—REMOVAL OR TREATMENT OF COMBUSTION PRODUCTS OR COMBUSTION RESIDUES; FLUES
- F23J1/00—Removing ash, clinker, or slag from combustion chambers
- F23J1/08—Liquid slag removal
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G2201/00—Pretreatment
- F23G2201/70—Blending
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G2201/00—Pretreatment
- F23G2201/80—Shredding
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G2203/00—Furnace arrangements
- F23G2203/30—Cyclonic combustion furnace
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G2204/00—Supplementary heating arrangements
- F23G2204/10—Supplementary heating arrangements using auxiliary fuel
- F23G2204/101—Supplementary heating arrangements using auxiliary fuel solid fuel
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23G—CREMATION FURNACES; CONSUMING WASTE PRODUCTS BY COMBUSTION
- F23G2209/00—Specific waste
- F23G2209/20—Medical materials
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23J—REMOVAL OR TREATMENT OF COMBUSTION PRODUCTS OR COMBUSTION RESIDUES; FLUES
- F23J2700/00—Ash removal, handling and treatment means; Ash and slag handling in pulverulent fuel furnaces; Ash removal means for incinerators
- F23J2700/001—Ash removal, handling and treatment means
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F23—COMBUSTION APPARATUS; COMBUSTION PROCESSES
- F23J—REMOVAL OR TREATMENT OF COMBUSTION PRODUCTS OR COMBUSTION RESIDUES; FLUES
- F23J2700/00—Ash removal, handling and treatment means; Ash and slag handling in pulverulent fuel furnaces; Ash removal means for incinerators
- F23J2700/003—Ash removal means for incinerators
Abstract
The present invention provides the environment-friendly disposal systems of medical waste, including sequentially connected screening machine, crusher, grinder, cyclone furnace, cold quenching pond and detritus tank；The screening machine is for sorting medical waste, the crusher is for the medical waste sorted out to be crushed, the grinder after mixing broken medical waste according to 1:2 mass ratio with raw coal for grinding, the mixed material that the cyclone furnace is used to be formed after grinding grinder burns into molten state, it is pipelined to cold quenching pond again and carries out cold quenching, the detritus tank is used to precipitate filtering for the product after cold quenching.The present invention can quickly solve heavy metal sewage sludge pollution on the environment in medical waste.
Description
Technical field
The present invention relates to field of garbage disposal, and in particular to the environment-friendly disposal system of medical waste.
Background technique
Heavy metal waste in the related technology mostly uses engineering reclamation activities, chemical remediation measure or biological prosthetic measure.
Wherein chemical remediation measure is that modifying agent or activating agent are launched into the lime-ash after incineration firing, causes pH value, the oxidation of lime-ash
Reducing condition or ion constitute situation and generate variation, so that heavy metal is adsorbed, restored or precipitated, realizing reduces lime-ash
The content of middle heavy metal.Biological prosthetic measure is that the toxicity of heavy metal is reduced using specific plant, animal or microorganism.But
It is that both methods takes a long time, is unfavorable for rapidly removing heavy metal.Engineering reclamation activities is the method using physics, will such as be contained
The rubbish or lime-ash progress deep layer for having heavy metal are turned over and are buried, or dilution is sprayed to it, although reducing the concentration of heavy metal, weight
The total content of metal is not reduced.
Summary of the invention
In view of the above-mentioned problems, the present invention provides the environment-friendly disposal system of medical waste.
The purpose of the present invention is realized using following technical scheme:
The environment-friendly disposal system of medical waste, including sequentially connected screening machine, crusher, grinder, cyclone furnace, cold quenching
Pond and detritus tank；For the screening machine for sorting to medical waste, the crusher is used for the medical waste that will be sorted out
It is crushed, the grinder after mixing broken medical waste according to 1:2 mass ratio with raw coal for grinding, institute
State mixed material of the cyclone furnace for being formed after grinding grinder and burn into molten state, then be pipelined to cold quenching pond into
Row cold quenching, the detritus tank are used to precipitate filtering for the product after cold quenching.
The invention has the benefit that the medical waste containing chromium can be burnt with coal dust, make wherein Cr VI
Etc. valence heavy metal ions be reduced into nontoxic trivalent chromium state completely by C, and form vitreous object under cold quenching effect, and
It is mothballed the heavy metal ion such as the trivalent chromium of lower valency in vitreous object, realizes the environmental protection with the insulation of nature biotechnology body
Processing, so as to quickly solve heavy metal sewage sludge pollution on the environment in medical waste.
Detailed description of the invention
The present invention will be further described with reference to the accompanying drawings, but the embodiment in attached drawing is not constituted to any limit of the invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is structural block diagram of the invention；
Fig. 2 is the structural block diagram of fault detection module.
Appended drawing reference:
Screening machine 1, crusher 2, grinder 3, cyclone furnace 4, cold quenching pond 5, detritus tank 6, flue gas processing device 7, failure inspection
Survey device 8, historical data acquisition unit 11, data pre-processing unit 12, feature extraction unit 13, real-time fault diagnosis feature to
Amount acquisition unit 14, fault diagnosis model establish unit 15, fault diagnosis recognition unit 16.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, the environment-friendly disposal system of medical waste is present embodiments provided, including sequentially connected screening machine 1, broken
Broken machine 2, grinder 3, cyclone furnace 4, cold quenching pond 5 and detritus tank 6；The screening machine 1 is described for sorting to medical waste
For the medical waste sorted out to be crushed, the grinder 3 is used for broken medical waste and raw coal crusher 2
According to being ground after the mixing of 1:2 mass ratio, the mixed material that the cyclone furnace 4 is used to be formed after grinding grinder 3 burns
It at molten state, then is pipelined to cold quenching pond 5 and carries out cold quenching, the detritus tank 6 for the product after cold quenching for precipitating
Filter.
Wherein, described that medical waste is sorted, it specially sorts out including relatively large metal and glass
Inorganic matter.
Preferably, the environment-friendly disposal system of the medical waste further includes flue gas processing device 7, the flue gas processing device 7
It is connect with cyclone furnace 4, the flue gas generated when for mixed material in cyclone furnace 4 to burn carries out denitration and electrostatic precipitation processes.
It preferably, further include for the fault detection means 8 for needing detection device to carry out fault detection.
The above embodiment of the present invention can burn the medical waste containing chromium with coal dust, make wherein Cr VI it is contour
Valence heavy metal ion is reduced into nontoxic trivalent chromium state by C completely, and forms vitreous object under cold quenching effect, and make low
The heavy metal ion such as the trivalent chromium of valence state are mothballed in vitreous object, are realized at the environmental protection insulated with nature biotechnology body
Reason；Flue gas processing device 7 is set simultaneously, the flue gas generated when handling can be handled, avoid the discharge of harmful smoke.
Preferably, the fault detection means 8 is provided with 4 fault detection modules, each fault detection module for pair
Screening machine 1, crusher 2, grinder 3, one of them in cyclone furnace 4 need detection device to carry out fault detection；
Wherein each failure inspection module include sequentially connected historical data acquisition unit 11, data pre-processing unit 12,
Feature extraction unit 13, real-time fault diagnosis feature vector acquisition unit 14, fault diagnosis model establishes unit 15 and failure is examined
Disconnected recognition unit 16；The historical data acquisition unit 11 be used for by sensor acquire need detection device in normal state and
The historical vibration signal data of multiple measuring points when being run under various malfunctions；The data pre-processing unit 12 is used for acquisition
To original historical vibration signal data pre-processed；The feature extraction unit 13 is used to believe from filtered historical vibration
Wavelet packet singular value features are extracted in number, and using the wavelet packet singular value features of extraction as fault diagnosis feature vector sample
This；The real-time fault diagnosis feature vector acquisition unit 14 for obtain need the real-time fault diagnosis feature of detection device to
Amount；The fault diagnosis model establishes unit 15 for establishing the fault diagnosis model based on improved support vector machines, and makes
Fault diagnosis model is trained with fault diagnosis feature vector sample, calculates the optimal solution of fault diagnosis model parameter,
Obtain the fault diagnosis model of training completion；The fault diagnosis recognition unit 16 is used to need this real time fail of detection device
Diagnostic characteristic vector is input in the fault diagnosis model of training completion, and completion needs the diagnosis of detection device failure to identify.
Preferably, when the data pre-processing unit 12 pre-processes collected original historical vibration signal data
Filter out the out of band components of collected original historical vibration signal data as the following formula using digital filter:
Wherein, E is the historical vibration signal data obtained after filtering, and E ' is collected original historical vibration signal number
According to R is the number of measuring point, χ=1,2,3 ... R-1；τ is the constant determined by digital filter self-characteristic,For sensing used
The intrinsic frequency acquisition of device.
This preferred embodiment pre-processes collected original historical vibration signal data using aforesaid way, can
Adaptive different vibration signal is eliminated the time domain waveform distortion in original historical vibration signal data, is improved to collected
Original historical vibration signal data carries out pretreated precision, to be beneficial to improve to needing detection device to carry out fault identification
Precision.
Preferably, the feature extraction unit 13 specifically executes:
(1) the historical vibration signal at a moment for needing detection device to measure when being in state W from measuring point Φ is set as WΦ
(E), Φ=1 ..., R, R are the number of measuring point, to WΦ(E) λ layer scattering WAVELET PACKET DECOMPOSITION is carried out, 2 in λ layers are extractedλA point
Coefficient is solved, all decomposition coefficients are reconstructed, with Xj(j=0,1 ..., 2λ- 1) reconstruction signal of λ layers of each node is indicated,
Construction feature matrixWherein the value of λ is combined according to historical experience and actual conditions and is determined, to feature
Matrix T [WΦ(E)] singular value decomposition is carried out, this feature matrix T [W is obtainedΦ(E)] feature vector:
Wherein γ1,γ2,…,γvFor by eigenmatrix T [WΦ(E)] singular value decomposed, v are by eigenmatrix T [WΦ
(E)] number for the singular value decomposed；
(2) it setsIndicate feature vectorIn maximum singular value,It indicates
Feature vectorIn minimum singular value, define WΦ(E) corresponding fault diagnosis feature vectorAre as follows:
(3) the fault diagnosis feature vector being calculated is screened, excludes underproof fault diagnosis feature vector,
Then this needs detection device when being in state W in the fault diagnosis feature vector sample of the fixed time are as follows:
In formula, R ' is the quantity of the underproof fault diagnosis feature vector excluded.
In this preferred embodiment, wavelet packet singular value features are extracted as fault diagnosis feature vector, can be effectively reduced
The influence of noise data, it is high with accuracy rate and calculate time short advantage, so as to improve to needing detection device to examine
Disconnected fault-tolerance.
Preferably, the fault diagnosis feature vector being calculated is screened using following manner:
Using when detection device being needed to be in state W all fault diagnosis feature vectors being calculated at the moment as should
The feature vector Screening Samples collection at moment calculates the standard deviation sigma of this feature vector Screening Samples collectionWWith desired value μWIf calculating
The fault diagnosis feature vector arrivedIt is unsatisfactory for following equation, then rejects the fault diagnosis feature vector:
In formula,For desired value μWMaximal possibility estimation,For standard deviation sigmaWMaximal possibility estimation
This preferred embodiment screens the fault diagnosis feature vector being calculated, to exclude underproof failure
Diagnostic characteristic vector, objective science, improve in the environment-friendly disposal system to medical waste it is each need detection device carry out therefore
Hinder the accuracy of diagnosis.
Preferably, the underproof fault diagnosis feature vector of rejecting is also stored into one by the feature extraction unit 13
In ephemeral data reservoir, work as satisfactionWhen, to the λ value in feature extraction unit 13 into
Row further amendment, specific as follows:
(1) if meeting following formula, the value of λ is modified on the basis of combining and determining according to original historical experience and actual conditions
For λ+1:
(2) if meeting following formula, the value of λ is modified on the basis of combining and determining according to original historical experience and actual conditions
For λ+2:
Wherein, R is the number of measuring point, and R ' is the quantity of underproof fault diagnosis feature vector, and Δ is to be manually set
Integer threshold values.
This preferred embodiment accounts for the ratio of measuring point number according to underproof fault diagnosis feature vector, automatically adjusts λ value,
It further reduced influence of the underproof fault diagnosis feature vector to needing detection device to carry out fault diagnosis, improve failure
The accuracy of diagnosis, the equipment to break down in the environment friendly system so as to accurately identify medical waste in time, so that
Staff can carry out on-call maintenance to the equipment to break down in the environment friendly system of medical waste.
Preferably, fault diagnosis model is established unit 15 and is established the event based on improved support vector machines using following manner
Hinder diagnostic model:
(1) using radial basis function as kernel function, using the kernel function by the fault diagnosis feature vector sample from original
Space reflection realizes fault diagnosis feature vector sample classification, structure to higher dimensional space, in higher dimensional space construction optimal decision function
Make optimal decision function are as follows:
In formula, x is the fault diagnosis feature vector sample of input, and ρ (x) is the fault diagnosis feature vector sample pair of input
The output answered, J (x) indicate radial basis function, and Ω is weight vectors, and d is deviation；
In addition,For the Optimization Factor of introducing, wherein R is the number of measuring point, and R ' is underproof fault diagnosis feature
The quantity of vector；
(2) objective function of support vector machines is defined are as follows:
The constraint condition of support vector machines are as follows:
yi(Ωxi+d)≥1-εi,εi>=0, i=1 ..., M
In formula, minX (Ω, d, λi) be support vector machines objective function,For the penalty factor after optimization, εiTo introduce
Error variance；M is the quantity of fault diagnosis feature vector sample；xiFor i-th of fault diagnosis feature vector sample of input,
yi(Ωxi+ d) it is the corresponding output of i-th of fault diagnosis feature vector sample inputted, Ω is weight vectors, and d is deviation；
Wherein, the optimal way of the value of the radius parameter of penalty factor and the kernel function are as follows: all fault diagnosises are special
Sign vector sample mean is divided into the subset not included mutually, sets the value of the value of the radius parameter of penalty factor and the kernel function
Range carries out two-dimensional encoded, generation primary group to the position vector of each particle；To the selected instruction of the corresponding parameter of each particle
Practice collection and carry out cross validation, obtained prediction model classification accuracy is as the corresponding target function value of particle, in population
Particle be iterated；All particles are evaluated with target function value, when the Evaluation: Current value of some particle is better than its history evaluation
When value, as the optimal history evaluation of the particle, current particle optimal location vector is recorded；Globally optimal solution is found, such as
Its value of fruit is better than current history optimal solution, then updates, when reaching the stop criterion of setting, then stop search, export optimal punish
The value of the radius parameter of penalty factor and the kernel function, otherwise returns to re-search for.
(3) objective function for solving the support vector machines, calculates weight vectors and deviation；
(4) weight vectors being calculated and deviation are substituted into optimal decision function is established fault diagnosis mould
Type.
This preferred embodiment reduces underproof fault diagnosis feature vector and sets to need to detect by introducing Optimization Factor
The standby influence for carrying out fault diagnosis, further improves the actual accuracy of the optimal decision function, is fault diagnosis model
Establish and good functional foundations be provided, thus the more accurate fault diagnosis model of building, improve to needing detection device to carry out therefore
Hinder the precision of diagnosis, in addition, the present embodiment using aforesaid way to the value of the radius parameter of penalty factor and the kernel function into
Row optimization, the optimization time is relatively short, and effect of optimization is good, so as to obtain the support vector machines of better performances, further mentions
Height is to the precision for needing detection device to carry out fault diagnosis.
According to above-described embodiment, inventor has carried out a series of tests, is the experimental data tested below:
Above-mentioned experimental data shows that the present invention substantially can quickly locate the heavy metal sewage sludge in medical waste
Reason, and can in system need detection device carry out real-time fault detection, thus when detection device being needed to break down can and
When repaired, guarantee system to the efficiency for the treatment of of!medical waste.Therefore, the present invention generates in terms of the processing to medical waste
The beneficial effect of highly significant.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although explaining in detail referring to preferred embodiment to the present invention, those skilled in the art are answered
Work as understanding, it can be with modification or equivalent replacement of the technical solution of the present invention are made, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (1)
1. the environment-friendly disposal system of medical waste, characterized in that including sequentially connected screening machine, crusher, grinder, whirlwind
Furnace, cold quenching pond and detritus tank；For the screening machine for sorting to medical waste, the crusher is used for the doctor that will be sorted out
It treats rubbish to be crushed, the grinder after mixing broken medical waste according to 1:2 mass ratio with raw coal for carrying out
Grinding, the mixed material that the cyclone furnace is used to be formed after grinding grinder burns into molten state, then is pipelined to
Cold quenching pond carries out cold quenching, and the detritus tank is used to precipitate filtering for the product after cold quenching；It further include flue gas processing device, the flue gas
Processing unit is connect with cyclone furnace, and the flue gas generated when for mixed material in cyclone furnace to burn carries out denitration and electrostatic precipitation
Processing；It further include the fault detection means for carrying out fault detection to crusher, grinder and cyclone furnace, the fault detection
Device is provided with 4 fault detection modules, and each fault detection module is used for in screening machine, crusher, grinder, cyclone furnace
One of them need detection device carry out fault detection；Each failure inspection module includes that sequentially connected historical data acquisition is single
Member, data pre-processing unit, feature extraction unit, real-time fault diagnosis feature vector acquisition unit, fault diagnosis model are established
Unit and fault diagnosis recognition unit；
The historical data acquisition unit is used to need detection device in normal state and various failure shapes by sensor acquisition
The historical vibration signal data of multiple measuring points when being run under state；
The data pre-processing unit is for pre-processing collected original historical vibration signal data；
The feature extraction unit is used to extract wavelet packet singular value features from filtered historical vibration signal data, and will
The wavelet packet singular value features of extraction are as fault diagnosis feature vector sample；
The real-time fault diagnosis feature vector acquisition unit is for obtaining the real-time fault diagnosis feature vector for needing detection device；
The fault diagnosis model establishes unit for establishing the fault diagnosis model based on improved support vector machines, and uses
Fault diagnosis feature vector sample is trained fault diagnosis model, calculates the optimal solution of fault diagnosis model parameter, obtains
The fault diagnosis model completed to training；
The fault diagnosis recognition unit has been trained for needing the real-time fault diagnosis feature vector of detection device to be input to this
At fault diagnosis model in, completion need the diagnosis of detection device failure to identify；
Wherein, the feature extraction unit specifically executes:
(1) the historical vibration signal at a moment for needing detection device to measure when being in state W from measuring point Φ is set as WΦ(E),
Φ=1 ..., R, R are the number of measuring point, to WΦ(E) λ layer scattering WAVELET PACKET DECOMPOSITION is carried out, 2 in λ layers are extractedλA resolving system
Number, is reconstructed all decomposition coefficients, with Xj(j=0,1 ..., 2λ- 1) reconstruction signal of λ layers of each node, building are indicated
EigenmatrixWherein the value of λ is combined according to historical experience and actual conditions and is determined, to eigenmatrix T
[WΦ(E)] singular value decomposition is carried out, this feature matrix T [W is obtainedΦ(E)] feature vector:
Wherein γ1,γ2,…,γvFor by eigenmatrix T [WΦ(E)] singular value decomposed, v are by eigenmatrix T [WΦ(E)] divide
The number of the singular value of solution；
(2) it setsIndicate feature vectorIn maximum singular value,Indicate feature to
AmountIn minimum singular value, define WΦ(E) corresponding fault diagnosis feature vectorAre as follows:
(3) the fault diagnosis feature vector being calculated is screened, excludes underproof fault diagnosis feature vector, then should
Need detection device when being in state W in the fault diagnosis feature vector sample of the fixed time are as follows:
In formula, R ' is the quantity of the underproof fault diagnosis feature vector excluded.
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| CN104898646A (en) * | 2015-04-30 | 2015-09-09 | 东北大学 | KPCA-based fused magnesium furnace fault diagnosis method for fault separation and reconstruction |
| CN105387464A (en) * | 2015-10-27 | 2016-03-09 | 四川和鼎环保工程有限责任公司 | Power generating method for comprehensively treating environmental garbage |
| CN105757687A (en) * | 2016-04-29 | 2016-07-13 | 义马环保电力有限公司 | Environment-friendly treatment method of medical garbage |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104898646A (en) * | 2015-04-30 | 2015-09-09 | 东北大学 | KPCA-based fused magnesium furnace fault diagnosis method for fault separation and reconstruction |
| CN105387464A (en) * | 2015-10-27 | 2016-03-09 | 四川和鼎环保工程有限责任公司 | Power generating method for comprehensively treating environmental garbage |
| CN105757687A (en) * | 2016-04-29 | 2016-07-13 | 义马环保电力有限公司 | Environment-friendly treatment method of medical garbage |
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Effective date of registration: 20181024 Address after: 225400 east of Taixing Road, Taixing high tech Industrial Development Zone, Taizhou, Jiangsu Applicant after: Taizhou Haixing environmental protection equipment installation Co., Ltd. Address before: 518000 Hai Wang building 708, 2225 Nanhai Road, Nanshan District, Shenzhen, Guangdong Applicant before: Shenzhen Kaida Photoelectric Technology Co. Ltd. |
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| GR01 | Patent grant | ||
| GR01 | Patent grant |