System and method for automatically detecting and intelligently correcting surface resistance of silicon rod

Abstract

The invention discloses a silicon rod surface resistance automatic detection and intelligent correction system and method. The system comprises a measurement execution module, a data processing module, a temperature correction module, an exception handling module and a result judgment module. The measurement execution module accurately positions and measures the temperature and the surface resistance of the silicon rod; the data processing module preliminarily corrects the data and identifies abnormity; the temperature correction module optimizes and corrects the measured value according to the temperature data and the influence curve; the exception handling module automatically retests the exception data; and the result judgment module gives final evaluation. The method sequentially comprises the steps of measurement preparation, data acquisition, primary processing, temperature correction, exception processing and result judgment and uploading. The problems that traditional measurement is greatly influenced by temperature, data deviation is prone to occurring and the automation degree is low are solved, the requirement of detection for the environment can be effectively lowered, energy waste is avoided, abnormal data are automatically recognized and processed, manual intervention is reduced, the detection accuracy and efficiency are improved, quality detection of the silicon rod in photovoltaic production is guaranteed, and the production efficiency is improved. And powerful technical support is provided for development of the photovoltaic industry.

Description

Technical Field

[0001] The present invention relates to the field of silicon rod detection technology, and in particular to a system and method for automatic detection and intelligent correction of silicon rod surface resistance, aiming to achieve high-precision, automatic detection and intelligent correction of silicon rod surface resistance. Background Art

[0002] In the current booming photovoltaic industry, silicon ingots, a key raw material for silicon wafer production, have a surface resistance that plays a decisive role in their power generation efficiency. Therefore, testing the surface resistance of silicon ingots has become an essential step in the photovoltaic crystal pulling process. Currently, measuring the surface resistance of silicon ingots relies primarily on manual or semi-automatic methods. Semi-automatic measurement typically utilizes an automated truss coupled with a fixture to hold the test instrument. After the measurement, the data is uploaded to a judgment system to obtain the test results.

[0003] However, existing measurement technologies present numerous challenges that are difficult to ignore. Testing instruments are extremely sensitive to temperature, and even small temperature changes can significantly affect the accuracy of measurement results. To ensure measurement accuracy, existing electrical performance testing often requires the construction of specialized heating systems and strictly temperature-controlled testing chambers. However, in actual production, due to the constraints of production cycles, the silicon rod heating time and the length of time it remains in the testing chamber are limited, making it difficult to ensure that the silicon rod temperature is consistent with room temperature. Seasonal changes, fluctuations in the cutting water temperature during the previous process, and initial temperature differences when the silicon rod is placed on the cutting machine can all lead to large fluctuations in measurement results, resulting in resistance deviations. Furthermore, surface conditions such as the roughness and flatness of the silicon rod surface, as well as factors such as the distance between the instrument's measuring head and the measuring surface and the measurement angle, can also easily lead to measurement deviations and even data anomalies. These issues not only lead to frequent batch quality issues during automated testing, but also seriously hinder the highly automated testing process, making it difficult to meet the photovoltaic industry's growing demand for high-quality, high-efficiency production. Summary of the Invention

[0004] The core purpose of the present invention is to provide a silicon rod surface resistance automatic detection intelligent correction system and method, which effectively solves the problems of low measurement accuracy, susceptibility to environmental interference and insufficient automation in existing detection technologies, ensures the accuracy and stability of silicon rod surface resistance detection, and improves the production quality and efficiency of the photovoltaic industry.

[0005] In a first aspect, an embodiment of the present invention provides a silicon rod surface resistance automatic detection and intelligent correction system, comprising:

[0006] The measurement execution module consists of a gantry truss, an X-axis, a Y-axis, a Z-axis, and a rotation axis. The Z-axis is connected to a spring damping fixture, a resistance measuring instrument, and a temperature measuring instrument, and is used to measure the surface resistance and temperature at any position on the two end surfaces of the silicon rod;

[0007] a data processing module, which receives the silicon rod surface resistance measurement value and temperature data collected by the measurement execution module, performs preliminary correction on the resistance measurement value according to a preset standard temperature curve, sets a standard range of silicon rod resistance value to identify abnormal data, and records historical measurement data;

[0008] The temperature correction module automatically corrects the current resistance measurement value based on the measured temperature data and the temperature effect curve on the instrument measurement value, and automatically adjusts the temperature-measurement value curve based on historical measurement data;

[0009] The abnormality handling module identifies abnormal data and locations based on the theoretical value range of the silicon rod electrical performance data, automatically starts the retest program, and can set the number of retests. When the number of retests exceeds the set value and the data is still abnormal, an audible and visual alarm is triggered and the alarm information is pushed to the host of the detection center;

[0010] The result judgment module makes a final judgment on the data after temperature correction and retesting. For N-type silicon rods, if the resistance measurement value is within the range of 0.4-1.6ohm / sq and the range of the three groups of resistance measurement values is ≤0.08ohm / sq, the data is judged to be valid. Otherwise, it is judged as abnormal data and the judgment result is uploaded to the judgment system.

[0011] In some embodiments of the present invention, the resistance measuring instrument is a semilabwmt-1c, the temperature measuring instrument and the resistance measuring instrument are installed in parallel, and the time difference between the temperature measurement and the resistance measurement is extremely small.

[0012] In some embodiments of the present invention, the retest procedure of the above-mentioned exception handling module is to first retest at the origin, and if the result is still abnormal, retest at another point on the same circumference.

[0013] In some embodiments of the present invention, when the data processing module performs preliminary correction on the resistance measurement value, it is based on a preset standard temperature curve to reduce the influence of temperature on the measurement result.

[0014] In some embodiments of the present invention, the temperature correction module dynamically generates a correction coefficient adapted for use by a field instrument by automatically learning historical measurement data.

[0015] In a second aspect, an embodiment of the present application provides a method for automatic detection and intelligent correction of silicon rod surface resistance, comprising the following steps:

[0016] In the measurement preparation, semilabwmt-1c was selected as the resistance measuring instrument and installed on the measurement execution module together with the temperature measuring instrument. The measurement points of the N-type silicon rod were determined to be the three vertices of the equilateral triangle inscribed in the 3 / 4R circle of the silicon rod end face.

[0017] Data acquisition: The measurement execution module moves to the silicon rod measurement point. The temperature measuring instrument first measures the silicon rod temperature, and the resistance measuring instrument then measures the electrical properties of the silicon rod and records the data.

[0018] Initial data processing: The data processing module receives the data, makes a preliminary correction to the resistance measurement value according to the preset standard temperature curve, and compares the data with the standard range to preliminarily determine whether the data is abnormal;

[0019] Intelligent temperature correction: the temperature correction module automatically corrects the current resistance measurement value according to the measured temperature and influence curve, and continuously collects historical data to optimize the temperature-measurement value curve;

[0020] Abnormal data processing: The abnormal processing module identifies abnormal data and location, starts the retest program, and sets the number of retests according to the production line rhythm requirements. If the number of retests exceeds the limit and the abnormality persists, an audible and visual alarm will be triggered and manual intervention will be notified;

[0021] Result determination and upload, the result determination module makes a final determination on the corrected and retested data, and uploads the determination results to the determination system.

[0022] In some embodiments of the present invention, in the above data collection step, the time interval between temperature measurement and resistance measurement is short, and the influence of temperature change on the measurement result can be ignored.

[0023] In some embodiments of the present invention, in the abnormal data processing step, the re-measurement procedure includes re-measurement of the origin and re-measurement of points on the same circumference.

[0024] In some embodiments of the present invention, in the above-mentioned intelligent temperature correction step, the temperature correction module generates a more accurate correction coefficient by automatically learning historical measurement data.

[0025] In some embodiments of the present invention, in the above result determination step, for N-type silicon rods, the resistance measurement value range and the extreme differences of the three groups of resistance measurement values are used as the basis for determining the validity of the data.

[0026] The embodiments of the present invention have at least the following advantages or beneficial effects:

[0027] The present invention constructs a complete silicon rod surface resistance automatic detection and intelligent correction system, covering measurement execution, data processing, temperature correction, exception handling and result judgment modules. The modules work together to form an organic whole. The measurement execution module provides basic data for subsequent data processing and analysis, the data processing module performs preliminary processing and anomaly identification on the original data, the temperature correction module further improves the measurement accuracy, the anomaly handling module ensures data reliability, and the result judgment module provides the final quality assessment. This integrated system design avoids the problems of isolation and lack of coordination in each link in traditional detection methods, greatly improves the overall efficiency and accuracy of detection, and ensures that the silicon rod surface resistance detection work is carried out efficiently and orderly.

[0028] The measurement execution module in this invention can measure any position on either end of the silicon ingot, ensuring comprehensive testing. The data processing module corrects resistance values based on a standard temperature curve and identifies abnormal data, providing reliable data for subsequent analysis. The temperature correction module automatically corrects measurement results based on the temperature-measurement value influence curve, reducing the impact of temperature on the measurement. The abnormality processing module remeasures and processes abnormal data to avoid misjudgments. The result judgment module determines data validity based on clear standards, providing an accurate basis for silicon ingot quality assessment. The synergistic effect of these functions comprehensively guarantees the quality of silicon ingot surface resistance testing.

[0029] The present invention uses the SemiLab WMT-1C as a resistance measuring instrument, which features high-precision measurement capabilities and can accurately determine the surface resistance of silicon rods. The temperature measuring instrument and resistance measuring instrument are installed in parallel, with minimal measurement time difference, effectively reducing measurement errors caused by temperature fluctuations. This instrument configuration and installation ensures synchronous and accurate acquisition of silicon rod temperature and surface resistance data during the measurement process, providing high-quality raw data for subsequent data processing and correction, thereby improving the accuracy and reliability of the entire detection system.

[0030] The exception handling module of the present invention uses retesting at the origin to eliminate abnormal data caused by temporary factors such as occasional poor fit between the measuring head and the silicon rod surface. If the retest result at the origin is still abnormal, retesting at points along the same circumference can prevent local surface issues from interfering with the measurement results. This step-by-step, targeted retesting procedure improves the accuracy of abnormal data processing, effectively reduces misjudgments and missed detections, and ensures the reliability of test results.

[0031] The data processing module of the present invention performs preliminary corrections to resistance measurements based on a preset standard temperature curve, compensating for the effects of temperature early in the data processing process. Since temperature is a significant factor influencing silicon rod surface resistance measurements, this preliminary correction effectively minimizes the impact of temperature on the results, making subsequent analysis and processing more accurate and laying the foundation for the accuracy of the entire detection process.

[0032] For N-type silicon rods, this invention uses the resistance measurement range and the range of three resistance measurement values as the basis for determining data validity. This scientific and reasonable judgment standard can accurately distinguish between qualified and unqualified silicon rods, providing an objective and accurate basis for silicon rod quality assessment. This scientific judgment helps companies promptly identify and address quality issues, improving production efficiency and product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0034] Figure 1 It is a principle block diagram of the present invention;

[0035] Figure 2 This is a structural block diagram of an electronic device provided by an embodiment of the present invention.

[0036] Description of the accompanying drawings: 101, memory; 102, processor; 103, communication interface. DETAILED DESCRIPTION

[0037] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0038] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0039] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0040] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further limitations, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device that includes the element.

[0041] In the description of the embodiments of the present invention, "a plurality of" means at least two.

[0042] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0043] An embodiment of the present invention provides a silicon rod surface resistance automatic detection and intelligent correction system, comprising:

[0044] The measurement execution module consists of a gantry truss, an X-axis, a Y-axis, a Z-axis, and a rotation axis. The Z-axis is connected to a spring damping fixture, a resistance measuring instrument, and a temperature measuring instrument, and is used to measure the surface resistance and temperature at any position on the two end surfaces of the silicon rod;

[0045] a data processing module, which receives the silicon rod surface resistance measurement value and temperature data collected by the measurement execution module, performs preliminary correction on the resistance measurement value according to a preset standard temperature curve, sets a standard range of silicon rod resistance value to identify abnormal data, and records historical measurement data;

[0046] The temperature correction module automatically corrects the current resistance measurement value based on the measured temperature data and the temperature effect curve on the instrument measurement value, and automatically adjusts the temperature-measurement value curve based on historical measurement data;

[0047] The abnormality handling module identifies abnormal data and locations based on the theoretical value range of the silicon rod electrical performance data, automatically starts the retest program, and can set the number of retests. When the number of retests exceeds the set value and the data is still abnormal, an audible and visual alarm is triggered and the alarm information is pushed to the host of the detection center;

[0048] The result judgment module makes a final judgment on the data after temperature correction and retesting. For N-type silicon rods, if the resistance measurement value is within the range of 0.4-1.6ohm / sq and the range of the three groups of resistance measurement values is ≤0.08ohm / sq, the data is judged to be valid. Otherwise, it is judged as abnormal data and the judgment result is uploaded to the judgment system.

[0049] In an embodiment of the present invention, the resistance measuring instrument is a semilabwmt-1c, the temperature measuring instrument and the resistance measuring instrument are installed in parallel, and the time difference between the temperature measurement and the resistance measurement is extremely small.

[0050] In the embodiment of the present invention, the retest procedure of the above-mentioned abnormality handling module is to first retest at the origin, and if the result is still abnormal, retest at another point on the same circumference.

[0051] In an embodiment of the present invention, when the data processing module performs preliminary correction on the resistance measurement value, it is based on a preset standard temperature curve to reduce the influence of temperature on the measurement result.

[0052] In the embodiment of the present invention, the temperature correction module dynamically generates a correction coefficient adapted for use by the field instrument by automatically learning historical measurement data.

[0053] The present application also provides a method for automatic detection and intelligent correction of silicon rod surface resistance, comprising the following steps:

[0054] In the measurement preparation, semilabwmt-1c was selected as the resistance measuring instrument and installed on the measurement execution module together with the temperature measuring instrument. The measurement points of the N-type silicon rod were determined to be the three vertices of the equilateral triangle inscribed in the 3 / 4R circle of the silicon rod end face.

[0055] Data acquisition: The measurement execution module moves to the silicon rod measurement point. The temperature measuring instrument first measures the silicon rod temperature, and the resistance measuring instrument then measures the electrical properties of the silicon rod and records the data.

[0056] Initial data processing: The data processing module receives the data, makes a preliminary correction to the resistance measurement value according to the preset standard temperature curve, and compares the data with the standard range to preliminarily determine whether the data is abnormal;

[0057] Intelligent temperature correction: the temperature correction module automatically corrects the current resistance measurement value according to the measured temperature and influence curve, and continuously collects historical data to optimize the temperature-measurement value curve;

[0058] Abnormal data processing: The abnormal processing module identifies abnormal data and location, starts the retest program, and sets the number of retests according to the production line rhythm requirements. If the number of retests exceeds the limit and the abnormality persists, an audible and visual alarm will be triggered and manual intervention will be notified;

[0059] Result determination and upload, the result determination module makes a final determination on the corrected and retested data, and uploads the determination results to the determination system.

[0060] In the embodiment of the present invention, in the above data collection step, the time interval between the temperature measurement and the resistance measurement is short, and the influence of temperature change on the measurement result can be ignored.

[0061] In an embodiment of the present invention, in the above abnormal data processing step, the re-measurement procedure includes re-measurement of the origin and re-measurement of points on the same circumference.

[0062] In an embodiment of the present invention, in the above-mentioned intelligent temperature correction step, the temperature correction module generates a more accurate correction coefficient by automatically learning historical measurement data.

[0063] In the embodiment of the present invention, in the above result determination step, for the N-type silicon rod, the resistance measurement value range and the extreme differences of the three groups of resistance measurement values are used as the basis for determining the validity of the data.

[0064] Example 1:

[0065] A system for automatically detecting and intelligently correcting silicon ingot surface resistance was constructed. The measurement execution module utilizes a high-precision gantry truss, achieving positioning accuracy of ±0.01mm on the X, Y, Z, and rotation axes, ensuring precise measurement positions. A semilabwmt-1c resistance meter and a high-precision temperature meter were selected and installed in parallel, ensuring measurement time differences within 0.1 seconds.

[0066] Software Setup: In the data processing module, based on extensive historical data and industry standards, the standard range for silicon ingot resistance was set to 0.4-1.6 ohm / sq, and a pre-measured standard temperature curve was also entered. The temperature correction module initialized the temperature-measurement influence curve and set the automatic learning cycle to update the curve every 100 data sets. The exception handling module set the maximum number of retests to three. When retesting points on the same circumference, new measurement points were selected using a uniform distribution principle.

[0067] Measurement process: The N-type silicon rod to be tested is placed in the measurement area, and the measurement execution module moves to the vertex position of the equilateral triangle inscribed in the 3 / 4R circumference of the silicon rod end face. The temperature measuring instrument measures the temperature as 23°C, and the resistance measuring instrument measures the resistance as 1.2 ohm / sq. After receiving the data, the data processing module performs a preliminary correction based on the standard temperature curve and finds that the value is within the standard range, eliminating the need to initiate the exception handling process. The temperature correction module further corrects the measured value based on the temperature and influence curves, and the final corrected value is 1.18 ohm / sq. The result judgment module determines that the data is valid and uploads it to the judgment system.

[0068] The system performed stably during the inspection of 1,000 N-type silicon ingots, achieving an average inspection time of 30 seconds per ingot. Compared to high-precision laboratory testing equipment, the measurement error was within ±0.05 ohm / sq, with an accuracy rate of 98%. Furthermore, effective temperature correction and exception handling mechanisms prevented misjudgments caused by temperature fluctuations and measurement anomalies, ensuring the reliability of silicon ingot quality inspection.

[0069] Comparative Example 1:

[0070] Traditional semi-automatic measurement method

[0071] Measurement Equipment and Operation: Measurements were performed using conventional semi-automatic measuring equipment, manually operated with an automated truss-gripping instrument. Prior to measurement, the silicon ingot temperature was not measured or corrected; instead, the appropriateness of the ambient temperature was determined solely by manual experience. The instrument used was the same as in Example 1, but lacked automatic temperature correction and exception handling capabilities.

[0072] Measurement process: Surface resistance of an N-type silicon ingot was measured at an ambient temperature of 20°C. An automated gantry was manually operated to move the measuring head to the ingot end face, resulting in a resistance value of 1.1 ohms / sq. Due to the lack of temperature correction or exception handling mechanisms, this measurement value was directly uploaded to the judgment system.

[0073] Analysis of the results: When measuring 100 N-type silicon ingots, compared to high-precision laboratory testing equipment, the results showed significant error, with an average error of ±0.15 ohm / sq and an accuracy rate of only 70%. Affected by ambient temperature fluctuations, the measurement results fluctuated significantly. Furthermore, the system was unable to effectively identify and address abnormal data caused by issues such as poor measurement head alignment. This resulted in a large number of unqualified silicon ingots being mistakenly identified as qualified, and qualified silicon ingots being mistakenly identified as unqualified, seriously impacting product quality assessment and production decision-making.

[0074] Example 2:

[0075] Based on the original system, the measurement execution module was upgraded and a high-precision pressure sensor was installed on the Z-axis to monitor the contact pressure between the measuring head and the surface of the silicon rod in real time, ensuring good fit between the measuring head and the surface of the silicon rod and reducing measurement errors caused by contact problems.

[0076] Software Optimization: A data filtering algorithm has been added to the data processing module to denoise collected data and improve data quality. A machine learning algorithm has been introduced into the temperature correction module to enhance the analysis of historical data and more accurately optimize the temperature-measurement curve. The exception handling module is now integrated with the production management system. When an audible and visual alarm is triggered, the exception information is automatically recorded in the production management system and associated with information such as the silicon ingot production batch and equipment number, facilitating subsequent traceability and analysis.

[0077] Measurement process: A batch of N-type silicon rods, which are significantly affected by ambient temperature, were tested. The measurement execution module obtained a silicon rod temperature of 26°C and an initial resistance measurement of 1.35 ohm / sq. After filtering and preliminary correction, the data processing module transmitted the data to the temperature correction module. Using an optimized algorithm and curve, the temperature correction module corrected the resistance value to 1.32 ohm / sq. During the measurement process, the measurement value of one silicon rod showed an anomaly. The anomaly handling module initiated a retest procedure. After retesting points at the origin and the same circumference, it was determined that the silicon rod had local surface defects. This anomaly information was fed back to the production management system, and the production department promptly adjusted the production process for this batch of silicon rods.

[0078] After optimization, the system's adaptability to ambient temperature fluctuations has been significantly enhanced. When inspecting silicon ingots subject to temperature fluctuations, the stability of measurement results has been improved, with the error range narrowed to ±0.03 ohm / sq. By integrating with the production management system, the efficiency of abnormal data processing has been improved, reducing the time from anomaly detection to production process adjustments by 50%. This effectively reduces production losses caused by silicon ingot quality issues and improves overall production efficiency.

[0079] Comparative Example 2:

[0080] Simple system lacking intelligent correction

[0081] System Setup: Build a simple silicon ingot surface resistance detection system, consisting of a measurement execution module and a basic data processing module. The measurement execution module has a simple structure and low positioning accuracy, and can only measure specific locations on the silicon ingot. The data processing module only provides data acquisition and simple display functions, without temperature correction, abnormal data identification, or processing capabilities.

[0082] Measurement process: When measuring an N-type silicon ingot, the measurement execution module obtains the ingot's surface resistance but cannot measure temperature. The data processing module directly displays the raw measurement value, allowing the operator to determine whether the data is reasonable based on experience. In one measurement, the measured value was 1.5 ohms / sq. The operator did not find any obvious abnormality and recorded it.

[0083] Results Analysis: During the measurement of 50 N-type silicon ingots, the lack of temperature correction and exception handling capabilities resulted in significant environmental and measurement error impacts. Compared to Example 1, the accuracy and reliability of the measurement results were poor, failing to provide effective support for silicon ingot quality assessment. This increased the defective rate in subsequent silicon wafer production due to substandard silicon ingot surface resistance.

[0084] like Figure 2 , an embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which implements a system as described in any one of the first aspects above when executed by the processor 102. If the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0085] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

[0086] It will be apparent to those skilled in the art that the present application is not limited to the details of the exemplary embodiments described above and that the present application can be implemented in other specific forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the present application is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A silicon rod surface resistance automatic detection and intelligent correction system, characterized in that: include: The measurement execution module consists of a gantry truss, an X-axis, a Y-axis, a Z-axis, and a rotation axis. The Z-axis is connected to a spring damping fixture, a resistance measuring instrument, and a temperature measuring instrument, and is used to measure the surface resistance and temperature at any position on the two end surfaces of the silicon rod; a data processing module, which receives the silicon rod surface resistance measurement value and temperature data collected by the measurement execution module, performs preliminary correction on the resistance measurement value according to a preset standard temperature curve, sets a standard range of silicon rod resistance value to identify abnormal data, and records historical measurement data; The temperature correction module automatically corrects the current resistance measurement value based on the measured temperature data and the temperature effect curve on the instrument measurement value, and automatically adjusts the temperature-measurement value curve based on historical measurement data; The abnormality handling module identifies abnormal data and locations based on the theoretical value range of the silicon rod electrical performance data, automatically starts the retest program, and can set the number of retests. When the number of retests exceeds the set value and the data is still abnormal, an audible and visual alarm is triggered and the alarm information is pushed to the host of the detection center; The result judgment module makes a final judgment on the data after temperature correction and retesting. For N-type silicon rods, if the resistance measurement value is within the range of 0.4-1.6ohm / sq and the range of the three groups of resistance measurement values is ≤0.08ohm / sq, the data is judged to be valid. Otherwise, it is judged as abnormal data and the judgment result is uploaded to the judgment system.

2. The silicon rod surface resistance automatic detection and intelligent correction system according to claim 1, characterized in that: The resistance measuring instrument is semilabwmt-1c, and the temperature measuring instrument and the resistance measuring instrument are installed in parallel. The time difference between the temperature measurement and the resistance measurement is extremely small.

3. The silicon rod surface resistance automatic detection and intelligent correction system according to claim 1, characterized in that: The retest procedure of the abnormality handling module is to retest at the origin first. If the result is still abnormal, retest at another point on the same circumference.

4. The silicon rod surface resistance automatic detection and intelligent correction system according to claim 1, characterized in that: When the data processing module performs preliminary correction on the resistance measurement value, it is based on a preset standard temperature curve to reduce the influence of temperature on the measurement result.

5. The silicon rod surface resistance automatic detection and intelligent correction system according to claim 1, characterized in that: The temperature correction module dynamically generates a correction coefficient adapted to the use of the on-site instrument by automatically learning historical measurement data.

6. A method for automatic detection and intelligent correction of silicon rod surface resistance, characterized in that: The following steps are involved: In the measurement preparation, semilabwmt-1c was selected as the resistance measuring instrument and installed on the measurement execution module together with the temperature measuring instrument. The measurement points of the N-type silicon rod were determined to be the three vertices of the equilateral triangle inscribed in the 3 / 4R circle of the silicon rod end face. Data acquisition: The measurement execution module moves to the silicon rod measurement point. The temperature measuring instrument first measures the silicon rod temperature, and the resistance measuring instrument then measures the electrical properties of the silicon rod and records the data. Initial data processing: The data processing module receives the data, makes a preliminary correction to the resistance measurement value according to the preset standard temperature curve, and compares the data with the standard range to preliminarily determine whether the data is abnormal; Intelligent temperature correction: the temperature correction module automatically corrects the current resistance measurement value according to the measured temperature and influence curve, and continuously collects historical data to optimize the temperature-measurement value curve; Abnormal data processing: The abnormal processing module identifies abnormal data and location, starts the retest program, and sets the number of retests according to the production line rhythm requirements. If the number of retests exceeds the limit and the abnormality persists, an audible and visual alarm will be triggered and manual intervention will be notified; Result determination and upload, the result determination module makes a final determination on the corrected and retested data, and uploads the determination results to the determination system.

7. The method for automatic detection and intelligent correction of silicon rod surface resistance according to claim 6, characterized in that: In the data acquisition step, the time interval between temperature measurement and resistance measurement is short, and the influence of temperature change on the measurement result can be ignored.

8. The method for automatic detection and intelligent correction of silicon rod surface resistance according to claim 6, characterized in that: In the abnormal data processing step, the re-measurement procedure includes re-measurement of the origin and re-measurement of points on the same circumference.

9. The method for automatic detection and intelligent correction of silicon rod surface resistance according to claim 6, characterized in that: In the temperature intelligent correction step, the temperature correction module generates a more accurate correction coefficient by automatically learning historical measurement data.

10. The method for automatic detection and intelligent correction of silicon rod surface resistance according to claim 6, characterized in that: In the result determination step, for the N-type silicon rod, the resistance measurement value range and the range of the three groups of resistance measurement values are used as the basis for determining the validity of the data.

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