A new dry process cement production control method and system based on cloud platform

Abstract

The present application relates to a new type of dry cement production control method and system based on a cloud platform, and relates to the technical field of production control. The method includes obtaining stockyard image information, the stockyard image information includes images of raw material accumulation; determining the material taking method based on the stockyard image information; controlling the material taking device to obtain the raw material based on the material taking method; controlling the raw material preparation device to prepare raw material based on the raw material, and controlling the detection device to detect the raw material. The present application has the effect of improving the processing speed of the raw material.

Description

Technical Field

[0001] The present application relates to the technical field of production control, and in particular to a new type of dry process cement production line control system based on a cloud platform. Background Art

[0002] In building construction and decoration projects, cement is an indispensable material as the basic raw material of the construction industry. It is mainly used in the production of concrete and mortar. Cement plays a very important role in people's lives. The cement production line is a cement equipment production line composed of a series of equipment for producing cement.

[0003] In the process of preparing cement, the processing requirements for cement raw materials in the early stage are high. Improper processing of raw materials will affect the speed of cement preparation in the later stage, and will also directly affect the quality of the prepared cement. The existing manual selection and testing of raw materials is labor-intensive and the processing speed of raw materials is slow. Summary of the invention

[0004] In order to increase the processing speed of raw materials, the present application provides a new dry process cement production control method and system based on a cloud platform.

[0005] In the first aspect, the present application provides a new dry process cement production control method based on a cloud platform, which adopts the following technical solution:

[0006] A new dry process cement production control method based on a cloud platform, comprising:

[0007] Acquiring stockyard image information, wherein the stockyard image information includes an image of raw material accumulation;

[0008] Determining a method for taking raw materials based on the stockpile image information;

[0009] Controlling the material taking device to obtain the raw material based on the material taking method;

[0010] The raw meal preparation equipment is controlled to prepare the raw meal based on the raw materials, and the detection device is controlled to detect the raw meal.

[0011] By adopting the above technical solution, the stockyard image information is obtained to obtain the stacking method of the raw materials in the stockyard. The raw materials can achieve a better homogenization effect by adopting different stacking methods. The material collection method of the raw materials is determined based on the stockyard image information, which reduces the workload of manually selecting the material collection method. The corresponding material collection method is selected for different stacking methods, and the material collection equipment is controlled to obtain the raw materials based on the material collection method, so that the material collection equipment can select all the material layers of the raw materials as much as possible. The raw material preparation equipment is controlled to prepare raw materials based on the raw materials, and the detection device is controlled to detect the raw materials. It is no longer necessary to manually detect the raw materials, thereby improving the processing speed of the raw materials.

[0012] In another possible implementation, the determining of the material taking method based on the stockpile image information includes:

[0013] Performing grayscale conversion on the stockpile yard image information to obtain grayscale information of the stockpile yard image information;

[0014] Determine threshold information for binarization processing based on the grayscale information;

[0015] Binarizing the stockpile image information based on the threshold information to obtain stockpile shape information;

[0016] A corresponding material taking method is determined based on the pile shape information.

[0017] By adopting the above technical solution, the stockpile image information is gray-scale converted, so that the stockpile image information is black and white, and the gray-scale information of the stockpile image information is obtained. The threshold information of the binarization processing is determined based on the gray-scale information, and the stockpile image information is binarized based on the threshold information. After the binarization processing, the characteristics of the raw material accumulation can be more clearly reflected, and the stockpile shape information of the raw material can be obtained. The stacking method of the raw materials is determined based on the stockpile shape information, and the material collection method is determined based on the stacking method. Selecting a suitable material collection method can minimize the fluctuation of the raw material composition caused by factors such as mining and transportation.

[0018] In another possible implementation, the controlling the material taking device to obtain the raw material based on the material taking method includes:

[0019] Acquire the position information of the material taking device and send the material taking information to the material taking device;

[0020] Determine a material taking route based on the location information of the material taking equipment and the material taking information;

[0021] Controlling the material taking device to move to the location of the raw material based on the material taking route;

[0022] The material taking device is controlled to obtain the raw material based on the material taking method.

[0023] By adopting the above technical solution, the position information of the material taking device is obtained and the material taking information is sent to the material taking device, and the material taking route is determined based on the position information and the material taking information of the material taking device. By planning the material taking route, the material taking device can accurately obtain the raw materials required for cement preparation. The material taking device is controlled to move to the position of the raw materials based on the material taking route, and the material taking device is controlled to obtain the raw materials based on the material taking method, which effectively reduces the occurrence of wrong raw materials and improves the efficiency of material taking.

[0024] In another possible implementation, controlling the raw meal preparation equipment to prepare the raw meal based on the raw material, and controlling the detection device to detect the raw meal, comprises:

[0025] Controlling the material taking device to transport the raw material to the raw material preparation device, and controlling the raw material preparation device to prepare the raw material based on the raw material;

[0026] Controlling the raw meal preparation equipment to prepare the raw meal based on the raw material;

[0027] After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data;

[0028] Determining whether the fineness detection data is within a standard fineness range;

[0029] If not, determining whether the raw material preparation equipment fails;

[0030] If a fault occurs, a warning message is output and the preparation of the raw material preparation equipment is stopped;

[0031] If no failure occurs, the raw material preparation equipment is controlled in a loop to prepare the raw material based on the raw material. After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data. It is determined whether the fineness detection data is within the standard fineness range. If not, it is determined whether the raw material preparation equipment has a failure. If a failure occurs, a warning message is output and the preparation steps of the raw material preparation equipment are stopped until it is within the standard fineness range or the raw material preparation equipment fails.

[0032] By adopting the above technical solution, the material taking equipment is controlled to transport the raw materials to the raw material preparation equipment, and the raw material preparation equipment is controlled to prepare raw materials based on the raw materials. After the preset time of raw material preparation, the detection device is controlled to detect the fineness of the raw materials and generate fineness detection data. The fineness will directly affect the quality of the cement prepared later. It is judged whether the fineness detection data is within the standard fineness range. If not, it is judged whether the raw material preparation equipment has a fault. If a fault occurs, it means that the raw material preparation equipment may not grind the raw materials, output a warning message and stop the preparation of the raw material preparation equipment. If no fault occurs, the raw material preparation continues and the detection device is controlled to detect the raw material until the fineness detection data of the raw material is within the fineness standard range, or the raw material preparation equipment fails, so as to ensure that the raw material prepared by the raw material preparation equipment can meet the cement preparation standard, thereby reducing the waste rate of cement.

[0033] In another possible implementation, the determining whether the raw material preparation equipment fails includes:

[0034] Acquiring the current time, the start time of the raw material preparation equipment, and the sound information of the raw material preparation equipment;

[0035] Calculating the operation time of the raw material preparation equipment based on the raw material preparation time and the current time;

[0036] Determine whether the running time is greater than the reasonable preparation time of the raw material, and determine whether the sound information is within a reasonable running decibel range during the running time;

[0037] If the operation time is not greater than the reasonable preparation time of the raw material, and the operation sound information is within the reasonable operation decibel range, it is determined that the raw material preparation equipment has not failed;

[0038] If the operating time is greater than the reasonable preparation time of the raw meal, and / or the operating sound information is not within the reasonable operating decibel range, it is determined that the raw meal preparation equipment has a fault.

[0039] By adopting the above technical solution, the current time, the start time of the raw material preparation equipment and the operation sound information of the raw material preparation equipment are obtained, the operation time of the raw material preparation equipment is calculated based on the start time and the current time, and it is judged whether the operation time is greater than the reasonable preparation time to determine whether the raw material preparation is overtime, and whether the operation sound information is within the reasonable operation decibel range during the operation time, so as to determine whether the internal grinding device of the raw material preparation equipment is broken or other faults. If the operation time is not greater than the reasonable preparation time of the raw material, and the operation sound information is within the reasonable operation decibel range, it means that the raw material preparation equipment has not failed, and the raw material needs to be continued to be prepared; if the operation time is greater than the reasonable preparation time of the raw material, and / or the operation sound information is not within the reasonable operation decibel range, it means that the raw material preparation equipment has failed and needs to be repaired in time.

[0040] In another possible implementation, the raw meal preparation equipment is controlled to prepare the raw meal based on the raw material, and the detection device is controlled to detect the raw meal, and then the method further includes:

[0041] If the fineness detection data is within the standard fineness range and the raw material preparation equipment has not failed, the cement preparation equipment is controlled to prepare the cement based on the raw material.

[0042] By adopting the above technical solution, if the fineness detection data is within the standard fineness range and the raw material preparation equipment has not failed, the cement preparation equipment is controlled to prepare cement based on the raw material, and the cement preparation is completed through the equipment in the cement production line.

[0043] In another possible implementation, the controlling the cement preparation equipment to prepare the cement based on the raw material further includes:

[0044] Obtaining quality inspection data of the cement;

[0045] Determine whether the quality inspection data meets the data required by the project;

[0046] If the data required by the project are met, the qualified information of the cement is output;

[0047] If the data required for the project is not met, then judging whether the quality inspection data meets the minimum standards for cement preparation;

[0048] If the minimum standard is met, outputting the unqualified information of the cement;

[0049] If the minimum standard is not met, the discard information of the cement is output.

[0050] By adopting the above technical solution, the quality inspection data of cement is obtained, and it is determined whether the quality inspection data meets the data required by the project, and then it is determined whether the cement can be used in the project. If the data required by the project is met, the qualified information of the cement is output to inform the staff that the cement preparation has been completed; if the data required by the project is not met, it is determined whether the quality inspection data meets the minimum standard for cement preparation. If the minimum standard is met, the unqualified information of the cement is output to inform the staff that the cement cannot be used in the project, but can still be used in other minor projects. If the minimum standard is not met, the discarded information of the cement is output to inform the staff that the cement cannot be used in all civil engineering projects. The corresponding information is output based on the quality inspection data, so that the staff can easily know the application of the cement.

[0051] In the second aspect, the present application provides a new dry process cement production control system based on a cloud platform, which adopts the following technical solutions:

[0052] A new dry process cement production control system based on cloud platform, including:

[0053] An image acquisition module is used to acquire image information of a stockpile yard, wherein the image information of the stockpile yard includes an image of raw material accumulation;

[0054] A determination module, used to determine a material taking method of the raw materials based on the stockyard image information;

[0055] A first control module, used for controlling the material taking device to obtain the raw material based on the material taking method;

[0056] The second control module is used to control the raw material preparation equipment to prepare raw material based on the raw material, and control the detection device to detect the raw material.

[0057] By adopting the above technical solution, the image acquisition module acquires the image information of the stockyard to obtain the stacking method of the raw materials in the stockyard. The raw materials can achieve a better homogenization effect by adopting different stacking methods. The determination module determines the material collection method of the raw materials based on the image information of the stockyard, reducing the workload of manually selecting the material collection method, selecting the corresponding material collection method for different stacking methods, and controlling the material collection equipment to obtain the raw materials based on the material collection method through the first control module, so that the material collection equipment can select all the material layers of the raw materials as much as possible. The second control module controls the raw material preparation equipment to prepare raw materials based on the raw materials, and controls the detection device to detect the raw materials, so that there is no need to manually detect the raw materials, thereby improving the processing speed of the raw materials.

[0058] In another possible implementation, when the determination module determines the material taking method based on the stockyard image information, it is specifically used to:

[0059] Performing grayscale conversion on the stockpile yard image information to obtain grayscale information of the stockpile yard image information;

[0060] Determine threshold information for binarization processing based on the grayscale information;

[0061] Binarizing the stockpile image information based on the threshold information to obtain stockpile shape information;

[0062] A corresponding material taking method is determined based on the pile shape information.

[0063] In another possible implementation, when the first control module controls the material taking device to obtain the raw material based on the material taking method, it is specifically used to:

[0064] Acquire the position information of the material taking device and send the material taking information to the material taking device;

[0065] Determine a material taking route based on the location information of the material taking equipment and the material taking information;

[0066] Controlling the material taking device to move to the location of the raw material based on the material taking route;

[0067] The material taking device is controlled to obtain the raw material based on the material taking method.

[0068] In another possible implementation, when the second control module controls the raw material preparation equipment to prepare the raw material based on the raw material and controls the detection device to detect the raw material, it is specifically used to:

[0069] Controlling the material taking device to transport the raw material to the raw material preparation device, and controlling the raw material preparation device to prepare the raw material based on the raw material;

[0070] Controlling the raw meal preparation equipment to prepare the raw meal based on the raw material;

[0071] After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data;

[0072] Determining whether the fineness detection data is within a standard fineness range;

[0073] If not, determining whether the raw material preparation equipment fails;

[0074] If a fault occurs, a warning message is output and the preparation of the raw material preparation equipment is stopped;

[0075] If no failure occurs, the raw material preparation equipment is controlled in a loop to prepare the raw material based on the raw material. After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data. It is determined whether the fineness detection data is within the standard fineness range. If not, it is determined whether the raw material preparation equipment has a failure. If a failure occurs, a warning message is output and the preparation steps of the raw material preparation equipment are stopped until it is within the standard fineness range or the raw material preparation equipment fails.

[0076] In another possible implementation, when determining whether the raw material preparation equipment fails, the second control module is specifically configured to:

[0077] Acquiring the current time, the start time of the raw material preparation equipment, and the operation sound information of the raw material preparation equipment;

[0078] Calculating the operation time of the raw material preparation equipment based on the start time and the current time;

[0079] Determine whether the operation time is greater than the reasonable preparation time of the raw material, and determine whether the operation sound information is within a reasonable operation decibel range during the operation time;

[0080] If the operation time is not greater than the reasonable preparation time of the raw material, and the operation sound information is within the reasonable operation decibel range, it is determined that the raw material preparation equipment has not failed;

[0081] If the operating time is greater than the reasonable preparation time of the raw meal, and / or the operating sound information is not within the reasonable operating decibel range, it is determined that the raw meal preparation equipment has a fault.

[0082] In another possible implementation, the system further includes:

[0083] The third control module is used for controlling the cement preparation equipment to prepare the cement based on the raw material when the fineness detection data is within the standard fineness range and the raw material preparation equipment has not failed.

[0084] In another possible implementation, the system further includes:

[0085] A data acquisition module is used to acquire the quality inspection data of the cement;

[0086] A first judgment module is used to judge whether the quality inspection data meets the data required by the project;

[0087] A first output module, used for outputting the qualified information of the cement when the data required by the project is met;

[0088] A second judgment module is used to judge whether the quality inspection data meets the minimum standard for cement preparation when the data required by the project is not met;

[0089] A second output module, for outputting unqualified information of the cement when the minimum standard is met;

[0090] The third output module is used to output the discard information of the cement when the minimum standard is not met.

[0091] In a third aspect, the present application provides an electronic device, which adopts the following technical solution:

[0092] An electronic device, comprising:

[0093] one or more processors;

[0094] Memory;

[0095] One or more applications, wherein one or more applications are stored in a memory and configured to be executed by one or more processors, and one or more applications are configured to: execute a new dry cement production control method based on a cloud platform as shown in any possible implementation of the first aspect.

[0096] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution:

[0097] A computer-readable storage medium, comprising: a computer program that can be loaded and executed by a processor to implement a new dry cement production control method based on a cloud platform as shown in any possible implementation of the first aspect.

[0098] In summary, the present application includes at least one of the following beneficial technical effects:

[0099] 1. Obtain the image information of the stockpile to obtain the stacking method of the raw materials in the stockpile. The raw materials can achieve better homogenization effects by adopting different stacking methods. Determine the material fetching method based on the image information of the stockpile, which reduces the workload of manually selecting the material fetching method, selects the corresponding material fetching method for different stacking methods, and controls the material fetching equipment to obtain the raw materials based on the material fetching method, so that the material fetching equipment can select all the material layers of the raw materials as much as possible. Control the raw material preparation equipment to prepare raw materials based on the raw materials, and control the detection device to detect the raw materials. Manual detection of the raw materials is no longer required, thereby improving the processing speed of the raw materials;

[0100] 2. Control the material taking equipment to transport the raw materials to the raw material preparation equipment, control the raw material preparation equipment to prepare raw materials based on the raw materials, and control the detection device to detect the fineness of the raw materials after a preset time, and generate fineness detection data. The fineness will directly affect the quality of the cement prepared later. Determine whether the fineness detection data is within the standard fineness range. If not, determine whether the raw material preparation equipment has a fault. If a fault occurs, it means that the raw material preparation equipment may not grind the raw materials, output a warning message and stop the preparation of the raw material preparation equipment. If no fault occurs, continue to prepare the raw material and control the detection device to detect the raw material until the fineness detection data of the raw material is within the standard fineness range, or the raw material preparation equipment fails, to ensure that the raw material prepared by the raw material preparation equipment can meet the cement preparation standard, thereby reducing the waste rate of cement. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 It is a flow chart of a new dry process cement production control method based on a cloud platform in an embodiment of the present application.

[0102] Figure 2 It is a flow chart of a new type of dry process cement production control system based on a cloud platform in an embodiment of the present application.

[0103] Figure 3 It is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0104] The following is combined with Figure 1-3 This application is described in further detail.

[0105] After reading this specification, those skilled in the art may make non-creative modifications to this embodiment as needed, but such modifications are protected by patent law as long as they are within the scope of the claims of this application.

[0106] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0107] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0108] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0109] The embodiment of the present application provides a new dry process cement production control method based on a cloud platform, which is executed by an electronic device, which can be a server or a terminal device, wherein the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud computing services. The terminal device can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and the embodiment of the present application does not limit this. Figure 1 As shown, the method includes step S101, step S102, step S103 and step S104, wherein:

[0110] Step S101, acquiring stockpile yard image information.

[0111] The stockpile image information includes images of raw material stacking.

[0112] For the embodiment of the present application, a monitoring device is installed in the greenhouse of the stockpile, and the electronic device can obtain the stockpile image information collected by the monitoring device based on the 5G network, and the electronic device can also obtain the stockpile image information uploaded to the cloud platform, which is not limited here. The stockpile image information includes at least one image of raw material accumulation, for example, for the preparation of silicate cement, the raw materials used are lime raw materials and clay raw materials.

[0113] Step S102, determining a method for taking raw materials based on the stockpile yard image information.

[0114] For the embodiments of the present application, the raw materials can achieve a better homogenization effect by adopting different stacking methods. The electronic equipment determines the stacking method of the raw materials based on the image information of the stockpile yard, and then determines the material collection method according to the stacking method, thereby reducing the workload of manually selecting the material collection method. Among them, the stacking methods of the raw materials include herringbone stacking method, wavy stacking method, horizontal layer stacking method, transverse inclined layer stacking method, longitudinal inclined layer stacking method and Chevcon stacking method. The material collection methods include end face collection, side collection and bottom collection.

[0115] Step S103, controlling the material taking device to obtain raw materials based on the material taking method.

[0116] For the embodiment of the present application, the reclaiming device can be a bridge scraper reclaimer, a bridge disc reclaimer or a rake reclaimer, which is not limited here. The electronic device controls the reclaiming device to obtain raw materials based on the reclaiming method, so that the reclaiming device can select all layers of the raw materials as much as possible.

[0117] Step S104, controlling the raw meal preparation equipment to prepare raw meal based on the raw materials, and controlling the detection device to detect the raw meal.

[0118] For the embodiment of the present application, the electronic device controls the raw material preparation equipment to prepare raw material based on the raw material, and the electronic device controls the detection device to detect the raw material. The raw material preparation equipment can be a raw material mill, and the electronic device controls the raw material mill to grind the raw material. When the electronic device detects the raw material, the electronic device can set the detection time, or randomly sample the raw material at any time, and the electronic device controls the discharge port for detection to open for sampling, and after the sampling is completed, the detection device is controlled to detect the sample.

[0119] In a possible implementation of the embodiment of the present application, in step S102, the material taking method of the raw material is determined based on the stockpile yard image information, specifically including step S1021 (not shown in the figure), step S1022 (not shown in the figure), step S1023 (not shown in the figure) and step S1024 (not shown in the figure), wherein:

[0120] Step S1021, performing grayscale conversion on the stockpile yard image information to obtain grayscale information of the stockpile yard image information.

[0121] For the embodiment of the present application, the stockyard image information acquired by the electronic device is a color image, and the color image is presented by superimposing the channel changes of the three colors of red (R), green (G) and blue (B). The electronic device performs grayscale conversion on the stockyard image information, that is, converts three channels into one channel, so that the stockyard image information is in black and white. The electronic device averages the RGB values ​​of the same pixel position of the stockyard image information, or averages the maximum and minimum values, performs grayscale conversion calculation, and obtains the grayscale information of the stockyard image information, so that the grayscale information of the stockyard image information is a grayscale value between 0 and 255.

[0122] Step S1022, determining threshold information for binarization processing based on the grayscale information.

[0123] For the embodiment of the present application, the electronic device can define the area of ​​the stockpile image information based on the grayscale information of the stockpile image information. The electronic device can determine the threshold information based on the law, that is, divide the image into two groups using a certain assumed grayscale value. When the inter-class variance of the two groups of images is the largest, the grayscale value at this time is the optimal threshold for image binarization.

[0124] Step S1023, binarizing the stockpile image information based on the threshold information to obtain stockpile shape information.

[0125] For the embodiments of the present application, based on the threshold information of the binarization processing, the electronic device can perform global fixed threshold processing on the stockpile image information, and the electronic device uses a unified threshold to perform binarization processing on the entire enhanced image; the electronic device can also perform local adaptive threshold processing on the stockpile image information, and the electronic device determines the binarization threshold of the pixel position according to the pixel value distribution of the pixel's neighborhood block, so that the binarization threshold of the image area with higher brightness is also higher, and the binarization threshold of the image area with lower brightness is also lower, and different threshold processing is used for images with different brightness, contrast and texture.

[0126] The electronic device performs binarization processing on the stockpile image information to obtain the stockpile shape information. The electronic device can segment the stockpile image information based on the stockpile shape information, segment the stockpile image information into a plurality of sub-images, each of which contains a stockpile shape information, match each stockpile shape information with the shape information in the database, and then determine the stockpile shape information in each sub-image. The stockpile shape information includes herringbone and wave shapes, etc.

[0127] Step S1024, determining a corresponding material taking method based on the pile shape information.

[0128] For the embodiment of the present application, the electronic device determines the stacking mode of the raw materials based on the stacking shape information, and then determines the material removal mode according to the stacking mode. For example:

[0129] The electronic device determines that the shape information of the stacking is a herringbone, and the electronic device determines that the stacking method corresponding to the herringbone is the herringbone stacking method. The electronic device can obtain the material picking method corresponding to the herringbone stacking method from the database or from the cloud platform, and the material picking method corresponding to the herringbone stacking method includes end face picking.

[0130] In a possible implementation of the embodiment of the present application, in step S103, the material taking device is controlled to obtain the raw material based on the material taking method, which specifically includes step S1031 (not shown in the figure), step S1032 (not shown in the figure), step S1033 (not shown in the figure) and step S1034 (not shown in the figure), wherein:

[0131] Step S1031, obtaining the position information of the material picking device and sending the material picking information to the material picking device.

[0132] For the embodiments of the present application, a locator may be installed on the material picking device, and the electronic device obtains the location information sent by the locator, and then obtains the location information of the material picking device. The electronic device may also obtain the location information of the material picking device through satellite positioning, which is not limited here. In the stockpile yard, a corresponding signal transmitter is installed at each position where the raw materials are piled, and the type of raw materials corresponding to each position is bound to the signal transmitter. The electronic device obtains the type of cement that needs to be prepared, and then determines the corresponding raw materials from the database or cloud platform, and controls the signal transmitter at the location of the raw materials to send the material picking information to the material picking equipment. The type of cement can be the type obtained by the electronic device by obtaining the user input, or it can be the type obtained by the electronic device by analyzing engineering information. For example:

[0133] When the electronic device obtains the user input that the type of cement to be prepared is silicate cement, the electronic device determines from the cloud platform that the raw materials required for preparing silicate are lime raw materials and clay raw materials. Among them, the raw materials corresponding to signal transmitter 1 are lime raw materials, and the raw materials corresponding to signal transmitter 2 are clay raw materials. Then the electronic device controls signal transmitter 1 and signal transmitter 2 to send material collection information to the material collection device.

[0134] Step S1032, determining a material picking route based on the location information of the material picking equipment and the material picking information.

[0135] For the embodiment of the present application, the electronic device determines the material taking route based on the location information and material taking information of the material taking device, the electronic device traverses the internal map of the entire stockpile yard, and determines the order of taking materials according to the number of the signal transmitter. The electronic device can determine the material taking route through the Dijkstra algorithm, and the electronic device can also determine the material taking route through the Bellford algorithm, the Floyd algorithm, etc. Take step S1031 as an example:

[0136] The electronic device determines according to the number of the signal transmitter that the material picking device should first go to signal transmitter 1 to pick up materials, and then go to signal transmitter 2 to pick up materials. The electronic device then determines the material picking route through the Dijkstra algorithm.

[0137] Step S1033, controlling the material taking equipment to move to the location of the raw material based on the material taking route.

[0138] In the embodiment of the present application, the electronic device controls the material taking device to move to the location of the raw material based on the material taking route. Taking step S1032 as an example:

[0139] The electronic device controls the material picking device to first move to the position of the signal transmitter 1 based on the material picking route, and then move to the position of the signal transmitter 2.

[0140] Step S1034, controlling the material taking device to obtain raw materials based on the material taking method.

[0141] For the embodiment of the present application, the electronic device controls the material taking device to obtain the raw material based on the material taking method, taking step S1031 and step S1024 as an example:

[0142] The electronic device at the position of the signal transmitter 1 obtains the lime raw material by means of the end face material taking method, and the electronic device at the position of the signal transmitter 2 obtains the clay raw material by means of the end face material taking method.

[0143] In a possible implementation of the embodiment of the present application, step S104 controls the raw material preparation equipment to prepare raw material based on the raw material, specifically including step S1041 (not shown in the figure), step S1042 (not shown in the figure), step S1043 (not shown in the figure), step S1044 (not shown in the figure), step S1045 (not shown in the figure) and step S1046 (not shown in the figure), wherein:

[0144] Step S1041, controlling the material taking equipment to transport the raw materials to the raw material preparation equipment, and controlling the raw material preparation equipment to prepare raw materials based on the raw materials.

[0145] In the embodiment of the present application, the position of the raw material preparation equipment in the cement production line is fixed, and the electronic device controls the material taking equipment to transport the raw materials to the raw material preparation equipment along a fixed route. The material taking equipment transports the raw materials to the raw material preparation equipment, and the electronic device can obtain image information of the raw material preparation equipment, analyze the image information, and then determine whether the raw material preparation equipment has assembled the raw materials. If assembled, the raw material preparation equipment is controlled to start, and the raw materials are prepared based on the raw materials.

[0146] Step S1042, after a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data.

[0147] In the embodiment of the present application, the electronic device controls the detection device to detect the fineness of the raw material after a preset time, and generates fineness detection data. Taking step S104 as an example:

[0148] A fineness tester is provided at the discharge port for testing. After the raw material is prepared for a preset time, the electronic device controls the detection device to detect the fineness of the raw material. Assuming the preset time is 1 hour, the electronic device obtains the image information of the discharge port, and determines whether the sampling is completed based on the image information. If the electronic device determines that the sampling has been completed, the electronic device controls the fineness tester to test the fineness of the sample. After the fineness test is completed, the electronic device obtains the test data of the tester and generates fineness detection data based on the test data. For example:

[0149] The fineness test data generated by the electronic equipment is: Fineness of Portland cement raw material: specific surface area 298㎡ / kg.

[0150] Step S1043, determining whether the fineness detection data is within the standard fineness range.

[0151] For the embodiment of the present application, the electronic device determines whether the fineness detection data is within the standard fineness range. The electronic device can obtain the standard fineness range from a database or from a cloud platform, which is not limited here. Taking step S1042 as an example:

[0152] The electronic device obtains the standard fineness range of silicate cement from the cloud platform: the specific surface area is greater than 300㎡ / kg, and the electronic device determines that the fineness detection data is not within the standard fineness range. If the fineness detection data is assumed to be 312㎡ / kg, the electronic device determines that the fineness detection data is within the standard fineness range.

[0153] Step S1044: If not, determine whether the raw material preparation equipment fails.

[0154] For the embodiment of the present application, the electronic device determines that the fineness detection data is not within the standard fineness range, and then the electronic device determines whether the raw material preparation equipment has a fault, and then determines whether the cement production line can successfully prepare cement.

[0155] Step S1045: if a fault occurs, a warning message is output and the preparation of the raw material preparation equipment is stopped.

[0156] For the embodiment of the present application, if the electronic device determines that the raw material preparation equipment has failed, the electronic device outputs a warning message. The electronic device may send a text message of "raw material preparation equipment failure" to the terminal device of the staff member, or the electronic device may control the speaker to send a voice message of "raw material preparation equipment failure", or other forms of warning messages, which are not limited here. After the electronic device determines that the raw material preparation equipment has failed, it stops the preparation of the raw material preparation equipment in a timely manner to reduce multiple damages to the raw material preparation equipment.

[0157] Step S1046, if no fault occurs, the raw material preparation equipment is controlled to prepare raw material based on the raw material in a loop, and after a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data, and it is determined whether the fineness detection data is within the standard fineness range. If not, it is determined whether the raw material preparation equipment has a fault. If a fault occurs, a warning message is output and the preparation steps of the raw material preparation equipment are stopped until it is within the standard fineness range or the raw material preparation equipment fails.

[0158] For the embodiment of the present application, if the electronic device determines that the raw material preparation device has not failed, the electronic device continues to control the raw material preparation device to prepare raw material based on the raw material. Taking step S1043 as an example:

[0159] The electronic device controls the raw meal preparation equipment to prepare raw meal based on the raw material, and after a preset time, controls the detection device to detect the fineness of the raw meal and generates fineness detection data. Assuming that the fineness detection data is a specific surface area of ​​298 m2 / kg, the electronic device determines that the fineness detection data is not within the standard fineness range, and determines whether the raw meal preparation equipment has a fault. Assuming that no fault has occurred, the electronic device continues to control the raw meal preparation equipment to prepare raw meal based on the raw material;

[0160] The electronic device controls the raw meal preparation equipment to prepare raw meal based on the raw material, and after a preset time, controls the detection device to detect the fineness of the raw meal and generates fineness detection data. Assuming that the fineness detection data is 300 m2 / kg of specific surface area, the electronic device determines that the fineness detection data is not within the standard fineness range, and determines whether the raw meal preparation equipment has a fault. Assuming that no fault has occurred, the electronic device continues to control the raw meal preparation equipment to prepare raw meal based on the raw material;

[0161] The electronic device controls the raw meal preparation equipment to prepare raw meal based on the raw materials. After a preset time, the detection device is controlled to detect the fineness of the raw meal and generate fineness detection data. Assuming that the fineness detection data is a specific surface area of ​​301 m2 / kg, the electronic device determines that the fineness detection data is within the standard fineness range.

[0162] In another achievable manner of this embodiment, taking step S1043 as an example:

[0163] The electronic device controls the raw meal preparation equipment to prepare raw meal based on the raw materials. After a preset time, the detection device is controlled to detect the fineness of the raw meal and generate fineness detection data. Assuming that the fineness detection data is a specific surface area of ​​298 m2 / kg, the electronic device determines that the fineness detection data is not within the standard fineness range and determines whether the raw meal preparation equipment has a fault. Assuming a fault occurs, the electronic device outputs a warning message and stops the preparation of the raw meal preparation equipment.

[0164] In a possible implementation of the embodiment of the present application, it is determined in step S1044 whether the raw material preparation equipment fails, specifically including step S1044a (not shown in the figure), step S1044b (not shown in the figure), step S1044c (not shown in the figure), step S1044d (not shown in the figure) and step S1044e (not shown in the figure), wherein:

[0165] Step S1044a, obtaining the current time, the start time of the raw material preparation equipment and the operation sound information of the raw material preparation equipment.

[0166] For the embodiments of the present application, the electronic device can obtain the current time from the built-in clock chip of the electronic device, and can also obtain the current time through the Internet and cloud servers, which are not limited here. The electronic device can obtain the start time of the raw material preparation equipment from the cloud platform, and can also obtain the start time of the raw material preparation equipment from the database, which are not limited here. The electronic device can obtain the operation sound information from the decibel sensor installed on the raw material preparation equipment, and the electronic device can also obtain the operation sound information by other means. For example:

[0167] The current time acquired by the electronic device is 10:00, the start time of the raw material preparation equipment when preparing raw material based on the raw material for the first time is 9:00, and the operating sound information is 88 decibels.

[0168] Step S1044b, calculating the running time of the raw material preparation equipment based on the start time and the current time.

[0169] For the embodiment of the present application, the electronic device calculates the running time of the raw material preparation device based on the start time and the current time, taking step S1044a as an example:

[0170] Running time = 10:00-9:00 = 1 hour.

[0171] Step S1044c, determining whether the operation time is greater than the reasonable preparation time of the raw material, and determining whether the operation sound information during the operation time is within the reasonable operation decibel range.

[0172] For the embodiments of the present application, the electronic device can obtain the reasonable preparation time and the reasonable operating decibel range from the database. The electronic device can also obtain the reasonable preparation time and the reasonable operating decibel range from the cloud platform, which is not limited here.

[0173] Take step S1044b as an example: the electronic device obtains a reasonable preparation time of 2 hours from the database, then the electronic device determines that 1 hour is not greater than the reasonable preparation time. Assuming the running time is 2.5 hours, the electronic device determines that the running time is greater than the reasonable preparation time.

[0174] Take step S1044a as an example: the electronic device obtains a reasonable operating decibel range of 80 to 115 decibels from the database, then the electronic device determines that 120 decibels is not within the reasonable operating decibel range. Assuming that the operating sound information is 110 decibels, the electronic device determines that it is within the reasonable operating decibel range.

[0175] Step S1044d: if the operation time is not greater than the reasonable preparation time of the raw material, and the operation sound information is within the reasonable operation decibel range, it is determined that the raw material preparation equipment has not failed.

[0176] For the embodiment of the present application, if the electronic device determines that the operation time is not greater than the reasonable preparation time, and the operation sound information is within the reasonable operation decibel range, the electronic device determines that the raw material preparation equipment has not failed. Taking step S1044c as an example:

[0177] If the operating time is 1.5 hours and the operating sound information is 110 decibels, the electronic device determines that the raw material preparation equipment has not failed.

[0178] Step S1044e: if the operation time is greater than the reasonable preparation time of the raw meal, and / or the operation sound information is not within the reasonable operation decibel range, it is determined that the raw meal preparation equipment has a fault.

[0179] For the embodiment of the present application, if the electronic device determines that the running time is greater than the reasonable preparation time, and / or the running sound information is not within the reasonable running decibel, the electronic device determines that the raw material preparation equipment has failed. If the running time is too long, but the fineness detection data still does not meet the standard, the raw material preparation equipment may have failed; if the raw material preparation equipment makes a loud noise during operation, the internal facilities may be broken, or the sound is low during operation, and there is basically no grinding sound, the raw material preparation equipment may have failed. Take step S1044c as an example:

[0180] If the operating time is 2.5 hours and the operating sound information is 120 decibels, the electronic device determines that the raw material preparation equipment has a fault.

[0181] In a possible implementation manner of the embodiment of the present application, the method further includes step S105 (not shown in the figure), which may be performed after step S104, wherein:

[0182] Step S105: If the fineness detection data is within the standard fineness range and the raw material preparation equipment has not failed, the cement preparation equipment is controlled to prepare cement based on the raw material.

[0183] For the embodiment of the present application, if the electronic device determines that the fineness detection data is within the standard fineness range and the raw material preparation equipment has not failed, it means that the raw material preparation is qualified and the next step of the cement production line can be prepared. The electronic device controls the cement preparation equipment to prepare cement based on the raw material. The cement preparation equipment may include clinker preparation equipment, etc.

[0184] In a possible implementation manner of the embodiment of the present application, the method further includes step S106 (not shown in the figure), step S107 (not shown in the figure), step S108 (not shown in the figure), step S109 (not shown in the figure), step S110 (not shown in the figure) and step S111 (not shown in the figure), wherein:

[0185] Step S106, obtaining cement quality inspection data.

[0186] For the embodiments of the present application, the electronic device can obtain the quality inspection data manually input by the user, or the electronic device can obtain the quality inspection data sent by the inspection device, and the quality inspection data may include chemical composition inspection, hardness inspection, and coagulation time, etc. For example:

[0187] The electronic device obtains the quality inspection data input by the user: the specific surface area of ​​silicate cement is 310 m2 / kg, magnesium oxide is 5%, sulfur trioxide is 3%, the initial setting time is 46 minutes, and the final setting time is 6.5 hours.

[0188] Step S107, determining whether the quality inspection data meets the data required for the project.

[0189] For the embodiment of the present application, the electronic device can obtain the data required for the project from the database, or from the cloud platform. Taking step S106 as an example:

[0190] The data required for the project obtained by the electronic equipment from the cloud platform are: the specific surface area of ​​silicate cement is greater than 310㎡ / kg, the magnesium oxide content is less than or equal to 5%, the sulfur trioxide is less than or equal to 3%, the initial setting time shall not be earlier than 45 minutes, and the final setting time shall not be later than 6.5 hours. It can be concluded that the quality inspection data meets the data required for the project.

[0191] Step S108: If the data required by the project is met, the qualified information of the cement is output.

[0192] For the embodiment of the present application, if the electronic device determines that the quality inspection data meets the data required for the project, the electronic device outputs the qualified information of the cement. The electronic device can send a text message of "the cement preparation is qualified" to the user's terminal device, and the electronic device can also control the speaker to send a voice message of "the cement preparation is qualified", which is not limited here. By outputting qualified information to inform the staff that the cement preparation has been completed, the cement can be applied to the project. Take step S106 and step S107 as an example:

[0193] The electronic device obtains that the quality inspection data input by the user meets the data required for the project, and sends a text message of "cement preparation is qualified" to the user's terminal device.

[0194] Step S109: If the data required by the project is not met, determine whether the quality inspection data meets the minimum standard for cement preparation.

[0195] For the embodiment of the present application, if the electronic device determines that the quality inspection data does not meet the data required by the project, the electronic device determines whether the quality inspection data meets the minimum standard for cement preparation. The electronic device can obtain the minimum standard for cement preparation from the database, or the electronic device can obtain the minimum standard for cement preparation from the cloud platform. Take step S107 as an example:

[0196] The electronic device obtains the quality inspection data input by the user: the specific surface area of ​​silicate cement is 310 m2 / kg, magnesium oxide is 5%, sulfur trioxide is 3.2%, the initial setting time is 44 minutes, and the final setting time is 6.5 hours.

[0197] The electronic equipment determined that the sulfur trioxide content and initial setting time of silicate cement in the quality inspection data did not meet the data required by the project. The electronic equipment obtained the minimum standard for cement preparation from the database: the specific surface area of ​​silicate cement is greater than 300 m2 / kg, the magnesium oxide content is less than or equal to 5%, the sulfur trioxide is less than or equal to 3.5%, the initial setting time shall not be earlier than 45 minutes, and the final setting time shall not be later than 6.5 hours. The electronic equipment judged that the initial setting time in the quality inspection data did not meet the minimum standard for cement preparation.

[0198] Step S110: If the minimum standard is met, unqualified information of cement is output.

[0199] For the embodiment of the present application, if the electronic device determines that the quality inspection data meets the minimum standard for cement preparation, the electronic device outputs the unqualified information of the cement, and the electronic device can send a text message of "unqualified cement preparation" to the user's terminal device, or the electronic device can control the speaker to send a voice message of "unqualified cement preparation", which is not limited here. By outputting the unqualified information of the cement, the staff is informed that the cement cannot be used in the project, but can still be used in other minor projects.

[0200] Step S111: if the minimum standard is not met, the discard information of the cement is output.

[0201] For the embodiment of the present application, if the electronic device determines that the quality inspection data does not meet the minimum standard for cement preparation, the electronic device outputs cement waste information, and the electronic device can send a text message of "cement waste" to the user's terminal device, or the electronic device can control the speaker to send a voice message of "cement waste", which is not limited here. By outputting cement waste information, the staff is informed that the cement cannot be used in all civil engineering projects.

[0202] The above-mentioned embodiment introduces a new dry-process cement production control method based on a cloud platform from the perspective of method flow. The following embodiment introduces a new dry-process cement production control system based on a cloud platform from the perspective of a virtual module or a virtual unit. For details, please refer to the following embodiment.

[0203] The present application embodiment provides a new dry process cement production control system 20 based on a cloud platform, such as Figure 2 As shown, a new dry process cement production control system 20 based on a cloud platform may specifically include:

[0204] An image acquisition module 201 is used to acquire image information of a stockpile yard, where the image information of the stockpile yard includes an image of raw material accumulation;

[0205] A determination module 202, for determining a material taking method based on the stockyard image information;

[0206] The first control module 203 is used to control the material taking device to obtain raw materials based on the material taking method;

[0207] The second control module 204 is used to control the raw meal preparation equipment to prepare raw meal based on the raw materials, and control the detection device to detect the raw meal.

[0208] By adopting the above technical solution, the image acquisition module 201 acquires the image information of the stockyard to obtain the stacking method of the raw materials in the stockyard. The raw materials can achieve a better homogenization effect by adopting different stacking methods. The determination module 202 determines the material collection method of the raw materials based on the image information of the stockyard, which reduces the workload of manually selecting the material collection method, selects the corresponding material collection method for different stacking methods, and controls the material collection equipment to obtain the raw materials based on the material collection method through the first control module 203, so that the material collection equipment can select all the material layers of the raw materials as much as possible. The second control module 204 controls the raw material preparation equipment to prepare raw materials based on the raw materials, and controls the detection device to detect the raw materials, so that there is no need to manually detect the raw materials, thereby improving the processing speed of the raw materials.

[0209] In a possible implementation of the embodiment of the present application, when the determination module 202 determines the material taking method based on the stockyard image information, it is specifically used to:

[0210] Performing grayscale conversion on the stockpile yard image information to obtain grayscale information of the stockpile yard image information;

[0211] Determine threshold information for binarization processing based on grayscale information;

[0212] Binarization is performed on the stockpile image information based on the threshold information to obtain the stockpile shape information;

[0213] Determine the corresponding material removal method based on the pile shape information.

[0214] In a possible implementation of the embodiment of the present application, when the first control module 203 controls the material taking device to take the raw material based on the material taking method, it is specifically used to:

[0215] Obtaining the location information of the material taking device and sending the material taking information to the material taking device;

[0216] Determine the material taking route based on the location information of the material taking equipment and the material taking information;

[0217] Controlling the material taking equipment to move to the location of the raw materials based on the material taking route;

[0218] Control the material taking equipment to obtain raw materials based on the material taking method.

[0219] In a possible implementation of the embodiment of the present application, when the second control module 204 controls the raw material preparation equipment to prepare the raw material based on the raw material and controls the detection device to detect the raw material, it is specifically used to:

[0220] Controlling the material taking device to transport the raw materials to the raw material preparation device, and controlling the raw material preparation device to prepare raw materials based on the raw materials;

[0221] Controlling the raw meal preparation equipment to prepare the raw meal based on the raw materials;

[0222] After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data;

[0223] Determine whether the fineness test data is within the standard fineness range;

[0224] If not, determine whether the raw material preparation equipment has failed;

[0225] If a fault occurs, a warning message is output and the preparation of the raw material preparation equipment is stopped;

[0226] If no fault occurs, the raw material preparation equipment is controlled to prepare raw material based on the raw materials, the fineness of the raw material is detected and fineness detection data is generated, and it is determined whether the fineness detection data is within the standard fineness range. If not, it is determined whether the raw material preparation equipment has a fault. If a fault occurs, a warning message is output and the preparation steps of the raw material preparation equipment are stopped until it is within the standard fineness range or the raw material preparation equipment fails.

[0227] In a possible implementation of the embodiment of the present application, when determining whether the raw material preparation equipment fails, the second control module 204 is specifically used to:

[0228] Obtain the current time, the start time of the raw material preparation equipment, and the operation sound information of the raw material preparation equipment;

[0229] Calculate the running time of the raw meal preparation equipment based on the start time and the current time;

[0230] Determine whether the operation time is greater than the reasonable preparation time of the raw material, and determine whether the operation sound information during the operation time is within the reasonable operation decibel range;

[0231] If the operation time is not greater than the reasonable preparation time of the raw meal, and the operation sound information is within the reasonable operation decibel range, it is determined that the raw meal preparation equipment has not failed;

[0232] If the operation time is greater than the reasonable preparation time of the raw meal, and / or the operation sound information is not within the reasonable operation decibel range, it is determined that the raw meal preparation equipment has failed.

[0233] In a possible implementation of the embodiment of the present application, the system 20 further includes:

[0234] The third control module is used to control the cement preparation equipment to prepare cement based on the raw material when the fineness detection data is within the standard fineness range and the raw material preparation equipment has no fault.

[0235] In a possible implementation of the embodiment of the present application, the system 20 further includes:

[0236] A data acquisition module is used to acquire cement quality inspection data;

[0237] The first judgment module is used to judge whether the quality inspection data meets the data required by the project;

[0238] The first output module is used to output cement qualification information when the data required by the project is met;

[0239] The second judgment module is used to judge whether the quality inspection data meets the minimum standard of cement preparation when the data required by the project is not met;

[0240] The second output module is used to output unqualified information of cement when the minimum standard is met;

[0241] The third output module is used to output cement discard information when the minimum standard is not met.

[0242] In the embodiment of the present application, the first control module 203, the second control module 204 and the third control module can be the same control module, or different control modules, or partially the same control modules. The first judgment module and the second judgment module can be the same judgment module, or different judgment modules. The first output module, the second output module and the third output module can be the same output module, or different output modules, or partially the same output modules.

[0243] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0244] An electronic device is provided in an embodiment of the present application, such as Figure 3 As shown, Figure 3 The electronic device 30 shown includes: a processor 301 and a memory 303. The processor 301 and the memory 303 are connected, such as through a bus 302. Optionally, the electronic device 30 may also include a transceiver 304. It should be noted that in actual applications, the transceiver 304 is not limited to one, and the structure of the electronic device 30 does not constitute a limitation on the embodiments of the present application.

[0245] The processor 301 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic devices, transistor logic devices, hardware components or any combination thereof. It may implement or execute various exemplary logic blocks, modules and circuits described in conjunction with the disclosure of this application. The processor 301 may also be a combination that implements computing functions. For example, it may include a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0246] The bus 302 may include a path to transmit information between the above components. The bus 302 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The bus 302 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0247] The memory 303 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, a RAM (Random Access Memory) or other types of dynamic storage devices that can store information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, optical disk storage (including compressed optical disk, laser disk, optical disk, digital versatile disk, Blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired application code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0248] The memory 303 is used to store the application code for executing the solution of the present application, and the execution is controlled by the processor 301. The processor 301 is used to execute the application code stored in the memory 303 to implement the contents shown in the above method embodiment.

[0249] The electronic devices include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), and fixed terminals such as digital TVs, desktop computers, etc. It can also be a server, etc. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0250] The embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run on a computer, the computer can execute the corresponding content in the aforementioned method embodiment. Compared with the related art, in the embodiment of the present application, the electronic device obtains the image information of the stockyard to obtain the stacking mode of the raw materials in the stockyard, and the raw materials can achieve a better homogenization effect by adopting different stacking modes. The electronic device determines the material collection mode of the raw materials based on the image information of the stockyard, which reduces the workload of manually selecting the material collection mode. For different stacking modes, the electronic device selects the corresponding material collection mode, and controls the material collection device to obtain the raw materials based on the material collection mode, so that the material collection device can select all the material layers of the raw materials as much as possible. The electronic device controls the raw material preparation equipment to prepare raw materials based on the raw materials, and controls the detection device to detect the raw materials. It is no longer necessary to manually detect the raw materials, thereby improving the processing speed of the raw materials.

[0251] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0252] The above description is only a partial implementation method of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A new dry process cement production control method based on cloud platform, characterized in that: include: Acquiring stockyard image information, wherein the stockyard image information includes an image of raw material accumulation; Determining a method for taking raw materials based on the stockpile image information; Controlling the material taking device to obtain the raw material based on the material taking method; Controlling the raw meal preparation equipment to prepare the raw meal based on the raw materials, and controlling the detection device to detect the raw meal; The controlling raw material preparation equipment to prepare raw material based on the raw material, and controlling the detection device to detect the raw material, comprises: Controlling the material taking device to transport the raw material to the raw material preparation device, and controlling the raw material preparation device to prepare the raw material based on the raw material; After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data; Determining whether the fineness detection data is within a standard fineness range; If not, determining whether the raw material preparation equipment fails; If a fault occurs, a warning message is output and the preparation of the raw material preparation equipment is stopped; If no failure occurs, the raw material preparation equipment is controlled in a loop to prepare the raw material based on the raw material. After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data. It is determined whether the fineness detection data is within the standard fineness range. If not, it is determined whether the raw material preparation equipment has a failure. If a failure occurs, a warning message is output and the preparation steps of the raw material preparation equipment are stopped until it is within the standard fineness range or the raw material preparation equipment fails.

2. A new dry process cement production control method based on cloud platform according to claim 1, characterized in that: The method of determining the material taking method based on the stockyard image information includes: Performing grayscale conversion on the stockpile yard image information to obtain grayscale information of the stockpile yard image information; Determine threshold information for binarization processing based on the grayscale information; Binarizing the stockpile image information based on the threshold information to obtain stockpile shape information; A corresponding material taking method is determined based on the pile shape information.

3. A new dry process cement production control method based on cloud platform according to claim 1, characterized in that: The controlling material taking device to obtain the raw material based on the material taking method includes: Acquire the position information of the material taking device and send the material taking information to the material taking device; Determine a material taking route based on the location information of the material taking equipment and the material taking information; Controlling the material taking device to move to the location of the raw material based on the material taking route; The material taking device is controlled to obtain the raw material based on the material taking method.

4. A new dry process cement production control method based on cloud platform according to claim 1, characterized in that: The determining whether the raw material preparation equipment fails comprises: Acquiring the current time, the start time of the raw material preparation equipment, and the operation sound information of the raw material preparation equipment; Calculating the operation time of the raw material preparation equipment based on the start time and the current time; Determine whether the operation time is greater than the reasonable preparation time of the raw material, and determine whether the operation sound information is within a reasonable operation decibel range during the operation time; If the operation time is not greater than the reasonable preparation time of the raw material, and the operation sound information is within the reasonable operation decibel range, it is determined that the raw material preparation equipment has not failed; If the operating time is greater than the reasonable preparation time of the raw meal, and / or the operating sound information is not within the reasonable operating decibel range, it is determined that the raw meal preparation equipment has a fault.

5. A new dry process cement production control method based on cloud platform according to claim 1, characterized in that: The raw material preparation equipment is controlled to prepare raw material based on the raw material, and the detection device is controlled to detect the raw material, and then further includes: If the fineness detection data is within the standard fineness range and the raw material preparation equipment has not failed, the cement preparation equipment is controlled to prepare the cement based on the raw material.

6. A new dry process cement production control method based on cloud platform according to claim 5, characterized in that: The controlling cement preparation device to prepare the cement based on the raw material further comprises: Obtaining quality inspection data of the cement; Determine whether the quality inspection data meets the data required by the project; If the data required by the project are met, the qualified information of the cement is output; If the data required for the project is not met, then judging whether the quality inspection data meets the minimum standards for cement preparation; If the minimum standard is met, outputting the unqualified information of the cement; If the minimum standard is not met, the discard information of the cement is output.

7. A new dry process cement production control system based on cloud platform, characterized in that: include: An image acquisition module is used to acquire image information of a stockpile yard, wherein the image information of the stockpile yard includes an image of raw material accumulation; A determination module, used to determine a material taking method of the raw materials based on the stockyard image information; A first control module, used for controlling the material taking device to obtain the raw material based on the material taking method; The second control module is used to control the material taking device to transport the raw material to the raw material preparation device, and control the raw material preparation device to prepare raw material based on the raw material; control the detection device to detect the fineness of the raw material after a preset time, and generate fineness detection data; and determine whether the fineness detection data is within the standard fineness range; If not, determining whether the raw material preparation equipment fails; If a fault occurs, a warning message is output and the preparation of the raw material preparation equipment is stopped; If no failure occurs, the raw material preparation equipment is controlled in a loop to prepare the raw material based on the raw material. After a preset time, the detection device is controlled to detect the fineness of the raw material and generate fineness detection data. It is determined whether the fineness detection data is within the standard fineness range. If not, it is determined whether the raw material preparation equipment has a failure. If a failure occurs, a warning message is output and the preparation steps of the raw material preparation equipment are stopped until it is within the standard fineness range or the raw material preparation equipment fails.

8. An electronic device, characterized in that: It includes: One or more processors; Memory; One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to: execute a new type of dry cement production control method based on a cloud platform according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a new type of dry cement production control method based on a cloud platform as described in any one of claims 1 to 6 is implemented.

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