CN115062807A - PCR recovery method and system - Google Patents
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Abstract
The invention provides a PCR recovery identification method and a system, relates to the field of plastic recovery, and is used for identifying the type of a PCR recovery identification object, and comprises a data acquisition stage and a data processing stage. The PCR recovery identification objects with different thicknesses and different temperatures are detected by using the micro spectrometer to obtain detection data, and the PCR recovery identification objects have the most outstanding characteristics of actually measured data at the optimal thickness and the optimal temperature, so that the accuracy of data comparison can be improved; the system can adapt to the PCR recovery method from the physical structure level, has good implementation convenience and continuous operation performance, and is beneficial to the practical application of factories.
Description
Technical Field
The invention relates to the field of plastic recovery, in particular to a PCR recovery method and a PCR recovery system.
Background
The PCR is called Post-Consumer Recycled material, namely, the Recycled plastics of consumption, such as PET, PE, PP, HDPE and the like, and particularly, the Recycled plastics of daily common articles, such as lunch boxes, shampoo bottles, mineral water bottles, washing machine barrels and the like, belong to the consumption Recycled plastics.
In the PCR recovery stage, the types of PCR are various, and different recovery methods are required for different PCR materials; in order to specifically apply the corresponding recovery method to different PCRs, the recovered PCRs need to be firstly subjected to type identification.
Disclosure of Invention
The invention provides a PCR recovery identification method and a system, which can detect PCR materials under the conditions of different thicknesses and temperatures by a micro spectrometer, can more accurately confirm the types of PCR by comparing with the existing data and is beneficial to the automatic realization of PCR recovery.
Correspondingly, the invention provides a PCR recovery identification method, which is used for identifying the type of a PCR recovery identification object and comprises a data acquisition stage and a data processing stage:
the data acquisition phase comprises:
execute
The secondary optical detection step obtaining a detection data set, wherein
The secondary optical detection step comprises: deforming the first local region to be identified by PCR collection to a thickness of
In a plate-like structure
Detecting the first local area with a micro spectrometer at temperature to generate detection data
；
The data processing stage comprises:
receiving a PCR recovery identification object
Group detection data;
by the said
Performing type recognition on the PCR recovery recognition object in a mode of comparing the group detection data with the optimal actual measurement data in the classification database;
the classification database comprises a plurality of groups of preset data groups, each group of preset data group comprises a PCR name and optimal actual measurement data corresponding to the PCR name, and the optimal actual measurement data are detection data obtained by measuring a material corresponding to the PCR name through a microscopic spectrometer at optimal thickness and optimal temperature;
wherein the content of the first and second substances,
， 
， 
， 
；
the total amount of the detected data is
The number of the groups is set to be,
the group detection data is sequentially sorted out,
to represent
And the detection data in the group detection data are sequenced and numbered.
In an alternative embodiment, the sequence numbers are
The plate-like structures are numbered in the order of thickness
The thickness of the plate-shaped structure satisfies the following conditions:
in an alternative embodiment, the micro spectrometer is a micro fourier transform infrared spectrometer;
detecting the first local area by using a micro spectrometer and generating detection data
The method comprises the following steps:
adjusting the micro Fourier transform infrared spectrometer to a transmission mode or a reflection mode and detecting the first local area to generate detection data
；
The detection data
Is an infrared spectrum.
Alternative embodiment, the said passing
The way of comparing the group detection data with the data in the classification database includes:
comparing data based on the peak characteristics of the infrared spectrum;
or comparing based on infrared spectrum similarity.
In an alternative embodiment, the data alignment based on the peak features of the infrared spectrum comprises:
at the detection data
Screening to obtain a plurality of peak points, and fitting the plurality of peak points by using a fixed order function to obtain a fitting curve;
and taking the fitted curve as an infrared spectrum, and comparing the similarity based on the infrared spectrum with the data in the classification database.
In an alternative embodiment, the comparing based on infrared spectroscopy similarity comprises:
performing similarity comparison of infrared spectra based on a point method;
comparing the similarity of infrared spectra based on a shape method;
performing similarity comparison of infrared spectra based on a segmentation method;
and performing similarity comparison of infrared spectra by a task-based method.
Alternative embodiments, by the
The type recognition of the PCR recovery recognition object by comparing the group detection data with the data in the classification database comprises the following steps:
detecting each group of data
Traversing the optimal measured data of all the preset data groups to carry out similarity comparison based on infrared spectrum and obtain similarity estimated values;
and judging the type of the PCR recovery identification object as the PCR name corresponding to the best measured data with the highest similarity estimation.
Correspondingly, the invention provides a PCR recovery identification system, which is used for realizing the PCR recovery identification method and comprises the following steps:
deformation equipment: for deforming the first local region of the PCR collection recognition object to a thickness of
The plate-like structure of (1);
heating equipment: for adjusting the temperature of the first local region to be identified by PCR recovery
；
A micro spectrometer: for detecting the first local region and generating detection data
；
Classifying the database: the method comprises the following steps that a plurality of groups of preset data sets are included, each group of preset data set comprises a PCR name and optimal measured data corresponding to the PCR name, and the optimal measured data are detection data obtained by measuring a material corresponding to the PCR name through a micro spectrometer at an optimal thickness and an optimal temperature;
a processing module: for receiving the detection data
And passing said detected data
And performing type identification on the PCR recovery identification object in a mode of comparing with data in a classification database.
Optionally, the device further comprises a heat-resistant conveying belt and a partitioned heating limiting device, wherein the heat-resistant conveying belt and the partitioned heating device are combined to form the deformation device and the heating device;
the working surface of the heat-resistant conveying belt translates towards a first direction;
the partition heating limiting device is arranged above the heat-resistant conveying belt;
the partition heating limiting device comprises a bottom plate and a plurality of temperature control units, the front surface of the bottom plate faces the working surface, and the temperature control units are arranged on the back surface of the bottom plate;
the partition heating limiting device is divided into more than two partitions in the first direction, the distance between the front face of the bottom plate of each partition and the working face of the heat-resistant conveying belt is gradually reduced along the direction of the first direction, and one temperature control unit is arranged on the back face of the bottom plate of each partition.
In an optional embodiment, a bottom plate of each partition is provided with an observation hole, and a transparent medium is filled in the observation hole;
and the micro spectrometer detects the corresponding first local area through the transparent medium.
In summary, the invention provides a PCR recovery method and system, which utilizes a micro spectrometer to detect PCR recovery identification objects with different thicknesses and different temperatures and obtain detection data, and utilizes the characteristic that the PCR recovery identification objects have the most prominent measured data at the optimal thickness and the optimal temperature, so as to improve the accuracy of data comparison; the system can adapt to the PCR recovery method from the physical structure level, has good implementation convenience and continuous operation performance, and is beneficial to the practical application of factories.
Drawings
FIG. 1 is a flowchart of a PCR recovery identification method according to an embodiment of the present invention.
FIG. 2 is a flow chart of a data acquisition phase of the PCR recovery identification method according to the embodiment of the present invention.
FIG. 3 is a flow chart of data processing stages according to an embodiment of the present invention.
FIG. 4 is an infrared spectrum of PLA.
FIG. 5 is a schematic structural diagram of a PCR recovery identification system according to an embodiment of the present invention.
Detailed Description
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, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In practice, PCR is classified into types and then each type of plastic is subjected to a specific mixing process. PCR refers to consumption of recycled plastics, and the consumption of recycled plastics is various at present, for example, only thousands of types of beverage packaging bottles exist, but statistics shows that due to cost pressure, besides color differences, the types of material components of packaging bottles of products of the same type are only dozens of types, so that the identification difficulty of PCR is greatly reduced.
FIG. 1 shows a flow chart of a PCR recovery identification method according to an embodiment of the present invention. Based on the above findings, the embodiment of the present invention provides a PCR recovery identification method for performing type identification on a PCR recovery identification object, and basically, the PCR recovery identification method includes two basic processes, namely a data acquisition stage and a data processing stage.
The data acquisition stage is mainly used for acquiring the digital data of the PCR recovery recognition object so that the processing module can analyze, recognize and classify the PCR in the data processing stage.
FIG. 2 shows a flow chart of a data acquisition phase of a PCR recovery identification method according to an embodiment of the present invention. Basically, the data acquisition phase comprises:
execute
A secondary optical detection step;
specifically, the first
The secondary optical detection step comprises:
deforming the first local region to be identified by PCR collection to a thickness of
In a plate-like structure
Detecting the first local area with a micro spectrometer at temperature to generate detection data
。
For the concept definition of the deformation, in the embodiment of the present invention, the PCR recovery is identified in any way in the prior artThe first partial region being worked to a thickness of
The plate-like structure of (1); the state of the PCR recovery recognition object may be a solid state and a molten state (liquid state) depending on the temperature.
Specifically, since the type of the PCR recovery identification object cannot be known before the PCR recovery identification object is classified, different PCR materials have different spectral absorption characteristics under different thicknesses, the spectral absorption characteristics of the PCR materials can show very different differences under different thicknesses, and different PCR materials can have a corresponding thickness, and the PCR material can have an optimal characteristic spectral curve under the thickness, in the embodiment of the present invention, the thickness of the PCR material needs to be changed and adjusted first.
In addition, because the microspectroscopic identification of the solid object has the requirement of particle size, common factory equipment hardly meets the processing requirement under the conventional working condition, and therefore, the microspectroscopic identification operation of the PCR of the embodiment of the invention requires that the PCR is in a liquid state. The PCR is generally an organic matter mixed material, does not have a fixed melting point, but has a melting temperature interval, the change of the temperature can switch the PCR between a solid state and a melting state, correspondingly, for the micro-spectrum identification, besides the requirement of the particle size is difficult to achieve, the PCR in the solid state has more cracks and gaps after being crushed, and the obtained detection data has no practicability; therefore, in the detection process, the PCR material is in a molten state through gradual adjustment of temperature, the spectrum obtained in the molten state has practical detection significance, and data which is possibly similar to the optimal measured data in the classification database can be obtained through changing the thickness of the PCR material in the molten state.
Specifically, for single-piece PCR, in actual processing, based on conventional processing techniques, such as pressing and crushing, the thickness of PCR is generally controlled from a thicker state to a thinner state, and therefore, when PCR is processed to a certain thickness value, all preset temperature values are traversed and PCR is processed to a certain thickness valueAcquiring the detection data thereof, and correspondingly executing in the design of the actual execution program
The specific flow of the secondary optical detection step is as follows:
s101: an initial value is set, wherein,
， 
；
s102: judgment of
Whether or not it is true, if
The program is over, if
Step S103 is executed;
s103: judgment of
Whether or not it is true, if
Go to step S106, if so
Executing step S104;
s104: deforming the first local region of the PCR collection identification target to a thickness of
In a plate-like structure
At temperature, detecting by using a microspectrometerFirst local area generation detection data
；
S105： 
After increasing by 1, jumping to step S103;
S106： 
after incrementing by 1, the process goes to step S102.
After the acquisition of the detection data is completed, the detection data needs to be processed, and the type of the PCR recovery identification object needs to be estimated according to the detection data.
FIG. 3 shows a flow diagram of the data processing stages of an embodiment of the present invention.
Specifically, the data processing stage includes:
s301: receiving a PCR recovery identification object
Group detection data;
specifically, according to the setting of the instrument and equipment related to detection,
the group detection data may have a precedence relationship during actual transmission, so that for the detection data of the same PCR recovery identification object, the detection data is cached by adopting a corresponding address pool, and the subsequent processing steps are performed when the quantity of the data to be detected meets a quantity condition.
In particular, as to
The transmission of the group detection data is realized because in practical implementation, a plurality of related detection devices in the factory environment work together, generally,
the group detection data are uploaded to the cloud and then processed through the processing module; specifically, the cloud end records data and is used for updating and learning the classification database.
Specifically, the classification database updating mainly involves two modes, namely cloud updating and local updating; the cloud updating mode is mainly characterized in that a software developer continuously learns the PCR products on the market in a datamation mode during the operation period, and the data can be obtained by active detection and can also be obtained by uploading of various downstream factories; correspondingly, the local updating mode is that a downstream factory collects data and confirms the type, black box relation (machine learning) is constructed through the relevance of the data, or the relation between the black box relation and the machine learning is constructed based on a selected function or a comparison mode.
S302: through the said
Performing type recognition on the PCR recovery recognition object in a mode of comparing the group detection data with the optimal actual measurement data in the classification database;
specifically, the classification database stores the best actual measurement data obtained by actual measurement in advance.
Specifically, the classification database comprises a plurality of groups of preset data groups; since the final derived classification result is the PCR name (representing the actual category of the PCR material), the primary key of the actually constructed preset data set may be the PCR name, and correspondingly, the actually measured data of the material should also be included.
Specifically, the form of the detection data in the preset data group is as follows:
the classification database comprises a plurality of groups of preset data sets, each group of preset data set comprises a PCR name and optimal measured data corresponding to the PCR name, and the optimal measured data are detection data obtained by measuring a material corresponding to the PCR name through a micro spectrometer under the optimal thickness and the optimal temperature.
Specifically, specific limitations regarding the above-mentioned letters are as follows:
in particular, the method comprises the following steps of,
is shown in common
The thickness of each preset plate-shaped structure,
the thicknesses of the preset plate-shaped structures are sequenced in turn,
to represent
The plate-shaped structure thicknesses in the preset plate-shaped structure thicknesses are sequenced and numbered;
the total amount of the detected data is
The number of the groups is set to be,
the group detection data is sequentially sorted out,
to represent
The detection data in the group detection data are sequenced and numbered;
Specifically, according to practical implementation conditions, for single-piece PCR, in practical processing, based on conventional processing techniques, such as pressing, crushing, and the like, the thickness variation control of PCR is generally processed from a thicker state to a thinner state, and therefore, when PCR is processed to a certain thickness value, all preset temperature values are traversed and detectedData, sequence number is
The plate-like structure has a thickness and a sequence number of
The thickness of the plate-shaped structure satisfies the following conditions:
Specifically, the micro spectrometer is a micro Fourier transform infrared spectrometer; the microscopic Fourier transform infrared spectrometer is an accessory of the infrared spectrometer, is mainly applied to structure identification, quantitative analysis, chemical dynamics research and the like, can provide a lot of information about functional groups by analysis, reflects the characteristics on molecular structures by the position and the intensity of an infrared peak, and can be used for identifying the structural composition of an unknown substance or determining a chemical group of the unknown substance; the absorption intensity of the absorption band is related to the content of chemical groups, so that the method can be used for quantitative analysis and purity identification, is widely applied to qualitative and quantitative analysis of various material evidence material (including organic and inorganic material evidence materials) samples in judicial identification at present, can accurately determine various chemical components of the material evidence material, and can quickly and effectively obtain a direct evidence obtaining result by adopting a comparative analysis method.
It should be noted that besides the infrared spectrum, the raman spectrum is one of the commonly used spectrum types, and the present invention is described by way of example of the infrared spectrum.
In the embodiment of the invention, the spectrum of the PCR recovery identification object is mainly obtained by a micro Fourier transform infrared spectrometer, and the type of the PCR recovery identification object is deduced according to the spectrum condition.
Specifically, the first local area is detected by using a micro spectrometer and detection data is generated
The method comprises the following steps: adjusting the micro Fourier transform infrared spectrometer to a transmission mode or a reflection mode and detecting the first local area to generate detection data
(ii) a The detection data
Is an infrared spectrum.
Further, by detecting data
The acquisition of (infrared spectrum) actually converts the PCR recovery identification object from an entity in the physical world into digital data for processing in a specific form, and the specific type of the PCR recovery identification object can be deduced through the identification of the digital data.
In particular, said passing is carried out for a characteristic of the infrared spectrum (the infrared spectrum is substantially a continuous function of the curve in a predetermined interval)
The way of comparing the group detection data with the data in the classification database includes:
comparing data based on the peak characteristics of the infrared spectrum; or comparing based on infrared spectrum similarity.
For ease of illustration, FIG. 4 shows an infrared spectrum (190 degrees Celsius, 0.5 mm) of PLA, where 1754cm -1 870cm due to hyperconjugate effect -1 Represents the peak of the ester, 757cm -1 Represents the peak appearance of the methyl group.
In addition, table 1 shows peak characteristics (characteristic peaks) of different materials.
Specifically, the material difference between different types of PCR may cause the change of the microscopic composition of the material itself, the actual detection area of the micro fourier transform infrared spectrometer is a fixed-shape area, and the group difference of different materials may cause the change of the peak of the infrared spectrum, so that, in essence, different PCR materials are to be identified, which are mainly identified according to the expression characteristics of the peak, and therefore, regarding the comparison of the infrared spectrum, the whole comparison (comparison of the whole infrared spectrum) or the local comparison (comparison of only the peak characteristics) may be implemented.
Specifically, for the peak feature comparison mode, since peaks are generally discrete, the comparison of discrete data is generally implemented by using an edit distance method or a longest common subsequence method in actual operation, but the edit distance method or the longest common subsequence method has a large actual calculation amount, and accordingly, the discrete data can be generally converted into continuous data and then compared.
Specifically, the mode of converting discrete data into continuous data is realized based on substitution fitting of a certain function, and the specific form of the function can be selected according to requirements; if the accuracy of data fitting is pursued, a high-order function can be selected, but the calculation amount of the high-order function is relatively large; for example, a low-order function may be selected for fast data processing.
It should be noted that the peak of the infrared spectrum is not ideal in actual operation (i.e. has only one fixed peak), and generally, due to the oscillation problem in actual operation, there is a structure similar to the peak waveform around the true peak of the infrared spectrum, and conventionally, the actual existing position of the peak can be guessed by averaging or the like. Correspondingly, the original infrared spectrum has certain variation fluctuation due to the influence of actual conditions, and the defect of inaccurate similarity judgment generally exists if the original infrared spectrum is directly used for comparing data; by extracting peaks and then performing a virtual implementation step of a continuous curve, a more ideal infrared spectrum (virtual data) shape can be obtained, so that the speed of the subsequent comparison process is increased.
Accordingly, the data source of the best measured data (i.e. the data processing method adopted by the best measured data) should be consistent with the data source of the detection data (i.e. the data processing method adopted by the detection data), and the embodiment can ensure the comparability between the detection data and the measured data.
Specifically, the data comparison based on the peak characteristics of the infrared spectrum comprises:
at the detection data
Screening to obtain a plurality of peak points, and fitting the plurality of peak points by using a fixed order function to obtain a fitting curve;
and taking the fitted curve as an infrared spectrum, and comparing the similarity based on the infrared spectrum with the data in the classification database.
For comparison of infrared spectra of detection data and actually measured data, similarity comparison between curves is substantially converted, and no matter the comparison is performed directly by using the infrared spectra or by extracting peak points and then performing comparison of construction of a fitting curve, the similarity comparison between curves can be realized based on the prior art, for example, comparison between curves in the prior art includes:
performing similarity comparison of infrared spectra based on a point method;
comparing the similarity of infrared spectra based on a shape method;
performing similarity comparison of infrared spectra based on a segmentation method;
and performing similarity comparison of infrared spectra by a task-based method.
Specifically, since the PCR material has the most obvious infrared spectrum characteristics at a specific thickness and a specific temperature, in practical implementation, only one infrared spectrum (a set of best measured data) with the most similar similarity is generally required to be found for the similarity comparison of the infrared spectra.
Thus, by said
The type recognition of the PCR recovery recognition object by comparing the group detection data with the data in the classification database comprises the following steps:
detecting each group of data
Traversing the optimal measured data of all the preset data groups to carry out similarity comparison based on infrared spectrum and obtain similarity estimated values;
and judging the type of the PCR recovery identification object as the PCR name corresponding to the best measured data with the highest similarity estimation.
It should be noted that the optimal measured data is obtained by screening a series of measured data, and the specificity of the PCR material can be clearly reflected by the optimal measured data, and there should be differences between the optimal measured data of different PCR materials that can be identified by a computer.
Correspondingly, the embodiment of the invention also provides a PCR recovery identification system, which is used for implementing the PCR recovery identification method, and comprises the following steps:
deformation equipment: for deforming the first local region of the PCR collection recognition object to a thickness of
The plate-like structure of (1);
heating equipment: for adjusting the temperature of the first local region to be identified by PCR recovery
；
A micro spectrometer: for detecting the first local region and generating detection data
；
Classifying the database: the method comprises the following steps that a plurality of groups of preset data sets are included, each group of preset data set comprises a PCR name and optimal measured data corresponding to the PCR name, and the optimal measured data are detection data obtained by measuring a material corresponding to the PCR name through a micro spectrometer at an optimal thickness and an optimal temperature;
a processing module: for receiving the detection data
And passing said detected data
And performing type identification on the PCR recovery identification object in a mode of comparing with data in a classification database.
Fig. 5 is a schematic structural diagram of a PCR recovery recognition system according to an embodiment of the present invention, wherein a heating device, a classification database, and a processing module in the PCR recovery recognition system are not shown in the figure, and may be selected according to specific situations in the prior art.
In practical implementation, the embodiment of the present invention further provides a more specific implementation manner for reference, and specifically, the PCR recovery identification system further includes a heat-resistant conveying belt 1 and a partitioned heating limiting device, where the heat-resistant conveying belt 1 and the partitioned heating device are combined to form the deformation device and the heating device;
the working surface of the heat-resistant transmission belt 1 translates towards a first direction;
the partition heating limiting device is arranged above the heat-resistant conveying belt;
the partition heating limiting device comprises a bottom plate 4 and a plurality of temperature control units, the front surface of the bottom plate faces the working surface, and the temperature control units are arranged on the back surface of the bottom plate;
the partition heating limiting device is divided into more than two partitions 2 in the first direction, the distance between the front surface of the bottom plate 4 of each partition and the working surface of the heat-resistant conveying belt is gradually reduced along the direction of the first direction, and one temperature control unit is arranged on the back surface of the bottom plate of each partition 4.
Specifically, an observation hole is formed in the bottom plate of each partition, and a transparent medium is filled in the observation hole; the micro spectrometer 3 detects the corresponding first local area through the transparent medium.
Specifically, referring to fig. 5, the arrow direction is the first direction, the PCR recycling identification object may be pre-processed or not, and enters between the heat-resistant conveying belt and the bottom plate from the left side of the drawing direction by way of pressing, the heat-resistant conveying belt is regarded as a plane, the distance between the bottom plate and the heat-resistant conveying belt is gradually reduced along the carton in the first direction, and the PCR recycling identification object fills the space between the heat-resistant conveying belt and the bottom plate as much as possible due to the continuous movement of the heat-resistant conveying belt and the pressing force existing at the left side, and by this embodiment, the first local structure of the PCR recycling identification object with different thicknesses can be obtained; in contrast, in the case of the temperature problem, since it takes a certain time for the PCR recovery recognition target to pass under each partition completely, the temperature of the substrate is controllably changed during this time, and the temperature is changed from low to high in view of the feasibility.
In the process that the PCR recovery identification object passes through the lower part of the bottom plate, each partition is provided with a corresponding micro spectrometer which can acquire detection data of the PCR recovery identification object below the corresponding partition and finally obtain the detection data
Group test data; the processing module utilizes
Carrying out species identification on the PCR recovery identification object by the group test data to obtain the species of the PCR recovery identification object; after the type of the PCR collection identification target is obtained, the subsequent classification and collection operation can be performed.
Specifically, in the above specific embodiment provided for the PCR recovery recognition system, the partition heating limiting device mainly has the function of adjusting the thickness and temperature of the PCR recovery recognition object 5, and for the micro spectrometer, since certain limitation requirements such as slicing, film formation and the like need to be provided for the detection sample, the design structure can be designed by utilizing the distance change between the bottom plate and the heat-resistant conveying belt, and the function similar to sample processing can be performed.
To sum up, the embodiment of the invention provides a PCR recovery method and a system, a micro spectrometer is used for detecting PCR recovery identification objects with different thicknesses and different temperatures to obtain detection data, and the PCR recovery identification objects have the most outstanding characteristics of actually measured data at the optimal thickness and the optimal temperature, so that the accuracy of data comparison can be improved; the system can adapt to the PCR recovery method from the physical structure level, has good implementation convenience and continuous operation performance, and is beneficial to the practical application of factories.
The PCR recovery method and system provided by the embodiment of the present invention are described in detail above, and the principle and the embodiment of the present invention are explained in detail herein by applying specific examples, and the description of the above embodiments is only used to help understanding the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. A PCR recovery identification method is used for identifying the type of a PCR recovery identification object, and is characterized by comprising a data acquisition stage and a data processing stage:
the data acquisition phase comprises:
execute
The secondary optical detection step obtaining a detection data set, wherein
The secondary optical detection step comprises: deforming the first local region of the PCR collection identification target to a thickness of
In a plate-like structure
Detecting the first local area with a micro spectrometer at temperature to generate detection data
；
The data processing stage comprises:
receiving a PCR recovery identification object
Group detection data;
by the said
Performing type recognition on the PCR recovery recognition object in a mode of comparing the group detection data with the optimal actual measurement data in the classification database;
the classification database comprises a plurality of groups of preset data groups, each group of preset data group comprises a PCR name and optimal actual measurement data corresponding to the PCR name, and the optimal actual measurement data are detection data obtained by measuring a material corresponding to the PCR name through a microscopic spectrometer at optimal thickness and optimal temperature;
wherein the content of the first and second substances,
， 
， 
， 
；
the total amount of the detected data is
The number of the groups is set to be,
the group detection data is sequentially sorted out,
to represent
And the detection data in the group detection data are sequenced and numbered.
2. The method for identifying PCR recovery according to claim 1, wherein the sequence number is
The plate-like structure has a thickness and a sequence number of
The thickness of the plate-shaped structure satisfies the following conditions:
3. the PCR recovery identification method of claim 1, wherein the micro spectrometer is a micro fourier transform infrared spectrometer;
detecting the first local area by using a micro spectrometer and generating detection data
The method comprises the following steps:
adjusting the micro Fourier transform infrared spectrometer to a transmission mode or a reflection mode and detecting the first local area to generate detection data
；
The detection data
Is an infrared spectrum.
4. The method for PCR recovery identification according to claim 1, wherein the passing is performed by
The way of comparing the group detection data with the data in the classification database includes:
comparing data based on the peak characteristics of the infrared spectrum;
or comparing based on infrared spectrum similarity.
5. The PCR recovery identification method of claim 4, wherein the data alignment based on the infrared spectrum peak features comprises:
at the detection data
Screening to obtain a plurality of peak points, and fitting the plurality of peak points by using a fixed order function to obtain a fitting curve;
and taking the fitted curve as an infrared spectrum, and comparing the similarity based on the infrared spectrum with the data in the classification database.
6. The PCR recovery identification method of claim 4, wherein the comparing based on infrared spectrum similarity comprises:
performing similarity comparison of infrared spectra based on a point method;
comparing the similarity of infrared spectrums based on a shape method;
performing similarity comparison of infrared spectra based on a segmentation method;
and performing similarity comparison of infrared spectra by a task-based method.
7. The method for PCR recovery identification according to claim 4, wherein the PCR recovery identification is carried out by
The type recognition of the PCR recovery recognition object by comparing the group detection data with the data in the classification database comprises the following steps:
detecting each group of data
Traversing the optimal measured data of all the preset data groups to carry out similarity comparison based on infrared spectrum and obtain similarity estimated values;
and judging the type of the PCR recovery identification object as the PCR name corresponding to the best measured data with the highest similarity estimation.
8. A PCR recovery identification system for implementing the PCR recovery identification method according to any one of claims 1 to 7, comprising:
deformation equipment: for deforming the first local region of the PCR collection recognition object to a thickness of
The plate-like structure of (1);
heating equipment: for adjusting the temperature of the first local region to be identified by PCR recovery
；
A micro spectrometer: for detecting the first local region and generating detection data
；
Classifying the database: the method comprises the following steps that a plurality of groups of preset data sets are included, each group of preset data set comprises a PCR name and optimal actual measurement data corresponding to the PCR name, and the optimal actual measurement data are detection data obtained by measuring a material corresponding to the PCR name through a micro spectrometer at the optimal thickness and the optimal temperature;
a processing module: for receiving the detection data
And passing said detected data
And performing type identification on the PCR recovery identification object in a mode of comparing with data in a classification database.
9. The recycling identification system of claim 8, further comprising a heat resistant conveyor belt and a zoned heating stop, the heat resistant conveyor belt and the zoned heating stop combining to form the deforming apparatus and the heating apparatus;
the working surface of the heat-resistant conveying belt translates towards a first direction;
the partition heating limiting device is arranged above the heat-resistant conveying belt;
the partition heating limiting device comprises a bottom plate and a plurality of temperature control units, the front surface of the bottom plate faces the working surface, and the temperature control units are arranged on the back surface of the bottom plate;
the partition heating limiting device is divided into more than two partitions in the first direction, the distance between the front face of the base plate of each partition and the working face of the heat-resistant conveying belt is gradually reduced along the direction of the first direction, and one temperature control unit is arranged on the back face of the base plate of each partition.
10. The recycling identification system of claim 9, wherein a viewing aperture is provided in the floor of each of said sections, said viewing aperture being filled with a transparent medium;
and the micro spectrometer detects the corresponding first local area through the transparent medium.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5489778A (en) * | 1992-11-21 | 1996-02-06 | Laser Zentrum Hannover E.V. | Process and installation for the identification of materials |
| US20130321805A1 (en) * | 2010-07-09 | 2013-12-05 | K-Space Associates, Inc. | Real-time temperature, optical band gap, film thickness, and surface roughness measurement for thin films applied to transparent substrates |
| CN106018324A (en) * | 2016-08-15 | 2016-10-12 | 中国计量大学 | Plastic identification apparatus and method based on near-infrared spectroscopy analysis |
| US20200197981A1 (en) * | 2017-05-11 | 2020-06-25 | 6511660 Canada Inc. | Systems and methods for spectral identification and optical sorting of materials |
| CN113095388A (en) * | 2021-04-01 | 2021-07-09 | 福建师范大学 | Solid waste plastic material identification method based on double-layer classification algorithm |
| WO2021231396A1 (en) * | 2020-05-11 | 2021-11-18 | Woods Hole Oceanographic Institution | Optical system and method to identify plastic |
-
2022
- 2022-08-19 CN CN202210995557.8A patent/CN115062807B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5489778A (en) * | 1992-11-21 | 1996-02-06 | Laser Zentrum Hannover E.V. | Process and installation for the identification of materials |
| US20130321805A1 (en) * | 2010-07-09 | 2013-12-05 | K-Space Associates, Inc. | Real-time temperature, optical band gap, film thickness, and surface roughness measurement for thin films applied to transparent substrates |
| CN106018324A (en) * | 2016-08-15 | 2016-10-12 | 中国计量大学 | Plastic identification apparatus and method based on near-infrared spectroscopy analysis |
| US20200197981A1 (en) * | 2017-05-11 | 2020-06-25 | 6511660 Canada Inc. | Systems and methods for spectral identification and optical sorting of materials |
| WO2021231396A1 (en) * | 2020-05-11 | 2021-11-18 | Woods Hole Oceanographic Institution | Optical system and method to identify plastic |
| CN113095388A (en) * | 2021-04-01 | 2021-07-09 | 福建师范大学 | Solid waste plastic material identification method based on double-layer classification algorithm |
Non-Patent Citations (2)
| Title |
|---|
| 李晓英等: "基于红外光谱分析的塑料识别方法", 《北京信息科技大学学报(自然科学版)》 * |
| 高虹等: "一种热致变色玻璃材料的制备及性能研究", 《功能材料》 * |
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