Steel bar weight negative deviation measurement control system and method, electronic device and storage medium

Abstract

The application discloses a kind of steel weight negative deviation measurement control system, method, electronic equipment and storage medium, the system includes: bundle branch number review submodule, negative deviation calculation module and negative deviation control module;Bundle branch number review submodule obtains bundle steel branch number, and it is sent to production manufacturing system and weighing system;Negative deviation calculation module calculates the branch number difference according to bundle steel branch number and the rated number of production manufacturing system, calculates negative deviation measurement value according to theoretical weight and actual weight, and compares the size relationship of negative deviation measurement value and negative deviation control limit value;Negative deviation control module sends control signal to weighing system according to the size relationship of branch number difference, negative deviation measurement value and negative deviation control limit value.The technical scheme of the embodiment of the application ensures the accuracy of data in the production process, reduces the error and cost of manual counting, improves production efficiency and product quality.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of steel bar rolling, and particularly relates to a steel bar weight negative deviation measurement control system and method, an electronic device and a storage medium. BACKGROUND

[0002] Negative deviation rolling is to control the cross-sectional size of finished steel within the range of nominal size during rolling, and through reasonable negative deviation rolling, the yield can be improved without increasing investment, which is an important way to reduce cost and increase efficiency in the rolling production process, and steel users also have strong demand for it.

[0003] The deviation value between the actual weight and the theoretical weight of the steel bar is generally compared when the steel bar is completed and stored in the warehouse, and when the deviation exceeds the safe experience value, the offline processing is performed. The negative deviation control limit value is based on the premise that the rated bundle number is accurate data, and when the actual number deviates from the rated number, only the deviation value between the actual weight and the theoretical weight is used as the control basis, and there may be a risk of allowing deviation out of control. SUMMARY

[0004] The present application provides a steel bar weight negative deviation measurement control system and method, an electronic device and a storage medium to solve the problem of steel bar weight deviation out of control.

[0005] According to one aspect of the present application, a steel bar weight negative deviation measurement control system is provided, comprising: a bundle number review sub-module, a negative deviation calculation module and a negative deviation control module;

[0006] The bundle number review sub-module is connected with the negative deviation calculation module, and the bundle number review sub-module is connected with the production and manufacturing system and the weighing system through a system interface. The bundle number review sub-module is used to obtain bundle steel bar number data and send the bundle steel bar number data to the production and manufacturing system and the weighing system, and the bundle steel bar number data includes bundle steel bar number.

[0007] The negative deviation calculation module is connected with the negative deviation control module, and the negative deviation calculation module is used to calculate the number difference value according to the bundle steel bar number and the rated number of the production and manufacturing system, and obtain the theoretical weight value according to the actual number of the steel bar. The negative deviation measurement value is calculated according to the theoretical weight value and the actual weight, and the size relationship between the negative deviation measurement value and the negative deviation control limit value is compared.

[0008] The negative deviation control module is connected with the weighing system through a system interface, and the negative deviation control module is used to send a control signal to the weighing system according to the size relationship between the number difference value, the negative deviation measurement value and the negative deviation control limit value.

[0009] Optionally, the bundle count review submodule comprises a camera and an AI server.

[0010] The camera is arranged on a steel bundle weighing platform of the weighing system, and is configured to acquire image data of the end face of the bundle of steel bars.

[0011] The AI server is configured to determine the bundle steel bar count based on a pre-trained target recognition model according to the image data of the end face of the bundle of steel bars.

[0012] Optionally, the AI server is deployed with an AI algorithm, and the AI algorithm comprises a deep learning algorithm.

[0013] The target recognition model is obtained by the AI server, comprising:

[0014] The deep learning algorithm is used to learn from the field image data collected in the early stage of the project, and the image data is manually labeled to construct a training data set.

[0015] According to the constructed neural network and deep learning algorithm, the training data set is used for training to obtain the target recognition model.

[0016] Optionally, the steel weight negative deviation measurement control system further comprises a human-computer interaction control module, the human-computer interaction control module is connected with the negative deviation control module, and the human-computer interaction control module is configured to process the bundle of steel bars according to the control signal sent by the negative deviation control module.

[0017] According to another aspect of the present application, a steel weight negative deviation measurement control method is provided, characterized in that it is applied to the steel weight negative deviation measurement control system of any embodiment of the present application, and the steel weight negative deviation measurement control system further comprises a human-computer interaction control module, and the method comprises:

[0018] The bundle count review submodule acquires bundle steel bar count data and sends the bundle steel bar count data to the production and manufacturing system and the weighing system, and the bundle steel bar count data comprises the bundle steel bar count.

[0019] The negative deviation calculation module calculates the count difference value according to the bundle steel bar count and the rated count of the production and manufacturing system, and acquires the theoretical weight value according to the actual count of the steel bars.

[0020] The negative deviation calculation module calculates the negative deviation measurement value according to the theoretical weight value and the actual weight, and compares the size relationship between the negative deviation measurement value and the negative deviation control limit value; wherein the negative deviation control limit value comprises a negative deviation control lower limit value and a negative deviation control upper limit value.

[0021] The negative deviation control module sends a control signal to the weighing system according to the size relationship between the count difference value, the negative deviation measurement value and the negative deviation control limit value.

[0022] The human-computer interaction control module processes the bundled steel bars according to the control signal.

[0023] Optionally, the negative deviation control module sends a control signal to the weighing system according to the size relationship among the number difference, the negative deviation measurement value and the negative deviation control limit value, including:

[0024] If the number difference = 0 and the negative deviation control lower limit value < the negative deviation measurement value < the negative deviation control upper limit value, the negative deviation control module sends data of the bundled steel bar number equal to the rated number to the weighing system, and the bundled steel bar enters the next process link.

[0025] If the number difference ≠ 0, the negative deviation control module sends data of the rated number deviating from the rated value to the weighing system, and the bundled steel bar suspends entering the next process link.

[0026] Optionally, the human-computer interaction control module processes the bundled steel bars according to the control signal, including:

[0027] If the number difference = 0 and the negative deviation control lower limit value < the negative deviation measurement value < the negative deviation control upper limit value, the human-computer interaction control module displays the rated number, the actual number, the actual number theoretical weight value, the weighing value, the steel bar negative deviation actual measurement calculation value, the negative deviation control target value, the negative deviation control lower limit value and the negative deviation control upper limit value, and prompts “normal”.

[0028] If the number difference ≠ 0, the human-computer interaction control module displays the rated number, the actual number, the actual number theoretical weight value, the weighing value, the steel bar negative deviation actual measurement calculation value, the negative deviation control target value, the negative deviation control lower limit value and the negative deviation control upper limit value, and prompts “number deviation value”.

[0029] Optionally, if the number difference ≠ 0, the human-computer interaction control module displays the rated number, the actual number, the actual number theoretical weight value, the weighing value, the steel bar negative deviation actual measurement calculation value, the negative deviation control target value, the negative deviation control lower limit value and the negative deviation control upper limit value, and prompts “number deviation value”, including:

[0030] If the bundled steel bar is delivered with the theoretical weight, when the number difference ≠ 0, it is prompted “offline processing”, and the bundled steel bar needs to be unpacked and processed, and then is online again.

[0031] If the bundled steel bar is delivered with the actual weight, when the number difference ≠ 0, it is prompted “number confirmation”, a preset value is set, if the number difference is less than the preset value, it is confirmed through the human-computer interaction control module, and the bundled steel bar enters the next process link.

[0032] If the number difference is greater than the preset value, the bundled steel bar is unpacked and processed, and then is online again, and the bundled steel bar does not enter the next process link.

[0033] According to another aspect of the present application, there is provided an electronic device comprising:

[0034] at least one processor; and

[0035] a memory communicatively connected with the at least one processor; wherein

[0036] the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform the steel weight negative deviation measurement control method according to any one of the embodiments of the present application.

[0037] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to implement the steel weight negative deviation measurement control method according to any one of the embodiments of the present application when executed by the processor.

[0038] The technical scheme of the embodiments of the present application, by setting the bundle count review sub-module, the negative deviation calculation module and the negative deviation control module, the bundle count review sub-module obtains the bundle steel reinforcement count data, and sends it to the production manufacturing system and the weighing system, ensures the accuracy and real-time of the data in the production process, can reduce the error and cost of manual counting. The negative deviation calculation module can calculate the count difference and the negative deviation measurement value, and the negative deviation control module sends a control signal to the weighing system according to the size relationship of the count difference, the negative deviation measurement value and the negative deviation control limit value, compares and monitors the negative deviation measurement value and the control limit value, and sends the corresponding control signal to the weighing system according to the data. The technical scheme of the embodiments of the present application ensures the accuracy of the data in the production process, reduces the error and cost of manual counting, improves the product negative deviation control level, reduces the risk of out-of-tolerance products, and improves the production efficiency and product quality.

[0039] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0041] Figure 1It is a structural schematic diagram of a steel weight negative deviation measurement control system provided by an embodiment of the present application.

[0042] Figure 2 It is an application scenario diagram of a bale steel reinforcement count review sub-module provided by an embodiment of the present application.

[0043] Figure 3 It is a schematic diagram of a bale steel reinforcement end face obtained by a bale steel reinforcement count review sub-module provided by an embodiment of the present application.

[0044] Figure 4 It is a flowchart of a steel weight negative deviation measurement control method provided by an embodiment of the present application.

[0045] Figure 5 It is a structural schematic diagram of an electronic device implementing a steel weight negative deviation measurement control method. DETAILED DESCRIPTION

[0046] In order to enable personnel in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0047] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "include" and "have" and their variants are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0048] Figure 1 A structural schematic diagram of a steel weight negative deviation measurement control system is provided for an embodiment of the present application. The present embodiment can be applicable to steel rolling and building materials, etc. The system can be implemented in the form of hardware and / or software, and can be configured in a steel rolling device, a baling weighing device, an automatic production line and a comprehensive control system. As shown in the figure, the system includes a bale count review sub-module 101, a negative deviation calculation module 102 and a negative deviation control module 103. Figure 1 ​

[0049] The bundle quantity review sub-module 101 is connected with the negative deviation calculation module 102, the bundle quantity review sub-module 101 is connected with the production manufacturing system 106 and the weighing system 105 through the system interface, the bundle quantity review sub-module 101 is used for obtaining the bundle steel quantity data and sending the bundle steel quantity data to the production manufacturing system 106 and the weighing system 105, and the bundle steel quantity data includes the bundle steel quantity;

[0050] The negative deviation calculation module 102 is connected with the negative deviation control module 103, the negative deviation calculation module 102 is used for calculating the quantity difference according to the bundle steel quantity and the rated quantity of the production manufacturing system, and obtaining the theoretical weight value according to the actual steel quantity; the negative deviation measurement value is calculated according to the theoretical weight value and the actual weight, and the size relationship between the negative deviation measurement value and the negative deviation control limit value is compared;

[0051] The negative deviation control module 103 is connected with the weighing system 105 through the system interface, the negative deviation control module 103 is used for sending the control signal to the weighing system 105 according to the size relationship between the quantity difference, the negative deviation measurement value and the negative deviation control limit value.

[0052] The bundle reinforcement quantity review sub-module 101 can obtain the bundle reinforcement end face image through the camera, determine the bundle reinforcement quantity data according to the bundle reinforcement end face image, and the bundle reinforcement quantity data includes the bundle reinforcement quantity. The bundle reinforcement quantity can be determined by using an AI algorithm. After obtaining the bundle reinforcement quantity data, the bundle reinforcement quantity data is sent to the production manufacturing system 106 and the weighing system 105. The negative deviation calculation module 102 can determine the quantity difference value according to the difference between the bundle reinforcement quantity and the rated quantity of the production manufacturing system 106, can obtain the theoretical weight value according to the actual quantity, the nominal diameter and the length value of the reinforcement, the theoretical weight value can be obtained by table lookup or calculation, and the table lookup can be obtained by querying the fixed-quantity packaging negative deviation control range table. The negative deviation measurement value is determined according to the difference between the theoretical weight and the actually measured weight. The calculated negative deviation measurement value is compared with the pre-set negative deviation control limit value. The negative deviation control limit value includes the negative deviation control upper limit value and the negative deviation control lower limit value. The negative deviation control limit value defines the acceptable deviation range of the reinforcement weight. If the negative deviation measurement value exceeds the deviation range, it indicates that the weight of the reinforcement is not within the specified quality control range. The negative deviation control module 103 can determine whether the production process needs to be adjusted according to the size relationship between the quantity difference value, the negative deviation measurement value and the negative deviation control upper limit value and the negative deviation control lower limit value. The negative deviation control module 103 sends a control signal to the weighing system 105. If the quantity difference value is not zero, the control signal instructs the weighing system 105 to pause sending the next process link, for example, to unpack the bundle reinforcement, increase or decrease the quantity, or to confirm the bundle reinforcement quantity. If the quantity difference value is zero, the control signal can enter the next process link according to the normal process.

[0053] The technical scheme of the embodiment of the application sets the bundle reinforcement quantity review sub-module, the negative deviation calculation module and the negative deviation control module, the bundle reinforcement quantity review sub-module obtains the bundle reinforcement quantity data and sends it to the production manufacturing system and the weighing system, ensuring the accuracy of the data in the production process and reducing the errors and costs of manual counting. The negative deviation calculation module can calculate the quantity difference value and the negative deviation measurement value, the negative deviation control module sends a control signal to the weighing system according to the size relationship between the quantity difference value, the negative deviation measurement value and the negative deviation control limit value, compares the negative deviation measurement value with the control limit value, and sends a corresponding control signal to the weighing system according to the data. The technical scheme of the embodiment of the application ensures the accuracy of the data in the production process, reduces the errors and costs of manual counting, improves the negative deviation control level of the product, reduces the risk of out-of-tolerance products, and improves the production efficiency and product quality.

[0054] Figure 2 It is an application scene diagram of the bundle reinforcement quantity review sub-module provided according to the embodiment of the application; Figure 3is a schematic view of a bale reinforcement end face obtained by a bale reinforcement count review sub-module according to an embodiment of the present application. In some optional embodiments of the present application, referring to Figure 2 and Figure 3 , the bale reinforcement count review sub-module comprises a camera and an AI server;

[0055] The camera is arranged on a steel bale weighing platform of the weighing system and is used to obtain image data of the bale reinforcement end face;

[0056] The AI server is used to determine the bale reinforcement count based on a pre-trained target recognition model according to the image data of the bale reinforcement end face.

[0057] The bale reinforcement count review sub-module can obtain the image data of the bale reinforcement end face through the camera, which can reduce the errors of manual counting and improve the production efficiency. The AI server can determine the bale reinforcement count according to the image data of the bale reinforcement end face. The AI algorithm is arranged in the AI server and can be a deep learning algorithm. The bale reinforcement count is determined based on a pre-trained target recognition model. The bale reinforcement count review sub-module can further comprise a fill light and a switch. The fill light can supplement or enhance the light to ensure that the camera captures a clear image. The switch can transmit the image data of the bale reinforcement end face to the AI server and transmit the bale reinforcement count to the production and manufacturing system and the weighing system.

[0058] In some optional embodiments of the present application, the AI server is deployed with an AI algorithm, and the AI algorithm comprises a deep learning algorithm;

[0059] The target recognition model obtained by the AI server comprises:

[0060] The deep learning algorithm is learned based on the image data collected in the early stage of the project, and the image data is manually annotated to construct a training data set;

[0061] The target recognition model is obtained by training the training data set according to the constructed neural network and deep learning algorithm.

[0062] The AI algorithm can adopt a deep learning algorithm. The deep learning algorithm needs to be learned through a large amount of data. The image data collected in the early stage of the project can be manually annotated to construct a training data set. The neural network is built, the deep learning algorithm is run, and the on-site data set is trained using big data resources. The initially trained target recognition model is tested against on-site data to measure the effect of the target recognition model. The target recognition model is iteratively optimized against deficiencies to meet the needs of the business system.

[0063] Specifically, the target recognition model can use a data-driven deep learning target detection algorithm to identify the steel bars. Since the steel bars may be occluded, rotated or moved during conveying or stacking, the end face features are easy to be lost, and a steel end face dynamic capture algorithm can be used to automatically adjust the collection angle and focal point according to the motion trajectory of the steel bars, reduce the loss of steel end face features, and improve the recognition accuracy of the AI model. After the initial identification of the AI model, there may be some misidentified points, which can be filtered out by K-means clustering algorithm to improve the accuracy. The K-means clustering algorithm is an unsupervised learning method, which can classify the points according to the identification results, and the similar identification points are classified into one class, while the isolated misidentified points are filtered out as outliers. The discrete points are generated due to collection errors or abnormal interference, and the Interquartile Range (IQR) is a statistical method for handling outliers or discrete points. The IQR method can analyze and filter the discrete points, remove the outliers that deviate from most data, and improve the accuracy of the result output. After the AI algorithm training is completed, it can be packaged in an AI server, and called when the weight signal of the steel bar baling scale is triggered.

[0064] In some optional embodiments of the present application, with continued reference to Figure 1 , the steel bar weight negative deviation measurement control system further comprises a man-machine interaction control module 104, the man-machine interaction control module 104 is connected with the negative deviation control module 103, and the man-machine interaction control module 104 is used for processing the baling steel bars according to the control signal sent by the negative deviation control module 103.

[0065] The man-machine interaction control module 104 comprises a display, control buttons and the like, and can process the baling steel bars according to the control signal sent by the negative deviation control module 103. The operator controls through the control buttons of the man-machine interaction control module 104. According to the control signal sent by the negative deviation control module, the man-machine interaction control module prompts the operator to take measures. The display can display the rated number of steel bars, the actual number of steel bars, the actual number of steel bars, the actual weight value of the theoretical weight, the actual measurement calculation value of the steel bar negative deviation, the negative deviation control target value, the negative deviation control lower limit value, the negative deviation control upper limit value and the like. The control buttons can be used to confirm the number of baling steel bars, and then the baling steel bars are sent to the weighing system 106 according to the actual number and the actual theoretical weight data.

[0066] Figure 4 A flowchart of a steel bar weight negative deviation measurement control method provided by the embodiments of the present application can be applied to the steel bar weight negative deviation measurement control system described in any embodiment of the present application, and the steel bar weight negative deviation measurement control system further comprises a man-machine interaction control module, which is described with reference to Figure 1 and Figure 4The method comprises:

[0067] S201, the bundle reinforcement count review submodule 101 acquires bundle reinforcement count data and sends the bundle reinforcement count data to the production manufacturing system 106 and the weighing system 105. The bundle reinforcement count data includes bundle reinforcement count.

[0068] The bundle reinforcement count review submodule 101 can acquire bundle reinforcement end face images through a camera. The AI server can determine the bundle reinforcement count based on a pre-trained target recognition model according to the bundle reinforcement end face images. After acquiring the bundle reinforcement count, the bundle reinforcement count is sent to the production manufacturing system 106 and the weighing system 105.

[0069] S202, the negative deviation calculation module 102 calculates a count difference value according to the bundle reinforcement count and the rated count of the production manufacturing system 106, and acquires a theoretical weight value according to the actual reinforcement count.

[0070] The negative deviation calculation module 102 can obtain the count difference value by subtracting the rated count of the production manufacturing system 106 from the bundle reinforcement count. For example, the predetermined count is 100, and the actual count is 95, so the count difference value is 5. The theoretical weight value is obtained according to the actual reinforcement count, the nominal diameter, and the length value. The theoretical weight value can be obtained by table lookup or calculation. The table lookup can be obtained by querying the fixed-count packaging negative deviation control range table.

[0071] S203, the negative deviation calculation module 102 calculates a negative deviation measurement value according to the theoretical weight value and the actual weight, and compares the size relationship between the negative deviation measurement value and the negative deviation control limit value. The negative deviation control limit value includes a negative deviation control lower limit value and a negative deviation control upper limit value.

[0072] The negative deviation calculation module 102 can determine the negative deviation measurement value by the difference between the theoretical weight and the actual weight. The calculated negative deviation measurement value is compared with the negative deviation control upper limit value and the negative deviation control lower limit value.

[0073] S204, the negative deviation control module 103 sends a control signal to the weighing system 105 according to the size relationship between the count difference value, the negative deviation measurement value, and the negative deviation control limit value.

[0074] The negative deviation control module 103 can compare the negative deviation measurement value with the negative deviation control upper limit value and the negative deviation control lower limit value according to the number difference value. According to the comparison result, a control signal is sent to the weighing system 105. If the negative deviation measurement value exceeds the control limit value, the control signal instructs the weighing system 105 to make adjustment, such as unpacking and increasing or decreasing the number of the bundled steel bars, so that the negative deviation returns to the control range. If the negative deviation measurement value is within the control limit value, the control signal can instruct to maintain the current production state.

[0075] S205, the man-machine interactive control module 104 processes the bundled steel bars according to the control signal.

[0076] The man-machine interactive control module 104 processes the bundled steel bars according to the control signal received from the negative deviation control module 103, and according to the different control signals sent by the negative deviation control module 103 to the weighing system 105, such as entering the next process link or being unpacked and increasing or decreasing the number of the bundled steel bars or confirming the number of the bundled steel bars.

[0077] The technical scheme of the embodiment of the application is that the bundled number review sub-module obtains the actual number data of the bundled steel bars and transmits the actual number data to the production and manufacturing system and the weighing system. Then, the number difference value and the negative deviation measurement value of the actual weight and the theoretical weight are calculated by the negative deviation calculation module, and compared with the negative deviation control limit value. If the deviation exceeds the control limit value, the negative deviation control module sends a control signal to the weighing system to ensure that the production process is adjusted. Finally, through the man-machine interactive control module, the operator can take corresponding measures according to the system feedback to ensure that the number and weight of the steel bars in the production process meet the standards.

[0078] In some optional embodiments of the application, the negative deviation control module sends a control signal to the weighing system according to the number difference value, the size relationship between the negative deviation measurement value and the negative deviation control limit value, including:

[0079] If the number difference value = 0, and the negative deviation control lower limit value < the negative deviation measurement value < the negative deviation control upper limit value, the negative deviation control module sends data of the bundled steel bar number equal to the rated number to the weighing system, and the bundled steel bars enter the next process link.

[0080] The number difference value is 0, which means that the number of the bundled steel bars is equal to the rated number of the production and manufacturing system 106. The negative deviation control lower limit value < the negative deviation measurement value < the negative deviation control upper limit value, which means that the weight deviation of the steel bars is within an acceptable range. At this time, the negative deviation control module 103 sends data of the bundled steel bar number equal to the rated number to the weighing system 105, and the production process does not need to be adjusted due to the number difference value and the weight deviation, and can continue the subsequent production. The bundled steel bars enter the next process link.

[0081] If the difference value of the number of pieces ≠ 0, the negative deviation control module sends data of the rated number of pieces deviating from the rated value to the weighing system, and the bundled steel reinforcement is suspended from entering the next process link.

[0082] If the difference value of the number of pieces ≠ 0, the negative deviation control module sends data of the rated number of pieces deviating from the rated value to the weighing system, and the bundled steel reinforcement is suspended from entering the next process link.

[0083] In some optional embodiments of the present application, with reference to Figure 1 , the man-machine interaction control module 104 processes the bundled steel reinforcement according to the control signal, including:

[0084] If the difference value of the number of pieces = 0, and the lower limit value of negative deviation control < the measured value of negative deviation < the upper limit value of negative deviation control, the man-machine interaction control module 104 displays the rated number of pieces, the actual number of pieces, the actual number of pieces theoretical weight value, the weighing value, the actual measured calculation value of the negative deviation of the steel reinforcement, the target value of negative deviation control, the lower limit value of negative deviation control, and the upper limit value of negative deviation control, and prompts “normal”;

[0085] If the difference value of the number of pieces ≠ 0, the man-machine interaction control module displays the rated number of pieces, the actual number of pieces, the actual number of pieces theoretical weight value, the weighing value, the actual measured calculation value of the negative deviation of the steel reinforcement, the target value of negative deviation control, the lower limit value of negative deviation control, and the upper limit value of negative deviation control, and prompts “number of pieces deviation value”.

[0086] In some optional embodiments of the present application, with reference to Figure 1 If the difference value of the number of pieces ≠ 0, the man-machine interaction control module 104 displays the rated number of pieces, the actual number of pieces, the actual number of pieces theoretical weight value, the weighing value, the actual measured calculation value of the negative deviation of the steel reinforcement, the target value of negative deviation control, the lower limit value of negative deviation control, and the upper limit value of negative deviation control, and prompts “number of pieces deviation value”, including:

[0087] If the bundled steel reinforcement is delivered with a theoretical weight, when the difference value of the number of pieces ≠ 0, it prompts “offline processing”, and the bundled steel reinforcement must be unpacked and processed, and then put back online.

[0088] Theoretical weight delivery means that the delivery of the bundled steel bars is based on the theoretically calculated weight. If the number difference is not equal to zero, i.e., the actual number is inconsistent with the rated number, the system will prompt "offline processing", and the bundled steel bars need to be unpacked, which can be to increase or decrease the number of steel bars, or to process the problematic steel bars. After unpacking, the steel bars need to be repacked and weighed again or other inspections.

[0089] If the bundled steel bars are delivered by actual weight, when the number difference is not equal to zero, the system will prompt "number confirmation", and a preset value will be set. If the number difference is less than the preset value, the confirmation will be made through the man-machine interaction control module 104, and the bundled steel bars will enter the next process link.

[0090] If the number difference is greater than the preset value, the bundled steel bars will be unpacked, and then re-entered online. The bundled steel bars will not enter the next process link.

[0091] The actual weight delivery means that the delivery of the bundled steel bars is based on the actual weight. If the number difference is not equal to zero, i.e., the actual number is inconsistent with the rated number, the system will prompt "number confirmation". The preset value can be set according to the production rhythm and product specifications, for example, the preset value can be set to 3. When the number difference is less than 3, i.e., the number difference is 1 or 2, it means that the difference is small, and the system can allow not to be offline and unpacked. The bundled steel bars will enter the next process link. When the number difference is greater than 3, it means that the difference is large, and the bundled steel bars need to be unpacked, which can be to increase or decrease the number of steel bars, or to process the problematic steel bars. After unpacking, the steel bars need to be repacked and weighed again or other inspections.

[0092] Figure 5 A structural diagram of an electronic device 10 that can be used to implement embodiments of the present application is shown. The electronic device is intended to represent a variety of forms including digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent a variety of forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices (e.g., headsets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit the implementations of the applications described and / or claimed in this document.

[0093] As Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., communicatively connected to the at least one processor 11, where the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or loaded into the random access memory (RAM) 13 from the storage unit 18. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0094] Various components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc., an output unit 17, such as various types of displays, a speaker, etc., a storage unit 18, such as a magnetic disk, an optical disk, etc., and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0095] The processor 11 can be various general and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs various methods and processes described above, such as the steel reinforcement weight negative bias measurement control method.

[0096] In some embodiments, the steel reinforcement weight negative bias measurement control method can be implemented as a computer program tangibly embodied in a computer readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the steel reinforcement weight negative bias measurement control method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to perform the steel reinforcement weight negative bias measurement control method by any other appropriate means, such as by means of firmware.

[0097] The various embodiments of the systems and techniques described above can be implemented in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0098] Computer programs used to implement the processes of the application can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer program

[0099] In the context of the present application, a computer-readable storage medium can be a tangible medium that can contain or store computer programs for use by or in connection with an instruction execution system, apparatus, or device. Computer-readable storage media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium will include one or more lines of a program of instructions in a transitory signal, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0100] To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0101] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0102] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. A server can be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system, to solve the defects of large management difficulty and weak business scalability in traditional physical host and VPS service.

[0103] It should be understood that the various forms of flow shown above can be re-ordered, added to, or deleted from without departing from the scope of the present disclosure. For example, the steps recited in the present disclosure can be executed in parallel, executed in sequence, or executed in a different order, as long as the desired results of the present disclosure are achieved, and the present disclosure is not limited herein.

[0104] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above, but only by the scope of the appended claims.

Claims

1. A control system for measuring and controlling the negative deviation of steel bar weight, characterized in that, include: The module includes a bundle count verification module, a negative deviation calculation module, and a negative deviation control module. The bundle count verification submodule is connected to the negative deviation calculation module. The bundle count verification submodule is connected to the production system and the weighing system through the system interface. The bundle count verification submodule is used to obtain the bundle count data of steel bars and send the bundle count data of steel bars to the production system and the weighing system. The bundle count data of steel bars includes the number of steel bars in the bundle. The negative deviation calculation module is connected to the negative deviation control module. The negative deviation calculation module is used to calculate the difference in the number of bundled steel bars and the rated number of steel bars in the production system, and to obtain the theoretical weight value based on the actual number of steel bars. The module also calculates the negative deviation measurement value based on the theoretical weight value and the actual weight, and compares the negative deviation measurement value with the negative deviation control limit. The negative deviation control module is connected to the weighing system through the system interface. The negative deviation control module is used to send a control signal to the weighing system according to the relationship between the number of branches difference, the negative deviation measurement value and the negative deviation control limit value. The bundle count verification submodule includes a camera and an AI server; The camera is installed on the steel bundle weighing platform of the weighing system to acquire image data of the end face of the bundled steel bars. The AI ​​server is used to determine the number of bundled steel bars based on the image data of the end face of the bundled steel bars and a pre-trained target recognition model.

2. The system according to claim 1, characterized in that, The AI ​​server is equipped with AI algorithms, including deep learning algorithms. Obtaining the target recognition model through the AI ​​server includes: The training dataset is constructed by learning from on-site image data collected in the early stages of the project using deep learning algorithms and manually annotating the image data. The target recognition model is obtained by training the constructed neural network and the deep learning algorithm using the training dataset.

3. The system according to claim 1, characterized in that, The steel bar weight negative deviation measurement and control system also includes a human-machine interaction control module, which is connected to the negative deviation control module. The human-machine interaction control module is used to process the bundled steel bars according to the control signals sent by the negative deviation control module.

4. A method for measuring and controlling negative deviation in the weight of reinforcing bars, characterized in that, The method is applied to the rebar weight negative deviation measurement and control system as described in any one of claims 1-3, wherein the rebar weight negative deviation measurement and control system further includes a human-machine interaction control module, and the method includes: The bundle count verification submodule acquires the bundle count data of steel bars and sends the bundle count data of steel bars to the production system and the weighing system. The bundle count data of steel bars includes the number of bundled steel bars. The negative deviation calculation module calculates the difference between the number of bundled steel bars and the rated number of bars in the production system, and obtains the theoretical weight value based on the actual number of steel bars. The negative deviation calculation module calculates the negative deviation measurement value based on the theoretical weight value and the actual weight, and compares the negative deviation measurement value with the negative deviation control limit; wherein, the negative deviation control limit includes a lower limit and an upper limit. The negative deviation control module sends a control signal to the weighing system based on the difference in the number of branches and the relationship between the measured negative deviation value and the negative deviation control limit. The human-computer interaction control module processes the bundled steel bars according to the control signal.

5. The method according to claim 4, characterized in that, The negative deviation control module sends a control signal to the weighing system based on the difference in the number of branches, the relationship between the measured negative deviation value and the negative deviation control limit, including: If the difference in the number of bars is 0, and the lower limit of the negative deviation control is less than the measured value of the negative deviation and less than the upper limit of the negative deviation control, the negative deviation control module sends the data of the number of bundled steel bars and the rated number of bars to the weighing system, and the bundled steel bars enter the next process step. If the difference in the number of rebars is not equal to 0, the negative deviation control module sends data showing that the number of bundled rebars deviates from the rated number of rebars to the weighing system, and the bundled rebars are paused from proceeding to the next process step.

6. The method according to claim 5, characterized in that, The human-computer interaction control module processes the bundled steel bars according to the control signal, including: If the difference in the number of supports is 0, and the lower limit of the negative deviation control is less than the measured value of the negative deviation and the upper limit of the negative deviation control, the human-machine interaction control module displays the rated number of supports, the actual number of supports, the theoretical weight of the actual number of supports, the weighing value, the measured value of the negative deviation of the steel bars, the lower limit of the negative deviation control, and the upper limit of the negative deviation control, and prompts "normal". If the difference in the number of supports is not equal to 0, the human-machine interaction control module displays the rated number of supports, the actual number of supports, the theoretical weight of the actual number of supports, the weighing value, the measured value of the negative deviation of the steel bars, the lower limit of the negative deviation control, and the upper limit of the negative deviation control, and prompts "the number of supports deviates".

7. The method according to claim 6, characterized in that, If the difference in the number of supports is not equal to 0, the human-machine interaction control module displays the rated number of supports, the actual number of supports, the theoretical weight of the actual number of supports, the weighing value, the measured value of the negative deviation of the reinforcing bars, the lower limit of the negative deviation control value, and the upper limit of the negative deviation control value, and prompts "Number of supports deviation value", including: If the bundled steel bars are delivered based on theoretical weight, and the difference in the number of bars is not equal to 0, a "take offline processing" message will be displayed. The bundled steel bars must be unpacked and then put back online. If the bundled steel bars are delivered by actual weight, and the difference in the number of bars is not equal to 0, a "Bundle Count Confirmation" message will be displayed, and a preset value will be set. If the difference in the number of bars is less than the preset value, confirmation will be made through the human-machine interaction control module, and the bundled steel bars will proceed to the next process step. If the difference in the number of bars is greater than the preset value, the bundled steel bars are unpacked and then put back online. The bundled steel bars do not enter the next process step.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the steel bar weight negative deviation measurement and control method according to any one of claims 4-7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for measuring and controlling the negative deviation of steel bar weight as described in any one of claims 4-7.

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