Intelligent monitoring system for household appliance glass production

Abstract

The invention discloses an intelligent monitoring system for household appliance glass production, and relates to the technical field of automation control, the intelligent monitoring system comprises an acquisition module, a calibration module, a compensation module, an identification module and a recording module, the acquisition module is used for acquiring initial parameters, the calibration module is used for calibrating the initial parameters, the compensation module is used for establishing a self-adaptive light intensity compensation mechanism, and the identification module is used for identifying the self-adaptive light intensity compensation mechanism. According to the system and the method, the influences of mechanical vibration, illumination interference and the like are eliminated by virtue of a three-dimensional coordinate transformation algorithm and an optical filtering technology of the calibration module, complex illumination changes are dynamically dealt with, and the accuracy and the reliability of the system are improved. Detailed data support is provided for process optimization, the early warning rejection accuracy and the quality tracing efficiency are improved, the refined control requirements of high-precision and high-yield production are met, and powerful guarantee is provided for efficient, stable and high-quality operation of household appliance glass production.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automation control, and in particular to an intelligent monitoring system for household appliance glass production. BACKGROUND

[0002] In recent years, with the rapid development of the intelligent household appliance industry, the market has increasingly high requirements for the quality of household appliance glass, not only in terms of basic light transmittance, strength and other physical properties, but also in terms of impurity control on the surface and inside of the glass and size precision, and household appliance glass, as a key appearance and functional component of intelligent household appliances, directly affects the safety, reliability and user experience of the product in the production process, and real-time monitoring of production data, abnormality early warning and quality tracing have become key requirements for ensuring production continuity and product quality.

[0003] The prior art relies on manual sampling inspection or a single sensor for traditional monitoring, which has low detection efficiency and high missed detection rate, and is difficult to adapt to high-speed continuous production, and although some automated systems can collect parameters and make basic judgments, they lack a self-adaptive environmental compensation mechanism and are easily affected by light fluctuations and mechanical vibrations, resulting in a decrease in detection accuracy, and the identification of impurities is mostly limited to simple size judgment, without recording detailed parameters such as position and shape, which is not conducive to quality tracing and process optimization, and the threshold setting and unqualified product processing lack dynamic calibration and linkage mechanisms, the setting of early warning and rejection thresholds lacks dynamic adjustment capability in the unqualified product processing link, and the binding tracing mechanism of the processing result and the production batch is imperfect, affecting the production traceability and quality improvement efficiency. SUMMARY

[0004] The technical problem solved by the present application is that traditional monitoring relies on manual sampling inspection or a single sensor, which has low detection efficiency and high missed detection rate, and is difficult to adapt to high-speed continuous production, and although some automated systems can collect parameters and make basic judgments, they lack a self-adaptive environmental compensation mechanism and are easily affected by light fluctuations and mechanical vibrations, resulting in a decrease in detection accuracy, and the identification of impurities is mostly limited to simple size judgment, without recording detailed parameters such as position and shape, which is not conducive to quality tracing and process optimization, and the threshold setting and unqualified product processing lack dynamic calibration and linkage mechanisms, the setting of early warning and rejection thresholds lacks dynamic adjustment capability in the unqualified product processing link, and the binding tracing mechanism of the processing result and the production batch is imperfect, affecting the production traceability and quality improvement efficiency.

[0005] To solve the above technical problems, the present application provides the following technical solution: an intelligent monitoring system for household appliance glass production, comprising a collection module, a calibration module, a compensation module, an identification module and a recording module: The collection module is used to obtain initial parameters; The calibration module is used to calibrate the initial parameters and determine early warning threshold parameters and rejection threshold parameters; The compensation module is configured to establish an adaptive light intensity compensation mechanism. The identification module is configured to identify impurities in the glass product and record characteristic parameters of the impurities. The recording module is configured to remove unqualified glass products according to the early warning threshold parameter and the removal threshold parameter, and record processing results of the unqualified glass products.

[0006] As a preferred scheme of the household appliance glass production intelligent monitoring system, the collection module is configured to deploy a laser scattering instrument in a detection area of a glass production line, set a laser scattering instrument emitting device and a laser scattering instrument receiving device above and below a transmission path to form a vertical light path, and set laser parameters of the laser scattering instrument according to production requirements, the production requirements including a glass type, impurity detection accuracy, and a glass thickness, the laser parameters including a laser wavelength, a laser power, and a laser gathering point, and simultaneously obtain initial parameters, the initial parameters including initial light path reference data of the laser scattering instrument and initial light intensity data of an ambient light sensor. The initial light path reference data includes a laser propagation trajectory in a glass sample, an initial power value of a laser emitting end, and a divergence angle of a laser beam in an environment, and the initial light intensity data includes an initial spectral component proportion of ambient light, an illumination intensity value of the detection area without laser and without additional light source, and illumination distribution data of the laser scattering instrument receiving device.

[0007] As a preferred scheme of the household appliance glass production intelligent monitoring system, the calibration module is configured to calibrate the initial parameters according to a quality standard of the glass, the calibration including light path data calibration and ambient light intensity data calibration, and determine an early warning threshold parameter and a removal threshold parameter. The quality standard includes a size range of impurities allowed to exist on a glass surface and inside the glass, a quantity limit of the impurities, and a light intensity attenuation threshold range caused by the impurities. The early warning threshold parameter is configured to send a prompt signal to remind an operator to pay attention to glass in the current detection area that is close to a qualified critical value. The removal threshold parameter is configured to trigger a removal mechanism to separate glass meeting the removal threshold parameter from the glass production line. The light path data calibration is configured to adjust position parameters of the laser scattering instrument emitting device and the laser scattering instrument receiving device in real time through a three-dimensional coordinate transformation algorithm, remove light path deviation caused by mechanical vibration and installation error, and adjust laser power according to a glass thickness and material characteristics to offset energy loss in a light path propagation process. The ambient light intensity data calibration is used to acquire specific wavelength components in ambient light through optical filtering technology, exclude interfering light lines overlapping with detection laser wavelength, and set multiple light intensity collection points in the detection area to compensate detection errors caused by production line light changes.

[0008] As a preferred scheme of the household appliance glass production intelligent monitoring system, the logic of determining the pre-warning threshold parameter and the rejection threshold parameter comprises: The impurity light intensity attenuation value detected by the laser is received, when the light intensity attenuation value is between the first threshold and the second threshold within the quality standard, it is determined as the first level, and the light intensity attenuation value is set as the pre-warning threshold parameter; When the light intensity attenuation value is greater than or equal to the second threshold within the quality standard, it is determined as the second level, and the light intensity attenuation value is set as the rejection threshold parameter.

[0009] As a preferred scheme of the household appliance glass production intelligent monitoring system, the compensation module is used to establish an adaptive light intensity compensation mechanism, the adaptive light intensity compensation mechanism is used to continuously detect the ambient light sensor, collect real-time light intensity data of the ambient light sensor, analyze ambient light fluctuation conditions according to the real-time light intensity data, obtain ambient light fluctuation results, and establish a dynamic compensation relationship between light intensity data and laser power adjustment according to the ambient light fluctuation results. The logic of obtaining the ambient light fluctuation results comprises: The real-time light intensity data of the ambient light sensor at different detection time periods and different monitoring points is collected, the different monitoring points include the periphery of the laser propagation path and the vicinity of the laser scattering instrument receiving device, the real-time light intensity data is compared with the initial light intensity data, and the fluctuation amplitude and change trend of the ambient light in intensity, distribution and spectral composition are analyzed according to the comparison result, the ambient light fluctuation results are obtained according to the fluctuation amplitude and change trend, and the ambient light fluctuation results include light intensity fluctuation range, abnormal fluctuation frequency and key area light stability.

[0010] As a preferred scheme of the household appliance glass production intelligent monitoring system, the logic of establishing a dynamic compensation relationship between light intensity data and laser power adjustment according to the ambient light fluctuation results comprises: According to the ambient light fluctuation results, the laser power adjustment amount is obtained by using a weight distribution rule, the weight distribution rule comprises setting a basic weight, quantifying ambient light fluctuation data and calculating an adjustment amount, and the laser power is adjusted according to the laser power adjustment amount; The setting of the basic weight is used to set the weight proportion of the light intensity fluctuation range as a first weight proportion, set the weight proportion of the abnormal fluctuation frequency as a second weight proportion, and set the weight proportion of the key area light stability as a third weight proportion. The quantized ambient light fluctuation data is used to convert the light intensity fluctuation range into a relative value as a first fluctuation quantization value, convert the abnormal fluctuation frequency into a frequency coefficient as a second fluctuation quantization value, and convert the key area light stability into a deviation coefficient as a third fluctuation quantization value. The calculation adjustment amount is used to multiply the first weight proportion by the first fluctuation quantization value to obtain a first adjustment amount, multiply the second weight proportion by the second fluctuation quantization value to obtain a second adjustment amount, multiply the third weight proportion by the third fluctuation quantization value to obtain a third adjustment amount, and add the first adjustment amount, the second adjustment amount, and the third adjustment amount to obtain a fourth adjustment amount, and the fourth adjustment amount is used as the laser power adjustment amount.

[0011] As a preferred scheme of the household appliance glass production intelligent monitoring system, the recognition module is configured to trigger a scanning process when the glass product enters a detection area, and the laser scattering instrument is configured to scan the glass product according to a preset frequency and a preset range, and recognize impurities in the glass product by using a light intensity attenuation value detected by laser, and record characteristic parameters of the impurities. The characteristic parameters include a position of the impurities, a size of the impurities, a number of the impurities, a shape of the impurities, and a scattering intensity of the impurities on laser.

[0012] As a preferred scheme of the household appliance glass production intelligent monitoring system, the logic of recognizing the impurities in the glass product by using the light intensity attenuation value detected by laser includes: The laser scattering instrument is configured to emit laser of a preset power to a glass product detection position, and detect a current light intensity attenuation value of a receiving device of the laser scattering instrument, compare the current light intensity attenuation value with a light intensity attenuation value when there is no impurity, and if the current light intensity attenuation value is out of a preset range of the light intensity attenuation value when there is no impurity, it is determined that there is an impurity in the glass product detection position.

[0013] As a preferred scheme of the household appliance glass production intelligent monitoring system, the recording module is configured to remove unqualified glass products according to the early warning threshold parameter and the rejection threshold parameter, record a processing result of the unqualified glass products, the processing result includes a processing time and a processing position, bind the processing result with production batch information of the unqualified glass products, and record the processing result.

[0014] As a preferred scheme of the household appliance glass production intelligent monitoring system, the logic of removing the unqualified glass products according to the early warning threshold parameter and the rejection threshold parameter by the recording module includes: The recording module is configured to receive a light intensity attenuation value of the impurities detected by laser, compare the light intensity attenuation value of the impurities with the early warning threshold parameter and the rejection threshold parameter. If the impurity light intensity attenuation value reaches the early warning threshold parameter, only the impurity information of the glass product is recorded and a prompt signal is sent out; If the impurity light intensity attenuation value reaches or exceeds the rejection threshold parameter, a rejection mechanism is triggered immediately to separate the glass product from the glass production line.

[0015] The beneficial effects of the present application: the present application provides an intelligent monitoring system for household appliance glass production, which acquires initial parameters through a collection module, eliminates the influence of mechanical vibration and light interference through the three-dimensional coordinate transformation algorithm and optical filtering technology of a calibration module, solves the problem that the detection precision of traditional monitoring is easily affected by the environment, an adaptive light intensity compensation mechanism established by a compensation module can dynamically respond to complex light changes and ensure the accuracy of impurity identification, adapts to high-pace continuous production, an identification module records the characteristic parameters of impurities in an all-round way, provides detailed data support for process optimization, the dynamic early warning threshold and rejection threshold determined by the calibration module, combined with the automatic processing of unqualified products and the binding and tracing of production batches realized by the recording module, improve the early warning and rejection accuracy and the quality tracing efficiency, and can be efficiently connected with the existing intelligent management system, meet the fine management and control needs of high-precision and high-qualified production, and provide a strong guarantee for efficient, stable and high-quality operation of household appliance glass production. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A basic flowchart of an intelligent monitoring system for household appliance glass production is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0017] To make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments.

[0018] Embodiment 1, refer to Figure 1 An intelligent monitoring system for household appliance glass production is provided for an embodiment of the present application, which comprises a collection module, a calibration module, a compensation module, an identification module and a recording module. The collection module is used to acquire initial parameters.

[0019] The calibration module is used to calibrate the initial parameters and determine the early warning threshold parameter and the rejection threshold parameter.

[0020] The compensation module is used to establish an adaptive light intensity compensation mechanism.

[0021] The identification module is used to identify impurities in the glass product and record the characteristic parameters of the impurities.

[0022] The recording module is configured to remove unqualified glass products according to the early warning threshold parameter and the rejection threshold parameter, and record the processing result of the unqualified glass products.

[0023] The acquisition module is configured to deploy a laser scattering instrument in a detection area of a glass production line, to set a laser scattering instrument emitting device and a laser scattering instrument receiving device above and below a conveying path respectively to form a vertical light path, and to set laser parameters of the laser scattering instrument according to production requirements, the production requirements including a glass type, an impurity detection accuracy, and a glass thickness, the laser parameters including a laser wavelength, a laser power, and a laser focus point, and to obtain initial parameters including initial light path reference data of the laser scattering instrument and initial light intensity data of an ambient light sensor.

[0024] The initial light path reference data includes a propagation trajectory of the laser in the glass sample, an initial power value of the laser emitting end, and a divergence angle of the laser beam in the environment, and the initial light intensity data includes a proportion of an initial spectral component of the ambient light, an illumination intensity value of the detection area without laser and without additional light source, and illumination distribution data of the laser scattering instrument receiving device.

[0025] The laser scattering instrument emitting device and the laser scattering instrument receiving device are respectively arranged above and below the conveying path to form a vertical light path, which can ensure the stability of the detection path when the laser penetrates the glass, reduce the influence of light path deviation on subsequent impurity recognition, set the laser parameters of the laser scattering instrument according to the production requirements, adapt the laser scattering detection to different production scenarios, improve the pertinence and accuracy of the detection, obtain the initial parameters, and provide an original reference standard for parameter calibration of the subsequent calibration module and adaptive light intensity adjustment of the compensation module, so as to ensure that the entire monitoring system has reliable data support from the detection source, and lay a foundation for realizing high-precision impurity recognition and quality monitoring.

[0026] The laser parameters of the laser scattering instrument are set according to the production requirements, the glass type requirements, the absorption and scattering characteristics of different materials to different wavelengths of laser, the selection of a laser wavelength that can reduce transmission loss and ensure clear scattering signals, the impurity detection accuracy requirements, the adjustment of the laser focus point to a more concentrated state to improve the resolution capability for small impurities, the correlation between the glass thickness and the laser power, the increase of laser energy attenuation in thick glass, and the appropriate increase of power to ensure that the receiving device can capture effective scattering signals, so as to adjust the detection performance of the laser scattering instrument to adapt to the production requirements, and lay a foundation for accurate impurity recognition.

[0027] The calibration module is configured to calibrate the initial parameters according to the quality standard of the glass, the calibration including light path data calibration and ambient light intensity data calibration, and to determine the early warning threshold parameter and the rejection threshold parameter.

[0028] The initial parameters are calibrated, and the double calibration of the light path data and the ambient light intensity data lays a foundation for subsequent accurate detection and intelligent decision-making, ensuring that the system can accurately and stably perform quality monitoring tasks.

[0029] The quality standards include the size range of impurities allowed to exist on the glass surface and inside, the number limit of impurities, and the threshold range of light intensity attenuation caused by impurities.

[0030] The warning threshold parameters are used to send prompt signals to remind the operator to pay attention to the glass in the current detection area that may be close to the qualified critical value.

[0031] This allows the operator to pay attention to the specific situation in a timely manner and judge whether it is necessary to adjust the production parameters, check the equipment status, or take other preventive measures based on experience or further inspection, so as to intervene before the glass product becomes completely unqualified, which helps to improve the stability of product quality, reduce the generation of potential unqualified products, and avoid possible production interruption or equipment damage.

[0032] The rejection threshold parameters are used to trigger the rejection mechanism to separate the glass that meets the rejection threshold parameters from the glass production line.

[0033] This ensures that unqualified products can be timely and effectively rejected, thereby ensuring the overall quality of the products leaving the factory, preventing defective products from entering the market, and maintaining the brand reputation and consumer rights and interests of the enterprise.

[0034] The light path data calibration is used to adjust the position parameters of the laser scattering instrument emitting device and the laser scattering instrument receiving device in real time through a three-dimensional coordinate transformation algorithm, remove the light path deviation caused by mechanical vibration and installation error, adjust the laser power to offset the energy loss in the light path propagation process according to the glass thickness and material characteristics.

[0035] The removal of the light path deviation caused by mechanical vibration and installation error ensures that the laser beam can always penetrate the glass stably and accurately and be captured by the receiving device, thereby providing a stable and reliable optical basis for subsequent accurate detection, adjusting the laser power to offset the energy loss in the light path propagation process, and compensating for these energy losses by adjusting the laser power, ensuring that the laser still maintains sufficient intensity after penetrating the glass, so that the receiving device can obtain clear and effective scattering signals, thereby ensuring the sensitivity and accuracy of detection are not affected by the characteristics of the glass itself.

[0036] The ambient light intensity data calibration is used to obtain specific wavelength components in the ambient light through optical filtering technology, exclude interfering light lines overlapping with the detection laser wavelength, and set multiple light intensity collection points in the detection area to compensate for detection errors caused by changes in production line illumination.

[0037] The interference light overlapping with the detection laser wavelength is excluded, the signal-to-noise ratio of the detection signal is significantly improved, the system can capture the real scattering information from the impurities in the glass more clearly, and the system can more comprehensively and accurately correct the influence of the ambient light on the detection result by collecting and analyzing the ambient light intensity data at multiple points, so that the accuracy and stability of the detection can be ensured regardless of the fluctuation of external light.

[0038] The logic for determining the early warning threshold parameter and the rejection threshold parameter includes: The impurity light intensity attenuation value detected by the laser is received, and when the light intensity attenuation value is between the first threshold and the second threshold within the quality standard, it is determined as the first level, and the light intensity attenuation value is set as the early warning threshold parameter.

[0039] When the light intensity attenuation value is greater than or equal to the second threshold within the quality standard, it is determined as the second level, and the light intensity attenuation value is set as the rejection threshold parameter.

[0040] The thresholds provide direct basis and rule instructions for subsequent prompting signals or triggering rejection mechanisms based on these threshold parameters, making the entire monitoring process logic clear and coherent and orderly.

[0041] The compensation module is used to establish an adaptive light intensity compensation mechanism, and the adaptive light intensity compensation mechanism is used to continuously detect the ambient light sensor and collect real-time light intensity data of the ambient light sensor, analyze the ambient light fluctuation according to the real-time light intensity data, obtain the ambient light fluctuation result, and establish a dynamic compensation relationship between the light intensity data and the laser power adjustment according to the ambient light fluctuation result.

[0042] When the ambient light intensity fluctuates, the system can automatically calculate the corresponding laser power adjustment, and adjust the output power of the laser according to the laser power adjustment, so as to offset the influence of the change of the ambient light on the detection accuracy. The system can effectively maintain the relative stability of the laser power in the detection process through real-time monitoring, analysis and automatic adjustment, thereby significantly improving the adaptability of the detection system in complex lighting environments and the accuracy of the detection results.

[0043] The logic for obtaining the ambient light fluctuation result includes: The real-time light intensity data of the ambient light sensor at different detection periods and different monitoring points is collected, the different monitoring points include the periphery of the laser propagation path and the vicinity of the laser scattering instrument receiving device, the real-time light intensity data is compared with the initial light intensity data, and the fluctuation amplitude and change trend of the ambient light in intensity, distribution and spectral composition are analyzed according to the comparison result, the ambient light fluctuation result is obtained according to the fluctuation amplitude and change trend, and the ambient light fluctuation result includes the illumination intensity fluctuation range, the abnormal fluctuation frequency and the key area illumination stability.

[0044] By comparing the real-time light intensity data with the initial light intensity data, the fluctuation range and trend of the ambient light in intensity, distribution and spectral composition can be comprehensively analyzed, and the fluctuation results of the ambient light such as the fluctuation range of the illumination intensity, the frequency of abnormal fluctuations and the illumination stability of the key area can be determined. The dynamic change characteristics of the illumination in the production environment can be intuitively reflected, and detailed ambient light change parameters are provided for subsequent quantitative calculation of the laser power adjustment amount, so that the compensation module can adjust the laser power to offset the ambient light interference and ensure the accuracy of the laser detection, and the entire monitoring system can better adapt to the complex and changeable production environment.

[0045] The logic for establishing a dynamic compensation relationship between the light intensity data and the laser power adjustment amount according to the ambient light fluctuation results includes: According to the ambient light fluctuation results, the laser power adjustment amount is obtained by using a weight distribution rule, the weight distribution rule includes setting a basic weight, quantifying the ambient light fluctuation data and calculating the adjustment amount, and adjusting the laser power according to the laser power adjustment amount.

[0046] The basic weight is used to set the weight proportion of the fluctuation range of the illumination intensity, as the first weight proportion, the weight proportion of the frequency of abnormal fluctuations, as the second weight proportion, and the weight proportion of the illumination stability of the key area, as the third weight proportion.

[0047] Quantifying the ambient light fluctuation data is used to convert the fluctuation range of the illumination intensity into a relative value as a first fluctuation quantization value, convert the frequency of abnormal fluctuations into a frequency coefficient as a second fluctuation quantization value, and convert the illumination stability of the key area into a deviation coefficient as a third fluctuation quantization value.

[0048] The calculation of the adjustment amount is used to multiply the first weight proportion by the first fluctuation quantization value to obtain a first adjustment amount, multiply the second weight proportion by the second fluctuation quantization value to obtain a second adjustment amount, multiply the third weight proportion by the third fluctuation quantization value to obtain a third adjustment amount, and add the first adjustment amount, the second adjustment amount and the third adjustment amount to obtain a fourth adjustment amount. The fourth adjustment amount is used as the laser power adjustment amount.

[0049] By considering the weights of different fluctuation factors and performing quantitative calculation, the system can realize more intelligent and adaptive power compensation, effectively offset the ambient light interference, and ensure the stability of the detection signal and the accuracy of the detection result.

[0050] The recognition module is used to trigger the scanning process when the glass product enters the detection area, and the laser scattering instrument scans the glass product according to the preset frequency and preset range, and identifies the impurities in the glass product through the light intensity attenuation value of the laser detection, and records the characteristic parameters of the impurities.

[0051] The characteristic parameters include the position of the impurity, the size of the impurity, the number of the impurity, the shape of the impurity, and the scattering intensity of the impurity to the laser.

[0052] When the glass product reaches the designated position, the recognition module automatically triggers the preset scanning process. The laser scattering instrument irradiates and detects the glass product according to the preset frequency and scanning range. By analyzing the light intensity attenuation value of the laser during penetration of the glass, the system can identify the impurities inside or on the surface of the glass. Once the impurities are detected, the system not only sends an identification signal, but also records the characteristic parameters of the impurities in detail, realizing quantitative detection and recording of internal and surface defects of the glass product, and providing accurate data support for subsequent rejection.

[0053] The logic of identifying impurities in the glass product by the light intensity attenuation value detected by the laser includes: The laser of a preset power is emitted to the glass product detection position, and the current light intensity attenuation value of the laser scattering instrument receiving device is detected. The current light intensity attenuation value is compared with the light intensity attenuation value without impurities. If the current light intensity attenuation value exceeds the preset range of the light intensity attenuation value without impurities, it is determined that there are impurities in the glass product detection position.

[0054] This judgment method based on the difference in light intensity attenuation directly relates to the scattering effect produced by the interaction of laser and impurities, which not only conforms to the detection principle of the laser scattering instrument, but also ensures the objectivity and accuracy of impurity recognition through quantitative light intensity data, providing a basic recognition result for subsequent recording of impurity characteristic parameters and judgment of product eligibility according to threshold parameters, which is a key link to realize precise monitoring of glass product quality.

[0055] The recording module is used to reject unqualified glass products according to the early warning threshold parameter and the rejection threshold parameter, and record the processing result of the unqualified glass products. The processing result includes processing time and processing position. The processing result is bound with the production batch information of the unqualified glass products and recorded.

[0056] The unqualified glass products are accurately rejected to ensure that the products not meeting the quality standards do not flow into the subsequent production links, and the product quality is guaranteed from the terminal link, realizing immediate processing of unqualified products and establishing full-chain traceability from the production source to the final processing, providing reliable data support for subsequent quality analysis, process improvement, and recall management of problem products.

[0057] The logic of the recording module for rejecting unqualified glass products according to the early warning threshold parameter and the rejection threshold parameter includes: The impurity light intensity attenuation value detected by the laser is received, and the impurity light intensity attenuation value is compared with the early warning threshold parameter and the rejection threshold parameter.

[0058] If the impurity light intensity attenuation value reaches the early warning threshold parameter, only the impurity information of the glass product is recorded and a prompt signal is sent out.

[0059] If the impurity light intensity attenuation value reaches or exceeds the rejection threshold parameter, the rejection mechanism is triggered immediately, and the glass product is separated from the glass production line.

[0060] The quality of the glass product is graded and controlled, which can not only find problems early and prompt, but also accurately reject unqualified glass products, and provides clear operation trigger conditions for the result record of the recording module, ensures that the entire unqualified product processing process is standardized and efficient, and further strengthens the accurate control of production quality.

[0061] The present application provides an intelligent monitoring system for household appliance glass production, which acquires initial parameters through a collection module, eliminates the influence of mechanical vibration and light interference through the three-dimensional coordinate transformation algorithm and optical filtering technology of a calibration module, solves the problem that the detection accuracy of traditional monitoring is easily affected by environmental interference, an adaptive light intensity compensation mechanism established by a compensation module can dynamically respond to complex light changes and ensure the accuracy of impurity identification, the system is suitable for high-speed continuous production, an identification module records the characteristic parameters of impurities in an all-round way and provides detailed data support for process optimization, dynamic early warning thresholds and rejection thresholds determined by the calibration module are combined with automatic processing of unqualified products and binding and tracing of production batches realized by the recording module, the accuracy of early warning and rejection and the efficiency of quality tracing are improved, the system can be efficiently connected with existing intelligent management systems, meets the fine control requirements of high-precision and high-quality production, and provides a powerful guarantee for efficient, stable and high-quality operation of household appliance glass production.

[0062] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (or computer- readable storage media) having computer-usable program code embodied in the medium. The medium can be any available storage media that can be accessed by a computer. By way of example, and not limitation, such computer-usable storage media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other storage medium(s) that can be used to carry or store desired computer program code in the form of instructions or data structures and that can be accessed by a computer. Also, the present application can be embodied in a computer program product that can be traded as goods or merchandise, through the storage medium described above or any other suitable medium. Accordingly, the computer medium can be any entity or device containing, or Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks

[0063] It should be noted that the above-mentioned embodiments are only used to illustrate but not to limit the technical solutions of the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application, and they should be covered in the scope of the claims of the present application.

Claims

1. An intelligent monitoring system for household appliance glass production, characterized in that: Including acquisition module, calibration module, compensation module, identification module and recording module: The acquisition module is used to obtain initial parameters; The calibration module is used to calibrate the initial parameters and determine the warning threshold parameters and the rejection threshold parameters; The compensation module is used to establish an adaptive light intensity compensation mechanism; The identification module is used to identify impurities in the glass product and record characteristic parameters of the impurities; The recording module is used to reject unqualified glass products according to the early warning threshold parameter and the rejection threshold parameter, and record the processing results of the unqualified glass products.

2. The intelligent monitoring system for household appliance glass production according to claim 1, characterized in that: The acquisition module is used to deploy a laser scatterer in the inspection area of ​​the glass production line, and respectively arrange a laser scatterer transmitter and a laser scatterer receiver above and below the transmission path to form a vertical optical path. The laser parameters of the laser scatterer are set according to production requirements, including glass type, impurity detection accuracy, and glass thickness. The laser parameters include laser wavelength, laser power, and laser focus point. Initial parameters are also obtained, including initial optical path reference data of the laser scatterer and initial light intensity data of the ambient light sensor. The initial optical path reference data includes the propagation trajectory of the laser in the glass sample, the initial power value of the laser emission end and the divergence angle of the laser beam in the environment. The initial light intensity data includes the initial spectral component ratio of the ambient light, the light intensity value when there is no laser and no additional light source in the detection area, and the light distribution data of the laser scattering instrument receiving device.

3. The intelligent monitoring system for household appliance glass production according to claim 1, characterized in that: The calibration module is used to calibrate the initial parameters according to the quality standard of the glass, wherein the calibration includes optical path data calibration and ambient light intensity data calibration, and determine the warning threshold parameter and the rejection threshold parameter; The quality standards include the size range of impurities allowed on the glass surface and inside, the quantity limit of impurities, and the threshold range of light intensity attenuation caused by impurities; The warning threshold parameter is used to send a prompt signal to remind the operator to pay attention to the glass that may be close to the qualified critical value in the current detection area; The rejection threshold parameter is used to trigger a rejection mechanism to separate the glass that meets the rejection threshold parameter from the glass production line; The optical path data calibration is used to adjust the position parameters of the laser scattering instrument transmitting device and the laser scattering instrument receiving device in real time through a three-dimensional coordinate transformation algorithm, eliminate the optical path deviation caused by mechanical vibration and installation error, and adjust the laser power according to the glass thickness and material properties to offset the energy loss during the optical path propagation process; The ambient light intensity data calibration is used to obtain specific wavelength components in the ambient light through optical filtering technology, eliminate interfering light that overlaps with the detection laser wavelength, and set multiple light intensity collection points in the detection area to compensate for detection errors caused by changes in production line lighting.

4. The intelligent monitoring system for household appliance glass production according to claim 3, characterized in that: The logic for determining the warning threshold parameters and the rejection threshold parameters includes: receiving a light intensity attenuation value of an impurity detected by laser detection, and determining that the light intensity attenuation value is between a first threshold value and a second threshold value within a quality standard as a first level, and setting the light intensity attenuation value as a warning threshold parameter; When the light intensity attenuation value is greater than or equal to the second threshold value within the quality standard, it is determined to be the second level, and the light intensity attenuation value is set as the rejection threshold parameter.

5. The intelligent monitoring system for household appliance glass production according to claim 1, characterized in that: The compensation module is used to establish an adaptive light intensity compensation mechanism, which is used to continuously detect the ambient light sensor and collect real-time light intensity data of the ambient light sensor, analyze the ambient light fluctuation according to the real-time light intensity data, obtain the ambient light fluctuation result, and establish a dynamic compensation relationship between the light intensity data and the laser power adjustment amount according to the ambient light fluctuation result; The logic for obtaining the ambient light fluctuation result includes: Collect real-time light intensity data of the ambient light sensor in different detection time periods and different monitoring points, the different monitoring points including the periphery of the laser propagation path and near the laser scattering instrument receiving device, compare the real-time light intensity data with the initial light intensity data, and analyze the fluctuation amplitude and change trend of the ambient light in intensity, distribution and spectral composition based on the comparison results, and obtain the ambient light fluctuation results based on the fluctuation amplitude and change trend, the ambient light fluctuation results including the light intensity fluctuation range, abnormal fluctuation frequency and light stability in key areas.

6. The intelligent monitoring system for household appliance glass production according to claim 5, characterized in that: The logic of establishing a dynamic compensation relationship between light intensity data and laser power adjustment amount according to the ambient light fluctuation result includes: According to the ambient light fluctuation result, a laser power adjustment amount is obtained using a weight allocation rule, wherein the weight allocation rule includes setting a basic weight, quantifying the ambient light fluctuation data, and calculating an adjustment amount, and adjusting the laser power according to the laser power adjustment amount; The set basic weight is used to set the weight ratio of the light intensity fluctuation range as the first weight ratio, set the weight ratio of the abnormal fluctuation frequency as the second weight ratio, and set the weight ratio of the light stability in the key area as the third weight ratio; The quantified ambient light fluctuation data is used to convert the light intensity fluctuation range into a relative value as a first fluctuation quantization value, convert the abnormal fluctuation frequency into a frequency coefficient as a second fluctuation quantization value, and convert the key area light stability into a deviation coefficient as a third fluctuation quantization value; The calculated adjustment amount is used to multiply the first weight ratio by the first fluctuation quantization value to obtain the first adjustment amount, multiply the second weight ratio by the second fluctuation quantization value to obtain the second adjustment amount, multiply the third weight ratio by the third fluctuation quantization value to obtain the third adjustment amount, and add the first adjustment amount, the second adjustment amount and the third adjustment amount to obtain the fourth adjustment amount, and use the fourth adjustment amount as the laser power adjustment amount.

7. The intelligent monitoring system for household appliance glass production according to claim 1, characterized in that: The identification module is used to trigger a scanning process when a glass product enters the detection area. The laser scattering instrument scans the glass product at a preset frequency and within a preset range, identifies impurities in the glass product through the light intensity attenuation value detected by the laser, and records the characteristic parameters of the impurities. The characteristic parameters include the position of the impurities, the size of the impurities, the number of the impurities, the shape of the impurities and the scattering intensity of the impurities on the laser.

8. The intelligent monitoring system for household appliance glass production according to claim 7, characterized in that: The logic of identifying impurities in glass products by using the light intensity attenuation value detected by laser includes: A laser of preset power is emitted to the glass product detection position, and the current light intensity attenuation value of the laser scattering instrument receiving device is detected. The current light intensity attenuation value is compared with the light intensity attenuation value when there are no impurities. If the current light intensity attenuation value exceeds the preset range of the light intensity attenuation value when there are no impurities, it is determined that impurities exist at the glass product detection position.

9. The intelligent monitoring system for household appliance glass production according to claim 1, characterized in that: The recording module is used to reject unqualified glass products based on the warning threshold parameters and the rejection threshold parameters, and record the processing results of the unqualified glass products, the processing results including the processing time and processing location, and bind the processing results with the production batch information of the unqualified glass products and record them.

10. The intelligent monitoring system for household appliance glass production according to claim 9, characterized in that: The logic of the recording module for rejecting unqualified glass products according to the warning threshold parameters and the rejection threshold parameters includes: receiving an impurity light intensity attenuation value detected by laser, and comparing the impurity light intensity attenuation value with a warning threshold parameter and a rejection threshold parameter; If the impurity light intensity attenuation value reaches the warning threshold parameter, only the impurity information of the glass product is recorded and a prompt signal is issued; If the impurity light intensity attenuation value reaches or exceeds the rejection threshold parameter, the rejection mechanism is immediately triggered to separate the glass product from the glass production line.

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