Abnormality monitoring method for indium phosphide crystal growing furnace

Abstract

The invention relates to the technical field of general control systems, in particular to an abnormity monitoring method for an indium phosphide crystal growing furnace, which comprises the following steps: analyzing the operation condition of the growing furnace based on the growth operation data of the growing furnace, and then analyzing the condition of the growing furnace by combining the operation condition of the growing furnace and the internal growth environment data, meanwhile, the growth state of the indium phosphide crystal is analyzed based on the growth state data of the indium phosphide crystal in the growth furnace, the growth quality of the indium phosphide crystal is estimated according to the analysis result of the condition of the growth furnace and the analysis result of the growth state of the indium phosphide crystal obtained through analysis, and a big data analysis mode is adopted; the growth furnace condition analysis result and the growth state analysis result of the indium phosphide crystal are analyzed in real time, so that the growth quality of the crystal is accurately estimated in real time, and the growth quality of the indium phosphide crystal and the monitoring safety are improved.

Description

Background Art

[0002] Indium phosphide (InP) wafer is an important semiconductor material, widely used in optoelectronics and high-speed electronics. InP wafer has direct band gap characteristics, which makes it widely used in optoelectronic devices such as laser diodes, photodetectors and optoelectronic integrated circuits. In addition, due to its high electron mobility and excellent thermal conductivity, InP is also suitable for high-frequency and high-speed electronic devices, such as radar systems, satellite communications and high-frequency amplifiers in optical fiber communications. In the process of manufacturing InP wafers, chemical vapor deposition (CVD), molecular beam epitaxy (MBE) or metal organic chemical vapor deposition (MOCVD) and other technologies are usually used. These technologies can accurately control the composition and structure of the material to meet the needs of different applications. In the process of InP crystal growth, it is usually necessary to grow in an InP crystal growth furnace. The abnormality of the crystal growth furnace directly leads to the quality of InP crystal growth. Therefore, it is necessary to monitor the growth process of the InP crystal growth furnace.

[0003] However, in the process of abnormal monitoring of the indium phosphide crystal growth furnace, the existing technology can only find the abnormal parameters by comparing the parameters at the same time, and cannot analyze the growth furnace situation analysis results and the indium phosphide crystal growth state analysis results in real time to accurately estimate the crystal growth quality in real time, resulting in the inability to distinguish whether the abnormal situation needs to be handled. This is a problem that needs to be solved urgently. Summary of the invention

[0004] In order to overcome the defects and shortcomings of the prior art, the present application provides an abnormal monitoring method for an indium phosphide crystal growth furnace, proposes to analyze the operation status of the growth furnace based on the growth operation data of the growth furnace, and then analyze the growth furnace status based on the comprehensive growth furnace operation status and internal growth environment data, and at the same time analyze the growth status of the indium phosphide crystal based on the growth status data of the indium phosphide crystal in the growth furnace, and estimate the growth quality of the indium phosphide crystal by analyzing the growth furnace status analysis results and the indium phosphide crystal growth status analysis results. By adopting a big data analysis method, the growth furnace status analysis results and the indium phosphide crystal growth status analysis results are analyzed in real time to accurately estimate the growth quality of the crystal in real time, thereby improving the growth quality and monitoring safety of the indium phosphide crystal growth.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions: In a first aspect, the present application provides an abnormality monitoring method for an indium phosphide crystal growth furnace, comprising the following steps: Acquire growth operation data and internal growth environment data of the growth furnace, and acquire growth state data of indium phosphide crystals in the growth furnace; Analyze the operation status of the growth furnace based on the growth operation data of the growth furnace, and then analyze the growth furnace status by combining the operation status of the growth furnace and the internal growth environment data; The growth state of indium phosphide crystals is analyzed based on the growth state data of indium phosphide crystals in the growth furnace; The growth quality of the indium phosphide crystal is estimated by analyzing the growth furnace condition analysis results and the growth state analysis results of the indium phosphide crystal; An analysis is performed to determine whether manual intervention is necessary based on the estimated growth quality of the indium phosphide crystal.

[0006] Optionally, the growth operation data of the growth furnace specifically includes: the operating current, operating voltage and vibration data of the crystal growth furnace during the operation, and other data types reflecting the operating status of the crystal growth furnace; the internal growth environment data of the growth furnace specifically includes: the temperature and pressure of each area inside the growth furnace, and other data types that affect the growth state of the indium phosphide crystal; the growth state data of the indium phosphide crystal in the growth furnace includes the real-time volume, real-time crystal surface defects and cracks area, and position data during the growth process of the indium phosphide crystal in the growth furnace. It should be noted that all parameters of this step are obtained through corresponding sensors.

[0007] Optionally, the step of analyzing the operation status of the growth furnace based on the growth operation data of the growth furnace includes: Acquire the growth operation data of the corresponding growth furnace at each moment, acquire the deviation between the growth operation data of the corresponding growth furnace at each moment and the safety value of the corresponding type of data, and then perform weighted superposition to obtain the growth furnace operation abnormality coefficient at the corresponding moment; The growth furnace operation abnormality coefficients at each corresponding moment during the growth furnace operation are integrated over the time range and then standardized to obtain the growth furnace abnormality. The growth furnace abnormality evaluation formula is: , where t is the operation time, m is the number of types of growth operation data in the growth furnace, and dt is the integral over the time range. is the influence weight of the i-th growth operation data, cit is the value of the i-th growth furnace growth operation data at time t, and cim is the safety value corresponding to the i-th growth furnace growth operation data at time t. In this step, the abnormal situation during the operation of the growth furnace is analyzed.

[0008] Optionally, the step of analyzing the growth furnace status based on the operation status of the growth furnace and the internal growth environment data includes the following specific steps: Acquire growth environment data of each monitoring point inside the growth furnace, and perform abnormal growth environment analysis of the monitoring point based on the deviation of the growth environment data of the corresponding monitoring point from the normal range of the growth environment. It should be noted that the number of monitoring points is determined and evenly distributed inside the growth furnace; The internal environment impact abnormality analysis is performed based on the distance of each monitoring point from the crystal growth range and the abnormal analysis results of the growth environment at the monitoring point. The internal environment impact abnormality analysis formula is: , where n is the number of monitoring points, Lm is the set distance standard value, Lc is the shortest distance between the c-th monitoring point and the crystal, Fc is the data type of the growth environment of the c-th monitoring point, Df is the influence weight of the f-th growth environment, and where kf is the value of the data type of the f-th growth environment of the monitoring point, and kfm is the normal value of the f-th growth environment of the monitoring point. In this way, the abnormal environment inside the growth furnace is analyzed through the above steps; The abnormal situation analysis results of the growth furnace and the abnormal analysis results of the internal environment impact are obtained, weighted, and then added to obtain the abnormal results of the growth furnace growth impact.

[0009] Optionally, the step of analyzing the growth state of the indium phosphide crystal includes: The growth state data of the indium phosphide crystal is obtained, and the growth quality analysis is performed based on the growth state data of the indium phosphide crystal.

[0010] Optionally, the estimating the growth quality of the indium phosphide crystal comprises the following specific steps: The obtained growth furnace growth influence abnormal results and growth defect analysis results are used to estimate the growth quality of the grown indium phosphide crystal, wherein the growth quality estimation formula is: , where r is the growth furnace growth influence coefficient, which is used to reflect the influence of growth furnace abnormality on growth quality, and tmax is the set indium phosphide wafer growth time; The estimated growth quality of the indium phosphide crystal is compared with the set growth quality standard value. If the growth quality of the indium phosphide crystal is greater than or equal to the set growth quality standard value, it means that the growth of the indium phosphide crystal is normal and there is no need to adjust the growth furnace parameters. If the growth quality of the indium phosphide crystal is less than the set growth quality standard value, it means that the growth of the indium phosphide crystal is abnormal and the growth furnace parameters need to be adjusted, and an early warning is issued.

[0011] In a second aspect, the present application provides an electronic device comprising: a processor and a memory, wherein the memory stores a computer program that can be called by the processor, and the processor executes an abnormality monitoring method for an indium phosphide crystal growth furnace by calling the computer program stored in the memory.

[0012] In a third aspect, the present application provides a computer-readable storage medium storing instructions, which, when executed on a computer, enable the computer to execute an abnormality monitoring method for an indium phosphide crystal growth furnace.

[0013] Compared with the prior art, this application has the following advantages and beneficial effects: The present application analyzes the operation status of the growth furnace based on the growth operation data of the growth furnace, and then analyzes the growth furnace status based on the comprehensive growth furnace operation status and internal growth environment data. At the same time, the growth status of the indium phosphide crystal is analyzed based on the growth status data of the indium phosphide crystal in the growth furnace. The growth quality of the indium phosphide crystal is estimated by analyzing the growth furnace status analysis results and the indium phosphide crystal growth status analysis results obtained by analysis. By adopting a big data analysis method, the growth furnace status analysis results and the indium phosphide crystal growth status analysis results are analyzed in real time to accurately estimate the growth quality of the crystal in real time, thereby improving the growth quality and monitoring safety of the indium phosphide crystal growth. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Other features, objects and advantages of the present application will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings: Figure 1 It is a schematic diagram of the overall process of an embodiment of the method of the present application; Figure 2 This is a flow chart of step 2 of the method embodiment of the present application; Figure 3 It is a schematic diagram of the data analysis process provided in the embodiment of the present application. DETAILED DESCRIPTION

[0015] The technical solution of the present application is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0016] See also Figure 1 , Figure 1 1 is a schematic diagram of the overall process of an abnormality monitoring method for an indium phosphide crystal growth furnace provided in an embodiment of the present application, which specifically includes the following steps: Step 1, obtaining growth operation data and internal growth environment data of the growth furnace, and obtaining growth state data of the indium phosphide crystal in the growth furnace; In this embodiment, if Figure 3 As shown, Figure 3: is a schematic diagram of a data analysis process provided by an embodiment of the present application, wherein the growth operation data of the growth furnace specifically includes: the operating current, operating voltage, and vibration data during the operation of the crystal growth furnace, and other data types that reflect the operating state of the crystal growth furnace; the internal growth environment data of the growth furnace specifically includes: the temperature and pressure of each area inside the growth furnace, and other data types that affect the growth state of the indium phosphide crystal; the growth state data of the indium phosphide crystal in the growth furnace includes the real-time volume, the area and position data of the real-time crystal surface defects and cracks during the growth process of the indium phosphide crystal in the growth furnace. It should be noted that all parameters of this step are obtained through corresponding sensors, for example, the operating current and operating voltage of the corresponding crystal growth furnace are obtained through current sensors and voltage sensors, respectively, and the various collected data are stored in corresponding storage components for call analysis; Step 2: Analyze the operation status of the growth furnace based on the growth operation data of the growth furnace, and then analyze the growth furnace status by combining the operation status of the growth furnace and the internal growth environment data; In this embodiment, the step of analyzing the operation status of the growth furnace based on the growth operation data of the growth furnace includes: Figure 2 As shown: Step 21, obtaining the growth operation data of the corresponding growth furnace at each moment, obtaining the deviation between the growth operation data of the corresponding growth furnace at each moment and the safety value of the corresponding type data, and then performing weighted superposition to obtain the growth furnace operation abnormality coefficient at the corresponding moment; Step 22: Integrate the growth furnace operation abnormality coefficients at each corresponding moment during the operation of the growth furnace over a time range and then standardize them to obtain the growth furnace abnormality. The growth furnace abnormality evaluation formula is: , where t is the operation time, m is the number of types of growth operation data in the growth furnace, and dt is the integral over the time range. is the influence weight of the ith growth operation data, cit is the value of the ith growth furnace growth operation data at time t, cim is the safety value corresponding to the ith growth furnace growth operation data at time t, for example, the safety current of the ith growth furnace growth operation data at time t is 2A, while the current at time t is 2.2A, and a current deviation of 0.2A occurs. In this step, the abnormal situation in the growth furnace operation process is analyzed; Step 23, acquiring growth environment data of each monitoring point inside the growth furnace, and performing abnormal growth environment analysis of the monitoring point based on the deviation of the growth environment data of the corresponding monitoring point from the normal range of the growth environment. It should be noted that the number of monitoring points is determined and evenly distributed inside the growth furnace; Step 24, perform an internal environment impact abnormality analysis based on the distance of each monitoring point from the crystal growth range and the abnormal growth environment analysis results of the monitoring point, wherein the internal environment impact abnormality analysis formula is: , where n is the number of monitoring points, Lm is the set distance standard value, Lc is the shortest distance between the c-th monitoring point and the crystal, Fc is the data type of the growth environment of the c-th monitoring point, Df is the influence weight of the f-th growth environment, and where kf is the value of the data type of the f-th growth environment of the monitoring point, and kfm is the normal value of the f-th growth environment of the monitoring point. In this way, the abnormal environment inside the growth furnace is analyzed through the above steps; Step 25, obtaining the growth furnace abnormality analysis result and the internal environment impact abnormality analysis result, weighting them and adding them together to obtain the growth furnace growth impact abnormality result; Step 3, analyzing the growth state of the indium phosphide crystal based on the growth state data of the indium phosphide crystal in the growth furnace; In this embodiment, the step of analyzing the growth state of the indium phosphide crystal includes: The growth state data of the indium phosphide crystal is obtained, and the growth quality analysis is performed based on the growth state data of the indium phosphide crystal. Here, there are multiple ways to perform the growth quality analysis based on the growth state data of the indium phosphide crystal, including one of the following ways or a combination of the following ways: In one embodiment, the growth defect analysis can be performed based on the area and position data of real-time crystal surface defects and cracks. In another embodiment, the growth size abnormality analysis can also be performed based on the comparison between the appearance size and the normal growth size. In another embodiment, the performance abnormality analysis can also be performed based on the comparison between the physical properties and the normal physical properties. The specific calculation formula for the growth defect analysis based on the area and position data of real-time crystal surface defects and cracks is: , where Ym is the length of the crystal, Yc is the average distance of the crystal defects, U is the number of defects inside the crystal, Vu is the volume of the u-th defect, and Vm is the volume of the crystal; Step 4: estimating the growth quality of the indium phosphide crystal by analyzing the obtained growth furnace situation analysis results and the growth state analysis results of the indium phosphide crystal; In this embodiment, estimating the growth quality of indium phosphide crystals includes the following specific steps: Step 41, obtaining the obtained growth furnace growth influence abnormal results and growth defect analysis results to estimate the growth quality of the grown indium phosphide crystal, wherein the growth quality estimation formula is: , where r is the growth furnace growth influence coefficient, which is used to reflect the influence of growth furnace abnormality on growth quality, and tmax is the set indium phosphide wafer growth time; Step 42, comparing the estimated growth quality of the indium phosphide crystal with the set growth quality standard value. If the growth quality of the indium phosphide crystal is greater than or equal to the set growth quality standard value, it means that the growth of the indium phosphide crystal is normal and there is no need to adjust the growth furnace parameters. If the growth quality of the indium phosphide crystal is less than the set growth quality standard value, it means that the growth of the indium phosphide crystal is abnormal and it is necessary to adjust the growth furnace parameters and issue an early warning. Step 5: Analyze whether manual intervention is needed based on the estimated growth quality of the indium phosphide crystal; In this embodiment, if the growth of the indium phosphide crystal is abnormal, the growth furnace parameters need to be adjusted, and the early warning analysis result is obtained, then it is determined that manual intervention is required.

[0017] Secondly, the benefits of this embodiment are as follows: the operation status of the growth furnace is analyzed based on the growth operation data of the growth furnace, and then the growth furnace status is analyzed by integrating the operation status of the growth furnace and the internal growth environment data. At the same time, the growth status of the indium phosphide crystal is analyzed based on the growth status data of the indium phosphide crystal in the growth furnace. The growth quality of the indium phosphide crystal is estimated by analyzing the growth furnace status analysis results and the indium phosphide crystal growth status analysis results obtained by analysis. By adopting a big data analysis method, the growth quality of the crystal is accurately estimated in real time by analyzing the growth furnace status analysis results and the indium phosphide crystal growth status analysis results in real time, thereby improving the growth quality and monitoring safety of the indium phosphide crystal growth. In addition, the setting parameters in this embodiment are obtained through historical data experiments. Here, one of the obtaining methods is as follows: obtaining the growth operation data and internal growth environment data of the historical growth furnace, obtaining the growth state data of the indium phosphide crystal in the growth furnace, substituting them into the growth quality estimation formula in each step of this embodiment to calculate the growth quality, and obtaining whether the final growth quality is qualified, substituting the growth quality judgment result and the growth quality calculation result into the data processing software (such as matlab or python) to perform continuous fitting and iteration of the data, and obtaining the values ​​of the relevant setting parameters that meet the maximum judgment accuracy.

[0018] The embodiment of the present application also provides an electronic device, including a memory, a processor and a communication bus; the memory and the processor are connected via the communication bus. The memory stores an abnormality monitoring method for an indium phosphide crystal growth furnace provided in the above embodiment, which can be loaded and executed by the processor.

[0019] The memory can be used to store instructions, programs, codes, code sets or instruction sets. The memory may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function, and instructions for implementing the abnormality monitoring method for an indium phosphide crystal growth furnace provided in the above embodiment, etc.; the data storage area may store data involved in the abnormality monitoring method for an indium phosphide crystal growth furnace provided in the above embodiment, etc.

[0020] The processor may include one or more processing cores. The processor executes various functions and processes data of the present application by running or executing instructions, programs, code sets or instruction sets stored in the memory, calling data stored in the memory. The processor may be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller and a microprocessor. It is understandable that for different devices, the electronic device used to implement the above-mentioned processor function may also be other, and the embodiments of the present application are not specifically limited.

[0021] The communication bus may include a path to transmit information between the above components. The communication bus may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation.

[0022] This embodiment provides a computer-readable storage medium on which an erasable computer program is stored. When the computer program is run on a computer device, the computer device executes the above-mentioned abnormality monitoring method for an indium phosphide crystal growth furnace.

[0023] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0024] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0025] Those skilled in the art will appreciate that the present application may be implemented as a system, method or computer program product.

[0026] Therefore, the present application can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" in the present application. In addition, in some embodiments, the present application can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.

[0027] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0028] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for monitoring abnormality of an indium phosphide crystal growth furnace, characterized in that: The following steps are involved: Acquire growth operation data and internal growth environment data of the growth furnace, and acquire growth state data of indium phosphide crystals in the growth furnace; Analyze the operation status of the growth furnace based on the growth operation data of the growth furnace, and then analyze the growth furnace status by combining the operation status of the growth furnace and the internal growth environment data; The growth state of indium phosphide crystals is analyzed based on the growth state data of indium phosphide crystals in the growth furnace; The growth quality of the indium phosphide crystal is estimated by analyzing the growth furnace condition analysis results and the growth state analysis results of the indium phosphide crystal; An analysis is performed to determine whether manual intervention is necessary based on the estimated growth quality of the indium phosphide crystal.

2. The abnormality monitoring method for an indium phosphide crystal growth furnace according to claim 1, characterized in that: The step of analyzing the operation status of the growth furnace based on the growth operation data of the growth furnace comprises: Acquire the growth operation data of the corresponding growth furnace at each moment, acquire the deviation between the growth operation data of the corresponding growth furnace at each moment and the safety value of the corresponding type of data, and then perform weighted superposition to obtain the growth furnace operation abnormality coefficient at the corresponding moment; The abnormality coefficients of the growth furnace operation at each corresponding moment during the operation of the growth furnace are integrated over a time range and then standardized to obtain the abnormality of the growth furnace.

3. The abnormality monitoring method for an indium phosphide crystal growth furnace according to claim 2, characterized in that: The comprehensive growth furnace operation status and internal growth environment data for growth furnace status analysis includes the following specific steps: Acquire growth environment data of each monitoring point inside the growth furnace, and perform abnormal growth environment analysis of the monitoring point based on the deviation between the growth environment data of the corresponding monitoring point and the normal range of the growth environment; The abnormal analysis of internal environment impact is carried out by the distance of each monitoring point from the crystal growth range and the abnormal analysis results of the growth environment at the monitoring point; The abnormal situation analysis results of the growth furnace and the abnormal analysis results of the internal environment impact are obtained, weighted, and then added to obtain the abnormal results of the growth furnace growth impact.

4. The abnormality monitoring method for an indium phosphide crystal growth furnace according to claim 3, characterized in that: The step of analyzing the growth state of the indium phosphide crystal comprises: The growth state data of the indium phosphide crystal is obtained, and the growth quality analysis is performed based on the growth state data of the indium phosphide crystal. The growth quality analysis is performed based on the growth state data of the indium phosphide crystal: the growth defect analysis is performed based on the area and position data of the real-time crystal surface defects and cracks. The specific calculation formula for the growth defect analysis is as follows: , where Ym is the length of the crystal, Yc is the average distance of the crystal defects, U is the number of defects inside the crystal, Vu is the volume of the u-th defect, and Vm is the volume of the crystal.

5. The abnormality monitoring method for an indium phosphide crystal growth furnace according to claim 4, characterized in that: The method of estimating the growth quality of indium phosphide crystals comprises the following specific steps: The obtained growth furnace growth influence abnormal results and growth defect analysis results are used to estimate the growth quality of the indium phosphide crystal after growth; The estimated growth quality of the indium phosphide crystal is compared with the set growth quality standard value. If the growth quality of the indium phosphide crystal is greater than or equal to the set growth quality standard value, it means that the growth of the indium phosphide crystal is normal and there is no need to adjust the growth furnace parameters. If the growth quality of the indium phosphide crystal is less than the set growth quality standard value, it means that the growth of the indium phosphide crystal is abnormal and the growth furnace parameters need to be adjusted, and an early warning is issued.

6. The abnormality monitoring method for an indium phosphide crystal growth furnace according to claim 1, characterized in that: The growth operation data of the growth furnace specifically include: the operating current, operating voltage and vibration data of the crystal growth furnace during the operation process, which reflect the data types of the operating status of the crystal growth furnace; the internal growth environment data of the growth furnace specifically include: the temperature and pressure of each area inside the growth furnace affect the data types of the growth state of the indium phosphide crystal, and the growth state data of the indium phosphide crystal in the growth furnace include the real-time volume, real-time crystal surface defects and cracks area, and position data during the growth process of the indium phosphide crystal in the growth furnace.

7. An electronic device comprising: A processor and a memory, wherein the memory stores a computer program that can be called by the processor; characterized in that the processor executes the abnormality monitoring method for an indium phosphide crystal growth furnace as described in any one of claims 1 to 6 by calling the computer program stored in the memory.

8. A computer-readable storage medium, characterized in that: Instructions are stored, and when the instructions are executed on a computer, the computer is caused to execute the abnormality monitoring method for an indium phosphide crystal growth furnace as described in any one of claims 1 to 6.

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