Thermistor chip sorting method and system based on industrial Internet of Things

Abstract

The invention relates to the technical field of sorting methods, in particular to a thermistor chip sorting method and system based on the industrial Internet of Things. According to the method, the image feature information and the size features are analyzed, the physical characteristics of each chip can be evaluated more accurately, so that the accuracy and efficiency of the sorting process are improved, the temperature rise rate is obtained by combining the image feature information, the size feature information and the appearance feature information, and the sorting efficiency is improved. The problem that whether the thermistor chip is qualified or not cannot be accurately detected in a traditional sorting technology can be effectively solved, and the actual working capacity of the chip can be evaluated more comprehensively by combining the appearance characteristics with the performance parameters such as the thermal response speed for analysis; the overall performance of the chip can be reflected more accurately by calculating the temperature rise rate and the temperature change response speed, and the actual working state and the response performance of the chip can be evaluated more directly by analyzing the temperature change and the resistance change rate of the thermistor chip within the preset time period.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial Internet of Things, and in particular to a thermistor chip sorting method and system based on the industrial Internet of Things. Background Art

[0002] Industrial Internet of Things refers to a type of system that applies Internet of Things technology to industrial environments, using technologies such as sensors, devices, networks and data analysis to connect and manage industrial equipment, production lines, machines and other assets. Its core purpose is to improve production efficiency, increase resource utilization, optimize maintenance plans, and support intelligent production decisions through real-time data collection, analysis and remote control. Thermistor chip is an electronic component used for temperature measurement and temperature compensation. Its resistance value changes with temperature. The resistance characteristics of thermistors make them widely used in temperature sensors, temperature control circuits, battery protection, instruments and meters, household appliances and other fields.

[0003] However, traditional sorting methods often rely on machine vision, size detection, appearance inspection and other means for preliminary screening, but ignore the detection of the core performance of the chip, which will affect the reliability and stability of the chip in practical applications. Summary of the invention

[0004] The main purpose of the present invention is to provide a thermistor chip sorting method based on industrial Internet of Things, aiming to solve the technical problems in the prior art.

[0005] The present invention proposes a thermistor chip sorting method based on industrial Internet of Things, comprising:

[0006] Acquire image feature information of the thermistor chips to be sorted, wherein the image feature information includes size feature information and appearance feature information;

[0007] Obtaining the plane size, thickness size and pin feature of the size feature information, and obtaining the temperature rise rate according to the plane size, thickness size and pin feature;

[0008] Obtaining the roughness and appearance defects of the appearance feature information, and obtaining the surface defect degree and the surface contamination degree according to the appearance defects;

[0009] Calculating a thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and calculating a temperature change response speed according to the thermal response speed and the temperature rise rate;

[0010] Acquire multiple actual temperature values ​​of the thermistor chips to be sorted within a preset time period, and acquire the actual resistance change rate according to the preset time period and the multiple actual temperature values;

[0011] Obtaining a dynamic response deviation according to the actual resistance change rate and the temperature change response speed, and determining whether the dynamic response deviation is greater than a preset deviation;

[0012] If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified, and is transported and sorted;

[0013] If the dynamic response deviation is not greater than the preset deviation, the thermistor chip to be sorted is determined to be unqualified and is transported and rejected.

[0014] Preferably, the step of obtaining the temperature rise rate according to the plane size, thickness size and pin characteristics comprises:

[0015] Acquire a length dimension and a width dimension according to the plane dimension, and acquire a cross-sectional area according to the length dimension and the width dimension;

[0016] Obtain the thermal conductivity of the thermistor chip to be sorted;

[0017] Obtaining thermal resistance based on the thermal conductivity, cross-sectional area, and thickness dimensions;

[0018] Obtaining thermal response time according to the thickness dimension, length dimension and width dimension;

[0019] Obtaining each pin diameter, each pin length and pin thermal conductivity according to the pin characteristics, and obtaining the total pin cross-sectional area according to a plurality of the pin diameters;

[0020] Obtaining a heat dissipation capability index according to the total cross-sectional area of ​​the pins, the thermal conductivity of the pins, and the lengths of the multiple pins;

[0021] The temperature rise rate is obtained according to the heat dissipation capability index, thermal resistance and thermal response time.

[0022] Preferably, the step of obtaining the thermal response time according to the thickness dimension, the length dimension and the width dimension comprises:

[0023] Obtain the material density and specific heat capacity of the thermistor chips to be sorted;

[0024] Obtaining the mass of the thermistor chips to be sorted according to the material density, thickness, length and width;

[0025] Obtaining the contact surface area of ​​the thermistor chip to be sorted according to the thickness dimension, length dimension and width dimension;

[0026] The thermal response time is obtained according to the contact surface area, mass and specific heat capacity.

[0027] Preferably, the step of calculating the thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and calculating the temperature change response speed according to the thermal response speed and the temperature rise rate comprises:

[0028] Obtain the material density, specific heat capacity and resistance thermal conductivity of the thermistor chips to be sorted;

[0029] Obtaining thermal diffusivity according to the material density, specific heat capacity and electrical resistance thermal conductivity;

[0030] Obtaining the thermal response time and plane size of the thermistor chip to be sorted, and obtaining the influence coefficient of the thermistor chip to be sorted according to the thermal response time, plane size and thermal diffusivity;

[0031] respectively obtaining a first weight of the roughness, a second weight of the surface defect degree, and a third weight of the surface contamination degree;

[0032] The thermal response speed is calculated according to the influence coefficient, plane size, resistance thermal conductivity, roughness, first weight, second weight, third weight, surface defect degree and surface contamination degree, wherein the calculation formula is:

[0033]

[0034] Among them, R(XS) represents thermal response speed, Y(X) represents influence coefficient, P(M) represents plane size, D(R) represents resistance thermal conductivity, α represents the first weight, β represents the second weight, γ represents the third weight, C(D) represents roughness, B(D) represents the degree of surface defects, and W(D) represents the degree of surface contamination;

[0035] Obtaining an impact factor according to the thermal response speed;

[0036] The temperature change response speed is calculated according to the influencing factor, the thermal response speed and the temperature rise rate, wherein the calculation formula is:

[0037] W(XS)=R(XS) y(z) *W(SL) 1-y(z) ;

[0038] Among them, W(XS) represents the temperature change response speed, R(XS) represents the thermal response speed, W(SL) represents the temperature rise rate, and y(z) represents the impact factor.

[0039] Preferably, the step of obtaining the actual resistance change rate according to the preset time period and multiple actual temperature values ​​comprises:

[0040] Obtain the resistivity, initial temperature value and initial resistance value of the thermistor chip to be sorted;

[0041] The corresponding actual resistance value is calculated according to the resistivity, the initial temperature value, the initial resistance value and each actual temperature value, wherein the calculation formula is:

[0042]

[0043] Among them, S(W) i represents the i-th actual resistance value, C(W) represents the initial temperature value, D(X) represents the resistivity, C(Z) represents the initial resistance value, S(Z) i represents the i-th actual temperature value, where i represents the sequence number of the actual temperature value;

[0044] The actual resistance change rate is calculated according to the preset time period and multiple actual resistance values, wherein the calculation formula is:

[0045]

[0046] Where S(XS) represents the actual resistance change rate, N represents the number of actual resistance values, Y(SD) represents the preset time period, S(W) represents the actual resistance change rate, N represents the actual resistance value ... a It represents the ath actual resistance value, and a represents the sequence number of the actual resistance value.

[0047] Preferably, the step of obtaining the dynamic response deviation according to the actual resistance change rate and the temperature change response speed comprises:

[0048] Acquire temperature sensitivity according to the actual resistance change rate;

[0049] Acquire a temperature hysteresis value according to the temperature sensitivity, and acquire a first temperature deviation according to the temperature hysteresis value;

[0050] Obtaining linearity according to the temperature change response speed;

[0051] Acquire a linear drift error according to the linearity, and acquire a second temperature deviation according to the linear drift error;

[0052] A dynamic response deviation is obtained according to the first temperature deviation and the second temperature deviation.

[0053] The present application also provides a thermistor chip sorting system based on industrial Internet of Things, comprising:

[0054] A first acquisition module is used to acquire image feature information of the thermistor chips to be sorted, wherein the image feature information includes size feature information and appearance feature information;

[0055] A second acquisition module is used to acquire the plane size, thickness size and pin characteristics of the size feature information, and acquire the temperature rise rate according to the plane size, thickness size and pin characteristics;

[0056] A third acquisition module is used to acquire the roughness and appearance defects of the appearance feature information, and acquire the surface defect degree and surface contamination degree according to the appearance defects;

[0057] A calculation module, used to calculate the thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and to calculate the temperature change response speed according to the thermal response speed and the temperature rise rate;

[0058] A fourth acquisition module, used to acquire multiple actual temperature values ​​of the thermistor chip to be sorted within a preset time period, and acquire an actual resistance change rate according to the preset time period and the multiple actual temperature values;

[0059] A judgment module, used for obtaining a dynamic response deviation according to the actual resistance change rate and the temperature change response speed, and judging whether the dynamic response deviation is greater than a preset deviation;

[0060] If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified, and is transported and sorted;

[0061] If the dynamic response deviation is not greater than the preset deviation, the thermistor chip to be sorted is determined to be unqualified and is transported and rejected.

[0062] Preferably, the second acquisition module includes:

[0063] Acquire a length dimension and a width dimension according to the plane dimension, and acquire a cross-sectional area according to the length dimension and the width dimension;

[0064] Obtain the thermal conductivity of the thermistor chip to be sorted;

[0065] Obtaining thermal resistance based on the thermal conductivity, cross-sectional area, and thickness dimensions;

[0066] Obtaining thermal response time according to the thickness dimension, length dimension and width dimension;

[0067] Obtaining each pin diameter, each pin length and pin thermal conductivity according to the pin characteristics, and obtaining the total pin cross-sectional area according to a plurality of the pin diameters;

[0068] Obtaining a heat dissipation capability index according to the total cross-sectional area of ​​the pins, the thermal conductivity of the pins, and the lengths of the multiple pins;

[0069] The temperature rise rate is obtained according to the heat dissipation capability index, thermal resistance and thermal response time.

[0070] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned thermistor chip sorting method based on the industrial Internet of Things when executing the computer program.

[0071] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned thermistor chip sorting method based on the industrial Internet of Things are implemented.

[0072] The beneficial effects of the present invention are as follows: the present invention can more accurately evaluate the physical characteristics of each chip by analyzing the image feature information and the size feature, thereby improving the accuracy and efficiency of the sorting process; by inferring the temperature rise rate by combining the size feature and the appearance feature, the performance of the chip can be more comprehensively judged; by obtaining the temperature rise rate by combining the image feature, the size feature and the appearance feature information, this method can effectively solve the problem that the traditional sorting technology cannot accurately detect whether the thermistor chip is qualified; by combining the appearance feature with the performance parameters such as the thermal response speed for analysis, the actual working ability of the chip can be more comprehensively evaluated; the calculation of the temperature rise rate and the temperature change response speed can more accurately reflect the overall performance of the chip; by comprehensively analyzing the surface By combining factors such as defects, degree of contamination and roughness, and calculating thermal response speed and temperature rise rate, it is possible to more accurately identify chips that may have performance problems. By analyzing the temperature change and resistance change rate of the thermistor chip within a preset time period, the actual working status and response performance of the chip can be more directly evaluated, and it can effectively determine whether it meets the predetermined temperature response characteristics. By monitoring the actual resistance change rate and the response speed of temperature change, it can be determined whether the dynamic response of the chip is stable. By combining the resistance change rate, temperature change and response speed under actual working conditions, such comprehensive performance testing can more comprehensively evaluate the overall quality of the chip. By analyzing the dynamic response deviation, it can timely identify chips with slow response or unstable response. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 The figure is a schematic diagram of a method flow according to an embodiment of the present invention.

[0074] Figure 2 FIG. 1 is a schematic diagram of a device structure according to an embodiment of the present invention.

[0075] Figure 3 A schematic diagram of the internal structure of a computer device according to an embodiment of the present application.

[0076] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0077] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0078] like Figure 1-Figure 3 As shown, the present application provides a thermistor chip sorting method based on industrial Internet of Things, comprising:

[0079] S1, obtaining image feature information of thermistor chips to be sorted, wherein the image feature information includes size feature information and appearance feature information;

[0080] S2, obtaining the plane size, thickness size and pin characteristics of the size characteristic information, and obtaining the temperature rise rate according to the plane size, thickness size and pin characteristics;

[0081] S3, obtaining the roughness and appearance defects of the appearance feature information, and obtaining the surface defect degree and surface contamination degree according to the appearance defects;

[0082] S4, calculating the thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and calculating the temperature change response speed according to the thermal response speed and the temperature rise rate;

[0083] S5, obtaining multiple actual temperature values ​​of the thermistor chips to be sorted within a preset time period, and obtaining an actual resistance change rate according to the preset time period and the multiple actual temperature values;

[0084] S6. Obtaining a dynamic response deviation according to the actual resistance change rate and the temperature change response speed, and determining whether the dynamic response deviation is greater than a preset deviation;

[0085] If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified, and is transported and sorted;

[0086] If the dynamic response deviation is not greater than the preset deviation, the thermistor chip to be sorted is determined to be unqualified and is transported and rejected.

[0087] As described in the above steps S1-S6, the industrial Internet of Things refers to a type of system that applies Internet of Things technology to an industrial environment, using technologies such as sensors, devices, networks and data analysis to connect and manage industrial equipment, production lines, machines and other assets. Its core purpose is to improve production efficiency, resource utilization, optimize maintenance plans, and support intelligent production decisions through real-time data collection, analysis and remote control. Thermistor chips are electronic components used for temperature measurement and temperature compensation, and their resistance values ​​change with temperature. The resistance characteristics of thermistors make them widely used in temperature sensors, temperature control circuits, battery protection, instruments and meters, home appliances and other fields. However, traditional sorting methods often rely on machine vision, size detection, appearance inspection and other means for preliminary screening, while ignoring the detection of the core performance of the chip, which will affect the reliability and stability of the chip in actual applications. If there is no real-time performance detection, unqualified chips may be mistakenly sorted into qualified products, which will affect the quality of the final product.The present invention obtains the temperature rise rate according to the plane size, thickness size and pin features of the image feature information of the thermistor chip to be sorted through the size feature information and appearance feature information, and then obtains the temperature rise rate according to the plane size, thickness size and pin features of the size feature information. By analyzing the image feature information (such as appearance) and the size feature (such as plane size, thickness size, pin features), the physical characteristics of each chip can be evaluated more accurately. This information can reflect the structural integrity and potential functional problems of the chip, thereby improving the accuracy and efficiency of the sorting process. By combining the size feature and the appearance feature to infer the temperature rise rate, the performance of the chip can be judged more comprehensively, rather than relying solely on appearance inspection or size measurement. The temperature rise rate is obtained by combining the image feature, the size feature and the appearance feature information, wherein the temperature rise rate refers to the rate at which the temperature changes with time, that is, the speed at which the temperature rises per unit time. This method can effectively solve the problem that the traditional sorting technology cannot accurately detect whether the thermistor chip is qualified, by obtaining the roughness and appearance defects of the appearance feature information, and obtaining the surface quality according to the appearance defects. The degree of defects and the degree of surface contamination, the thermal response speed is calculated according to the roughness, the degree of surface defects and the degree of surface contamination, and the temperature change response speed is calculated according to the thermal response speed and the temperature rise rate, where the thermal response speed refers to the response speed of an object or system to external temperature changes, usually refers to the time required from the application of the heat source to the object temperature reaching a steady state, the temperature change response speed refers to the response speed of the temperature to external changes under certain conditions, by combining the appearance characteristics (such as roughness, surface defects, degree of contamination) with performance parameters such as thermal response speed, the actual working ability of the chip can be more comprehensively evaluated, the surface defects, roughness and degree of contamination directly affect the thermal conductivity of the chip, and these factors will cause the temperature response characteristics of the thermistor to be unstable or delayed, so the calculation of the temperature rise rate and the temperature change response speed can more accurately reflect the overall performance of the chip, by comprehensively analyzing factors such as surface defects, degree of contamination and roughness, and combining the calculation of thermal response speed and temperature rise rate, those chips that may have performance problems can be more accurately identified.This method can eliminate unqualified products in advance in the sorting process, improve the accuracy and intelligence level of the sorting process, and better realize intelligent sorting by introducing multi-dimensional information such as appearance characteristics, roughness, surface contamination, etc., and combining the thermal performance of the chip (such as thermal response speed, temperature rise rate, etc.) for comprehensive analysis. By obtaining multiple actual temperature values ​​of the thermistor chip to be sorted within a preset time period, and obtaining the actual resistance change rate according to the preset time period and multiple actual temperature values, the dynamic response deviation is obtained through the actual resistance change rate and the temperature change response speed, wherein the dynamic response deviation refers to the deviation between the actual response and the expected response under dynamic environmental conditions, and it is judged whether the dynamic response deviation is greater than the preset deviation. If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified and transported for sorting. Otherwise, the thermistor chip to be sorted is determined to be unqualified and transported for rejection. By analyzing the temperature change and resistance change rate of the thermistor chip within the preset time period, the actual working state and response performance of the chip can be more directly evaluated. This method is more The method focuses on the actual performance of the chip, and can effectively determine whether it meets the predetermined temperature response characteristics. By monitoring the actual resistance change rate and the response speed of temperature changes, it can be determined whether the dynamic response of the chip is stable. The performance of the thermistor chip is not only related to its appearance, but also closely related to its response speed and stability to temperature changes. The method can more accurately detect whether the chip has normal working characteristics. Through automated temperature and resistance data acquisition and processing, it can significantly reduce errors in manual operations and improve the stability and consistency of the test results. By combining the resistance change rate, temperature change and response speed under actual working conditions, such comprehensive performance testing can more comprehensively evaluate the overall quality of the chip, avoiding the one-sidedness of judging whether the chip is qualified or not based on appearance or simple static tests. Through the analysis of dynamic response deviations, slow-response or unstable chips can be identified in time. Through more accurate detection methods, the losses and risks caused by unqualified chips entering the market or products can be reduced, and problems such as unstable performance of terminal products caused by defective chips can be avoided.

[0088] In one embodiment, the step S2 of obtaining the temperature rise rate according to the plane size, thickness size and pin characteristics includes:

[0089] S21, obtaining a length dimension and a width dimension according to the plane dimension, and obtaining a cross-sectional area according to the length dimension and the width dimension;

[0090] S22, obtaining the thermal conductivity of the thermistor chip to be sorted;

[0091] S23, obtaining thermal resistance according to the thermal conductivity, cross-sectional area and thickness, wherein the calculation formula is: Among them, R(Z) represents thermal resistance, H(C) represents thickness dimension, R(D) represents thermal conductivity, and H(M) represents cross-sectional area;

[0092] S24, obtaining a thermal response time according to the thickness dimension, the length dimension and the width dimension;

[0093] S25. Obtain each pin diameter, each pin length and pin thermal conductivity according to the pin characteristics, and obtain the total pin cross-sectional area according to the plurality of pin diameters, using the formula: Among them, Y(ZJ) represents the total cross-sectional area of ​​the pin, Y(Z) b represents the diameter of the bth pin, M represents the number of pin diameters, and b represents the serial number of the pin diameter;

[0094] S26. Obtain a heat dissipation capability index according to the total cross-sectional area of ​​the pins, the thermal conductivity of the pins, and the lengths of the multiple pins, wherein the calculation formula is: Among them, S(RN) represents the heat dissipation capacity index, Y(RD) represents the thermal conductivity of the pin, Y(ZJ) represents the total cross-sectional area of ​​the pin, and Y(CD) n represents the length of the th pin, n represents the serial number of the pin length, and T represents the number of pin lengths.

[0095] S27. Obtaining a temperature rise rate according to the heat dissipation capability index, thermal resistance and thermal response time.

[0096] As described in the above steps S21-S27, the present invention obtains the length dimension and the width dimension through the plane dimension, and obtains the cross-sectional area according to the length dimension and the width dimension, obtains the thermal conductivity of the thermistor chip to be sorted, and then obtains the thermal resistance according to the thermal conductivity, the cross-sectional area and the thickness dimension, and obtains the thermal response time through the thickness dimension, the length dimension and the width dimension. By measuring physical parameters such as thermal conductivity, thermal resistance, and thermal response time, the quality of the thermistor chip can be objectively evaluated from a functional perspective. These parameters directly reflect the thermal performance of the chip in actual work, and can more accurately determine whether the chip meets the design requirements. By measuring the thermal resistance and the thermal response time, more accurate performance data can be obtained, which further helps to determine whether the chip has the performance in actual work. The response speed and stability required in the application can be comprehensively evaluated through the comprehensive analysis of cross-sectional area, thermal conductivity, thermal resistance, and thermal response time to fully evaluate the thermal conductivity and response performance of the chip, rather than relying solely on static appearance or size inspection. The thermal resistance and thermal response time of the chip directly affect its response speed to external temperature changes. If the thermal resistance of the chip is too large or the thermal response time does not meet the standard, its response in actual work may become sluggish or unstable, resulting in unqualified performance. By quantifying key parameters such as thermal conductivity, thermal resistance, and thermal response, chips with good appearance but unqualified internal performance can be identified, reducing the possibility of misjudgment and missed judgment. The sorting method of thermistor chips is detected by multi-dimensional parameters such as size, thermal conductivity, thermal resistance, and thermal response time. Compared with traditional appearance inspection, it can more accurately evaluate the thermal performance and working stability of the chip, which not only improves the accuracy and objectivity of the detection, but also reduces the misjudgment and missed judgment caused by relying solely on appearance standards. It can screen out qualified chips more comprehensively and reliably, obtain the diameter of each pin, the length of each pin and the thermal conductivity of the pin through the pin characteristics, and obtain the total cross-sectional area of ​​the pin based on multiple pin diameters, and then obtain the heat dissipation capacity index based on the total cross-sectional area of ​​the pin, the thermal conductivity of the pin and multiple pin lengths, and obtain the temperature rise rate based on the heat dissipation capacity index, thermal resistance and thermal response time. Since the thermal conductivity, diameter and length of the pin directly affect the heat conduction efficiency, the total cross-sectional area of ​​the pin is calculated by considering the diameters of multiple pins, and then combined with the thermal conductivity and Length can accurately calculate the chip's heat dissipation index. This evaluation method can comprehensively reflect the chip's thermal conductivity, avoiding the insufficiency of the chip's heat dissipation ability based on appearance alone. The pin is the main channel for the chip to dissipate heat. Accurately calculating the pin's heat dissipation index can predict whether the chip can effectively dissipate heat during operation, thereby avoiding unstable performance or damage to the chip due to overheating. The traditional sorting method relies on appearance inspection (such as size, color, shape, etc.) to determine whether the chip is qualified. However, the appearance of the chip may not have obvious defects, but its pin size, thermal conductivity, heat dissipation capacity, etc. may have problems, which directly affect its heat dissipation effect and working stability. The temperature rise rate is calculated by combining the heat dissipation index, thermal resistance and thermal response time.It can comprehensively evaluate the thermal performance and response speed of the chip. By calculating the heat dissipation index and temperature rise rate based on pin characteristics (diameter, length, thermal conductivity), it can provide a more accurate, objective and comprehensive chip quality evaluation compared to the traditional sorting method that only relies on appearance inspection. This method can not only improve the screening accuracy of thermistor chips and avoid thermal performance problems that cannot be detected by appearance, but also improve production efficiency, reduce scrap rate, and help ensure the reliability and stability of chips in long-term work.

[0097] In one embodiment, the step S24 of obtaining the thermal response duration according to the thickness dimension, the length dimension and the width dimension includes:

[0098] S241, obtaining the material density and specific heat capacity of the thermistor chips to be sorted;

[0099] S242, obtaining the mass of the thermistor chips to be sorted according to the material density, thickness, length and width;

[0100] S243, obtaining the contact surface area of ​​the thermistor chip to be sorted according to the thickness dimension, length dimension and width dimension, wherein the calculation formula is: J(BM)=2[H(C)*K(C)+H(C)*C(C)+K(C)*C(C)]; wherein J(BM) represents the contact surface area, H(C) represents the thickness dimension, K(C) represents the width dimension, and C(C) represents the length dimension;

[0101] S244. Obtain thermal response time according to the contact surface area, mass and specific heat capacity.

[0102] As described in the above steps S241-S244, the present invention obtains the material density and specific heat capacity of the thermistor chip to be sorted, and obtains the mass of the thermistor chip to be sorted according to the product of the material density, thickness dimension, length dimension and width dimension. The quality of the chip is inferred by the density, specific heat capacity and size of the material, which can avoid misjudgment caused by changes in the appearance of the chip. Appearance detection can only identify obvious defects (such as cracks, scratches, etc.), while calculation through physical properties (such as quality) can judge the qualification of the chip through more basic physical properties, thereby improving the accuracy of sorting. Traditional appearance detection mostly relies on manual inspection or image recognition technology, which may have problems of errors and subjective judgment. Calculating chip quality using material density, specific heat capacity and size can achieve a more efficient automated sorting system. By calculating the quality of the chip, the internal material distribution of the chip can be indirectly determined. If there is a difference from the expected quality, it may indicate that the chip has potential internal defects or is unqualified. Calculating the quality of thermistor chips based on material density, specific heat capacity, size and other parameters can provide a more scientific, accurate and objective quality inspection method for the sorting process, reduce the limitations of appearance inspection, and obtain the contact surface area of ​​the thermistor chip to be sorted through thickness, length and width dimensions, and then obtain the thermal response time by dividing the contact surface area by the product of mass and specific heat capacity. The thermal response time of the thermistor chip (i.e., the response time of its temperature change) is not only related to the material properties of the chip, but also to its contact surface area, Factors such as mass and specific heat capacity are closely related. By calculating the surface area, the thermal response time of the thermistor can be more accurately calculated. By calculating the thermal response time through physical parameters (such as size, mass, specific heat capacity, etc.), the performance of the chip can be evaluated more objectively and accurately. By measuring the thermal response time, uncertain factors can be eliminated and the stability and consistency of the test results can be improved. The use of quantitative physical parameters such as size, mass and specific heat capacity to calculate the thermal response time can make it easier to achieve automated detection. By using physical parameters such as size, mass, specific heat capacity, etc. to calculate the thermal response time, it can provide more accurate, objective and reliable performance evaluation compared to the traditional single appearance inspection method. This method helps to improve the level of automation, reduce the possibility of misjudgment and missed judgment, improve the scientific nature of quality control, and can reduce costs and improve production efficiency in the long run.

[0103] In one embodiment, the step S4 of calculating the thermal response speed according to the roughness, the surface defect degree and the surface contamination degree, and calculating the temperature change response speed according to the thermal response speed and the temperature rise rate includes:

[0104] S41, obtaining the material density, specific heat capacity and thermal conductivity of the thermistor chips to be sorted;

[0105] S42, obtaining thermal diffusivity according to the material density, specific heat capacity and resistance thermal conductivity;

[0106] S43, obtaining the thermal response time and plane size of the thermistor chip to be sorted, and obtaining the influence coefficient of the thermistor chip to be sorted according to the thermal response time, plane size and thermal diffusivity;

[0107] S44, respectively obtaining a first weight of the roughness, a second weight of the surface defect degree, and a third weight of the surface contamination degree;

[0108] S45, calculating the thermal response speed according to the influence coefficient, plane size, resistance thermal conductivity, roughness, first weight, second weight, third weight, surface defect degree and surface contamination degree, wherein the calculation formula is:

[0109]

[0110] Among them, R(XS) represents thermal response speed, Y(X) represents influence coefficient, P(M) represents plane size, D(R) represents resistance thermal conductivity, α represents the first weight, β represents the second weight, γ represents the third weight, C(D) represents roughness, B(D) represents the degree of surface defects, and W(D) represents the degree of surface contamination;

[0111] S46, obtaining an impact factor according to the thermal response speed;

[0112] S47, calculating the temperature change response speed according to the influencing factor, the thermal response speed and the temperature rise rate, wherein the calculation formula is:

[0113] W(XS)=R(XS) y(z) *W(SL) 1-y(z) ;

[0114] Among them, W(XS) represents the temperature change response speed, R(XS) represents the thermal response speed, W(SL) represents the temperature rise rate, and y(z) represents the impact factor.

[0115] As described in the above steps S41-S47, the present invention obtains the material density, specific heat capacity and thermal conductivity of the thermistor chip to be sorted, and obtains the thermal diffusivity according to the material density, specific heat capacity and thermal conductivity of the thermistor chip to be sorted, obtains the thermal response time and plane size of the thermistor chip to be sorted, and obtains the influence coefficient of the thermistor chip to be sorted according to the thermal response time, plane size and thermal diffusivity, and infers the thermal diffusivity and thermal response time through material properties such as density, specific heat capacity and thermal conductivity of the thermistor, so as to provide a more accurate judgment basis than simply relying on appearance inspection. Appearance inspection mainly relies on visual recognition and is easily affected by environmental factors (such as light, viewing angle, etc.) and human subjective factors, while physical characteristics-based inspection can provide a more accurate judgment basis than physical characteristics-based inspection. The thermal detection method has a more stable scientific basis, reduces human errors, and ensures higher detection accuracy. Through parameters such as thermal diffusivity and thermal response time, the thermal response characteristics of the chip under actual working conditions can be directly obtained, so as to more comprehensively evaluate the performance of the chip and avoid misjudgment based on appearance characteristics alone. By calculating the thermal diffusivity through parameters such as density, specific heat capacity, and resistance thermal conductivity, a more comprehensive understanding of the thermal performance of the chip can be achieved, which is crucial for the performance of the chip in the actual working environment. The calculation of physical parameters such as thermal diffusivity, thermal response time and influence coefficient can identify potential quality problems of the chip in a quantitative way, especially those defects that are not visible on the surface but affect performance.For example, the thermal response characteristics of a chip may reflect problems such as uneven material distribution and internal structural defects, which cannot be identified by appearance inspection. By combining the material's density, specific heat capacity, resistance thermal conductivity and other physical properties to calculate the thermal diffusivity and influence coefficient, the performance of the thermistor chip can be evaluated. Compared with traditional quality inspection methods such as appearance alone, this method has significant advantages. It can provide higher detection accuracy, comprehensiveness and reliability, while improving the level of automated sorting, reducing misjudgments and missed judgments, optimizing quality control, reducing scrap rates and improving production efficiency, and ultimately achieving more scientific and efficient chip sorting and quality management. By respectively obtaining the first weight of roughness, the second weight of surface defect degree and the third weight of surface contamination degree, and calculating the thermal response speed according to the influence coefficient, plane size, resistance thermal conductivity, roughness, the first weight, the second weight, the third weight, the surface defect degree and the surface contamination degree, the influence factor is obtained through the thermal response speed, and the temperature change response speed is calculated according to the influence factor, the thermal response speed and the temperature rise rate. Traditional sorting methods mostly rely on appearance inspection, which may only consider visible defects on the surface and ignore other potential influencing factors, such as the roughness, contamination degree, resistance thermal conductivity, etc. of the chip. By combining roughness, surface Defects, surface contamination and other indicators are converted into quantitative weight values, and their influence on thermal response speed is considered, which can more comprehensively reflect the real working state of thermistor chips. By combining comprehensive factors such as thermal response speed, influencing factors and temperature rise rate, the performance of the chip under actual working conditions can be more accurately evaluated, the impact of surface defects or contamination on performance can be reduced, and defects that are not easy to detect can be avoided. Compared with the static appearance inspection method, the temperature change response speed can simulate the reaction of the chip in the actual working environment. The chip will be affected by temperature fluctuations during actual use, and the measurement of thermal response speed can reflect the thermal stability and performance sensitivity of the chip. By assigning different weights to roughness, defect degree and contamination degree, the system can make a comprehensive evaluation according to the influence of different factors, avoiding the uncertainty caused by lack of experience or subjective judgment in manual inspection, thereby achieving more efficient sorting. The sorting method based on thermal response speed can make a more comprehensive, accurate and reliable quality assessment of thermistor chips based on the various physical properties of the chip, making up for the limitations of the traditional appearance inspection method that only relies on appearance inspection. This not only improves the accuracy and efficiency of sorting, but also effectively improves product quality and reduces the circulation of unqualified products.

[0116] In one embodiment, the step S5 of obtaining the actual resistance change rate according to the preset time period and multiple actual temperature values ​​includes:

[0117] S51, obtaining the resistivity, initial temperature value and initial resistance value of the thermistor chip to be sorted;

[0118] S52, calculating the corresponding actual resistance value according to the resistivity, the initial temperature value, the initial resistance value and each actual temperature value, wherein the calculation formula is:

[0119]

[0120] Among them, S(W) i represents the i-th actual resistance value, C(W) represents the initial temperature value, D(X) represents the resistivity, C(Z) represents the initial resistance value, S(Z) i represents the i-th actual temperature value, where i represents the sequence number of the actual temperature value;

[0121] S53, calculating the actual resistance change rate according to the preset time period and multiple actual resistance values, wherein the calculation formula is:

[0122]

[0123] Where S(XS) represents the actual resistance change rate, N represents the number of actual resistance values, Y(SD) represents the preset time period, S(W) represents the actual resistance change rate, N represents the actual resistance value ... a It represents the ath actual resistance value, and a represents the sequence number of the actual resistance value.

[0124] As described in the above steps S51-S53, the present invention obtains the resistivity, initial temperature value and initial resistance value of the thermistor chip to be sorted, and calculates the corresponding actual resistance value according to the resistivity, initial temperature value, initial resistance value and each actual temperature value, and then calculates the actual resistance change rate according to the preset time period and multiple actual resistance values. By obtaining parameters such as the resistivity and initial resistance value, the resistance change under actual working conditions can be more accurately predicted, rather than relying solely on static resistance measurement. The resistance value of the thermistor changes with temperature. The working performance abnormality of the chip may not be found simply through appearance or static measurement. By monitoring the resistance change at different temperatures, the electrical performance of the chip in actual use can be better reflected. By measuring and analyzing the resistance change rate of the thermistor under multiple temperature conditions, the stability of the chip in the working environment can be evaluated. For example, if the resistance change rate of the chip is abnormal (too large or too small), it may indicate that the chip has manufacturing defects, material problems or unstable performance. Some thermistor chips may show abnormal resistance changes at a specific temperature even if the appearance is intact due to minor material inhomogeneity and temperature characteristics inconsistency during the manufacturing process. Traditional appearance inspection or single resistance test may not be able to find these problems. However, by comprehensively calculating the resistance change rate, it is possible to more effectively identify chips that appear normal but do not meet performance standards, and reduce the misjudgment rate and missed judgment rate. This detection method based on resistivity, initial resistance value and temperature change can significantly improve the accuracy and efficiency of sorting compared to the existing detection method based only on appearance or static resistance value. It can not only better evaluate the performance of thermistor chips in actual applications, but also reduce human errors and improve the level of automation.

[0125] In one embodiment, the step S6 of obtaining the dynamic response deviation according to the actual resistance change rate and the temperature change response speed includes:

[0126] S61, obtaining temperature sensitivity according to the actual resistance change rate;

[0127] S62, obtaining a temperature hysteresis value according to the temperature sensitivity, and obtaining a first temperature deviation according to the temperature hysteresis value;

[0128] S63, obtaining linearity according to the temperature change response speed;

[0129] S64, obtaining a linear drift error according to the linearity, and obtaining a second temperature deviation according to the linear drift error;

[0130] S65. Obtain a dynamic response deviation according to the first temperature deviation and the second temperature deviation.

[0131] As described in the above steps S61-S65, in the present invention, the temperature sensitivity is obtained by the actual resistance change rate, and then the temperature hysteresis value is obtained according to the temperature sensitivity, and the first temperature deviation is obtained according to the temperature hysteresis value, and the linearity is obtained by the temperature change response speed, and then the linear drift error is obtained according to the linearity, and the second temperature deviation is obtained according to the linear drift error, and then the dynamic response deviation is obtained according to the first temperature deviation and the second temperature deviation, wherein the temperature sensitivity refers to the reaction degree of the system, device or sensor to the temperature change, usually refers to the influence of the temperature change on the output signal or response, and the temperature hysteresis value refers to the response of the system during the temperature change. The linearity is the time delay or deviation between the response and the temperature change. The linearity is an indicator that describes the relationship between the output of the temperature sensor or measurement system and the actual temperature. The linear drift error refers to the linear deviation of the output of the temperature sensor or measurement system over time during long-term use. Parameters such as temperature sensitivity, temperature hysteresis, and linearity are the key characteristics of thermistor chips under actual working conditions. Only relying on appearance or simple resistance value detection cannot fully reflect the dynamic performance of the chip. By measuring the resistance change rate, temperature sensitivity, temperature hysteresis, etc., the working stability and accuracy of the chip can be more accurately evaluated to avoid missing potential performance issues. The problem is that by calculating the dynamic response deviation, the real-time response ability of the chip during temperature changes can be revealed. Parameters such as temperature hysteresis value and linear drift error are crucial for the accurate temperature detection of the chip. Temperature hysteresis value and temperature deviation reflect the delay and deviation of the chip's response during temperature changes, which directly affect the accuracy and stability of the chip in practical applications. Appearance inspection cannot capture these subtle performance differences. Through this method, the hysteresis effect and temperature response deviation of the chip can be evaluated in detail. Temperature sensitivity and linearity are key indicators for evaluating the performance of thermistor chips. Good linearity can ensure that the chip is stable over a wide temperature range. The accuracy of the thermistor chip is improved, while the linear drift error indicates the performance change of the chip after long-term use. By analyzing these dynamic changes, the quality and reliability of the chip can be judged more accurately. The comprehensive evaluation method based on resistance change rate, temperature sensitivity, hysteresis effect, linearity and other parameters can significantly improve the accuracy and efficiency of the thermistor chip sorting process. Compared with the traditional detection method that only relies on appearance and static resistance value, this method can comprehensively and accurately reflect the actual working performance of the chip, avoid missed judgment and misjudgment, improve product quality consistency and reliability, reduce the flow of unqualified products into the market, and provide data support for quality optimization in the production process.

[0132] The present application also provides a thermistor chip sorting system based on industrial Internet of Things, comprising:

[0133] A first acquisition module is used to acquire image feature information of the thermistor chips to be sorted, wherein the image feature information includes size feature information and appearance feature information;

[0134] A second acquisition module is used to acquire the plane size, thickness size and pin characteristics of the size feature information, and acquire the temperature rise rate according to the plane size, thickness size and pin characteristics;

[0135] A third acquisition module is used to acquire the roughness and appearance defects of the appearance feature information, and acquire the surface defect degree and surface contamination degree according to the appearance defects;

[0136] A calculation module, used to calculate the thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and to calculate the temperature change response speed according to the thermal response speed and the temperature rise rate;

[0137] A fourth acquisition module, used to acquire multiple actual temperature values ​​of the thermistor chip to be sorted within a preset time period, and acquire an actual resistance change rate according to the preset time period and the multiple actual temperature values;

[0138] A judgment module, used for obtaining a dynamic response deviation according to the actual resistance change rate and the temperature change response speed, and judging whether the dynamic response deviation is greater than a preset deviation;

[0139] If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified, and is transported and sorted;

[0140] If the dynamic response deviation is not greater than the preset deviation, the thermistor chip to be sorted is determined to be unqualified and is transported and rejected.

[0141] In one embodiment, the second acquisition module includes:

[0142] Acquire a length dimension and a width dimension according to the plane dimension, and acquire a cross-sectional area according to the length dimension and the width dimension;

[0143] Obtain the thermal conductivity of the thermistor chip to be sorted;

[0144] Obtaining thermal resistance based on the thermal conductivity, cross-sectional area, and thickness dimensions;

[0145] Obtaining thermal response time according to the thickness dimension, length dimension and width dimension;

[0146] Obtaining each pin diameter, each pin length and pin thermal conductivity according to the pin characteristics, and obtaining the total pin cross-sectional area according to a plurality of the pin diameters;

[0147] Obtaining a heat dissipation capability index according to the total cross-sectional area of ​​the pins, the thermal conductivity of the pins, and the lengths of the multiple pins;

[0148] The temperature rise rate is obtained according to the heat dissipation capability index, thermal resistance and thermal response time.

[0149] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned thermistor chip sorting method based on the industrial Internet of Things when executing the computer program.

[0150] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned thermistor chip sorting method based on the industrial Internet of Things are implemented.

[0151] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0152] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0153] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A thermistor chip sorting method based on industrial Internet of Things, characterized in that: include: Acquire image feature information of the thermistor chips to be sorted, wherein the image feature information includes size feature information and appearance feature information; Obtaining the plane size, thickness size and pin feature of the size feature information, and obtaining the temperature rise rate according to the plane size, thickness size and pin feature; Obtaining the roughness and appearance defects of the appearance feature information, and obtaining the surface defect degree and the surface contamination degree according to the appearance defects; Calculating a thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and calculating a temperature change response speed according to the thermal response speed and the temperature rise rate; Acquire multiple actual temperature values ​​of the thermistor chips to be sorted within a preset time period, and acquire the actual resistance change rate according to the preset time period and the multiple actual temperature values; Obtaining a dynamic response deviation according to the actual resistance change rate and the temperature change response speed, and determining whether the dynamic response deviation is greater than a preset deviation; If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified, and is transported and sorted; If the dynamic response deviation is not greater than the preset deviation, the thermistor chip to be sorted is determined to be unqualified and is transported and rejected.

2. The thermistor chip sorting method based on industrial Internet of Things according to claim 1 is characterized in that: The step of obtaining the temperature rise rate according to the plane size, thickness size and pin characteristics comprises: Acquire a length dimension and a width dimension according to the plane dimension, and acquire a cross-sectional area according to the length dimension and the width dimension; Obtain the thermal conductivity of the thermistor chip to be sorted; Obtaining thermal resistance based on the thermal conductivity, cross-sectional area, and thickness dimensions; Obtaining thermal response time according to the thickness dimension, length dimension and width dimension; Obtaining each pin diameter, each pin length and pin thermal conductivity according to the pin characteristics, and obtaining the total pin cross-sectional area according to a plurality of the pin diameters; Obtaining a heat dissipation capability index according to the total cross-sectional area of ​​the pins, the thermal conductivity of the pins, and the lengths of the multiple pins; The temperature rise rate is obtained according to the heat dissipation capability index, thermal resistance and thermal response time.

3. The thermistor chip sorting method based on industrial Internet of Things according to claim 2 is characterized in that: The step of obtaining the thermal response time according to the thickness dimension, the length dimension and the width dimension comprises: Obtain the material density and specific heat capacity of the thermistor chips to be sorted; Obtaining the mass of the thermistor chips to be sorted according to the material density, thickness, length and width; Obtaining the contact surface area of ​​the thermistor chip to be sorted according to the thickness dimension, length dimension and width dimension; The thermal response time is obtained according to the contact surface area, mass and specific heat capacity.

4. The thermistor chip sorting method based on industrial Internet of Things according to claim 1 is characterized in that: The step of calculating the thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and calculating the temperature change response speed according to the thermal response speed and the temperature rise rate comprises: Obtain the material density, specific heat capacity and resistance thermal conductivity of the thermistor chips to be sorted; Obtaining thermal diffusivity according to the material density, specific heat capacity and electrical resistance thermal conductivity; Obtaining the thermal response time and plane size of the thermistor chip to be sorted, and obtaining the influence coefficient of the thermistor chip to be sorted according to the thermal response time, plane size and thermal diffusivity; respectively obtaining a first weight of the roughness, a second weight of the surface defect degree, and a third weight of the surface contamination degree; The thermal response speed is calculated according to the influence coefficient, plane size, resistance thermal conductivity, roughness, first weight, second weight, third weight, surface defect degree and surface contamination degree, wherein the calculation formula is: Among them, R(XS) represents thermal response speed, Y(X) represents influence coefficient, P(M) represents plane size, D(R) represents resistance thermal conductivity, α represents the first weight, β represents the second weight, γ represents the third weight, C(D) represents roughness, B(D) represents the degree of surface defects, and W(D) represents the degree of surface contamination; Obtaining an impact factor according to the thermal response speed; The temperature change response speed is calculated according to the influencing factor, the thermal response speed and the temperature rise rate, wherein the calculation formula is: W(XS)=R(XS) y(z) *W(SL) 1-y(z) ; Among them, W(XS) represents the temperature change response speed, R(XS) represents the thermal response speed, W(SL) represents the temperature rise rate, and y(z) represents the impact factor.

5. The thermistor chip sorting method based on industrial Internet of Things according to claim 1 is characterized in that: The step of obtaining the actual resistance change rate according to the preset time period and multiple actual temperature values ​​includes: Obtain the resistivity, initial temperature value and initial resistance value of the thermistor chip to be sorted; The corresponding actual resistance value is calculated according to the resistivity, the initial temperature value, the initial resistance value and each actual temperature value, wherein the calculation formula is: Among them, S(W) i represents the i-th actual resistance value, C(W) represents the initial temperature value, D(X) represents the resistivity, C(Z) represents the initial resistance value, S(Z) i represents the i-th actual temperature value, where i represents the sequence number of the actual temperature value; The actual resistance change rate is calculated according to the preset time period and multiple actual resistance values, wherein the calculation formula is: Where S(XS) represents the actual resistance change rate, N represents the number of actual resistance values, Y(SD) represents the preset time period, S(W) represents the actual resistance change rate, N represents the actual resistance value ... a represents the ath actual resistance value, and α represents the sequence number of the actual resistance value.

6. The method for sorting thermistor chips based on industrial Internet of Things according to claim 5, characterized in that: The step of obtaining the dynamic response deviation according to the actual resistance change rate and the temperature change response speed comprises: Acquire temperature sensitivity according to the actual resistance change rate; Acquire a temperature hysteresis value according to the temperature sensitivity, and acquire a first temperature deviation according to the temperature hysteresis value; Obtaining linearity according to the temperature change response speed; Acquire a linear drift error according to the linearity, and acquire a second temperature deviation according to the linear drift error; A dynamic response deviation is obtained according to the first temperature deviation and the second temperature deviation.

7. A thermistor chip sorting system based on industrial Internet of Things, characterized in that: include: A first acquisition module is used to acquire image feature information of the thermistor chips to be sorted, wherein the image feature information includes size feature information and appearance feature information; A second acquisition module is used to acquire the plane size, thickness size and pin characteristics of the size feature information, and acquire the temperature rise rate according to the plane size, thickness size and pin characteristics; A third acquisition module is used to acquire the roughness and appearance defects of the appearance feature information, and acquire the surface defect degree and surface contamination degree according to the appearance defects; A calculation module, used to calculate the thermal response speed according to the roughness, the degree of surface defects and the degree of surface contamination, and to calculate the temperature change response speed according to the thermal response speed and the temperature rise rate; A fourth acquisition module, used to acquire multiple actual temperature values ​​of the thermistor chip to be sorted within a preset time period, and acquire an actual resistance change rate according to the preset time period and the multiple actual temperature values; A judgment module, used for obtaining a dynamic response deviation according to the actual resistance change rate and the temperature change response speed, and judging whether the dynamic response deviation is greater than a preset deviation; If the dynamic response deviation is greater than the preset deviation, the thermistor chip to be sorted is determined to be qualified, and is transported and sorted; If the dynamic response deviation is not greater than the preset deviation, the thermistor chip to be sorted is determined to be unqualified and is transported and rejected.

8. The thermistor chip sorting system based on industrial Internet of Things according to claim 7 is characterized in that: The second acquisition module includes: Acquire a length dimension and a width dimension according to the plane dimension, and acquire a cross-sectional area according to the length dimension and the width dimension; Obtain the thermal conductivity of the thermistor chip to be sorted; Obtaining thermal resistance based on the thermal conductivity, cross-sectional area, and thickness dimensions; Obtaining thermal response time according to the thickness dimension, length dimension and width dimension; Obtaining each pin diameter, each pin length and pin thermal conductivity according to the pin characteristics, and obtaining the total pin cross-sectional area according to a plurality of the pin diameters; Obtaining a heat dissipation capability index according to the total cross-sectional area of ​​the pins, the thermal conductivity of the pins, and the lengths of the multiple pins; The temperature rise rate is obtained according to the heat dissipation capability index, thermal resistance and thermal response time.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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