A method and system for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things

Abstract

The present invention relates to the technical field of cadmium zinc telluride crystal growth quality supervision, and in particular to a cadmium zinc telluride crystal growth quality supervision method and system based on the Internet of Things. The method effectively improves the growth quality of cadmium zinc telluride crystals. The method deploys sensors in a growth furnace based on the Bridgman method to collect temperature data and position data, establishes a temperature field temperature cloud map based on the temperature data and position data, and then establishes a dynamic growth model. The dynamic growth model is used to obtain an ampoule motion trajectory through real-time analysis, and the trajectory is associated with the temperature field temperature cloud map in relative motion to obtain a temperature field relative motion model. The ampoule relative motion temperature data is obtained based on the temperature field relative motion model to obtain a corresponding correction data set. A correction instruction corresponding to the correction data set is set to correct the correction data set.

Description

Technical Field

[0001] The present invention relates to the technical field of cadmium zinc telluride crystal growth quality supervision technology, and in particular to a cadmium zinc telluride crystal growth quality supervision method and system based on the Internet of Things. Background Art

[0002] Cadmium zinc telluride crystal is an important substrate material for mercury cadmium telluride infrared detectors. It is commonly grown using the Bridgman method, and directional cooling crystallization is achieved through the relative movement of the ampoule and the temperature field in the growth furnace. As a directly controllable parameter, the temperature field can be adjusted through appropriate furnace temperature distribution and pulling rate. The temperature field has the most important influence on the quality of crystal growth. The accurate description of the temperature field is a complex heat transfer problem, involving three heat transfer mechanisms: conduction, convection, and radiation, as well as the interaction between them. The cadmium zinc telluride crystal growth furnace has a cylindrical cavity structure. Its main feature is that it has a dual temperature zone. The upper and middle sections of the furnace provide the ingot melting temperature, and the lower section provides heat preservation annealing after crystal growth. The middle section is a temperature gradient adjustment zone.

[0003] However, if the temperature gradient is uneven during the process of achieving directional cooling crystallization through the relative movement of the ampoule and the temperature field in the growth furnace, defects or uneven growth may occur inside the crystal. Secondly, the relative movement temperature of the ampoule in the growth furnace temperature field during relative movement and the relative movement of the temperature field need to be precisely controlled. Therefore, in order to solve the above problems, the present invention provides a method and system for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things;

[0005] The purpose of the present invention can be achieved by the following technical solution: a method for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things, the method comprising the following steps:

[0006] Step S1: Deploy sensors in the growth furnace based on the Bridgman method to collect temperature data and position data, establish a temperature field cloud map based on the temperature data and position data, and then establish a dynamic growth model;

[0007] Step S2: obtaining the motion trajectory of the ampoule in real time according to the dynamic growth model, and correlating the relative motion with the temperature cloud map of the temperature field to obtain the relative motion model of the temperature field;

[0008] Step S3: obtaining the relative motion temperature data of the ampoule based on the temperature field relative motion model, and then obtaining the corresponding corrected data set;

[0009] Step S4: setting a correction instruction corresponding to the correction data set, and correcting the correction data set.

[0010] Furthermore, the process of deploying sensors in the growth furnace based on the Bridgman method to collect temperature data and position data includes:

[0011] Performing structural mapping on the growth furnace to obtain a growth furnace cylinder, wherein the growth furnace cylinder includes an upper bottom surface of the growth furnace, a lower bottom surface of the growth furnace, a height, and an axis; the upper bottom surface of the growth furnace and the lower bottom surface of the growth furnace include a center and a radius;

[0012] The growth furnace cylinder is divided into upper, middle, and lower sections, and the upper-middle section dividing points and the middle-lower section dividing points corresponding to the upper, middle, and lower sections are obtained; temperature points are respectively deployed in the upper, middle, and lower sections and marked as i, where i=1, 2, ..., j, and j is a positive integer; temperature sensors are deployed at the upper-middle section dividing point, the middle-lower section dividing point, and the temperature points to collect corresponding temperature data;

[0013] Among them, the starting temperature point and the central temperature point are deployed in the upper section, several middle temperature points and several central temperature points are deployed in the middle section, and the central temperature point and the ending temperature point are deployed in the lower section;

[0014] A head position node and a center position node are set on the ampoule device, and a head position sensor and a center position sensor are installed on the head position node and the center position node respectively; the head position sensor is used to collect the ampoule tilt angle; the center position sensor is used to collect the ampoule horizontal position data and vertical position data;

[0015] A speed sensor is installed at the central position node to collect ampoule relative speed data; the ampoule tilt angle, ampoule horizontal position data, vertical position data and ampoule relative speed data are integrated to generate an ampoule motion data set.

[0016] Furthermore, the temperature field temperature cloud map establishment process includes:

[0017] Set the cutting height corresponding to the temperature point, place each temperature point on the radius corresponding to the cut upper bottom surface of the growth furnace, use the axis as the critical surface to cut the growth furnace cylinder according to the cutting height to obtain the corresponding cut lower bottom surface of the growth furnace, and then obtain the cut growth furnace cylinder, and obtain the volume of the cut growth furnace cylinder, which is marked as the temperature data display area; connect the temperature data display areas corresponding to each temperature point according to the growth furnace cylinder to generate a temperature field temperature cloud map.

[0018] Furthermore, the process of establishing the dynamic growth model includes:

[0019] A dynamic rectangular coordinate system is established with the central position node as the origin, the horizontal position data and the vertical position data as the abscissa and ordinate respectively, and the relative velocity data of the ampoule is represented in the direction starting from the origin; then the dynamic rectangular coordinate system is mapped to the temperature field cloud map to construct a dynamic growth model.

[0020] Furthermore, the process of obtaining the ampoule motion trajectory includes:

[0021] Taking the starting temperature point as the starting position, set the starting acquisition time point and acquisition cycle, obtain the acquisition time point corresponding to each temperature point according to the acquisition cycle, and obtain the real-time data set corresponding to the acquisition time point in real time based on the dynamic growth model. The real-time data set includes the temperature data display area where the central position node is located, temperature data, and ampoule movement data set;

[0022] Obtaining the ampoule motion trajectory according to the ampoule motion dataset;

[0023] That is, the specific formula is: ;

[0024] in, and It is represented as the motion trajectory of the ampoule corresponding to the acquisition time point t; and It is represented by the horizontal position data and vertical position data of the ampoule corresponding to the acquisition time point t; and It is represented by the start time of acquisition and the relative speed data of the ampoule corresponding to the acquisition time t. is the inclination angle of the ampoule.

[0025] Furthermore, the process of acquiring the temperature field relative motion model includes:

[0026] Obtain the temperature data display area corresponding to the ampoule motion trajectory at the acquisition time point, and obtain the temperature data corresponding to the temperature data display area, set the corresponding temperature data threshold range according to the temperature data display area where the ampoule motion trajectory is located, and compare it with the corresponding temperature data;

[0027] If the temperature data is within the temperature data threshold range, the next acquisition time point is obtained, and the corresponding ampoule motion trajectory is obtained, and then the temperature data threshold range corresponding to the temperature data display area where the ampoule motion trajectory is located is compared again, until the temperature data corresponding to the temperature data display area where the acquisition time point is located does not fall within the temperature data threshold range, then the corresponding temperature data display area is marked as an abnormal display area; otherwise, the corresponding temperature data display area is marked as a normal display area;

[0028] Acquire the ampoule relative velocity data and corresponding temperature data of the ampoule motion trajectory corresponding to the abnormal display area, and couple the ampoule relative velocity data and temperature data with the ampoule motion trajectory to construct a temperature field relative motion model;

[0029] That is, the specific formula is: ;

[0030] in, It is expressed as the temperature data change rate of the abnormal display area corresponding to the acquisition time point t; Expressed as the gradient corresponding to the temperature data T; and Expressed as the temperature data corresponding to the ampoule motion trajectory and The second derivative of Expressed as thermal diffusivity.

[0031] Furthermore, the process of obtaining the corrected data set includes:

[0032] Obtain the relative motion temperature data of the ampoule corresponding to the acquisition time point according to the temperature data change rate;

[0033] That is, the specific formula is: ;

[0034] in, Expressed as ampoule relative motion temperature data;

[0035] Data mapping is performed between the relative motion temperature data of the ampoule and the corresponding abnormal display area to obtain a corrected data set corresponding to the abnormal display area.

[0036] Furthermore, a correction instruction corresponding to the correction data set is set, and the process of correcting the correction data set includes:

[0037] A corresponding instruction code is set for each temperature data display area, marked as #i, and the correction instruction corresponding to the correction data set is (#i, T(t)). The correction instruction corresponding to the correction data set is sent to a preset temperature control device, and the abnormal display area and ampoule relative motion temperature data corresponding to the instruction code are obtained. Then, the temperature corresponding to the abnormal display area is adjusted to the ampoule relative motion temperature data, and the correction is completed.

[0038] Furthermore, the following modules are included:

[0039] Acquisition and deployment module: used to deploy sensors in the growth furnace based on the Bridgman method, collect temperature data and position data, and establish a temperature field temperature cloud map based on the temperature and position data, and then establish a dynamic growth model;

[0040] Data association module: used to obtain the ampoule motion trajectory through real-time analysis based on the dynamic growth model, and to associate the relative motion with the temperature field cloud map to obtain the temperature field relative motion model;

[0041] Correction data set generation module: used to obtain the relative motion temperature data of the ampoule based on the relative motion model of the temperature field, and then obtain the corresponding correction data set;

[0042] Correction module: used to set the correction instructions corresponding to the correction data set and correct the correction data set.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The present invention deploys sensors in a growth furnace based on the Bridgman method to collect temperature data and position data, establishes a temperature field temperature cloud map based on the temperature data and position data, and then establishes a dynamic growth model; obtains the motion trajectory of the ampoule in real time through analysis of the dynamic growth model, and associates the relative motion with the temperature field temperature cloud map to obtain a temperature field relative motion model; monitors the temperature data in real time based on the temperature data and the temperature data display area; and visually observes whether the temperature of the upper, middle, and lower sections of the temperature field is uniform. The uniform temperature effectively improves the growth quality.

[0045] 2. Based on the temperature field relative motion model, the relative motion temperature data of the ampoule is obtained, and then the corresponding correction data set is obtained; the correction instructions corresponding to the correction data set are set to correct the correction data set; effectively regulating the relative motion temperature data of the ampoule can improve the growth quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0047] Figure 1 Flowchart of the present invention.

[0048] Figure 2 Schematic diagram of the dynamic growth model.

[0049] Figure 3 This is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0050] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention. Example

[0051] like Figure 1 As shown, a method for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things comprises the following steps:

[0052] Step S1: Deploy sensors in the growth furnace based on the Bridgman method to collect temperature data and position data, establish a temperature field cloud map based on the temperature data and position data, and then establish a dynamic growth model;

[0053] Step S2: obtaining the motion trajectory of the ampoule in real time according to the dynamic growth model, and correlating the relative motion with the temperature cloud map of the temperature field to obtain the relative motion model of the temperature field;

[0054] Step S3: obtaining the relative motion temperature data of the ampoule based on the temperature field relative motion model, and then obtaining the corresponding corrected data set;

[0055] Step S4: setting a correction instruction corresponding to the correction data set, and correcting the correction data set. Example

[0056] This embodiment further limits the embodiment 1, and the step S1 is implemented by the following process:

[0057] The process of deploying sensors in the growth furnace based on the Bridgman method to collect temperature data and position data includes:

[0058] Performing structural mapping on the growth furnace to obtain a growth furnace cylinder, wherein the growth furnace cylinder includes an upper bottom surface of the growth furnace, a lower bottom surface of the growth furnace, a height, and an axis; the upper bottom surface of the growth furnace and the lower bottom surface of the growth furnace include a center and a radius;

[0059] The growth furnace cylinder is divided into upper, middle, and lower sections, and the upper-middle section dividing points and the middle-lower section dividing points corresponding to the upper, middle, and lower sections are obtained; temperature points are respectively deployed in the upper, middle, and lower sections and marked as i, where i=1, 2, ..., j, and j is a positive integer; temperature sensors are deployed at the upper-middle section dividing point, the middle-lower section dividing point, and the temperature points to collect corresponding temperature data;

[0060] Among them, the starting temperature point and the central temperature point are deployed in the upper section, several middle temperature points and several central temperature points are deployed in the middle section, and the central temperature point and the ending temperature point are deployed in the lower section;

[0061] It should be further explained that, in a specific embodiment, the temperature sensor includes but is not limited to a platinum resistance temperature sensor, etc.;

[0062] A head position node and a center position node are set on the ampoule device, and a head position sensor and a center position sensor are installed on the head position node and the center position node respectively; the head position sensor is used to collect the ampoule tilt angle; the center position sensor is used to collect the ampoule horizontal position data and vertical position data;

[0063] A speed sensor is installed at the central position node to collect ampoule relative speed data; the ampoule tilt angle, ampoule horizontal position data, vertical position data and ampoule relative speed data are integrated to generate an ampoule motion data set.

[0064] In the above embodiment, it needs to be further explained that the position sensor includes but is not limited to a linear encoder, a Hall sensor, etc.; the furnace is divided into upper, middle and lower sections for temperature acquisition and control because the cadmium zinc telluride crystal growth furnace is a cylindrical cavity structure, and its main feature is that it has a dual temperature zone, the upper and middle sections of the furnace provide the ingot melting temperature, the lower section provides the heat preservation annealing after the crystal growth, and the middle section is a temperature gradient adjustment zone; different temperature points are deployed in different regional sections, among which several temperature points are deployed in the middle section to ensure the stability of the temperature gradient.

[0065] The temperature field temperature cloud map establishment process includes:

[0066] like Figure 2 As shown, the cutting height corresponding to the temperature point is set, and each temperature point is located on the radius corresponding to the cut bottom surface of the growth furnace. The axis is used as the critical surface and the growth furnace cylinder is cut according to the cutting height to obtain the corresponding cut bottom surface of the growth furnace, and then the cut growth furnace cylinder is obtained. The volume of the cut growth furnace cylinder is obtained and marked as the temperature data display area; the temperature data display areas corresponding to each temperature point are connected according to the growth furnace cylinder to generate a temperature field temperature cloud map;

[0067] In the above embodiment, it needs to be further explained that the cadmium zinc telluride crystal growth furnace is a cylindrical cavity structure; the settings of the cutting heights are not all the same, but are set according to the positions corresponding to the temperature points and the temperature points between adjacent ones. Furthermore, the temperature inside the growth furnace can be better concretized with the axis as the critical surface; therefore, the temperature data display area obtained is the area corresponding to the upper, middle and lower sections; and then the temperature data is monitored in real time based on the temperature data and the temperature data display area; it can be intuitively observed whether the temperature of the temperature field corresponding to the upper, middle and lower sections is uniform, and uniform temperature can improve the growth quality.

[0068] The process of establishing the dynamic growth model includes:

[0069] A dynamic rectangular coordinate system is established with the central position node as the origin, the horizontal position data and the vertical position data as the abscissa and ordinate respectively, and the relative velocity data of the ampoule is represented in the direction starting from the origin; then the dynamic rectangular coordinate system is mapped to the temperature field cloud map to construct a dynamic growth model.

[0070] It should be further explained that, in a specific implementation process, the inclination angle of the ampoule is the angle with the vertical axis. Example

[0071] This embodiment further limits the embodiment 1, and the step S2 is implemented by the following process:

[0072] The process of obtaining the ampoule motion trajectory includes:

[0073] Taking the starting temperature point as the starting position, set the starting acquisition time point and acquisition cycle, obtain the acquisition time point corresponding to each temperature point according to the acquisition cycle, and obtain the real-time data set corresponding to the acquisition time point in real time based on the dynamic growth model. The real-time data set includes the temperature data display area where the central position node is located, temperature data, and ampoule movement data set;

[0074] Obtaining the ampoule motion trajectory according to the ampoule motion dataset;

[0075] That is, the specific formula is: ;

[0076] in, and It is represented as the motion trajectory of the ampoule corresponding to the acquisition time point t; and It is represented by the horizontal position data and vertical position data of the ampoule corresponding to the acquisition time point t; and It is represented by the start time of collection and the relative speed data of the ampoule corresponding to the collection time t; is the inclination angle of the ampoule.

[0077] The process of acquiring the temperature field relative motion model includes:

[0078] Obtain the temperature data display area corresponding to the ampoule motion trajectory at the acquisition time point, and obtain the temperature data corresponding to the temperature data display area, set the corresponding temperature data threshold range according to the temperature data display area where the ampoule motion trajectory is located, and compare it with the corresponding temperature data;

[0079] If the temperature data is within the temperature data threshold range, the next acquisition time point is obtained, and the corresponding ampoule motion trajectory is obtained, and then the temperature data threshold range corresponding to the temperature data display area where the ampoule motion trajectory is located is compared again, until the temperature data corresponding to the temperature data display area where the acquisition time point is located does not fall within the temperature data threshold range, then the corresponding temperature data display area is marked as an abnormal display area; otherwise, the corresponding temperature data display area is marked as a normal display area;

[0080] Acquire the ampoule relative velocity data and corresponding temperature data of the ampoule motion trajectory corresponding to the abnormal display area, and couple the ampoule relative velocity data and temperature data with the ampoule motion trajectory to construct a temperature field relative motion model;

[0081] That is, the specific formula is: ;

[0082] in, It is expressed as the temperature data change rate of the abnormal display area corresponding to the acquisition time point t; Expressed as the gradient corresponding to the temperature data T; and Expressed as the temperature data corresponding to the ampoule motion trajectory and The second derivative of Expressed as thermal diffusivity. Example

[0083] This embodiment further limits the embodiment 1, and the step S3 is implemented by the following process:

[0084] The process of obtaining the corrected data set includes:

[0085] Obtain the relative motion temperature data of the ampoule corresponding to the acquisition time point according to the temperature data change rate;

[0086] That is, the specific formula is: ;

[0087] in, Expressed as ampoule relative motion temperature data;

[0088] Data mapping is performed between the relative motion temperature data of the ampoule and the corresponding abnormal display area to obtain a corrected data set corresponding to the abnormal display area.

[0089] In the above embodiment, it needs to be further explained that, based on obtaining the temperature data corresponding to the abnormal display area and obtaining the ampoule motion trajectory, the temperature data and the ampoule motion trajectory are coupled to establish a temperature field relative motion model, and based on the temperature field relative motion model, the ampoule relative motion temperature data corresponding to the ampoule in the abnormal display area is obtained, and then a corrected data set is obtained; the temperature data corresponding to the abnormal display area can be better corrected to improve the growth quality. Example

[0090] This embodiment further limits the embodiment 1, and the step S4 is implemented by the following process:

[0091] Set the correction instructions corresponding to the correction data set. The process of correcting the correction data set includes:

[0092] A corresponding instruction code is set for each temperature data display area, marked as #i, and the correction instruction corresponding to the correction data set is (#i, T(t)). The correction instruction corresponding to the correction data set is sent to a preset temperature control device, and the abnormal display area and ampoule relative motion temperature data corresponding to the instruction code are obtained. Then, the temperature corresponding to the abnormal display area is adjusted to the ampoule relative motion temperature data, and the correction is completed. Example

[0093] like Figure 3 As shown, the present invention also provides a supervision system for a CdZnTe crystal growth quality supervision method based on the Internet of Things, comprising the following modules:

[0094] Acquisition and deployment module: used to deploy sensors in the growth furnace based on the Bridgman method, collect temperature data and position data, and establish a temperature field temperature cloud map based on the temperature and position data, and then establish a dynamic growth model;

[0095] Data association module: used to obtain the ampoule motion trajectory through real-time analysis based on the dynamic growth model, and to associate the relative motion with the temperature field cloud map to obtain the temperature field relative motion model;

[0096] Correction data set generation module: used to obtain the relative motion temperature data of the ampoule based on the relative motion model of the temperature field, and then obtain the corresponding correction data set;

[0097] Correction module: used to set the correction instructions corresponding to the correction data set and correct the correction data set.

[0098] The features and exemplary embodiments of various aspects of the present application are described in detail above. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail in combination with the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The above description of the embodiments is merely to provide a better understanding of the present application by showing examples of the present application.

[0099] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things, characterized in that: The method comprises the following steps: Step S1: Deploy sensors in the growth furnace based on the Bridgman method to collect temperature data and position data, establish a temperature field cloud map based on the temperature data and position data, and then establish a dynamic growth model; Step S2: obtaining the motion trajectory of the ampoule in real time according to the dynamic growth model, and correlating the relative motion with the temperature cloud map of the temperature field to obtain the relative motion model of the temperature field; Step S3: obtaining the relative motion temperature data of the ampoule based on the temperature field relative motion model, and then obtaining the corresponding corrected data set; Step S4: setting a correction instruction corresponding to the correction data set, and correcting the correction data set; The process of deploying sensors in the growth furnace based on the Bridgman method to collect temperature data and position data includes: Performing structural mapping on the growth furnace to obtain a growth furnace cylinder, dividing the growth furnace cylinder into upper, middle, and lower sections, and obtaining upper-middle segmentation points and middle-lower segmentation points corresponding to the upper, middle, and lower sections; and deploying temperature points in the upper, middle, and lower sections, respectively, and marking them as i, where i=1, 2, ..., j, and j is a positive integer; and deploying temperature sensors at the upper-middle segmentation point, the middle-lower segmentation point, and the temperature points to collect corresponding temperature data; A head position node and a center position node are set on the ampoule device, and a head position sensor and a center position sensor are installed on the head position node and the center position node respectively; the head position sensor is used to collect the ampoule tilt angle; the center position sensor is used to collect the ampoule horizontal position data and vertical position data; A speed sensor is installed at the central position node to collect ampoule relative speed data; the ampoule tilt angle, ampoule horizontal position data, vertical position data and ampoule relative speed data are integrated to generate an ampoule motion data set; The process of obtaining the ampoule motion trajectory includes: Taking the starting temperature point as the starting position, set the starting acquisition time point and acquisition cycle, obtain the acquisition time point corresponding to each temperature point according to the acquisition cycle, and obtain the real-time data set corresponding to the acquisition time point in real time based on the dynamic growth model. The real-time data set includes the temperature data display area where the central position node is located, temperature data, and ampoule movement data set; Obtaining the ampoule motion trajectory according to the ampoule motion dataset; That is, the specific formula is: ; in, and It is represented as the motion trajectory of the ampoule corresponding to the acquisition time point t; and It is represented by the horizontal position data and vertical position data of the ampoule corresponding to the acquisition time point t; and It is represented by the start time of collection and the relative speed data of the ampoule corresponding to the collection time t; is the tilt angle of the ampoule; The process of acquiring the temperature field relative motion model includes: Obtain the temperature data display area corresponding to the ampoule motion trajectory at the acquisition time point, and obtain the temperature data corresponding to the temperature data display area, set the corresponding temperature data threshold range according to the temperature data display area where the ampoule motion trajectory is located, and compare it with the corresponding temperature data; If the temperature data is within the temperature data threshold range, the next acquisition time point is obtained, and the corresponding ampoule motion trajectory is obtained, and then the temperature data threshold range corresponding to the temperature data display area where the ampoule motion trajectory is located is compared again, until the temperature data corresponding to the temperature data display area where the acquisition time point is located does not fall within the temperature data threshold range, then the corresponding temperature data display area is marked as an abnormal display area; otherwise, the corresponding temperature data display area is marked as a normal display area; Acquire the ampoule relative velocity data and corresponding temperature data of the ampoule motion trajectory corresponding to the abnormal display area, and couple the ampoule relative velocity data and temperature data with the ampoule motion trajectory to construct a temperature field relative motion model; That is, the specific formula is: ; in, It is expressed as the temperature data change rate of the abnormal display area corresponding to the acquisition time point t; Expressed as the gradient corresponding to the temperature data T; and Expressed as the temperature data corresponding to the ampoule motion trajectory and The second derivative of Expressed as thermal diffusivity.

2. The method for monitoring the growth quality of CdZnTe crystals based on the Internet of Things according to claim 1, wherein: The temperature field temperature cloud map establishment process includes: Set the cutting height corresponding to the temperature point, place each temperature point on the radius corresponding to the cut upper bottom surface of the growth furnace, use the axis as the critical surface to cut the growth furnace cylinder according to the cutting height to obtain the corresponding cut lower bottom surface of the growth furnace, and then obtain the cut growth furnace cylinder, and obtain the volume of the cut growth furnace cylinder, which is marked as the temperature data display area; connect the temperature data display areas corresponding to each temperature point according to the growth furnace cylinder to generate a temperature field temperature cloud map.

3. The method for monitoring the growth quality of CdZnTe crystals based on the Internet of Things according to claim 1, wherein: The process of establishing the dynamic growth model includes: A dynamic rectangular coordinate system is established with the central position node as the origin, the horizontal position data and the vertical position data as the abscissa and ordinate respectively, and the relative velocity data of the ampoule is represented in the direction starting from the origin; then the dynamic rectangular coordinate system is mapped to the temperature field cloud map to construct a dynamic growth model.

4. The method for monitoring the growth quality of CdZnTe crystals based on the Internet of Things according to claim 1, wherein: The process of obtaining the corrected data set includes: Obtain the relative motion temperature data of the ampoule corresponding to the acquisition time point according to the temperature data change rate; That is, the specific formula is: ; in, Expressed as ampoule relative motion temperature data; Data mapping is performed between the relative motion temperature data of the ampoule and the corresponding abnormal display area to obtain a corrected data set corresponding to the abnormal display area.

5. The method for monitoring the growth quality of CdZnTe crystals based on the Internet of Things according to claim 1, wherein: Set the correction instructions corresponding to the correction data set. The process of correcting the correction data set includes: A corresponding instruction code is set for each temperature data display area, marked as #i, and the correction instruction corresponding to the correction data set is (#i, T(t)). The correction instruction corresponding to the correction data set is sent to a preset temperature control device, and the abnormal display area and ampoule relative motion temperature data corresponding to the instruction code are obtained. Then, the temperature corresponding to the abnormal display area is adjusted to the ampoule relative motion temperature data, and the correction is completed.

6. A system for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things, applied to a method for monitoring the growth quality of cadmium zinc telluride crystals based on the Internet of Things as claimed in any one of claims 1 to 5, characterized in that: Includes the following modules: Acquisition and deployment module: used to deploy sensors in the growth furnace based on the Bridgman method, collect temperature data and position data, and establish a temperature field temperature cloud map based on the temperature and position data, and then establish a dynamic growth model; Data association module: used to obtain the ampoule motion trajectory through real-time analysis based on the dynamic growth model, and to associate the relative motion with the temperature field cloud map to obtain the temperature field relative motion model; Correction data set generation module: used to obtain the relative motion temperature data of the ampoule based on the relative motion model of the temperature field, and then obtain the corresponding correction data set; Correction module: used to set the correction instructions corresponding to the correction data set and correct the correction data set.

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