Coal raw material quality detection information display method, device, equipment and medium

Abstract

Embodiments of the present disclosure disclose a coal raw material quality detection information display method, device, equipment and medium. A specific embodiment of the method includes: in response to detecting a selection operation on a coal raw material quality detection control, displaying a coal raw material quality detection page on a current interface, wherein the coal raw material quality detection page displays a raw material entry control, a raw material query control, a quality prediction control and a data analysis control; in response to detecting a selection operation on the raw material entry control, displaying a raw material entry page on the current interface; in response to detecting a selection operation on the raw material query control, displaying a raw material query page on the current interface; in response to detecting a selection operation on the quality prediction control, displaying a quality prediction page on the current interface; and in response to detecting a selection operation on the data analysis control, displaying a data analysis page on the current interface. The embodiment reduces the outflow of unqualified products.

Description

Technical Field

[0001] The embodiments disclosed herein relate to the field of computer technology, specifically to methods, apparatus, equipment, and media for displaying coal raw material quality testing information. Background Technology

[0002] In the coal chemical production process, it is usually necessary to sample and analyze the products produced by the coal chemical production unit at regular intervals. Currently, the common method for sampling and analyzing the products produced by coal chemical production units is to perform the sampling and analysis manually.

[0003] However, manual sampling and analysis of products typically presents the following technical problems:

[0004] First, when product quality defects are discovered, there is usually a delay, and the product quality control is lagging behind, which can easily lead to defective products being released.

[0005] Second, the product quality testing parameters cannot be adaptively adjusted according to demand, resulting in an overly rigid product quality testing process that easily leads to the outflow of substandard products.

[0006] Third, the sampling logs of the chemical production unit were not preliminarily tested, resulting in low analysis efficiency and poor timeliness of the test. In addition, the sampling information is sensitive and was not encrypted, which could easily lead to the leakage of the sampling information.

[0007] Furthermore, it is difficult for humans to predict future trends in product indicators and to control product quality in advance, which can easily lead to the outflow of substandard products.

[0008] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0009] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0010] Some embodiments of this disclosure provide methods, apparatus, electronic devices, and computer-readable media for displaying coal raw material quality testing information to solve one or more of the technical problems mentioned in the background section above.

[0011] In a first aspect, some embodiments of this disclosure provide a method for displaying coal raw material quality testing information. The method includes: in response to detecting a selection operation applied to a coal raw material quality testing control, displaying a coal raw material quality testing page on a current interface, wherein the coal raw material quality testing page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control; in response to detecting a selection operation applied to the raw material input control, displaying a raw material input page on the current interface, wherein the raw material input page displays a sampling device selection control and a raw material data input subpage, the raw material data input subpage including a raw material sampling result input control, and the raw material data input subpage further including at least one... A raw material data input box; in response to a selection operation applied to the raw material query control, a raw material query page is displayed on the current interface, wherein the raw material query page displays a sampling device query control, a time query input box, and a query control; in response to a selection operation applied to the quality prediction control, a quality prediction page is displayed on the current interface, wherein the quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical index selection box; in response to a selection operation applied to the data analysis control, a data analysis page is displayed on the current interface, wherein the data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box.

[0012] Secondly, some embodiments of this disclosure provide a coal raw material quality testing information display device. The device includes: a first display unit configured to display a coal raw material quality testing page on the current interface in response to detecting a selection operation applied to a coal raw material quality testing control, wherein the coal raw material quality testing page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control; and a second display unit configured to display a raw material input page on the current interface in response to detecting a selection operation applied to the raw material input control, wherein the raw material input page displays a sampling device selection control and a raw material data input subpage, the raw material data input subpage including a raw material sampling result input control, and the raw material data input subpage further including at least one raw material data input... The system includes: a third display unit, configured to display a raw material query page on the current interface in response to a detected selection operation applied to the raw material query control, wherein the raw material query page displays a sampling device query control, a time query input box, and a query control; a fourth display unit, configured to display a quality prediction page on the current interface in response to a detected selection operation applied to the quality prediction control, wherein the quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical index selection box; and a fifth display unit, configured to display a data analysis page on the current interface in response to a detected selection operation applied to the data analysis control, wherein the data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box.

[0013] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0014] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0015] The above-described embodiments of this disclosure have the following beneficial effects: the coal raw material quality inspection information display method of some embodiments of this disclosure alleviates the lag in product quality control and reduces the outflow of unqualified products. Specifically, the reason why unqualified products are easily outflowed is that when unqualified products are discovered, there is usually a delay of some time, resulting in a lag in product quality control. Based on this, the coal raw material quality inspection information display method of some embodiments of this disclosure firstly, in response to the detection of a selection operation applied to the coal raw material quality inspection control, displays a coal raw material quality inspection page on the current interface. The coal raw material quality inspection page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control. Thus, product quality analysis and inspection can be completed through the raw material input control, raw material query control, quality prediction control, and data analysis control. Secondly, in response to the detection of a selection operation applied to the raw material input control, displays a raw material input page on the current interface. The raw material input page displays a sampling device selection control and a raw material data input subpage. The raw material data input subpage includes a raw material sampling result input control and at least one raw material data input box. Thus, raw material data of the product can be entered in real time. Next, in response to the detected selection operation applied to the aforementioned raw material query control, a raw material query page is displayed on the current interface. This page displays a sampling device query control, a time query input box, and a query control. This allows users to query the current information of the sample raw materials. Then, in response to the detected selection operation applied to the aforementioned quality prediction control, a quality prediction page is displayed on the current interface. This page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical indicator selection box. This allows for predictive analysis of the sample raw materials. Finally, in response to the detected selection operation applied to the aforementioned data analysis control, a data analysis page is displayed on the current interface. This page displays a sampling device query box, an analytical raw material query box, and a date input box. This allows for real-time quality analysis of the samples, alleviating product quality control delays and reducing the outflow of non-conforming products. Attached Figure Description

[0016] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0017] Figure 1 This is a flowchart of some embodiments of the coal raw material quality testing information display method according to the present disclosure;

[0018] Figure 2This is a schematic diagram of the structure of some embodiments of the coal raw material quality testing information display device according to the present disclosure;

[0019] Figure 3 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0020] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0021] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0022] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0023] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0024] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0025] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0026] Figure 1 This is a flowchart of some embodiments of the coal raw material quality inspection information display method according to the present disclosure. A flowchart 100 of some embodiments of the coal raw material quality inspection information display method according to the present disclosure is shown. The coal raw material quality inspection information display method includes the following steps:

[0027] Step 101: In response to the detection of a selection operation applied to the coal raw material quality inspection control, the coal raw material quality inspection page is displayed on the current interface.

[0028] In some embodiments, the executing entity (e.g., a client) of the coal raw material quality inspection information display method can display a coal raw material quality inspection page on the current interface in response to detecting a selection operation applied to the coal raw material quality inspection control. This coal raw material quality inspection page displays raw material input controls, raw material query controls, quality prediction controls, and data analysis controls. Here, the coal raw material quality inspection page can refer to a page for real-time monitoring of coal raw material quality. The coal raw material quality inspection control can be an icon control set in the executing entity for accessing the coal raw material quality inspection page. Selection operations can include, but are not limited to, clicking, scrolling, and swiping. The current interface can refer to the main display interface of the executing entity. Coal raw materials can include, but are not limited to, refined benzene products, methylcyclohexane, sodium hydroxide, etc.

[0029] In practice, after the aforementioned executing entity detects a click on the coal raw material quality detection control, it displays the coal raw material quality detection page on the main display interface.

[0030] Optionally, the coal raw material quality inspection page also displays a raw material device selection box, a raw material sample name selection box, and a raw material sample status information display subpage. Here, the raw material device selection box can be a selection box for selecting the device used to produce the raw material. The raw material sample name selection box can be a selection box for selecting the name of the raw material sample. The raw material sample status information display subpage can be a display page for showing the status information of the raw material sample, which is a subpage of the coal raw material quality inspection page and is nested within it.

[0031] Optionally, in response to detecting a selection operation on any raw material device in the raw material device selection box and a selection operation on any raw material sample name in the raw material sample name selection box, the raw material sample status information corresponding to any raw material device and any raw material sample name is displayed on the raw material sample status information display subpage.

[0032] In some embodiments, the execution entity may, in response to detecting a selection operation on any raw material device in the raw material device selection box and a selection operation on any raw material sample name in the raw material sample name selection box, display the raw material sample status information corresponding to any raw material device and any raw material sample name on the raw material sample status information display subpage. The raw material sample status information indicates whether the raw material sample corresponding to any raw material sample name is normal.

[0033] For example, when the aforementioned executing entity detects a click operation on any raw material device in the raw material device selection box, or a click operation on any raw material sample name in the raw material sample name selection box, it displays the corresponding raw material sample status information for each of the aforementioned raw material devices and raw material sample names on the raw material sample status information display subpage. For instance, any raw material device could be a benzene hydrogenation unit. Any raw material sample name could be refined benzene.

[0034] Step 102: In response to detecting a selection operation applied to the raw material input control, the raw material input page is displayed on the current interface.

[0035] In some embodiments, the aforementioned execution entity may display a raw material entry page on the current interface in response to detecting a selection operation applied to the raw material entry control. The raw material entry page displays a sampling device selection control and a raw material data input subpage. The raw material data input subpage includes a raw material sampling result entry control and at least one raw material data input box. The sampling device selection control may refer to a selection control box for selecting a sampling device. Optionally, the raw material entry page may further include a raw material sampling result entry subpage. Here, the raw material sampling result entry subpage may be a page for displaying raw material sampling result entry information, a subpage of the raw material entry page, and nested within the raw material entry page.

[0036] In practice, after detecting a click operation on the raw material input control, the aforementioned executing entity displays the raw material input page on the current interface.

[0037] Optionally, in response to detecting a selection operation performed on any of the sampling devices in the sampling device selection control, a sampling log corresponding to any of the sampling devices is selected from the local database.

[0038] In some embodiments, the execution entity may, in response to detecting a selection operation performed on any of the sampling devices in the sampling device selection control, select the sampling log corresponding to any of the sampling devices from the local database. That is, after detecting a click operation performed on any of the sampling devices in the sampling device selection control, the execution entity may select the sampling log corresponding to any of the sampling devices from the local database. In other words, it can query the sampling log collected by any sampling device from the local database. The sampling log may refer to information about samples collected by the sampling device within a certain operating time period.

[0039] Optionally, the parameters contained in the above sampling log are added to at least one of the above raw material data input boxes, and in response to the detection of a selection operation on the above raw material sampling result entry control, the corresponding raw material sampling result entry information is displayed on the above raw material sampling result entry subpage.

[0040] In some embodiments, the executing entity can add the parameters contained in the sampling log to the at least one raw material data input box, and in response to detecting a selection operation applied to the raw material sampling result entry control, display the corresponding raw material sampling result entry information on the raw material sampling result entry subpage. Here, the at least one raw material data input box may include, but is not limited to: a batch input box, a sampling time input box, a brine concentration input box, a calcium ion concentration input box, a magnesium ion concentration input box, a sulfate concentration input box, an iodide ion concentration input box, and an ammonium ion input box. That is, the executing entity can input the parameters contained in the sampling log into the corresponding raw material data input boxes. Furthermore, after detecting a click operation applied to the raw material sampling result entry control, the executing entity displays the corresponding raw material sampling result entry information on the raw material sampling result entry subpage. Here, the raw material sampling result entry information is the parameter information added to the at least one raw material data input box.

[0041] Optionally, before selecting the sampling log corresponding to any of the above sampling devices from the local database, the method further includes:

[0042] The first step involves receiving the initial sampling log corresponding to any of the aforementioned sampling devices, and then performing component analysis on the initial sampling log to generate sampling log analysis information. This sampling log analysis information includes a set of sampling indicator data. Specifically, principal component analysis can be performed on the initial sampling log to generate the sampling log analysis information. The sampling indicator data set can be the various core indicators of the initial sampling log parsed from the principal component analysis.

[0043] The second step is to consult the sampling index data lookup table corresponding to each of the above sampling devices. That is, each sampling device has its own sampling index data lookup table. This table can be used to preliminarily verify whether each sampling index value is within the normal range.

[0044] The third step involves analyzing the sampling log data according to the aforementioned sampling indicator data comparison table to generate sampling log detection results. Specifically, when sampling indicator data exists in the sampling log analysis information that is outside the normal indicator value range, an anomaly-indicating sampling log detection result is generated.

[0045] Fourth step: In response to determining that the above sampling log detection results indicate no abnormalities, determine the device identifier of any of the above sampling devices.

[0046] The fifth step is to combine the aforementioned device identifier, the aforementioned initial sampling log, and the current timestamp into the sampling log information to be encrypted. "Combining" can refer to merging.

[0047] The sixth step involves performing a first encryption process on the aforementioned sampled log information to be encrypted, thereby generating first encrypted sampled log information. This first encryption process can be achieved using the SM3 encryption algorithm.

[0048] Step 7: Combine the first encrypted sampling log information, the local database identifier, and the sampling log information to be encrypted into alternative encrypted sampling log information.

[0049] Step 8: Based on the preset public key of the corresponding local database, perform a second encryption process on the above-mentioned candidate encrypted sampling log information to generate encrypted sampling log information, and store the encrypted sampling log information in the local database. The second encryption process can refer to symmetric encryption.

[0050] The content in steps one through eight above constitutes an inventive point of this disclosure, solving the third technical problem mentioned in the background art: "Easy to lead to leakage of sampling information." Factors that easily lead to leakage of sampling information often include: failure to perform preliminary testing on the sampling logs of chemical production units, resulting in low analysis efficiency, poor timeliness of testing, and the sensitivity of the sampling information due to lack of encryption. Solving these factors can improve the security of the sampling information. To achieve this effect, firstly, in response to receiving the initial sampling log corresponding to any of the aforementioned sampling devices, the initial sampling log is subjected to component analysis processing to generate sampling log analysis information. This sampling log analysis information includes sampling index data sets. Thus, the initial sampling log can be preliminarily parsed. Secondly, a sampling index data lookup table corresponding to any of the aforementioned sampling devices is queried; based on the sampling index data lookup table, the sampling log analysis information is tested to generate sampling log test results. Thus, the sampling log can be preliminarily tested to remove abnormal sampling logs. This improves analysis efficiency and ensures the timeliness of testing. Next, in response to the determination that the above-mentioned sampling log detection results indicate no anomalies, the device identifier of any of the above-mentioned sampling devices is determined. Then, the device identifier, the initial sampling log, and the current timestamp are combined to form sampling log information to be encrypted. Next, the sampling log information to be encrypted is subjected to a first encryption process to generate first encrypted sampling log information. Thus, the uniqueness of the device identifier and the current timestamp can be used to encrypt the sampling log information. Then, the first encrypted sampling log information, the local database identifier, and the sampling log information to be encrypted are combined to form candidate encrypted sampling log information. Finally, based on a preset public key corresponding to the local database, the candidate encrypted sampling log information is subjected to a second encryption process to generate encrypted sampling log information, and the encrypted sampling log information is stored in the local database. Thus, the sampling log information can be further encrypted to improve the security of the sampling information.

[0051] Step 103: In response to detecting the selection operation performed on the above-mentioned raw material query control, the raw material query page is displayed on the current interface.

[0052] In some embodiments, the execution entity may display a raw material query page on the current interface in response to detecting a selection operation applied to the raw material query control. This raw material query page displays a sampling device query control, a time query input box, and a query control. Here, the sampling device query control may refer to a selection control box for selecting a sampling device. The time query input box may be an input box for entering a query time period. After clicking the query control, the execution entity can perform a query operation based on the information in the sampling device query control and the time query input box.

[0053] In practice, the aforementioned executing entity can display the raw material query page on the current interface after detecting a click operation performed on the aforementioned raw material query control.

[0054] Optionally, in response to detecting a selection operation on any of the sampling devices in the above-mentioned sampling device query control, detecting an input operation input to the above-mentioned time query input box, and detecting a click operation on the above-mentioned query control, at least one sampling information is displayed on the above-mentioned raw material query page.

[0055] In some embodiments, the execution entity may, in response to detecting a selection operation on any of the sampling devices in the sampling device query control, an input operation into the time query input box, and a click operation on the query control, display at least one piece of sampling information on the raw material query page. Here, the sampling information may include, but is not limited to: batch, sampling time, brine concentration, calcium ion concentration, magnesium ion concentration, sulfate concentration, iodide ion concentration, and ammonium ion.

[0056] Step 104: In response to detecting a selection operation applied to the aforementioned quality prediction control, display the quality prediction page on the current interface.

[0057] In some embodiments, the execution entity may display a quality prediction page on the current interface in response to detecting a selection operation applied to the quality prediction control. This quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical indicator selection box. Here, the sampling device selection box can be a selection box for selecting a sampling device. The sample name selection box can be a selection box for selecting a sample name. The sample raw material batch selection box can be a selection box for selecting a batch of sample raw materials. The analytical indicator selection box can be a selection box for selecting an analytical indicator. Here, the analytical indicator can be an indicator of a specific element to be analyzed in the sample raw material. Optionally, the quality prediction page also displays a prediction control. That is, after clicking the prediction control, the execution entity can perform an indicator prediction operation.

[0058] Optionally, in response to detecting a selection operation on any sampling device in the sampling device selection box, a selection operation on any sample name in the sample name selection box, a selection operation on any sample raw material batch in the sample raw material batch selection box, a selection operation on any analytical indicator in the analytical indicator selection box, and a click operation on the prediction control, associated indicator prediction information is generated.

[0059] In some embodiments, the execution entity can generate associated indicator prediction information in response to detecting a selection operation on any sampling device in the sampling device selection box, a selection operation on any sample name in the sample name selection box, a selection operation on any sample raw material batch in the sample raw material batch selection box, a selection operation on any analytical indicator in the analytical indicator selection box, and a click operation on the prediction control. The indicator prediction information includes indicator prediction curves within a preset time period. That is, the execution entity can use a pre-trained indicator prediction neural network model to predict the selected sampling device name, sample name, sample raw material batch, and analytical indicator. Here, the indicator prediction neural network model can be a pre-trained neural network model that takes the sampling device name, sample name, sample raw material batch, and analytical indicator as input and outputs indicator prediction information. For example, the indicator prediction neural network model can be a convolutional neural network model. For example, the analytical indicator can be sodium hydroxide concentration.

[0060] In practice, the aforementioned implementing entities can generate relevant indicator forecast information through the following steps:

[0061] The first step is to obtain the sample indicator information set. This set includes indicator information and sample labels. The sample indicator information may include the sampling device name, sample name, sample raw material batch, and analytical indicator. The sample label can represent the indicator change curve corresponding to the indicator information.

[0062] The second step is to split the above sample indicator information set into sub-sample indicator information groups. That is, the above sample indicator information set can be divided into a predetermined number of sub-sample indicator information groups. Here, the predetermined number can refer to the number of sub-server sequences included in the distributed system.

[0063] The third step is to determine the initial indicator prediction model corresponding to the above sample indicator information set. That is, the initial indicator prediction model can refer to an untrained convolutional neural network model.

[0064] Fourth, for each subsample indicator information group in the above subsample indicator information group set, perform the following processing steps:

[0065] The first sub-step involves transmitting the aforementioned sub-sample indicator information group to a sequence of sub-servers within a pre-defined distributed system. The initial indicator prediction model comprises multiple sub-models, and one of these sub-models is deployed on a sub-server within the sub-server sequence. Each sub-server has a set of computing nodes. The distributed system can be a distributed server cluster. Computing nodes can be processors. Multiple sub-models can refer to a multi-layered network.

[0066] The second sub-step involves splitting the model parameter set of the corresponding sub-model for each sub-server in the aforementioned sub-server sequence to generate a sub-model parameter set. Specifically, the model parameter set can be evenly divided into a target number of sub-model parameter sets. Here, the target number can be the number of computing nodes included in the sub-server.

[0067] The third sub-step involves assigning each sub-model parameter set in the generated sub-model parameter set to a computing node in the corresponding sub-server, and controlling the sub-server to train the deployed sub-model to obtain a trained sub-model. That is, each computing node can perform calculations on its assigned sub-model parameter set. Thus, simultaneous calculations by multiple computing nodes can accelerate model training.

[0068] The fifth step is to combine the trained sub-models into a trained indicator prediction model.

[0069] Step 6: Input the selected sampling device name, sample name, sample raw material batch, and analytical index into the above-mentioned index prediction model to obtain index prediction information. Here, the selected sampling device name, sample name, sample raw material batch, and analytical index can refer to the information selected from the above-mentioned sampling device selection box, sample name selection box, sample raw material batch selection box, and analytical index selection box.

[0070] The aforementioned content, as an inventive point of this disclosure, solves the fourth technical problem mentioned in the background art: "Easy to lead to the outflow of substandard products." Factors that easily lead to the outflow of substandard products are often as follows: it is difficult for humans to predict the future trend of product indicators, and it is difficult to control product quality in advance. Solving these factors can reduce the outflow of substandard products. To achieve this effect, firstly, a sample indicator information set is obtained. Secondly, the sample indicator information set is split into sub-sample indicator information sets. This facilitates the training of the indicator prediction model. Thirdly, the initial indicator prediction model corresponding to the sample indicator information set is determined. Next, for each sub-sample indicator information set in the sub-sample indicator information set, the following processing steps are performed: First, the sub-sample indicator information set is transmitted to a sub-server sequence in a preset distributed system. The initial indicator prediction model includes multiple sub-models, and one of the multiple sub-models is deployed on a sub-server in the sub-server sequence. Each sub-server has a set of computing nodes. Therefore, multiple sub-servers can be used to train the model simultaneously, thereby accelerating the model training speed. Next, for each sub-server in the above sub-server sequence, the model parameter set of the corresponding sub-model is split to generate a sub-model parameter set. Then, for each sub-model parameter set generated in each sub-model parameter set, each sub-model parameter set is assigned to a computing node in the corresponding sub-server, and the sub-server is controlled to train the deployed sub-model to obtain a trained sub-model. This allows multiple computing nodes to be used to train the parameters of each sub-model, further accelerating the training speed. Then, the trained sub-models are combined into a trained indicator prediction model. Finally, the input sampling device name, sample name, sample raw material batch, and analytical indicators are input into the indicator prediction model to obtain indicator prediction information. This allows for the prediction of future trends in product indicators, facilitating early control of product quality and reducing the outflow of defective products.

[0071] Optionally, in response to determining that the predicted value of any of the above-mentioned indicator prediction curves meets the indicator early warning conditions, an alarm message is displayed on the above-mentioned quality prediction page.

[0072] In some embodiments, the execution entity may display an alarm message on the quality prediction page in response to determining that any predicted value of any indicator in the indicator prediction curve meets the indicator warning condition. Here, the warning condition may be "the predicted value of the indicator is greater than the preset maximum value of the indicator or the predicted value of the indicator is less than the preset minimum value of the indicator". That is, the execution entity may render a flashing red alarm message on the quality prediction page in response to determining that any predicted value of any indicator in the indicator prediction curve meets the indicator warning condition.

[0073] Step 105: In response to detecting a selection operation applied to the aforementioned data analysis control, display the data analysis page on the current interface.

[0074] In some embodiments, the execution entity may display a data analysis page on the current interface in response to detecting a selection operation applied to the data analysis control. The data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box. Here, the sampling device query box can be a selection box for querying sampling devices. That is, the sampling device query box contains multiple names of sampling devices for selection. The analytical raw material query box can be a selection box for querying the name of analytical raw material samples; that is, the analytical raw material query box contains multiple raw material sample names for selection. Optionally, the data analysis page also displays an indicator display subpage, an indicator query subpage, an indicator alarm subpage, an alarm count subpage, and an alarm duration subpage. The indicator query subpage includes an indicator query selection box and an indicator query time input box. The indicator query selection box can be a selection box for selecting a specific parameter indicator in a raw material sample; that is, the indicator query selection box contains multiple parameter indicators in the raw material sample for selection. The indicator display subpage, indicator query subpage, indicator alarm subpage, alarm count subpage, and alarm duration subpage are all subpages of the data analysis page, and are nested within the data analysis page.

[0075] Optionally, in response to detecting a selection operation of any sampling device in the above-mentioned sampling device query box, a selection operation of any analytical material in the above-mentioned analytical material query box, and an input operation in the above-mentioned date input box, at least one indicator query information is displayed on the above-mentioned indicator display subpage.

[0076] In some embodiments, the execution entity may, in response to detecting a selection operation on any sampling device in the sampling device query box, a selection operation on any analytical raw material in the analytical raw material query box, and an input operation on the date input box, display at least one indicator query information on the indicator display subpage. Here, the at least one indicator query information may be indicator information retrieved by the execution entity based on the name of any sampling device, the raw material name of any analytical raw material, and the date entered in the date input box. For example, the name of the sampling device may be an electrolysis device. The raw material name of any analytical raw material may be the alkaline solution of the electrolytic cell. The indicator query information may include the sample name, the indicator name, and the number of alarms. For example, the indicator query information may be: alkaline solution of the electrolytic cell, sodium hydroxide concentration, and 27 alarms.

[0077] Optionally, in response to detecting a click operation applied to any of the above-mentioned at least one indicator query information, the corresponding indicator alarm trend chart is displayed on the above-mentioned indicator alarm subpage, the corresponding alarm count is displayed on the above-mentioned alarm count subpage, and the corresponding alarm duration change chart is displayed on the above-mentioned alarm duration subpage.

[0078] In some embodiments, the executing entity may, in response to detecting a click operation applied to any of the at least one indicator query information, display a corresponding indicator alarm trend chart on the indicator alarm subpage, display the corresponding number of alarms on the alarm count subpage, and display a corresponding alarm duration change chart on the alarm duration subpage. That is, after detecting a click operation applied to any of the at least one indicator query information, the executing entity may display an indicator alarm trend chart corresponding to any of the aforementioned indicator query information on the indicator alarm subpage, display the alarm count corresponding to any of the aforementioned indicator query information on the alarm count subpage, and display a change chart of the alarm duration corresponding to any of the aforementioned indicator query information on the alarm duration subpage. Here, the indicator alarm trend chart may represent the change in the number of alarms for the indicator corresponding to the indicator query information over a period of time. The alarm duration change chart may represent the change in the alarm duration for the indicator corresponding to the indicator query information over a period of time.

[0079] Optionally, in response to detecting a selection operation on any indicator in the indicator query selection box and an input operation on the indicator query time input box, the corresponding indicator prediction curve is displayed on the indicator query subpage.

[0080] In some embodiments, the executing entity may, in response to detecting a selection operation on any indicator in the indicator query selection box and an input operation on the indicator query time input box, display the corresponding indicator change curve on the indicator query subpage. That is, the executing entity can display the indicator change curve for any given indicator on the indicator query subpage based on the indicator name and the query time in the indicator query time input box. The indicator change curve can represent the change curve of the indicator value within the query time.

[0081] Optionally, the aforementioned coal raw material quality inspection page also displays raw material early warning indicator configuration controls and raw material knowledge base controls.

[0082] Optionally, in response to detecting a selection operation applied to the aforementioned raw material early warning indicator configuration control, the raw material early warning indicator configuration page is displayed on the current interface.

[0083] In some embodiments, the execution entity may, in response to detecting a selection operation applied to the raw material early warning indicator configuration control, display a raw material early warning indicator configuration page on the current interface. This page displays a device query box and a sample name input box. The device query box may be a selection box for querying sampling devices; that is, the device query box may have multiple pre-built names of sampling devices for selection. The sample name input box may be an input box for entering the name of the sample being sampled.

[0084] Optionally, in response to detecting a selection operation on any device name in the above-mentioned device query box and an input operation on a sample name in the above-mentioned sample name input box, a subpage of warning indicators to be configured is displayed on the above-mentioned raw material warning indicator configuration page.

[0085] In some embodiments, the executing entity may, in response to detecting a selection operation on any device name in the device query box and an input operation on a sample name in the sample name input box, display a subpage of early warning indicators to be configured on the raw material early warning indicator configuration page. This subpage displays at least one early warning analysis indicator to be configured, and each indicator corresponds to an upper limit input box, a lower limit input box, and a save control. That is, the subpage of early warning indicators to be configured is nested within the raw material early warning indicator configuration page. In practice, the executing entity can configure early warning indicators on the subpage corresponding to any device name and sample name.

[0086] Optionally, in response to detecting input operations applied to the upper limit input box and lower limit input box of any of the early warning analysis indicators to be configured, and detecting selection operations applied to the save control corresponding to any of the aforementioned early warning analysis indicators to be configured, the early warning analysis indicators are saved and configured.

[0087] In some embodiments, the execution entity may save the configured early warning analysis indicator in response to detecting input operations on the upper limit and lower limit input boxes corresponding to any of the early warning analysis indicators to be configured, and detecting selection operations on the save control corresponding to any of the early warning analysis indicators to be configured. That is, configuring the early warning analysis indicator can refer to the input upper limit and lower limit values ​​of the indicator.

[0088] Optionally, in response to detecting a selection operation performed on the aforementioned raw material knowledge base control, the raw material knowledge base page is displayed on the current interface.

[0089] In some embodiments, the execution entity may display a raw material knowledge base page on the current interface in response to detecting a selection operation applied to the raw material knowledge base control. The raw material knowledge base page displays a device input box, a name input box, a fault rule configuration subpage, and a fault rule display subpage. The fault rule configuration subpage displays a fault name input box, a fault cause input box, a maintenance suggestion input box, and a fault parameter configuration subpage. The fault parameter configuration subpage displays at least one fault parameter input box. The device input box may refer to an input box for inputting the sampling device. The name input box may refer to an input box for inputting the sample name. The maintenance suggestion input box may refer to an input box for inputting fault repair suggestions.

[0090] Optionally, in response to detecting a selection operation on any device name in the device input box, an input operation on the name input box, an input operation on the fault name input box, an input operation on the fault cause input box, an input operation on at least one fault parameter input box, and an input operation on the maintenance suggestion input box, the corresponding fault rule configuration information is displayed on the fault rule display subpage.

[0091] In some embodiments, the execution entity may, in response to detecting a selection operation on any device name in the device input box, an input operation on the name input box, an input operation on the fault name input box, an input operation on the fault cause input box, an input operation on at least one fault parameter input box, and an input operation on the maintenance suggestion input box, display the corresponding fault rule configuration information on the fault rule display subpage. That is, technicians can enter a fault name in the fault name input box, a fault cause in the fault cause input box, a maintenance suggestion in the maintenance suggestion input box, and a fault parameter in at least one fault parameter input box. Thus, the corresponding fault rule configuration information can be displayed on the fault rule display subpage. For example, the device name could be an electrolysis device; the sample name could be an alkaline solution in the electrolytic cell; the fault name could be an electrolyte concentration that is too low; the fault cause could be: a sudden drop in current, insufficient power supply current, or excessively high liquid level control; and the maintenance suggestion could be: check the adsorption process, monitor the power supply, and adjust the liquid level promptly.

[0092] The aforementioned content, as an inventive point of this disclosure, solves the second technical problem mentioned in the background art: "Easy to cause the outflow of unqualified products." Factors that easily lead to the outflow of unqualified products often include: the inability of product quality testing parameters to adaptively adjust according to demand, resulting in an overly rigid product quality testing process. Solving these factors can reduce the outflow of unqualified products. To achieve this effect, firstly, in response to the detection of a selection operation applied to the aforementioned raw material early warning indicator configuration control, a raw material early warning indicator configuration page is displayed on the current interface. This page displays a device query box and a sample name input box. This facilitates the configuration of product quality testing parameters on the raw material early warning indicator configuration page. Secondly, in response to the detection of a selection operation applied to the aforementioned raw material knowledge base control, a raw material knowledge base page is displayed on the current interface. This page displays a device input box, a name input box, a fault rule configuration subpage, and a fault rule display subpage. This allows for the configuration of fault rules on the raw material knowledge base page, facilitating fault resolution. Then, in response to the detection of a selection operation on any device name in the aforementioned device query box and an input operation on a sample name in the aforementioned sample name input box, a subpage for configuring early warning indicators is displayed on the aforementioned raw material early warning indicator configuration page. This subpage displays at least one early warning analysis indicator to be configured, and each indicator has an upper limit input box, a lower limit input box, and a save control. This allows for real-time configuration of product quality testing parameters. Finally, in response to the detection of input operations on the upper limit and lower limit input boxes corresponding to any early warning analysis indicator to be configured, and the detection of a selection operation on the save control corresponding to any of the aforementioned early warning analysis indicators to be configured, the configured early warning analysis indicator is saved. This allows for adaptive adjustment of testing parameters according to needs, avoiding an overly rigid testing process. Consequently, the outflow of non-conforming products is reduced.

[0093] Further reference Figure 2 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a coal raw material quality inspection information display device. These embodiments of the coal raw material quality inspection information display device are similar to... Figure 1 Corresponding to the method embodiments shown, this coal raw material quality inspection information display device can be specifically applied to various electronic devices.

[0094] like Figure 2As shown, a coal raw material quality inspection information display device 200 in some embodiments includes: a first display unit 201, a second display unit 202, a third display detection unit 203, a fourth display unit 204, and a fifth display unit 205. The first display unit 201 is configured to display a coal raw material quality inspection page on the current interface in response to a detected selection operation applied to the coal raw material quality inspection control. This coal raw material quality inspection page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control. The second display unit 202 is configured to display a raw material input page on the current interface in response to a detected selection operation applied to the raw material input control. This raw material input page displays a sampling device selection control and a raw material data input subpage. The raw material data input subpage includes a raw material sampling result input control and at least one raw material data input box. The third display unit 203 is configured to respond to... Upon detecting a selection operation applied to the aforementioned raw material query control, a raw material query page is displayed on the current interface, wherein the raw material query page displays a sampling device query control, a time query input box, and a query control; the fourth display unit 204 is configured to display a quality prediction page on the current interface in response to detecting a selection operation applied to the aforementioned quality prediction control, wherein the quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical index selection box; the fifth display unit 205 is configured to display a data analysis page on the current interface in response to detecting a selection operation applied to the aforementioned data analysis control, wherein the data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box.

[0095] It is understandable that the units recorded in the coal raw material quality inspection information display device 200 are related to the reference. Figure 1 The steps in the described method correspond accordingly. Therefore, the operations, features, and beneficial effects described above for the method also apply to the coal raw material quality detection information display device 200 and the units contained therein, and will not be repeated here.

[0096] The following is for reference. Figure 3 This illustration shows a structural schematic of an electronic device (e.g., a client) 300 suitable for implementing some embodiments of the present disclosure. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 3The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.

[0097] like Figure 3 As shown, the electronic device 300 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device 300. The processing unit 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0098] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic device 300 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 An electronic device 300 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 3 Each box shown can represent a device or multiple devices as needed.

[0099] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a storage device 308, or installed from a ROM 302. When the computer program is executed by the processing device 301, it performs the functions defined in the methods of some embodiments of this disclosure.

[0100] It should be noted that, in some embodiments of this disclosure, the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0101] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0102] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: in response to detecting a selection operation applied to the coal raw material quality detection control, display a coal raw material quality detection page on the current interface, wherein the coal raw material quality detection page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control; in response to detecting a selection operation applied to the raw material input control, display a raw material input page on the current interface, wherein the raw material input page displays a sampling device selection control and a raw material data input subpage, wherein the raw material data input subpage includes a raw material sampling result input control, and the raw material data input subpage also... The system includes at least one raw material data input box; in response to a detected selection operation applied to the raw material query control, a raw material query page is displayed on the current interface, wherein the raw material query page displays a sampling device query control, a time query input box, and a query control; in response to a detected selection operation applied to the quality prediction control, a quality prediction page is displayed on the current interface, wherein the quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical index selection box; in response to a detected selection operation applied to the data analysis control, a data analysis page is displayed on the current interface, wherein the data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box.

[0103] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0104] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0105] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including: a first display unit, a second display unit, a third display detection unit, a fourth display unit, and a fifth display unit. The names of these units do not necessarily limit the specific unit itself; for example, the first display unit may also be described as "a unit that displays a coal raw material quality detection page on the current interface in response to detecting a selection operation applied to a coal raw material quality detection control."

[0106] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0107] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for displaying coal raw material quality inspection information, comprising: In response to the detection of a selection operation applied to the coal raw material quality detection control, a coal raw material quality detection page is displayed on the current interface. The coal raw material quality detection page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control. The coal raw material includes at least one of the following: refined benzene products, methylcyclohexane, and sodium hydroxide. In response to detecting a selection operation applied to the raw material input control, a raw material input page is displayed on the current interface. The raw material input page displays a sampling device selection control and a raw material data input subpage. The raw material data input subpage includes a raw material sampling result input control and at least one raw material data input box. In response to detecting a selection operation applied to the raw material query control, a raw material query page is displayed on the current interface, wherein the raw material query page displays a sampling device query control, a time query input box, and a query control; In response to the detection of a selection operation applied to the quality prediction control, a quality prediction page is displayed on the current interface, wherein the quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical index selection box. In response to detecting a selection operation applied to the data analysis control, a data analysis page is displayed on the current interface, wherein the data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box; The raw material entry page also includes a subpage for entering raw material sampling results; and The method further includes: In response to detecting a selection operation on any sampling device in the sampling device selection control, the sampling log corresponding to any sampling device is selected from the local database, wherein the sampling log refers to the information of the sample collected by the sampling device during a certain period of operation. Add each parameter contained in the sampling log to the at least one raw material data input box, and in response to detecting a selection operation applied to the raw material sampling result entry control, display the corresponding raw material sampling result entry information on the raw material sampling result entry subpage; The quality prediction page also displays prediction controls; and The method further includes: In response to the detection of a selection operation on any sampling device in the sampling device selection box, a selection operation on any sample name in the sample name selection box, a selection operation on any sample raw material batch in the sample raw material batch selection box, a selection operation on any analytical indicator in the analytical indicator selection box, and a click operation on the prediction control, associated indicator prediction information is generated, wherein the indicator prediction information includes an indicator prediction curve within a preset time period. In response to determining that any predicted value of an indicator in the indicator prediction curve meets the indicator early warning condition, an alarm prompt message is displayed on the quality prediction page; The method further includes, prior to selecting the sampling log corresponding to any of the sampling devices from the local database: In response to receiving the initial sampling log corresponding to any of the sampling devices, the initial sampling log is subjected to component analysis processing to generate sampling log analysis information; Query the sampling index data lookup table corresponding to any of the sampling devices; Based on the sampling index data comparison table, the sampling log analysis information is detected to generate sampling log detection results; In response to determining that the sampling log detection result indicates no abnormality, the device identifier of any sampling device is determined; The device identifier, the initial sampling log, and the current timestamp are combined to form the sampling log information to be encrypted; The sampling log information to be encrypted is subjected to a first encryption process to generate first encrypted sampling log information; The first encrypted sampling log information, the local database identifier, and the sampling log information to be encrypted are combined to form candidate encrypted sampling log information; Based on the preset public key of the corresponding local database, the candidate encrypted sampling log information is subjected to a second encryption process to generate encrypted sampling log information, and the encrypted sampling log information is stored in the local database.

2. The method according to claim 1, wherein, The coal raw material quality testing page displays a raw material device selection box, a raw material sample name selection box, and a subpage displaying raw material sample status information. as well as The method further includes: In response to the detection of a selection operation on any raw material device in the raw material device selection box and a selection operation on any raw material sample name in the raw material sample name selection box, the raw material sample status information corresponding to any raw material device and any raw material sample name is displayed on the raw material sample status information display subpage, wherein the raw material sample status information indicates whether the raw material sample corresponding to any raw material sample name is normal.

3. The method according to claim 1, wherein, The method further includes: In response to detecting a selection operation on any sampling device in the sampling device query control, an input operation to the time query input box, and a click operation on the query control, at least one sampling information is displayed on the raw material query page.

4. A coal raw material quality inspection information display device, comprising: The first display unit is configured to display a coal raw material quality detection page on the current interface in response to a selection operation detected on the coal raw material quality detection control. The coal raw material quality detection page displays a raw material input control, a raw material query control, a quality prediction control, and a data analysis control. The coal raw material includes at least one of the following: refined benzene products, methylcyclohexane, and sodium hydroxide. The second display unit is configured to display a raw material entry page on the current interface in response to detecting a selection operation applied to the raw material entry control. The raw material entry page displays a sampling device selection control and a raw material data input subpage. The raw material data input subpage includes a raw material sampling result entry control and at least one raw material data input box. The third display unit is configured to display a raw material query page on the current interface in response to detecting a selection operation applied to the raw material query control. The raw material query page displays a sampling device query control, a time query input box, and a query control. The fourth display unit is configured to display a quality prediction page on the current interface in response to detecting a selection operation applied to the quality prediction control, wherein the quality prediction page displays a sampling device selection box, a sample name selection box, a sample raw material batch selection box, and an analytical index selection box. The fifth display unit is configured to display a data analysis page on the current interface in response to detecting a selection operation applied to the data analysis control, wherein the data analysis page displays a sampling device query box, an analytical raw material query box, and a date input box; The raw material entry page also includes a subpage for entering raw material sampling results; and The device is also configured to: In response to detecting a selection operation on any sampling device in the sampling device selection control, the sampling log corresponding to any sampling device is selected from the local database, wherein the sampling log refers to the information of the sample collected by the sampling device during a certain period of operation. Add each parameter contained in the sampling log to the at least one raw material data input box, and in response to detecting a selection operation applied to the raw material sampling result entry control, display the corresponding raw material sampling result entry information on the raw material sampling result entry subpage; The quality prediction page also displays prediction controls; and The device is also configured to: In response to the detection of a selection operation on any sampling device in the sampling device selection box, a selection operation on any sample name in the sample name selection box, a selection operation on any sample raw material batch in the sample raw material batch selection box, a selection operation on any analytical indicator in the analytical indicator selection box, and a click operation on the prediction control, associated indicator prediction information is generated, wherein the indicator prediction information includes an indicator prediction curve within a preset time period. In response to determining that any predicted value of an indicator in the indicator prediction curve meets the indicator early warning condition, an alarm prompt message is displayed on the quality prediction page; Prior to selecting the sampling log corresponding to any of the sampling devices from the local database, the device is further configured to: In response to receiving the initial sampling log corresponding to any of the sampling devices, the initial sampling log is subjected to component analysis processing to generate sampling log analysis information; Query the sampling index data lookup table corresponding to any of the sampling devices; Based on the sampling index data comparison table, the sampling log analysis information is detected to generate sampling log detection results; In response to determining that the sampling log detection result indicates no abnormality, the device identifier of any sampling device is determined; The device identifier, the initial sampling log, and the current timestamp are combined to form the sampling log information to be encrypted; The sampling log information to be encrypted is subjected to a first encryption process to generate first encrypted sampling log information; The first encrypted sampling log information, the local database identifier, and the sampling log information to be encrypted are combined to form candidate encrypted sampling log information; Based on the preset public key of the corresponding local database, the candidate encrypted sampling log information is subjected to a second encryption process to generate encrypted sampling log information, and the encrypted sampling log information is stored in the local database.

5. An electronic device, comprising: One or more processors; A storage device on which one or more programs are stored; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-3.

6. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-3.

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