A product quality calculation method, device, system and storage medium

Abstract

The application discloses an algorithm correction method, device, system and storage medium, which are used for optimizing a product quality online detection algorithm and improving the accuracy of online detection. The method comprises the following steps: in the process of detecting the product quality value according to a preset algorithm, acquiring a first offline value of a key impurity component of the product according to a first preset time interval, and acquiring a second offline value of all impurity components of the product according to a second preset time interval; correcting a first coefficient in the preset algorithm according to the first offline value; and correcting a second coefficient in the preset algorithm according to the second offline value. By using the scheme provided in the application, the coefficients of the online algorithm are corrected by more accurate offline values, the algorithm is optimized, and the accuracy of online detection is improved.

Description

Technical Field

[0001] This application relates to the field of online detection technology for chemical products, and in particular to a product quality calculation method, apparatus, system and storage medium. Background Technology

[0002] Currently, there are two methods for quality inspection in chemical production processes: offline sampling and analysis, and online detection and analysis. Offline sampling and analysis requires a significant amount of time but yields relatively accurate results; online analysis has a shorter measurement time but lower accuracy compared to offline analysis.

[0003] In many chemical production processes, high efficiency in quality inspection is required. Therefore, online analyzers are often used for real-time detection and analysis. However, this approach cannot guarantee the accuracy of product testing. Thus, providing a product quality calculation method to optimize online product quality detection algorithms and improve the accuracy of online detection is a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a product quality calculation method, apparatus, system, and storage medium to optimize the online product quality detection algorithm and improve the accuracy of online detection.

[0005] This application provides a product quality calculation method, including:

[0006] During the online detection of product quality values ​​according to a preset algorithm, the first offline value of key impurity components of the product is obtained according to a first preset time interval, and the second offline value of all impurity components of the product is obtained according to a second preset time interval, wherein the first preset time interval is less than the second preset time interval.

[0007] The first coefficient in the preset algorithm is corrected based on the first offline value;

[0008] The second coefficient in the preset algorithm is corrected based on the second offline value.

[0009] The beneficial effects of this embodiment are as follows: During the online detection of product quality values ​​according to a preset algorithm, offline values ​​corresponding to product impurity components are obtained. Then, the coefficients in the preset algorithm are corrected based on the offline values, thereby optimizing the algorithm and improving the accuracy of online detection by using more accurate offline values ​​to correct the coefficients of the online algorithm. Secondly, the first offline value is the offline value of the key impurity components of the product, and the key impurity components can ensure the optimization effect of the corrected first parameter. At the same time, since it is not necessary to obtain the components of all impurities, the acquisition speed of the first offline value is also improved.

[0010] In one embodiment, the online detection of product quality values ​​according to a preset algorithm includes:

[0011] Calculate the product quality value using the following formula:

[0012] ;

[0013] Where y1 is the product quality value; b is the first coefficient; a The second coefficient; x1 and x n This refers to the content of key impurity components.

[0014] In one embodiment, obtaining the first offline value of a key impurity component of the product according to a first preset time interval includes:

[0015] When the time since the last acquisition of the first offline value of the key impurity component of the product reaches the first preset time interval, the first offline value of the key impurity component of the product sent by the preset terminal is received.

[0016] The second offline values ​​of all impurity components of the product are obtained according to the second preset time interval, including:

[0017] When the time since the last acquisition of the second offline value of all impurity components of the product reaches a second preset time interval, the second offline value of all impurity components of the product sent by the preset terminal is received, wherein the preset terminal is the terminal corresponding to the mechanism that calculates the first offline value and / or the second offline value.

[0018] In one embodiment, correcting the first coefficient in the preset algorithm based on the first offline value includes:

[0019] Substitute the first offline value into the following formula to correct the first coefficient in the preset algorithm:

[0020] ;

[0021] in, The coefficients after b are updated; and The first offline value for the key impurity component of the product; and This refers to the online detection result of the content of key impurity components corresponding to the sampling time of the first offline value.

[0022] In one embodiment, correcting the second coefficient in the preset algorithm based on the second offline value includes:

[0023] Substitute the second offline value into the following formula to correct the second coefficient in the preset algorithm:

[0024] ;

[0025] in, for a Updated coefficients; , ..., This is the second offline value for all impurity components in the product; and The online detection result of the content of key impurity components corresponding to the sampling time of the second offline value; x 1 and x n This is the online detection result of the content of key impurity components at the current moment.

[0026] In one embodiment, the method further includes:

[0027] After correcting the first coefficient in the preset algorithm based on the first offline value, the product quality value is calculated according to the following formula:

[0028] ;

[0029] in, The first coefficient is corrected as follows The product quality value calculated subsequently; a The second coefficient before correction; The first coefficient after correction; and This is the online detection result of the content of key impurity components at the current moment.

[0030] In one embodiment, the method further includes:

[0031] After correcting the second coefficient in the preset algorithm based on the second offline value, the product quality value is calculated according to the following formula:

[0032] ;

[0033] in, This is the product quality value calculated after correcting for both the first and second coefficients; This is the corrected second coefficient; The first coefficient after correction; and This is the online detection result of the content of key impurity components at the current moment.

[0034] This application also provides a product quality calculation apparatus for implementing the product quality calculation method described in any of the above embodiments, comprising:

[0035] The online value calculation module is used to detect product quality values ​​online according to a preset algorithm;

[0036] A short-cycle verification module is used to correct the first coefficient in the preset algorithm based on the first offline value;

[0037] The long-period verification module is used to correct the second coefficient in the preset algorithm based on the second offline value.

[0038] This application also provides a product quality calculation system, including:

[0039] At least one processor; and,

[0040] A memory communicatively connected to the at least one processor; wherein,

[0041] The memory stores instructions that can be executed by the processor, which are executed by the at least one processor to implement the product quality calculation method described in any of the above embodiments.

[0042] This application also provides a computer-readable storage medium, which, when the instructions in the storage medium are executed by a processor corresponding to the product quality calculation system, enables the product quality calculation system to implement the product quality calculation method described in any of the above embodiments.

[0043] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0044] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the present application and form part of the specification. They are used together with the embodiments of the present application to explain the application and do not constitute a limitation thereof. In the drawings:

[0046] Figure 1 This is a flowchart of a product quality calculation method in one embodiment of this application;

[0047] Figure 2 This is a schematic diagram of a product quality calculation apparatus for implementing the product quality calculation method described in any of the above embodiments.

[0048] Figure 3 This is a schematic diagram of the hardware structure of a product quality calculation system according to this application. Detailed Implementation

[0049] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application.

[0050] Figure 1 This is a flowchart of a product quality calculation method according to an embodiment of this application, such as... Figure 1 As shown, the method can be implemented as follows: S11-S13:

[0051] In step S11, during the online detection of product quality values ​​according to a preset algorithm, the first offline value of key impurity components of the product is obtained according to a first preset time interval, and the second offline value of all impurity components of the product is obtained according to a second preset time interval, wherein the first preset time interval is less than the second preset time interval.

[0052] In step S12, the first coefficient in the preset algorithm is corrected based on the first offline value;

[0053] In step S13, the second coefficient in the preset algorithm is corrected based on the second offline value.

[0054] In this application, the product quality value is first detected online according to a preset algorithm, a process typically implemented using an online analyzer. The online detection process can be carried out as follows:

[0055] Calculate the product quality value using the following formula:

[0056] Formula (1)

[0057] Where y1 is the product quality value; b is the first coefficient; a The second coefficient; x1 and x n This refers to the content of key impurity components.

[0058] In this process, according to a first preset time interval, offline chromatography is used to periodically analyze relevant samples to obtain the first offline value of the key impurity component of the product. Simultaneously, according to a second preset time interval, the second offline values ​​of all impurity components of the product are obtained. Specifically, obtaining the first offline value of the key impurity component according to the first preset time interval includes: receiving the first offline value of the key impurity component sent by a preset terminal when the time since the last acquisition of the first offline value of the key impurity component reaches the first preset time interval. Obtaining the second offline value of all impurity components according to the second preset time interval includes: receiving the second offline value of all impurity components sent by a preset terminal when the time since the last acquisition of the second offline value of all impurity components reaches the second preset time interval, wherein the preset terminal is the terminal corresponding to the organization that calculates the first offline value and / or the second offline value. Since the acquisition period for the offline values ​​of all impurity components is relatively long, the second preset time interval for obtaining the second offline value is longer than the first preset time interval for obtaining the first offline value. That is, this application is divided into short-term correction and long-term correction. Short-term correction is the process of correcting the first coefficient using the first offline value obtained through the first preset time interval, while long-term correction is the process of correcting the second coefficient using the second offline value obtained through the second preset time interval. For example, the first preset time interval can be 24 hours, and the second preset time interval can be 1440 hours.

[0059] After obtaining the first offline value, the first coefficient in the preset algorithm can be corrected based on the first offline value;

[0060] Specifically, assuming that offline chromatography yields the offline values ​​of key impurity components... , The corresponding online analyzer detected the contents of key impurity components at the following times: , At the current moment, the online analyzer detects the contents of key impurity components as x1 and x2, respectively. n The product quality value calculated solely based on the key impurity components is... Then the new first coefficient is:

[0061] Formula (2)

[0062] in, The coefficients after b are updated; and The first offline value for the key impurity component of the product; and This refers to the online detection result of the content of key impurity components corresponding to the sampling time of the first offline value.

[0063] The formula for calculating the product quality value based on the updated first coefficient is as follows:

[0064] Formula (3)

[0065] in, The first coefficient is corrected as follows The product quality value calculated subsequently; a The second coefficient before correction; The first coefficient after correction; and This is the online detection result of the content of key impurity components at the current moment.

[0066] The process of correcting the second coefficient in the preset algorithm based on the second offline value is as follows:

[0067] Substitute the second offline value into the following formula to correct the second coefficient in the preset algorithm:

[0068] ; Formula (4)

[0069] in, for a Updated coefficients; , ..., This is the second offline value for all impurity components in the product; and The online detection result of the content of key impurity components corresponding to the sampling time of the second offline value; x 1 and x n This is the online detection result of the content of key impurity components at the current moment.

[0070] Simultaneously, after correcting the second coefficient in the preset algorithm based on the second offline value, the product quality value is calculated according to the following formula:

[0071] ; Formula (5)

[0072] in, This is the product quality value calculated after correcting for both the first and second coefficients; This is the corrected second coefficient; The first coefficient after correction; and This is the online detection result of the content of key impurity components at the current moment.

[0073] The following section uses online chromatographic analysis of EDC content in EDC products as an example to illustrate the product quality calculation method provided in this application in detail:

[0074] EDC is an organic compound with the chemical formula C8H. 17 N3, or 1-ethyl-(3-dimethylaminopropyl)carbodiimide, is a water-soluble carbodiimide. Assume the impurities in EDC are carbon tetrachloride, trichloroethane, benzene, 1,1-dichloroethane, chloroprene, vinyl chloride, and chloroethane, with carbon tetrachloride, trichloroethane, and benzene being the main impurities.

[0075] Let the initial first coefficient be... The coefficient is 0.98, and the second coefficient b is 0.2; the contents of the key impurity components carbon tetrachloride, trichloroethane, and benzene measured online are 0.2%, 0.1%, and 0.1%, respectively. The detection data is transmitted to the online analysis and calculation module, and the analytical value calculated based only on the key impurity components is obtained according to the above formula (1):

[0076] y1=0.98×(1-0.002-0.001-0.001)+0.02=0.99608;

[0077] Assuming a short-term calibration period of 24 hours, offline chromatography is used to periodically analyze relevant samples to obtain the offline values ​​of key impurity components: carbon tetrachloride, trichloroethane, and benzene content are 0.1%, 0.1%, and 0.1%, respectively. The corresponding online analysis values ​​are 0.15%, 0.1%, and 0.1%. This value is transmitted to the short-term calibration module, and the calculation formula in the online analysis calculation module is corrected according to a certain method. Then, the correction value of parameter b is calculated according to the above formula (2). as follows:

[0078] b'=0.02-0.98×(0.001-0.0015+0.001-0.001+0.001-0.001)=0.02049.

[0079] After updating the first coefficient, the product quality value is calculated according to the above formula (3):

[0080] y2=0.98×(1-0.002-0.001-0.001)+0.02049=0.99657.

[0081] Assuming a long-term calibration period of 1440h, offline chromatography is used to periodically analyze relevant samples to obtain the offline values ​​of all impurity components: carbon tetrachloride, trichloroethane, benzene, 1,1-dichloroethane, chloroprene, vinyl chloride, and chloroethane are 0.14%, 0.1%, 0.1%, 0.02%, 0.01%, 0.03%, and 0.02%, respectively. The corresponding online analysis values ​​of key components are 0.13%, 0.1%, and 0.1%. This value is transmitted to the long-term calibration module, and the calculation formula in the online analysis calculation module is corrected according to a certain method. Then, the second coefficient is calculated according to formula (4). Correction value :

[0082] ;

[0083] After correcting for both the first and second coefficients, the product quality value is calculated according to formula (5). as follows:

[0084] y3=0.9785×(1-0.002-0.001-0.001)+0.02049=0.995076.

[0085] The beneficial effects of this embodiment are as follows: During the online detection of product quality values ​​according to a preset algorithm, offline values ​​corresponding to product impurity components are obtained. Then, the coefficients in the preset algorithm are corrected based on the offline values, thereby optimizing the algorithm and improving the accuracy of online detection by using more accurate offline values ​​to correct the coefficients of the online algorithm. Secondly, the first offline value is the offline value of the key impurity components of the product, and the key impurity components can ensure the optimization effect of the corrected first parameter. At the same time, since it is not necessary to obtain the components of all impurities, the acquisition speed of the first offline value is also improved.

[0086] In one embodiment, step S11 above, which involves online detection of the product quality value according to a preset algorithm, can be implemented as follows:

[0087] Calculate the product quality value using the following formula:

[0088] ;

[0089] Where y1 is the product quality value; b is the first coefficient; a The second coefficient; x1 and x n This refers to the content of key impurity components.

[0090] In one embodiment, obtaining the first offline value of the key impurity component of the product according to the first preset time interval in step S11 above can be implemented by the following steps:

[0091] When the time since the last acquisition of the first offline value of the key impurity component of the product reaches the first preset time interval, the first offline value of the key impurity component of the product sent by the preset terminal is received.

[0092] In step S11 above, obtaining the second offline value of all impurity components of the product according to the second preset time interval can be implemented as follows:

[0093] The executing entity of this application can be a computer or a terminal device. When the time since the last acquisition of the second offline value of all impurity components of the product reaches a second preset time interval, the second offline value of all impurity components of the product sent by a preset terminal is received. The preset terminal is the terminal corresponding to the institution that calculates the first offline value and / or the second offline value. Each time the first or second offline value is acquired, the time corresponding to the offline value is recorded. It should be noted that before acquiring the offline value, the product needs to be sampled. The sampled product is then sent to an institution, such as a laboratory, with offline value calculation capabilities for calculation. After the offline value is calculated, it can be sent to the executing entity of this application through a terminal device in the institution, or to the computer or terminal of relevant personnel through a terminal device in the institution. The personnel then input the specific offline value into the executing entity of this application. Therefore, the time corresponding to the recorded offline value refers to the sampling time. During sampling, the sampling time is determined through sensor monitoring, instruction reception, etc. Additionally, the online detection value corresponding to the sampling time is also recorded. When the terminal device in the institution sends the offline value, it also sends the product sampling time corresponding to the offline value to the executing entity.

[0094] The main methods for calculating offline values ​​include high-performance liquid chromatography (HPLC). For example, in HPLC, the mobile phase corresponding to the product is pumped into a chromatographic column packed with a stationary phase. After the components are separated in the column, they enter a detector for detection, thereby obtaining the offline values ​​corresponding to each impurity in the product. In addition, offline values ​​can also be obtained using methods such as ultraviolet absorption spectroscopy, thin-layer chromatography, gas chromatography, and atomic absorption spectroscopy. The specific implementation processes will not be elaborated here.

[0095] In one embodiment, step S12 above can be implemented as follows:

[0096] Substitute the first offline value into the following formula to correct the first coefficient in the preset algorithm:

[0097] ;

[0098] in, The coefficients after b are updated; and The first offline value for the key impurity component of the product; and This refers to the online detection result of the content of key impurity components corresponding to the sampling time of the first offline value.

[0099] In one embodiment, step S13 above can be implemented as follows:

[0100] Substitute the second offline value into the following formula to correct the second coefficient in the preset algorithm:

[0101] ;

[0102] in, for a Updated coefficients; , ..., This is the second offline value for all impurity components in the product; and The online detection result of the content of key impurity components corresponding to the sampling time of the second offline value; x 1 and x n This is the online detection result of the content of key impurity components at the current moment.

[0103] In one embodiment, the method may also be implemented as follows:

[0104] After correcting the first coefficient in the preset algorithm based on the first offline value, the product quality value is calculated according to the following formula:

[0105] ;

[0106] in, The first coefficient is corrected as follows The product quality value calculated subsequently; a The second coefficient before correction; The first coefficient after correction; and This is the online detection result of the content of key impurity components at the current moment.

[0107] In one embodiment, the method may also be implemented as follows:

[0108] After correcting the second coefficient in the preset algorithm based on the second offline value, the product quality value is calculated according to the following formula:

[0109] ;

[0110] in, This is the product quality value calculated after correcting for both the first and second coefficients; This is the corrected second coefficient; The first coefficient after correction; and This is the online detection result of the content of key impurity components at the current moment.

[0111] Figure 2 This is a schematic diagram of the structure of a product quality calculation device for implementing the product quality calculation method described in any of the above embodiments, comprising:

[0112] The online value calculation module is used to detect product quality values ​​online according to a preset algorithm;

[0113] A short-cycle verification module is used to correct the first coefficient in the preset algorithm based on the first offline value;

[0114] The long-period verification module is used to correct the second coefficient in the preset algorithm based on the second offline value.

[0115] Figure 3 This is a schematic diagram of the hardware structure of a product quality calculation system 300 according to this application, including:

[0116] At least one processor 320; and,

[0117] Memory 304 communicatively connected to the at least one processor; wherein,

[0118] The memory stores instructions that can be executed by the processor, which are executed by the at least one processor to implement the product quality calculation method described in any of the above embodiments.

[0119] Reference Figure 3 The product quality calculation system 300 may include one or more of the following components: processing component 302, memory 304, power supply component 306, multimedia component 308, audio component 310, input / output (I / O) interface 312, sensor component 314, and communication component 316.

[0120] Processing component 302 typically controls the overall operation of the product quality calculation system 300. Processing component 302 may include one or more processors 320 to execute instructions to complete all or part of the steps of the methods described above. Furthermore, processing component 302 may include one or more modules to facilitate interaction between processing component 302 and other components. For example, processing component 302 may include a multimedia module to facilitate interaction between multimedia component 308 and processing component 302.

[0121] Memory 304 is configured to store various types of data to support the operation of the product quality calculation system 300. Examples of this data include instructions for any application or method operating on the product quality calculation system 300, such as text, images, videos, etc. Memory 304 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0122] Power supply component 306 provides power to various components of product quality calculation system 300. Power supply component 306 may include power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to product quality calculation system 300.

[0123] Multimedia component 308 includes a screen that provides an output interface between product quality calculation system 300 and user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 308 may also include a front-facing camera and / or a rear-facing camera. When product quality calculation system 300 is in an operating mode, such as shooting mode or video mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0124] Audio component 310 is configured to output and / or input audio signals. For example, audio component 310 includes a microphone (MIC) configured to receive external audio signals when the product quality calculation system 300 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 304 or transmitted via communication component 316. In some embodiments, audio component 310 also includes a speaker for outputting audio signals.

[0125] I / O interface 312 provides an interface between processing component 302 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, start buttons, and lock buttons.

[0126] Sensor assembly 314 includes one or more sensors for providing status assessments of various aspects of the product quality calculation system 300. For example, sensor assembly 314 may include a sound sensor. Additionally, sensor assembly 314 may detect the on / off state of the product quality calculation system 300, the relative positioning of components (e.g., the display and keypad of the product quality calculation system 300), changes in the position of the product quality calculation system 300 or a component of the product quality calculation system 300, the presence or absence of user contact with the product quality calculation system 300, the orientation or acceleration / deceleration of the product quality calculation system 300, and temperature changes of the product quality calculation system 300. Sensor assembly 314 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 314 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 314 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0127] Communication component 316 is configured to enable product quality computing system 300 to provide wired or wireless communication capabilities with other devices and cloud platforms. Product quality computing system 300 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 316 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 316 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0128] In an exemplary embodiment, the product quality calculation system 300 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the product quality calculation method described above.

[0129] This application also provides a computer-readable storage medium, which, when the instructions in the storage medium are executed by a processor corresponding to the product quality calculation system, enables the product quality calculation system to implement the product quality calculation method described in any of the above embodiments.

[0130] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0131] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0132] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0134] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for calculating product quality, characterized in that, include: During the online detection of product quality values ​​according to a preset algorithm, the first offline value of key impurity components of the product is obtained according to a first preset time interval, and the second offline value of all impurity components of the product is obtained according to a second preset time interval, wherein the first preset time interval is less than the second preset time interval. The first coefficient in the preset algorithm is corrected based on the first offline value; The second coefficient in the preset algorithm is corrected based on the second offline value; After correcting for both the first and second coefficients, calculate the product quality value; The online detection of product quality values ​​according to a preset algorithm includes: Calculate the product quality value using the following formula: ； Where y1 is the product quality value; b is the first coefficient; a The second coefficient; x1, ..., x m Content of key impurity components; The step of correcting the first coefficient in the preset algorithm based on the first offline value includes: Substitute the first offline value into the following formula to correct the first coefficient in the preset algorithm: ； in, The coefficients after b are updated; … The first offline value for the key impurity component of the product; … The online detection result of the content of key impurity components corresponding to the sampling time of the first offline value; The step of correcting the second coefficient in the preset algorithm based on the second offline value includes: Substitute the second offline value into the following formula to correct the second coefficient in the preset algorithm: ； in, for a Updated coefficients; , ..., The second offline value for all impurity components of the product, where m < n; , ..., The online detection result of the content of key impurity components corresponding to the sampling time of the second offline value; x1, ..., x m This is the online detection result of the content of key impurity components at the current moment.

2. The method as described in claim 1, characterized in that, The first offline value of the key impurity component of the product is obtained according to the first preset time interval, including: When the time since the last acquisition of the first offline value of the key impurity component of the product reaches the first preset time interval, the first offline value of the key impurity component of the product sent by the preset terminal is received. The second offline values ​​of all impurity components of the product are obtained according to the second preset time interval, including: When the time since the last acquisition of the second offline value of all impurity components of the product reaches a second preset time interval, the second offline value of all impurity components of the product sent by the preset terminal is received, wherein the preset terminal is the terminal corresponding to the mechanism that calculates the first offline value and / or the second offline value.

3. The method as described in claim 1, characterized in that, The method further includes: After correcting the first coefficient in the preset algorithm based on the first offline value, the product quality value is calculated according to the following formula: ； Where y2 is the first coefficient correction. The product quality value calculated subsequently; a The second coefficient before correction; The first coefficient after correction; x 1… x m This is the online detection result of the content of key impurity components at the current moment.

4. The method as described in claim 1, characterized in that, The method further includes: After correcting the second coefficient in the preset algorithm based on the second offline value, the product quality value is calculated according to the following formula: ； Where y3 is the product quality value calculated after correcting for both the first and second coefficients; This is the corrected second coefficient; The first coefficient after correction; x 1… x m This is the online detection result of the content of key impurity components at the current moment.

5. A product quality calculation apparatus for implementing the method of any one of claims 1-4, characterized in that, include: The online value calculation module is used to detect product quality values ​​online according to a preset algorithm; A short-cycle verification module is used to correct the first coefficient in the preset algorithm based on the first offline value; The long-period verification module is used to correct the second coefficient in the preset algorithm based on the second offline value.

6. A product quality calculation system, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the processor, the instructions being executed by the at least one processor to implement the product quality calculation method as described in any one of claims 1-4.

7. A computer-calibrated storage medium, characterized in that, When the instructions in the storage medium are executed by the processor corresponding to the product quality calculation system, the product quality calculation system is able to implement the product quality calculation method as described in any one of claims 1-4.

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