A cloud-based metal detector intelligent control system and method

Abstract

The application discloses a kind of cloud-based metal detector intelligent control system and method, and the bar code on the product to be detected is scanned at the entrance of metal detector;When the communication link is normal, product information code is sent to cloud server, and the corresponding product detection parameter is matched by cloud server and is issued to metal detector, and metal detector stores it to local storage module and loads and executes detection;When the communication link is disconnected, corresponding parameters are found from local storage module, or the parameters input by manual are received, and detection is executed by manual control mode.The application can also upload running parameters to the cloud in real time, enabling remote start-stop control, parameter version management, and pushing algorithm upgrade packages to the metal detector through the cloud to implement online upgrade of detection algorithms, improving detection accuracy and reducing false alarm rate, enabling centralized management of multiple metal detectors, improving line change efficiency and ensuring production continuity.

Description

Technical Field

[0001] This invention relates to the field of metal detection, and in particular to a control system and method for controlling a metal detection machine using cloud computing, belonging to the field of intelligent manufacturing technology. Background Technology

[0002] Existing metal detectors have the following technical problems in parameter management and equipment control:

[0003] (1) Parameter configuration depends on manual operation: Although existing metal detectors support the storage of multiple parameters (usually 100-200 types), the selection and retrieval of parameters require manual operation by the operator at the device end. In the flexible production mode of multiple varieties and small batches, product switching is frequent. Manual parameter selection is not only inefficient, but also prone to incorrect parameter selection or omission of updates, resulting in decreased detection accuracy or increased false alarm rate.

[0004] (2) Parameter management is scattered and the versions are not consistent: The parameters of multiple metal detectors in the factory are stored and managed independently. When the detection parameters of a product need to be optimized and adjusted, it is necessary to go to the site to modify them one by one. The parameter versions of different devices may be inconsistent, which affects the consistency of product quality control.

[0005] (3) Lack of remote control capability: The start-up, shutdown and parameter adjustment of existing metal detectors require on-site operation. Managers cannot centrally control equipment distributed in different workshops, factories or even cities, resulting in high operation and maintenance costs.

[0006] (4) Fixed and non-upgradeable detection algorithm: The detection algorithm of the existing metal detector is fixed in the equipment at the factory and cannot be upgraded or optimized during use. As the production environment changes and the types of products increase, the original algorithm may not be able to meet the detection accuracy requirements, and it is necessary to return it to the factory or have engineers update it on-site, which results in a long maintenance cycle and high cost.

[0007] Therefore, the industry needs an intelligent control system and method for metal detectors that can achieve automatic product identification, automatic parameter matching and downloading, remote centralized management and control, and continuous upgrading of detection algorithms. Summary of the Invention

[0008] The purpose of this invention is to provide a cloud-based intelligent control system and method for metal detectors, in order to solve the problems in the prior art such as parameter configuration relying on manual operation, decentralized parameter management, lack of remote control, and non-upgradable detection algorithms.

[0009] The present invention provides the following technical solution.

[0010] In a first aspect, the present invention provides a cloud-based intelligent control system for a metal detector, comprising: a metal detector body, a barcode scanning module, a communication module, a local storage module, and a cloud server.

[0011] The metal detector body includes a detection coil, a signal processing unit, and a main controller. A barcode scanning module, fixedly installed at the entrance of the metal detector body and connected to it, is used to scan product information codes on the products to be inspected. A communication module, connected to the metal detector body, is used to establish a communication link between the metal detector body and a cloud server. A local storage module, connected to the metal detector body, is used to store product detection parameters, detection algorithms, and historical detection data. The cloud server, connected to the communication module, communicates with the metal detector body through the communication module.

[0012] The cloud server includes: a product parameter database, which stores the correspondence between product identifiers and product testing parameters; a parameter matching and distribution unit, which matches and distributes product testing parameters based on the product information sent by the metal detector; a remote control unit, which sends start and stop control commands to the metal detector; and an algorithm upgrade management unit, which stores multiple versions of the detection algorithm and pushes algorithm upgrade packages to the metal detector.

[0013] Secondly, the present invention provides a cloud-based intelligent control method for a metal detector, comprising the following steps: Step S1: The cloud server sends instructions to control the metal detector on the production line to start running; Step S2: After receiving the command, the metal detector communication module controls the metal detector body to start running; Step S3: The barcode scanning module at the entrance of the metal detector scans the product information code on the product to be inspected to obtain product information; Step S4: The metal detector sends the product information to the cloud server; Step S5: The cloud server matches the corresponding product testing parameters in the product parameter database based on the product information and sends the product testing parameters to the metal detector; Step S6: The metal detector receives the product testing parameters, stores the product testing parameters in the local storage module, and loads the product testing parameters into the metal detector; the metal detector performs metal detection according to the product testing parameters. Step S7: When the communication link is disconnected, search for the product detection parameters corresponding to the product information in the local storage module of the metal detector; if the parameters are found in the local storage module, load the parameters; if not found, receive the detection parameters input manually and load them. Step S8: With the communication link continuously disconnected, the metal detector is started and stopped manually.

[0014] Furthermore, in step S5, the step of the cloud server matching product testing parameters based on product information includes: Step S51: After receiving the product information, the cloud server parses it to obtain the product identifier; Step S52: Retrieve the product detection parameters corresponding to the product identifier in the product parameter database. The product detection parameters include one or more of the following: detection sensitivity, detection frequency, phase angle, product effect compensation value, detection threshold, and rejection delay time. Step S53: If the corresponding parameter is found, send the parameter to the metal detector; if the corresponding parameter is not found, return a message indicating that the parameter was not found to the metal detector.

[0015] Furthermore, the method also includes a parameter uploading step: during the operation of the metal detector, the current operating parameters of the metal detector are uploaded to the cloud server in real time. The operating parameters include one or more of the following: detection sensitivity, detection frequency, threshold setting value, product effect compensation parameters, equipment operating status, and detection statistics. The cloud server receives and stores the operating parameters for remote monitoring and parameter version management.

[0016] Furthermore, the method also includes a remote start / stop control step: the cloud server sends a start command or a stop command to the metal detector; after receiving the start command, the metal detector controls the drive module to start the conveyor belt and begin metal detection; after receiving the stop command, it controls the drive module to stop the conveyor belt and stop metal detection.

[0017] Furthermore, the method also includes an algorithm upgrade step: Step S1: The algorithm upgrade management unit on the cloud server detects that the new version of the algorithm is available; Step S2: The algorithm upgrade management unit pushes the algorithm upgrade package to the target metal detector; Step S3: The metal detector receives the algorithm upgrade package and updates its local detection algorithm; Step S4: After the new algorithm runs, the system automatically records the detection data and uploads it to the cloud server.

[0018] The algorithm upgrade includes one or more of the following: signal processing algorithm upgrade, product effect suppression algorithm upgrade, metal foreign object recognition algorithm upgrade, and adaptive frequency adjustment algorithm upgrade, which are used to improve metal detection accuracy and reduce false alarm rate.

[0019] Furthermore, the method also includes a parameter version management step: Step S1: The cloud server manages the version of each product testing parameter in the product parameter database, recording the version number, modification time, modification content, and the person who made the modification each time the parameter is modified; Step S2: The cloud server can query the parameter version number currently used by each metal detector. When it finds that the parameter version used by a certain device is not the latest version, it will automatically send the latest version of the parameters. Step S3: When the metal detector receives the product detection parameters, it also receives the parameter version number and stores it in the local storage module. Step S4: Administrators can view the parameter modification history through the cloud management interface.

[0020] Compared with the prior art, the beneficial effects of the present invention are: (1) Automatic matching and download of product parameters to improve line change efficiency: The product is automatically identified by scanning the code, and the cloud server automatically matches and sends the corresponding test parameters. No manual selection or setting is required. When changing lines for multiple products, the parameter configuration is shortened from minutes to seconds, and human error in parameter selection is avoided, ensuring test accuracy. (2) Centralized parameter management and version unification: The testing parameters of all products are stored uniformly on the cloud server, realizing centralized management and version unification of parameters across multiple devices. Parameter modifications are updated in one place and take effect for all personnel, eliminating the problem of inconsistent parameter versions. The parameter version management mechanism allows for the traceability of each modification record, meeting the audit requirements of the quality management system. (3) Remote start-up and centralized management: Managers can remotely control the start-up and shutdown of metal detectors through cloud servers, and centrally manage multiple devices distributed in different locations, thereby reducing operation and maintenance costs and improving management efficiency. (4) Cloud-based upgrade of detection algorithms to continuously improve detection accuracy: The algorithm upgrade package is pushed to the metal detector via cloud OTA, including signal processing algorithm, product effect suppression algorithm, metal foreign object identification algorithm, adaptive frequency adjustment algorithm, etc., so that the detection accuracy of the equipment can be continuously improved and the false alarm rate can be continuously reduced without returning to the factory or manual on-site updates. Attached Figure Description Figure 1 This is a schematic diagram of the system structure of the present invention; Figure 2 This is a functional block diagram of the cloud server of the present invention; Figure 3 This is a flowchart illustrating the overall process of the invention. Figure 4 This is a flowchart of the parameter matching and download process in network mode according to the present invention; Figure 5 This is a flowchart of the parameter lookup and configuration process in offline mode according to the present invention; Figure 6 This is a flowchart of the algorithm upgrade process of the present invention; Figure 7 This is a flowchart of the parameter version management process of the present invention; Detailed Implementation

[0021] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0022] Example 1: System Overall Structure

[0023] like Figure 1 As shown, the cloud-based intelligent control system for metal detectors of the present invention includes a metal detector body 100, a barcode scanning module 200, a communication module 300, a local storage module 400, a human-machine interaction module 500, a conveyor belt drive module 600, a rejection device 700, and a cloud server 800.

[0024] The metal detector body 100 includes a detection coil 110, a signal processing unit 120, and a main controller 130. The detection coil 110 employs a combination of a transmitting coil and a receiving coil to generate an alternating electromagnetic field. When a product containing metal impurities passes through, the metal impurities disturb the electromagnetic field, and the receiving coil senses a signal change. The signal processing unit 120 amplifies, filters, performs analog-to-digital conversion, and performs digital signal processing on the sensed signal to extract the metal characteristic signal. The signal processing unit then sends the metal characteristic signal to the main controller 130.

[0025] The barcode scanning module 200 is fixedly installed at the entrance of the metal detector body 100, and includes a barcode reader and a barcode scanning bracket. The barcode reader is an industrial-grade fixed barcode scanner. The barcode scanning bracket is installed on the upper part of the frame on the entrance side of the metal detector to ensure that the product barcode can be reliably read when the product moves on the conveyor belt.

[0026] The communication module 300 supports multiple communication methods. First, wired communication, connecting to the factory LAN via an RJ45 Ethernet interface. Second, wireless communication, including at least one of WiFi, 4G LTE, and 5G, suitable for different deployment scenarios.

[0027] The local storage module 400 uses an industrial-grade Flash memory, and the stored content includes: (1) Product testing parameters: a complete parameter set for no less than 1,000 products; (2) Detection algorithm program: including the algorithm program files of the current version and historical versions; (3) Historical testing data: no less than 1 million testing records, each record including timestamp, product information, testing parameters, testing results, equipment status, etc.

[0028] The human-machine interface module 500 includes a 12864 LCD screen plus buttons or a color touchscreen. The touchscreen is preferred. It displays current product information, detection parameters, detection status, communication status, detection count, alarm records, parameter version number, etc. In offline mode, operators can manually select product parameters, start or stop the equipment, and manually trigger rejections via the touchscreen.

[0029] like Figure 2 As shown, the cloud server 800 includes the following functional modules: (1) Product parameter database 810, which stores the correspondence between the identifiers and test parameters of all products, and supports the addition, modification, deletion, version management and batch import and export of parameters; (2) The parameter matching and sending unit 820 receives the product information sent by the metal detector, matches the corresponding parameters in the product parameter database and sends them to the equipment; (3) The remote control unit 830 sends control commands such as start, stop, and speed adjustment to the metal detector, and supports single-unit control and batch control; (4) Algorithm upgrade management unit 840 stores and manages multiple versions of metal detection algorithms (including signal processing algorithms, product effect suppression algorithms, metal foreign object identification algorithms, adaptive frequency adjustment algorithms, etc.) and pushes upgrade packages to the device; (5) Parameter version management unit 850 manages the version of each product testing parameter, records the version number, time, content and personnel of each modification, and monitors the current parameter version of each device; (6) Data storage unit 860 stores all operating parameters and detection data uploaded by all devices.

[0030] Example 2: Network Mode Workflow

[0031] like Figure 3 and Figure 4 As shown, when the communication link is normal, the workflow of this invention includes: Step S1: The cloud server 800 sends a command to control the metal detector on the production line to start running; Step S2: After receiving the command, the communication module 300 controls the metal detector body 100 to start running; Step S3: The product is conveyed on the conveyor belt towards the metal detector. When the product reaches the entrance, the barcode scanning module 200 scans the barcode on the product to obtain the barcode information. The barcode information is usually the product's barcode number; Step S4: The main controller 130 of the metal detector determines whether the communication link between the communication module 300 and the cloud server 800 is normal. The determination method includes heartbeat packet detection, TCP connection status detection, etc. When the communication link is normal, the main controller 130 of the metal detector sends product information to the cloud server 800 through the metal detector communication module 300. Step S5: After receiving the product information, the parameter matching and distribution unit 820 of the cloud server 800 parses and obtains the product identifier, and retrieves the product detection parameters corresponding to the product identifier in the product parameter database. The product detection parameters include, but are not limited to: (1) Detection sensitivity: Fe (iron) sensitivity, Non-Fe (non-ferrous) sensitivity, SUS (stainless steel) sensitivity; (2) Detection frequency: Working frequency setting value, usually one or more frequencies in the range of 10kHz-900kHz; (3) Phase angle: Product effect compensation phase angle; (4) Product effect compensation value: Used to offset the influence of the product's own conductivity / magnetism on the detection signal; (5) Detection threshold: The signal threshold for determining whether a metal foreign object exists; (6) Removal delay time: The time delay from detecting a metal foreign object to triggering the removal device. If the corresponding parameter is found, the cloud server 800 sends the parameter to the metal detector; if it is not found, a parameter not found prompt is returned, and manual intervention is required. Step S6: The main controller 130 of the metal detector receives the product detection parameters, stores them in the local storage module 400 (and saves the parameter version number), and loads the parameters to configure the detection parameters of the metal detector. The remote control unit 830 of the cloud server 800 sends a start command, and the main controller 130 of the metal detector controls the conveyor belt drive module 600 to start the conveyor belt, and the product passes through the detection coil 110 for metal detection.

[0032] During the detection process, the main controller 130 of the metal detector uploads the current operating parameters (detection sensitivity, frequency, threshold, product effect compensation value, equipment operating status, detection statistics, etc.) to the cloud server 800 in real time or periodically. The data storage unit of the cloud server 800 receives and stores the data.

[0033] If a metallic foreign object is detected, the main controller 130 of the metal detector controls the rejection device 700 to perform the rejection action.

[0034] Example 3: Workflow in Offline Mode

[0035] like Figure 5 As shown, when the communication link is disconnected, the workflow of this invention includes: The main controller 130 of the metal detector retrieves the product detection parameters corresponding to the product information from the local storage module 400. Since parameters downloaded from the cloud are stored in the local storage module 400 each time in network mode, the local storage module 400 contains a copy of the parameters for all products previously detected by the device. If the corresponding parameter is found, the main controller 130 of the metal detector loads the parameter and configures the metal detector. The main controller 130 of the metal detector then controls the conveyor belt drive module 600 to start the conveyor belt and perform metal detection. If no parameter is found (i.e., the product has never been tested on this device), the human-machine interface module 500 displays a "Parameter Not Found" message. The operator can manually input the testing parameters via buttons or the touchscreen, or modify the parameters of a similar product. In the offline state, the operator inputs a start command through the human-machine interface module 500. The metal detector's main controller 130 then controls the conveyor belt drive module 600 to start the conveyor belt for metal detection. The detected data is stored in the local storage module 400. When the communication link is restored, the metal detector's main controller uploads the detected data and operating parameters stored during the offline period to the cloud server 800 in batches. The cloud server 800 receives and stores the data, managing it in conjunction with the cloud-based detected data.

[0036] Example 4: Algorithm Upgrade Process

[0037] like Figure 6 As shown, the algorithm upgrade process of this invention includes: Step S1: The algorithm upgrade management unit 840 of the cloud server 800 detects that the new version of the algorithm is available; Step S2: The algorithm upgrade management unit 840 pushes the algorithm upgrade package to the target metal detector; Step S3: The metal detector receives the algorithm upgrade package, and the main controller 130 of the metal detector updates its local detection algorithm. The update process includes: verifying the integrity of the upgrade package → backing up the current algorithm → writing the new algorithm → restarting the detection program → verifying the running status of the new algorithm. After the update is completed, the new version of the algorithm is used for metal detection. Step S4: After the new algorithm runs, the system automatically records the detection data and uploads it to the cloud server 800. If the new algorithm is not effective, administrators can trigger a rollback to restore the previous version of the algorithm.

[0038] The algorithm upgrade package includes: (1) Signal processing algorithm upgrade: optimize filter parameters, improve noise suppression algorithm, and improve signal-to-noise ratio; (2) Upgraded product effect suppression algorithm: Improved product effect compensation model to more accurately separate product signal and metal signal, especially suitable for high humidity and high salinity products; (3) Upgrade of metal foreign object recognition algorithm: Introduce more advanced feature extraction and classification algorithms to improve the recognition rate of metal foreign objects of different shapes and materials; (4) Upgrade of adaptive frequency adjustment algorithm: Optimize multi-band scanning strategy and frequency adaptive switching logic to improve the detection sensitivity of complex products.

[0039] Example 5: Parameter Version Management Process

[0040] like Figure 7 As shown, the parameter version management process of this invention includes: Step S1: The product parameter database 810 on the cloud server 800 manages the version of the testing parameters for each product. Each time a parameter is modified, the version number (e.g., V1.0, V1.1, V2.0), modification time, modification content (which parameters were modified, their values ​​before and after the modification), and the person who made the modification are recorded. Step S2: The parameter version management unit 850 of the cloud server 800 can query the parameter version number currently used by each metal detector. When it is found that the parameter version used by a certain device is not the latest version, the latest version of the parameters is automatically issued and a message is displayed that "the parameters have been updated to version Vx.x". Step S3: When the metal detector receives the parameters sent from the cloud, it also receives the parameter version number and stores it in the local storage module 400. Step S4: Managers can view the parameter modification history through the cloud management interface, which meets the requirements of HACCP, GMP, ISO22000 and other quality management systems for traceability of parameter changes.

[0041] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any person skilled in the art can make some modifications or alterations to the disclosed technical content to create equivalent embodiments without departing from the spirit and scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention, without departing from the content of the present invention, shall still fall within the scope of the present invention.

Claims

1. A cloud-based intelligent control system for a metal detector, characterized in that, It includes the metal detector body, barcode scanning module, communication module, local storage module, and cloud server; The metal detector body is internally equipped with a detection coil, a signal processing unit, and a main controller; The scanning module is fixedly installed at the entrance of the metal detector and connected to the metal detector body. It is used to scan the information code on the product to be inspected. The communication module is connected to the metal detector body and is used to establish a communication link between the metal detector body and the cloud server. The local storage module is connected to the metal detector body and is used to store product detection parameters, detection algorithms and historical detection data; The cloud server is connected to the communication module, and communicates with the metal detection machine body through the communication module.

2. The cloud-based intelligent control system for metal detectors according to claim 1, characterized in that, The communication module includes at least one of a wired communication unit and a wireless communication unit. The wired communication unit includes one or more of Ethernet, Modbus, and Entecact; the wireless communication unit includes one or more of a WiFi communication circuit, a 4G communication circuit, or a 5G communication circuit.

3. The cloud-based intelligent control system for metal detectors according to claim 1, characterized in that, The cloud server also includes a product parameter database, a parameter matching and distribution unit, a remote control unit, and an algorithm upgrade management unit; The product parameter database stores the correspondence between product information codes and product testing parameters; The parameter matching and sending unit is used to match product detection parameters according to the product information code sent by the metal detector and send them out. The remote control unit is used to send start / stop control commands to the metal detector; The algorithm upgrade management unit is used to store multiple versions of the detection algorithm and push algorithm upgrade packages to the metal detector.

4. The cloud-based intelligent control system for metal detectors according to claim 1, characterized in that, The cloud server also includes a parameter version management unit, which is used to manage the version of each product testing parameter in the product parameter database, record the version number, modification time, modification content and modification personnel for each parameter modification, and monitor the parameter version currently used by each metal detection machine.

5. A cloud-based intelligent control method for a metal detector, characterized in that, Includes the following steps: Step S1: The cloud server sends instructions to control the metal detector on the production line to start running; Step S2: After receiving the command, the communication module controls the metal detector to start running; Step S3: The barcode or QR code on the product to be inspected is scanned by the barcode scanning module at the entrance of the metal detector to obtain product information; Step S4: The metal detector sends the product information to the cloud server; Step S5: The cloud server matches the corresponding product testing parameters in the product parameter database based on the product information and sends the product testing parameters to the metal detector; Step S6: The metal detector receives the product testing parameters, stores the product testing parameters in the local storage module, and loads the product testing parameters into the metal detector; the metal detector performs metal detection according to the product testing parameters. Step S7: When the communication link is disconnected, retrieve the product detection parameters corresponding to the product information from the local storage module of the metal detector; If the parameter is found in the local storage module, it will be loaded; otherwise, the detection parameters input manually will be received and loaded. Step S8: With the communication link continuously disconnected, the metal detector is started and stopped manually.

6. The cloud-based intelligent control method for metal detectors according to claim 5, characterized in that, In step S5, the step of the cloud server matching product testing parameters based on product information includes: Step S51: After receiving the product information, the cloud server parses it to obtain the product identifier; Step S52: Retrieve the product detection parameters corresponding to the product identifier in the product parameter database. The product detection parameters include one or more of the following: detection sensitivity, detection frequency, phase angle, product effect compensation value, detection threshold, and rejection delay time. Step S53: If the corresponding parameter is found, send the parameter to the metal detector; if the corresponding parameter is not found, return a message indicating that the parameter was not found to the metal detector.

7. The cloud-based intelligent control method for metal detectors according to claim 5, characterized in that, It also includes a parameter upload function: During the operation of the metal detector, the current operating parameters of the metal detector are uploaded to the cloud server in real time or periodically. The operating parameters include one or more of the following: detection sensitivity, detection frequency, threshold setting value, product effect compensation parameters, equipment operating status, and detection statistics.

8. The cloud-based intelligent control method for metal detectors according to claim 5, characterized in that, It also includes remote start / stop control steps: Step S1: The cloud server sends a start command or stop command to the metal detector; Step S2: After receiving the start command, the metal detector controls the conveyor belt drive module to start the conveyor belt and begin metal detection; after receiving the stop command, it controls the conveyor belt drive module to stop the conveyor belt and stop metal detection.

9. The cloud-based intelligent control method for metal detectors according to claim 5, characterized in that, It also includes algorithm upgrade steps: Step S1: The algorithm upgrade management unit on the cloud server detects that the new version of the algorithm is available; Step S2: The algorithm upgrade management unit pushes the algorithm upgrade package to the target metal detector; Step S3: The metal detector receives the algorithm upgrade package and updates its local detection algorithm; Step S4: After the new algorithm runs, the system automatically records the detection data and uploads it to the cloud server.

10. The cloud-based intelligent control method for metal detectors according to claim 5, characterized in that, It also includes parameter version management steps: Step S1: The cloud server manages the version of each product testing parameter in the product parameter database, recording the version number, modification time, modification content, and the person who made the modification each time the parameter is modified; Step S2: The cloud server can query the parameter version number currently used by each metal detector. When it finds that the parameter version used by a certain device is not the latest version, it will automatically send the latest version of the parameters. Step S3: When the metal detector receives the product detection parameters from the cloud, it also receives the parameter version number and stores it in the local storage module. Step S4: Administrators can view the parameter modification history through the cloud management interface.

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