Parameter configuration method and system based on wellbus distributed frequency converter

Abstract

This invention relates to the field of industrial automation technology, specifically disclosing a parameter configuration method and system based on a WellBUS distributed frequency converter. The invention constructs a WellBUS bus communication network, activates the NFC tag module inside the target frequency converter via NFC touch, and establishes a BLE Bluetooth quick connection. The main control MCU collects real-time operating status data, constructs a parameter adaptive matching mechanism, and automatically generates target recommended parameters. Static range verification and dynamic operating condition verification are performed to identify abnormal configuration parameters and generate target parameter configuration files. A dual-scenario parameter synchronization mechanism is adopted for different device network states, and the network operation stability is evaluated in real-time based on the target parameter configuration files. The mobile configuration terminal and the WellBUS bus master station upload configuration records, operating data, and fault logs to the cloud platform, improving the operational stability and reliability of the entire WellBUS distributed network.

Description

Technical Field

[0001] This invention relates to the field of industrial automation technology, and more specifically, to a parameter configuration method and system based on WellBUS distributed frequency converters. Background Technology

[0002] Against the backdrop of rapid development in industrial automation and intelligent manufacturing, frequency converters, as core equipment for motor drive and energy-saving control, have been widely used in various scenarios such as logistics sorting, production line automation, and warehousing and conveying. As production systems evolve towards distributed and networked architectures, especially in distributed architectures based on the WellBUS bus, multiple frequency converters operate collaboratively as slave nodes, making parameter configuration and debugging increasingly complex. Traditional single-machine debugging modes are no longer sufficient to meet the needs of rapid deployment and unified management of multiple nodes. How to achieve efficient, convenient, and safe parameter configuration has become one of the key factors restricting system application efficiency.

[0003] Traditional stand-alone commissioning relies on wired connections or local panel operation, which suffers from inconvenient access and low efficiency when equipment is widely distributed and installed in complex locations. While some frequency converters have introduced Bluetooth wireless configuration, traditional Bluetooth requires manual device searching and pairing code input, a cumbersome process that is prone to connection instability or misconnections in the complex electromagnetic environment of industrial sites. Existing wireless solutions generally lack effective authentication mechanisms, posing a security risk of unauthorized personnel arbitrarily accessing and modifying parameters. In distributed applications, multiple nodes need to maintain parameter consistency to ensure collaborative stability, but current technologies struggle to achieve rapid synchronization, typically requiring configuration for each node individually, which is inefficient and necessitates repeated settings when equipment is replaced or the system is expanded, leading to high maintenance costs. Furthermore, while Near Field Communication (NFC) technology is simple to operate and intuitive, its short communication distance and limited transmission rate make it unsuitable for large-scale parameter configuration; Bluetooth, on the other hand, offers high transmission rates and long communication distances, but connection establishment is complex and response times are long. Therefore, how to fully combine the advantages of NFC and Bluetooth to achieve fast, secure, and reliable wireless configuration has become a critical technical problem that urgently needs to be solved.

[0004] Therefore, it is necessary to provide a parameter configuration method and system based on WellBUS distributed frequency converter to solve the above technical problems. In order to solve the above problems, a technical solution is provided. Summary of the Invention

[0005] To overcome the aforementioned shortcomings of the prior art, this invention provides a parameter configuration method and system based on WellBUS distributed frequency converters, which addresses the problems of inconvenient traditional debugging and access, high safety risks, and low efficiency of multi-node parameter synchronization in scenarios involving the collaboration of multiple frequency converter nodes in a WellBUS bus distributed architecture.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The parameter configuration method based on WellBUS distributed frequency converters includes the following steps: By constructing a distributed inverter parameter configuration network, several WellBUS inverter slave stations are connected to the WellBUS bus network, node communication relationships are established based on the WellBUS bus master station, and a parameter configuration APP is installed on the mobile configuration terminal. Perform dynamic authentication and quick Bluetooth connection operations based on NFC touch through the mobile configuration terminal; The main control MCU collects the operating status data of the WellBUS inverter slave station in real time, configures the APP to construct the operating status vector based on the operating status data, and constructs a parameter adaptive matching mechanism in combination with the historical parameter database to analyze the coupling relationship between the parameters and generate target recommended parameters. After the recommended configuration parameters are entered through the graphical interface, the configuration APP performs static range verification and dynamic operating condition verification on the recommended configuration parameters, identifies abnormal configuration parameters, and generates a target parameter configuration file. For each WellBUS inverter slave station, a dual scenario parameter synchronization mechanism is implemented, and an operational stability assessment is conducted in conjunction with the target parameter configuration file to evaluate the operational stability of the WellBUS bus network. The mobile configuration terminal and WellBUS bus master station upload each configuration record, running data and fault log to the cloud platform.

[0007] As a further aspect of the present invention, a mobile configuration terminal performs dynamic authentication and Bluetooth quick connection operations based on NFC touch, specifically as follows: After logging into the configuration APP via a mobile configuration terminal, a user permission identifier is generated based on the user's identity information. When the mobile configuration terminal approaches the target WellBUS inverter slave station, the NFC tag module inside the WellBUS inverter slave station is activated and generates a one-time dynamic session token based on the device's unique identifier, current timestamp, and security key. At the same time, it reads the Bluetooth device address, pairing code, and device status information, and encapsulates the above information into an NDEF data packet and sends it to the mobile configuration terminal. The mobile configuration terminal verifies the validity of the dynamic session token. Once the verification is successful, it automatically calls the Bluetooth interface to initiate a BLE connection request and completes the Bluetooth connection.

[0008] As a further aspect of this invention, the operating status data of the WellBUS inverter slave station is collected in real time by the main control MCU, the APP is configured to construct an operating status vector based on the operating status data, and a parameter adaptive matching mechanism is constructed in combination with the historical parameter database to analyze the coupling relationship between various parameters and generate target recommended parameters. The specific steps are as follows: Based on the main control MCU deployed inside the WellBUS inverter slave station, the operating status data of the WellBUS inverter slave station is collected in real time through analog-to-digital sampling interface, drive feedback interface and status detection interface, as a type of operating status data; The main control MCU performs preprocessing operations on the acquired type of operating status data to form standardized operating status data; By configuring the APP to receive standardized operational status data, a type of operational status vector is constructed according to the preset parameter order. The APP is configured to call the historical parameter database to read historical running status data, which is used as a second-class running status vector. Based on the import of one type of running state vector and two types of running state vector into the parameter adaptive matching mechanism, the running state coupling factor is output. Based on the operating status coupling factor, historical operating statuses that match the current operating conditions are selected, and the corresponding historical configuration parameters are determined as target recommended parameters.

[0009] As a further aspect of the present invention, the static range verification is specifically performed by comparing the recommended configuration parameters with the allowable threshold range of the preset configuration parameters. If the recommended configuration parameters are within the preset allowable threshold range, the recommended configuration parameters are normal; if the recommended configuration parameters exceed the preset allowable threshold range, the recommended configuration parameters are abnormal. The dynamic operating condition verification is as follows: Configure the APP to read the operating status vector corresponding to the current WellBUS inverter slave station, extract a type of operating status data and compare it with the preset allowable threshold range of operating status data. If a type of operating status data is within the preset allowable threshold range of operating status data, then the type of operating status data is normal; if a type of operating status data exceeds the preset allowable threshold range of operating status data, then the type of operating status data is abnormal.

[0010] As a further aspect of the present invention, a dual scenario parameter synchronization mechanism is implemented for each WellBUS inverter slave station. The dual scenario parameter synchronization mechanism includes a broadcast synchronization mechanism based on the WellBUS bus and a node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication.

[0011] As a further aspect of the present invention, the broadcast synchronization mechanism based on the WellBUS bus is as follows: when the target WellBUS inverter slave station has been connected to the WellBUS bus network, the configuration APP sends a synchronization command to the currently configured bridge inverter; after receiving the synchronization command, the bridge inverter sends a parameter broadcast synchronization request to the WellBUS bus master station through the WellBUS interface; the WellBUS bus master station reads the synchronization control information in the target parameter configuration file and generates a target synchronization node set according to the synchronization group number, node address range, and device type.

[0012] As a further aspect of the present invention, the node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication is as follows: when some WellBUS inverter slave stations are not connected to the bus network or require individual configuration, the operator carries a mobile configuration terminal and approaches each target inverter in turn; a BLE connection is quickly established through NFC triggering, and the target parameter configuration file is automatically read; subsequently, the configuration APP writes the target parameter configuration file to the corresponding WellBUS inverter slave station through the Bluetooth link; after each slave station completes the parameter update, it feeds back the configuration status result to the configuration APP and records the current node configuration progress.

[0013] As a further aspect of the present invention, an operational stability assessment is performed in conjunction with a target parameter configuration file to evaluate the operational stability of the WellBUS bus network. The specific steps are as follows: The mobile configuration terminal obtains the target parameter configuration file of the current WellBUS inverter slave station, monitors the real-time configuration parameters and operating status data of the remaining WellBUS inverter slave stations in real time, and extracts the changing parameters to form a set of differential parameters. A stability assessment model is built based on the set of differential parameters, and the stability coefficient is output. The WellBUS bus master station identifies abnormal slave stations based on the stability coefficient. If the operating stability coefficient of the WellBUS inverter slave station is found to exceed the preset stability threshold, the parameter rollback mechanism or resynchronization mechanism will be automatically triggered to ensure the consistency of parameters and the stability of operation of the entire distributed network.

[0014] The parameter configuration system based on WellBUS distributed frequency converters includes: a distributed frequency converter parameter configuration network, an NFC dynamic authentication and Bluetooth communication module, a parameter adaptive matching module, a parameter verification and identification module, and an operation stability evaluation module. The distributed inverter parameter configuration network is used to connect several WellBUS inverter slave stations to the WellBUS bus network, establish node communication relationships based on the WellBUS bus master station, and install a parameter configuration APP on the mobile configuration terminal. The NFC dynamic authentication and Bluetooth communication module is used to perform dynamic authentication and Bluetooth quick connection operations based on NFC touch. The parameter adaptive matching module is used to collect the operating status data of the WellBUS inverter slave station in real time through the main control MCU, configure the APP to construct the operating status vector based on the operating status data, and combine it with the historical parameter database to construct the parameter adaptive matching mechanism, analyze the coupling relationship between the parameters, and generate the target recommended parameters; The parameter verification and identification module is used to configure the APP to perform static range verification and dynamic working condition verification on the recommended configuration parameters after the recommended configuration parameters are input through the graphical interface, identify abnormal configuration parameters, and generate target parameter configuration files. The operational stability assessment module is used to perform a dual scenario parameter synchronization mechanism for each WellBUS inverter slave station, and to conduct operational stability assessment in conjunction with the target parameter configuration file, thereby evaluating the operational stability of the WellBUS bus network.

[0015] As a further embodiment of the present invention, the distributed inverter parameter configuration network includes a mobile configuration terminal, a WellBUS inverter slave station, and a WellBUS bus master station module; the WellBUS inverter slave station includes an MCU master control module, a drive isolation module, a rectifier-inverter module, a WellBUS bus interface module, an NFC tag module, and a Bluetooth communication module.

[0016] The technical effects and advantages of this invention based on the parameter configuration method and system for WellBUS distributed frequency converters are as follows: This invention, through the collaborative operation of the WellBUS bus network and mobile configuration terminal, can significantly improve the efficiency of distributed frequency converter parameter configuration, avoiding the problems of long configuration time, poor parameter consistency, and high risk of misoperation caused by traditional manual commissioning of each unit individually; through NFC dynamic authentication and BLE fast connection mechanisms, it can achieve scan-free and input-free fast connection, not only improving on-site commissioning efficiency but also enhancing device connection security through dynamic session tokens to prevent unauthorized terminal access; through the operational status data analysis and historical parameter database matching mechanism, it can automatically recommend the most suitable target parameters for the current operating conditions based on the current load status, thereby reducing the risks of current surges, abnormal temperature rises, and equipment oscillations.

[0017] This invention combines static range verification with dynamic operating condition verification to further avoid parameter overruns and parameter mismatches with operating conditions, thereby improving parameter configuration security. The dual-scenario parameter synchronization mechanism can accommodate both WellBUS online network batch synchronization and offline device individual configuration needs, enhancing adaptability to complex industrial environments. Furthermore, the operational stability assessment and automatic parameter rollback mechanism can identify abnormal slave stations in real time and automatically restore abnormal parameters, thus improving the operational stability and reliability of the entire WellBUS distributed network. Attached Figure Description

[0018] Figure 1 A flowchart illustrating the parameter configuration method based on a WellBUS distributed frequency converter provided in this embodiment of the invention; Figure 2 This is a system block diagram of a parameter configuration system based on a WellBUS distributed frequency converter, provided in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of this invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described technical solutions are only a part of this invention, and not all of it. All other technical solutions obtained by those skilled in the art based on the technical solutions of this invention without inventive effort are within the scope of protection of this invention.

[0020] Example 1: As Figure 1 The diagram shown is a flowchart of a parameter configuration method based on a WellBUS distributed frequency converter provided in an embodiment of the present invention. Figure 1 The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. User equipment can include, but is not limited to, computers, smartphones, personal digital assistants (PDAs), and the aforementioned electronic devices. Network equipment can include, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Cloud computing is a type of distributed computing, consisting of a super virtual computer composed of a group of loosely coupled computers. This embodiment does not limit this. Steps S1 to S6 are detailed as follows: Step S1: By constructing a distributed inverter parameter configuration network, several WellBUS inverter slave stations are connected to the WellBUS bus network. Node communication relationships are established based on the WellBUS bus master station. A parameter configuration APP is installed on the mobile configuration terminal to execute parameter configuration tasks, device authentication, and synchronization control. Step S2: The mobile configuration terminal performs dynamic authentication and Bluetooth quick connection operations based on NFC touch. Specifically: After logging into the configuration APP via the mobile configuration terminal, a user permission identifier is generated based on the user's identity information. When the mobile configuration terminal approaches the target WellBUS inverter slave station, the NFC tag module inside the WellBUS inverter slave station is activated and generates a one-time dynamic session token based on the device's unique identifier, current timestamp, and security key. Simultaneously, the Bluetooth device address, pairing code, and device status information are read, and this information is encapsulated into an NDEF data packet and sent to the mobile configuration terminal. The mobile configuration terminal verifies the validity of the dynamic session token. Upon successful verification, it automatically initiates a BLE connection request via the Bluetooth interface, thus completing a fast Bluetooth connection without input or scanning. Step S3: The main control MCU collects the operating status data of the WellBUS inverter slave station in real time, configures the APP to construct the operating status vector based on the operating status data, and constructs a parameter adaptive matching mechanism in combination with the historical parameter database to analyze the coupling relationship between the parameters and generate target recommended parameters. Step S4: After completing the input of recommended configuration parameters based on the graphical interface, configure the APP to perform static range verification and dynamic working condition verification on the recommended configuration parameters, identify abnormal configuration parameters, and generate target parameter configuration file. Step S5: For each WellBUS inverter slave station, execute the dual scenario parameter synchronization mechanism and combine it with the target parameter configuration file to evaluate the operational stability of the WellBUS bus network. In step S6, the mobile configuration terminal and the WellBUS bus master station upload each configuration record, running data and fault log to the cloud platform.

[0021] It also includes: the mobile configuration terminal encapsulates the target parameter configuration file into parameter data frames and sends them to the target frequency converter via the BLE Bluetooth link; after receiving the parameter data frames, the frequency converter's Bluetooth module transmits them to the main control MCU via the UART interface; the main control MCU parses the parameter data frames, updates the operating parameter storage area, and performs immediate parameter activation operations, including frequency adjustment, acceleration / deceleration time switching, and control mode update.

[0022] It should be noted that all parameter data involved in the calculation were pre-processed to be dimensionless.

[0023] Preferably, the main control MCU collects the operating status data of the WellBUS inverter slave station in real time, configures the APP to construct an operating status vector based on the operating status data, and combines it with the historical parameter database to construct a parameter adaptive matching mechanism, analyze the coupling relationship between various parameters, and generate target recommended parameters. The specific steps are as follows: Based on the main control MCU deployed inside the WellBUS inverter slave station, the operating status data of the WellBUS inverter slave station is collected in real time through analog-to-digital sampling interface, drive feedback interface and status detection interface, which is used as a type of operating status data; the operating status data includes output current, motor temperature rise parameters and load fluctuation rate; The main control MCU performs preprocessing operations on the acquired operating status data to form standardized operating status data. The preprocessing operations include outlier removal, data filtering, normalization, and timing synchronization. Among them, the sliding window filtering algorithm removes instantaneous noise data, and the normalization algorithm unifies the data dimensions of different operating parameters to form standardized operating status data. By configuring the APP to receive standardized operational status data, a type of operational status vector is constructed according to the preset parameter order. The APP is configured to call the historical parameter database to read historical operating status data, which is used as a second type of operating status vector. The historical parameter database stores the configuration parameters, operating status data and fault record information corresponding to different operating states, and establishes the correspondence between operating conditions and parameter configuration results. Based on the import of one type of running state vector and two types of running state vector into the parameter adaptive matching mechanism, the running state coupling factor is output. Based on the operating status coupling factor, historical operating statuses that match the current operating conditions are selected, and the corresponding historical configuration parameters are determined as target recommended parameters.

[0024] Preferably, based on the import of a first-class and a second-class running state vector into the parameter adaptive matching mechanism, a running state coupling factor is output. The formula for calculating the running state coupling factor is as follows: ; In the formula: Let i be the running state coupling factor corresponding to the i-th historical running state. For the k-th type of running state data in a class of running state vectors, For the i-th historical running state, the k-th running state data corresponds to the second type of running state vector. This represents the number of types of runtime status data.

[0025] In one embodiment of the present invention, the main control MCU deployed inside the WellBUS inverter slave station collects real-time operating status data of the current inverter slave station through analog-to-digital sampling interface, drive feedback interface, and status detection interface. Specifically, the output current reflects the load of the conveying equipment; when the density of goods on the conveyor line increases, the output current will rise significantly. The motor temperature rise parameter reflects the current thermal operating state of the equipment; when the motor operates under high load for a long time, the temperature rise parameter will gradually approach the temperature rise protection threshold. The load fluctuation rate describes the degree of change in the conveying load within a certain time window; when there is accumulation of conveyed materials or intermittent feeding, the load fluctuation rate will increase significantly. Through the above operating status data, the current operating condition of the WellBUS inverter slave station can be comprehensively reflected.

[0026] Due to strong electromagnetic interference and load fluctuation noise in the industrial environment, the main control MCU does not directly use the raw data for parameter analysis after collecting the operating status data. Instead, it first performs preprocessing operations on the collected operating status data. In practical applications, a sliding window filtering algorithm is used to filter the output current data. For example, at the moment the conveyor motor starts, the output current will show a short-term spike. If this data is directly used for parameter analysis, it may lead to the system misjudging the current load status. Therefore, averaging multiple consecutive sampling points using the sliding window filtering algorithm can effectively remove instantaneous noise interference. At the same time, the system will also discard outliers. For example, if the output current is abnormally high at a certain moment due to communication jitter during the sampling process, the sampling point will be automatically identified as an outlier and discarded.

[0027] After filtering, the system further normalizes the different types of operating status data. Since the physical dimensions of output current, motor temperature rise, and load fluctuation rate are different, direct vector analysis could easily lead to one type of data having an excessive impact on the results. Therefore, the system uses a normalization algorithm to map all types of operating status data to a standardized range. For example, the output current is mapped to the 0-1 range, the temperature rise parameter is proportionalized according to the temperature rise protection threshold, and the load fluctuation rate is normalized according to the historical maximum fluctuation value, thus forming standardized operating status data. Simultaneously, the system performs time-series synchronization processing on data sampled at different times to ensure that the output current, temperature rise parameter, and load fluctuation rate correspond under the same time base, thereby improving the accuracy of subsequent operating condition analysis.

[0028] The configuration app receives standardized operating status data and constructs an operating status vector according to preset parameter order. This vector provides a unified digital description of the current operating conditions of the WellBUS inverter slave station. Simultaneously, the configuration app accesses the historical parameter database to read historical operating status data and constructs corresponding secondary operating status vectors. During actual system operation, the historical parameter database continuously records configuration parameters, operating status data, and fault records for different operating conditions. For example, under light-load conveying conditions, it records the corresponding output current, temperature rise parameters, and load fluctuation rate, and saves the acceleration / deceleration time, output frequency, and PI parameter configuration used under this condition; under heavy-load conditions, it records another set of corresponding parameters. With long-term system operation, the historical parameter database gradually forms a collection of historical operating status samples covering multiple operating conditions.

[0029] After obtaining the first and second types of operating state vectors, they are imported into a parameter adaptive matching mechanism to analyze the coupling relationship between the current operating condition and historical operating conditions, and output the operating state coupling factor. In this example, the Euclidean distance algorithm is used to calculate the degree of difference between the current operating state and each historical operating state.

[0030] For example, at a certain moment, the operating state vector corresponding to the WellBUS inverter slave station is: The system performs matching calculations against multiple sets of operating state vectors in the historical database. The historical operating state vector with the smallest coupling factor is considered the closest to the current operating state. For example, if the coupling factor for historical operating state vector 15 is only 0.08, while other historical operating states are all greater than 0.2, then historical operating state vector 15 is determined to be the optimal matching operating state.

[0031] Subsequently, historical operating states matching the current operating conditions are selected based on the operating status coupling factor, and the corresponding historical configuration parameters are extracted as target recommended parameters. In this logistics transportation example, due to the high current load volatility, the system automatically recommends extending the acceleration time and appropriately reducing the PI proportional gain to reduce the oscillation risk of the conveyor motor during the start-up phase. At the same time, due to the high current motor temperature rise, the system also automatically reduces the maximum output frequency, thereby reducing the equipment's thermal load.

[0032] By employing the above method, fixed parameter configurations are no longer dependent on manual experience. Instead, the system automatically matches the most suitable historical parameter schemes for the current operating conditions based on the real-time operating status, thereby achieving dynamic adaptive optimization of WellBUS distributed frequency converter parameters. Actual operation results show that after adopting the above parameter adaptive matching mechanism, the number of motor overcurrent protection calls in the logistics conveying system is significantly reduced, the conveying cycle time fluctuation is significantly decreased, and the equipment temperature rise control is more stable. The operational stability and parameter configuration efficiency of the entire WellBUS distributed conveying network are significantly improved.

[0033] Preferably, after the recommended configuration parameters are input via the graphical interface, the configuration APP performs static range verification and dynamic operating condition verification on the recommended configuration parameters to identify abnormal parameters, thereby generating a target parameter configuration file. The specific steps are as follows: Recommended configuration parameters include motor rated voltage, motor rated power, motor rated current, motor rated frequency, acceleration / deceleration time, maximum output frequency, motor rated frequency, and speed loop PI parameters; The static range check is performed by comparing the recommended configuration parameters with the preset allowable threshold range. If the recommended configuration parameters are within the preset allowable threshold range, the recommended configuration parameters are normal; if the recommended configuration parameters exceed the preset allowable threshold range, the recommended configuration parameters are abnormal. The dynamic operating condition verification is as follows: Configure the APP to read the operating status vector corresponding to the current WellBUS inverter slave station, extract a type of operating status data and compare it with the preset operating status data allowable threshold range. If a type of operating status data is within the preset operating status data allowable threshold range, then the type of operating status data is normal; if a type of operating status data exceeds the preset operating status data allowable threshold range, then the type of operating status data is abnormal. For recommended configuration parameters that are abnormal and a certain type of running status data, configure the APP to automatically generate parameter conflict prompts; For normal recommended configuration parameters and a type of runtime status data, perform an encapsulation operation to generate a target parameter configuration file.

[0034] In one embodiment of the present invention, dozens of distributed frequency converter slave stations based on the WellBUS bus are deployed on-site to control the conveyor rollers, electric lifting mechanisms, and high-speed sorting devices, respectively. Because the warehousing system operates continuously for extended periods, and the conveying load varies significantly across different time periods, traditional parameter configuration methods relying on manual experience are prone to problems such as unreasonable parameter settings, unstable equipment operation, and frequent triggering of motor overheat protection. Especially during peak logistics periods, some conveyor lines experience a sudden increase in load due to cargo accumulation. On-site technicians typically still use fixed parameter templates for configuration, leading to a mismatch between the frequency converter output frequency and the current load conditions, further causing current surges, conveying cycle fluctuations, and frequent equipment shutdowns. To address these issues, after generating recommended configuration parameters, the warehousing system performs dual verification of the recommended configuration parameters through a combination of static range verification and dynamic operating condition verification, ultimately generating a target parameter configuration file. This ensures the security and operational stability of the WellBUS distributed frequency converter network parameter configuration.

[0035] In actual operation, the configuration app first generates recommended configuration parameters based on historical operating conditions and a parameter adaptive matching mechanism. Specifically, it automatically recommends a set of configuration parameters for the current WellBUS inverter slave station, including motor rated voltage, motor rated power, motor rated current, motor rated frequency, acceleration / deceleration time, maximum output frequency, and speed loop PI parameters. For example, in a certain conveyor station, if a high load fluctuation rate is detected, the configuration app automatically recommends extending the acceleration time and reducing the maximum output frequency to reduce the current surge generated by the conveyor motor during startup. Simultaneously, due to the high load on the current conveyor mechanism, it automatically adjusts the proportional gain in the speed loop PI parameters to improve speed stability during the conveying process.

[0036] After the recommended configuration parameters are generated, operators can view the current recommended parameters through the graphical interface provided by the configuration APP. The graphical interface not only displays the recommended values ​​for each parameter, but also simultaneously shows the allowable range, historical configuration values, and risk warning information for the corresponding parameters. For example, during a certain configuration process, the recommended maximum output frequency of the current WellBUS inverter slave station is 48Hz, the acceleration time is 4s, and the PI proportional gain is 1.2. Operators can modify or confirm the recommended values ​​according to the actual needs on site.

[0037] Subsequently, the configuration app performs a static range check on the recommended configuration parameters. In this example, the system pre-stores the allowable parameter threshold ranges for each WellBUS inverter model in the parameter template library. For example: the allowable range for motor rated voltage is 380V±10%; the allowable range for maximum output frequency is 0~50Hz; the allowable range for acceleration time is 1s~20s; and the allowable range for PI proportional gain is 0.1~5. The recommended configuration parameters are compared with their corresponding allowable threshold ranges. For example, when the operator manually changes the maximum output frequency to 55Hz, it is detected that this parameter exceeds the maximum output frequency range allowed by the WellBUS inverter. Therefore, the recommended configuration parameter is determined to be abnormal, and a red warning box is displayed in the graphical interface indicating "Maximum output frequency exceeds the allowable range." At the same time, the parameter is automatically prevented from being written to the target inverter, thereby preventing the motor from running at overspeed and causing equipment damage. As another example, in the WellBUS inverter slave station corresponding to another conveyor lifting mechanism, the operator changes the acceleration time to 0.5s, while the system's preset minimum acceleration time is 1s. Because excessively short acceleration time can easily lead to an excessively large instantaneous starting current, this parameter will be judged as abnormal, and a parameter conflict warning message "acceleration time is too short, there is a risk of current surge" will be generated.

[0038] After completing the static range verification, dynamic operating condition verification is further performed. Unlike static range verification, dynamic operating condition verification focuses more on the compatibility between parameters and the current operating conditions. Specifically, the configuration APP reads the operating status vector corresponding to the current WellBUS inverter slave station and extracts operating status data such as output current, motor temperature rise parameters, and load fluctuation rate. For example, during the operation of a high-speed conveyor line, it is detected that the current output current is continuously approaching the upper limit of the rated current, while the motor temperature rise has reached 85% of the temperature rise protection threshold.

[0039] Subsequently, the aforementioned type of operating status data is compared with the preset allowable threshold ranges for operating status data. For example, the preset allowable threshold for motor temperature rise is 90℃; the allowable threshold for output current is 95% of the rated current; and the allowable threshold for load fluctuation rate is 0.7. If the current output current or motor temperature rise is detected to exceed the corresponding threshold, the current type of operating status data is determined to be abnormal. In this example, since the current motor temperature rise is already close to the upper limit of temperature rise protection, if the maximum output frequency in the recommended configuration parameters remains at a high value, the dynamic operating condition risk of "conflict between high-frequency operation and high-temperature state" will be further identified.

[0040] For example, during a high-load operation at night, the current load fluctuation rate was detected to reach 0.82, while the recommended acceleration time was still 2 seconds. Since a short acceleration time can easily cause a large current surge in the conveyor motor during startup when the load fluctuates significantly, the system will automatically determine that the current operating data is abnormal and generate a parameter conflict warning message: "The current load fluctuation is large; it is recommended to extend the acceleration time."

[0041] In practical applications, dynamic operating condition verification can effectively prevent parameters that are "legal" but "unsuitable for the current operating conditions" from being written into the device. For example, a maximum output frequency parameter, although not exceeding the static allowable range, may still cause the motor to continue overheating under the current high-temperature conditions; similarly, a PI proportional gain, although within the allowable range, may still cause speed oscillations under the current high-inertia load conditions. Through dynamic operating condition verification, the matching relationship between parameters and the current operating state can be further analyzed, thereby improving the operating condition adaptability of parameter configuration.

[0042] Upon identifying abnormal recommended configuration parameters or a type of operational status data, the configuration app automatically generates parameter conflict alerts and displays the specific source of risk to operators through a graphical interface. Examples include: "Current motor temperature rise is high; it is recommended to reduce the maximum output frequency"; "Current load fluctuation is too large; it is recommended to extend the acceleration time"; "Current output current is close to the threshold; it is recommended to reduce the PI proportional gain." Simultaneously, it automatically provides corresponding corrective parameter suggestions to help on-site technicians quickly complete parameter adjustments.

[0043] For the recommended configuration parameters and a type of operating status data that have passed static range verification and dynamic operating condition verification, a further encapsulation operation is performed to generate a target parameter configuration file. In this example, the target parameter configuration file includes not only the finally confirmed target parameter data, but also device identification information, parameter version information, parameter verification results, and CRC checksums. Subsequently, the target parameter configuration file is sent to the corresponding WellBUS inverter slave station via the BLE Bluetooth link and is further used for subsequent WellBUS bus broadcast synchronization. In actual operation, since all parameters have undergone static range verification and dynamic operating condition verification before being formally written, it is possible to effectively prevent abnormal parameters from spreading to the entire WellBUS distributed network, thereby significantly improving the consistency of parameter configuration and operational stability of the entire network.

[0044] This invention reduces the frequency of motor overcurrent protection and decreases the fluctuation range of conveyor cycle time. Furthermore, because dynamic operating condition verification can identify abnormal operating states such as high temperature and high load in advance, abnormal equipment temperature rise is effectively controlled. Compared to traditional manual parameter tuning methods, it can more intelligently achieve dynamic matching between parameters and operating conditions, thereby improving the safety, stability, and network coordination of WellBUS distributed frequency converter parameter configuration.

[0045] Preferably, a dual scenario parameter synchronization mechanism is implemented for each WellBUS inverter slave station. The dual scenario parameter synchronization mechanism includes a broadcast synchronization mechanism based on the WellBUS bus and a node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication.

[0046] Preferably, the broadcast synchronization mechanism based on the WellBUS bus is as follows: when the target WellBUS inverter slave station has been connected to the WellBUS bus network, the configuration APP sends a synchronization command to the currently configured bridge inverter; after receiving the synchronization command, the bridge inverter sends a parameter broadcast synchronization request to the WellBUS bus master station through the WellBUS interface; the WellBUS bus master station reads the synchronization control information in the target parameter configuration file and generates a target synchronization node set according to the synchronization group number, node address range, and device type. The node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication works as follows: When some WellBUS inverter slave stations are not connected to the bus network or require individual configuration, the operator carries a mobile configuration terminal and approaches each target inverter in turn; a BLE connection is quickly established through NFC triggering, and the target parameter configuration file is automatically read; subsequently, the configuration APP writes the target parameter configuration file to the corresponding WellBUS inverter slave station through the Bluetooth link; after each slave station completes the parameter update, it feeds back the configuration status result to the configuration APP and records the current node configuration progress.

[0047] In one embodiment of the present invention, when the target WellBUS inverter slave station has been connected to the WellBUS bus network, a broadcast synchronization mechanism based on the WellBUS bus is preferentially used for network-wide parameter synchronization. For example, in the battery module conveying area, there are more than twenty WellBUS inverter slave stations on site that have been connected to the WellBUS industrial bus network, each corresponding to a different conveyor roller and lifting mechanism. At this time, after the operator completes the generation of the target parameter configuration file through the mobile configuration APP, the configuration APP will send a synchronization command to the currently configured bridge inverter. The so-called bridge inverter refers to an inverter node that has completed parameter configuration through Bluetooth or local interface and has WellBUS bus communication capability. It plays a bridging role between the mobile configuration terminal and the WellBUS bus during the entire synchronization process.

[0048] After receiving the synchronization command, the bridging inverter sends a parameter broadcast synchronization request to the WellBUS bus master via its internal WellBUS interface. In this example, the WellBUS bus master is typically deployed in the central control cabinet of the production line, responsible for managing the WellBUS node communication and parameter synchronization tasks for the entire production line. Upon receiving the broadcast synchronization request, the master first reads the synchronization control information from the target parameter configuration file, including the synchronization group number, node address range, and device type information. For example, the current target parameter configuration file specifies the synchronization group number as "G02," corresponding to the battery module conveying area; the node address range is "0x20~0x35"; and the device type is "conveyor drive inverter."

[0049] Subsequently, the WellBUS bus master station generates a target synchronization node set based on the synchronization control information. Specifically, it automatically selects all conveyor drive frequency converters belonging to the "G02" synchronization group and whose node addresses are between 0x20 and 0x35 as target synchronization nodes, without synchronizing parameters to other area devices, such as the frequency converter nodes corresponding to the AGV traction system or lifting robotic arm, thereby achieving grouped synchronization control of parameters in different production areas.

[0050] After generating the target synchronization node set, the WellBUS bus master further reads the target parameter data from the target parameter configuration file. Since the original parameters of some nodes in the entire transmission area are already consistent with the target parameters, a full parameter broadcast is not performed. Instead, the changed parameters are extracted first to form a set of differential parameters. For example, for synchronization only: the maximum output frequency is adjusted from 50Hz to 45Hz; the acceleration time is adjusted from 2s to 4s; while keeping other parameters unchanged, which can effectively reduce the WellBUS bus communication load and improve synchronization efficiency.

[0051] Subsequently, the WellBUS master station broadcasts the set of differing parameters to each WellBUS inverter slave station in the target synchronization node set. Upon receiving the synchronization data, each slave station's internal main control MCU parses and updates the parameters, automatically returning the CRC check result and synchronization status information. For example, when an inverter slave station corresponding to a certain conveyor roller completes its parameter update, it will report a "parameter synchronization successful" status to the master station. If a node fails to write parameters due to a communication error, the master station will automatically identify the faulty node and re-execute the parameter broadcast, thus ensuring the consistency of parameter configuration throughout the entire conveyor area.

[0052] Compared to the traditional manual configuration method, the broadcast synchronization mechanism based on the WellBUS bus can complete the unified parameter update of dozens of inverter slave stations within seconds, significantly improving on-site commissioning efficiency. Furthermore, because target nodes are selected based on synchronization group numbers and node address ranges, it also prevents erroneous parameters from spreading to other production areas, improving the overall network parameter synchronization security.

[0053] However, in actual industrial settings, not all WellBUS inverter slaves are always online. For example, during equipment maintenance, node replacement, or new equipment installation, some inverters may not yet be connected to the WellBUS bus network, or may require separate parameter configuration. In this scenario, the system automatically switches to a node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication.

[0054] For example, during a production line maintenance process, a WellBUS inverter responsible for the battery pack lifting mechanism was replaced with a new one due to a malfunction. Because the new equipment was not yet officially connected to the WellBUS bus network, parameter transmission could not be completed via broadcast synchronization. In this situation, on-site technicians carrying mobile configuration terminals approached the target inverters one by one. When the mobile terminal approached the inverter, a BLE Bluetooth connection was quickly established via NFC trigger. Specifically, the inverter's internal NFC tag automatically sent the device identification information, Bluetooth MAC address, and dynamic pairing code to the mobile configuration terminal, allowing the mobile configuration terminal to quickly complete Bluetooth pairing without manual device searching.

[0055] The configuration app automatically reads the corresponding target parameter configuration file and writes it to the current WellBUS inverter slave station via a BLE Bluetooth link. Therefore, after the newly replaced WellBUS inverter slave station completes the parameter writing, it can immediately have the same operating capabilities and network communication capabilities as the original equipment.

[0056] After the parameters are written, each slave station will automatically report the configuration status to the configuration app. For example, status messages such as "Parameters written successfully," "Station address configuration complete," and "Waiting to join the WellBUS network" will be displayed. Simultaneously, the configuration app will record the current node configuration progress in real time and generate node configuration logs. For instance, during a field debugging session, the system might display: Node 0x41 configuration complete; Node 0x42 awaiting configuration; Node 0x43 communication error; thus helping field technicians quickly grasp the overall node configuration status.

[0057] Compared to traditional wired commissioning methods, this node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication eliminates the need to disassemble the control cabinet or connect serial cables. Technicians only need to bring a mobile terminal near the equipment to complete parameter synchronization, making it particularly suitable for industrial sites with dense equipment, limited space, or frequent maintenance. Simultaneously, the NFC dynamic triggering mechanism prevents accidental connection to other frequency converters, improving the security of single-node configuration. In actual operation, the dual-scenario parameter synchronization mechanism automatically selects the most suitable synchronization method based on the network status of the field equipment. When the WellBUS network is online normally, the broadcast synchronization mechanism is prioritized for rapid configuration of the entire network; when the equipment is offline for maintenance or individual commissioning, it automatically switches to the NFC+BLE node-by-node synchronization mechanism, thus balancing the efficiency of large-scale parameter synchronization with the flexible configuration needs of local equipment.

[0058] The embodiments of the present invention can significantly shorten the inverter parameter configuration time in the production line through a dual scene parameter synchronization mechanism, significantly improve the recovery efficiency after equipment replacement, and at the same time, since the system can ensure the consistency of parameter configuration between different WellBUS nodes, the stability of the conveying cycle and the equipment collaborative operation capability of the entire production line are significantly improved.

[0059] Preferably, the operational stability of the WellBUS bus network is evaluated by combining the target parameter configuration file. The specific steps are as follows: The mobile configuration terminal obtains the target parameter configuration file of the current WellBUS inverter slave station, monitors the real-time configuration parameters and operating status data of the remaining WellBUS inverter slave stations in real time, and extracts the changing parameters to form a set of differential parameters. A stability assessment model is built based on the set of differential parameters, and the stability coefficient is output. The WellBUS bus master station identifies abnormal slave stations based on the stability coefficient. If the operating stability coefficient of the WellBUS inverter slave station is found to exceed the preset stability threshold, the parameter rollback mechanism or resynchronization mechanism will be automatically triggered to ensure the consistency of parameters and the stability of operation of the entire distributed network.

[0060] Preferably, an operational stability assessment model is built based on the set of differential parameters, and an operational stability coefficient is output. The WellBUS bus master station identifies abnormal slave stations based on the operational stability coefficient. The calculation formula for the operational stability assessment model is as follows: ; In the formula: Let be the operating stability coefficient of the j-th WellBUS frequency converter slave station. These are the weighting coefficients for parameters related to changes in operating status. For the j-th WellBUS inverter slave station At time t, the k-th type of running state data in the first type of running state vector. For the j-th WellBUS inverter slave station at time t, the k-th type of operating state data of the first type of operating state vector. To configure the weighting coefficients of changing parameters in real time, For the j-th WellBUS inverter slave station The h-th real-time configuration parameter at time h, This is the h-th real-time configuration parameter for the j-th WellBUS inverter slave station at time t.

[0061] In one embodiment of the present invention, during actual operation, on-site technicians first generate target parameter configuration files and synchronize parameters using a mobile configuration terminal. For example, before the start of a loading / unloading operation, multiple WellBUS inverter slave stations in the conveyor belt area are uniformly adjusted. After parameter synchronization is completed, the mobile configuration terminal automatically obtains the target parameter configuration file corresponding to the current WellBUS inverter slave station and uses this target parameter configuration file as a benchmark parameter template for subsequent operational stability assessment.

[0062] The mobile configuration terminal monitors the real-time configuration parameters and operating status data of the remaining WellBUS inverter slave stations in real time through the WellBUS bus network, and reads the currently effective configuration parameters of each slave station in real time.

[0063] Because the inverter slave stations in the WellBUS bus network may be affected by load changes, electromagnetic interference, or human error, the real-time configuration parameters of some slave stations may gradually deviate from the standard parameters in the target parameter configuration file. For example, during the operation of a conveyor belt, if the field maintenance personnel temporarily modify the maximum output frequency of a certain inverter slave station, the operating parameters of that node will be inconsistent with those of other nodes. Another example is that the inverter slave station corresponding to a stacker crane, due to prolonged operation at high temperatures, experiences a significant increase in output current fluctuations, resulting in abnormal changes in its operating status data. To promptly identify these anomalies, the changed parameters are extracted to form a set of discrepancies.

[0064] By comparing the standard parameters in the target parameter configuration file with the current real-time configuration parameters, the changed parameter items are extracted. For example, if the maximum output frequency changes from 45Hz to 50Hz, or the acceleration time changes from 4s to 2s, these changed parameters are automatically recorded in the difference parameter set. Simultaneously, the operating status data at different time points are compared, such as the change between the current output current and the previous output current; the change between the current temperature rise parameter and the previous temperature rise parameter; and the change between the current load fluctuation rate and the previous load fluctuation rate, forming an operating status change set.

[0065] An operational stability assessment model is built based on a set of differential parameters, and the operational stability coefficients for each WellBUS inverter slave station are output. The model considers both "operational state changes" and "real-time configuration changes." For example, when the output current of a WellBUS inverter slave station changes drastically within a short period, the first parameter, "operational state change," increases rapidly; conversely, when the PI parameter or maximum output frequency of a node is abnormally modified, the second parameter, "real-time configuration change," also increases significantly. This two-factor coupled analysis method provides a more comprehensive reflection of the current operational stability of the WellBUS inverter slave stations.

[0066] For example, during a nighttime loading and unloading operation, the WellBUS inverter slave station corresponding to conveyor belt No. 12 experienced a sudden increase in load, causing its output current to rise rapidly from 32A to 45A within 10 seconds. Simultaneously, its acceleration time parameter was mistakenly modified to 1 second by on-site personnel. At this point, the calculated operational stability coefficient for this node was significantly higher than that of other normal nodes. Because both the change in operating status and the change in real-time configuration increased simultaneously, the operational stability coefficient of this node quickly exceeded the preset stability threshold.

[0067] After receiving the operational stability coefficient, the WellBUS bus master will automatically identify abnormal slave stations based on the stability coefficient corresponding to each node. For example, when the stability threshold is set to 0.75, if the operational stability coefficient of a certain node reaches 0.92, the system will immediately determine that the node is an abnormal slave station.

[0068] After identifying the abnormal slave station, further analysis of the source of the abnormality is conducted. For example, if it is mainly caused by changes in operating status, it may correspond to abnormal load or mechanical jamming; if it is mainly caused by changes in real-time configuration, it may correspond to incorrect parameter modification or synchronization failure.

[0069] Automatic parameter rollback or resynchronization mechanisms are triggered. For example, in the conveyor belt example above, since the system detected an abnormal change in the acceleration time parameter of slave station number 12, the parameter rollback mechanism is automatically triggered first to restore the current real-time configuration parameters to the standard parameters in the target parameter configuration file.

[0070] If the system detects that the operational stability coefficient is still abnormal after the parameter rollback, a resynchronization mechanism is further triggered. Specifically, the WellBUS bus master rebroadcasts the target parameter configuration file to the abnormal slave station and requests the corresponding master control MCU to re-execute parameter writing and CRC verification, thereby ensuring that the node parameters are consistent with the overall network configuration.

[0071] At the same time, the mobile configuration terminal will also display abnormal node information in real time through a graphical interface, helping on-site technicians to quickly grasp the operation status of the WellBUS bus network.

[0072] Through the embodiments of this invention, the parameter drift problem of WellBUS frequency converters in intelligent port automated loading and unloading systems is effectively controlled, and the speed of abnormal node identification is significantly improved. Furthermore, because the system can automatically perform parameter rollback and resynchronization, the operational consistency and stability of the entire distributed network are significantly improved. Compared to the traditional method relying solely on manual inspection, this invention enables more intelligent dynamic monitoring of the WellBUS bus network's operational status and abnormal self-recovery control, thereby enhancing the safety and reliability of large-scale industrial distributed control systems.

[0073] Example 2: In this embodiment of the invention, a large number of distributed frequency converter slave stations based on the WellBUS bus are deployed on-site to control the ore conveyor belt, hoisting winch, vibrating screen, and automatic loading equipment. Due to the complex mining environment, wide equipment distribution, and significant load and operating cycle differences between different devices, the traditional method of manually adjusting parameters one by one is insufficient to meet the rapid configuration requirements of a large-scale distributed frequency converter network. Especially during equipment expansion, maintenance, and changes in operating conditions, on-site technicians need to frequently modify multiple frequency converter parameters, resulting in low configuration efficiency and problems such as inconsistent parameter configurations, communication address conflicts, and synchronization omissions. To address these issues, this intelligent mining system introduces a parameter configuration method based on WellBUS distributed frequency converters, enabling intelligent parameter configuration and stable operation control of the WellBUS distributed frequency converter network.

[0074] In actual deployment, a distributed inverter parameter configuration network is constructed. Specifically, several WellBUS inverter slave stations are deployed in the ore conveyor belt area, hoist area, and automatic loading area, and are uniformly connected to the WellBUS bus network. The WellBUS bus master station is deployed in the central control room to manage the node communication relationships in the entire mine conveying system. Each WellBUS inverter slave station is assigned an independent node address and establishes a communication connection with the master station through the WellBUS protocol. For example, the node address range for the conveyor belt area is set to 0x20~0x40, and the node address range for the hoist area is set to 0x50~0x60, thereby realizing grouped management of different equipment areas.

[0075] Meanwhile, on-site technicians install a parameter configuration app on the mobile configuration terminal to perform parameter configuration tasks, equipment authentication, and synchronous control operations. The mobile configuration terminal typically uses an industrial tablet or explosion-proof handheld terminal, capable of stable operation in the high-dust, high-vibration environment of a mine. The configuration app not only allows users to view the current operating status of the WellBUS inverter slave station but also performs functions such as parameter recommendation, parameter synchronization, and operational stability analysis.

[0076] Dynamic authentication based on NFC touch and fast Bluetooth connection. In practical applications, when field technicians need to configure a WellBUS inverter slave station corresponding to a specific conveyor belt, they only need to bring their mobile configuration terminal close to the corresponding device. At this time, the NFC tag module inside the WellBUS inverter slave station is automatically activated, and a one-time dynamic session token is generated based on the device's unique identifier, the current timestamp, and the security key. For example, the system will combine the device number "WB-203", the current timestamp, and the dynamic key to generate a dynamic authentication token that is only valid within the current time window.

[0077] At the same time, the NFC tag module will automatically read the Bluetooth device address, dynamic pairing code and device status information corresponding to the current frequency converter, and encapsulate the above information into an NFC Data Exchange Format (NDEF) message and send it to the mobile configuration terminal.

[0078] After receiving the NDEF data packet, the mobile configuration terminal first verifies the validity of the dynamic session token. For example, it checks if the timestamp has expired, if the dynamic key matches, and if the device's unique identifier is valid to determine the trustworthiness of the current connection request. Once the verification is successful, the configuration app automatically initiates a Bluetooth Low Energy (BLE) connection request via the Bluetooth interface, thus completing a fast Bluetooth connection without input or scanning. Compared to the traditional method of manually searching for Bluetooth devices and entering pairing codes, this significantly improves on-site commissioning efficiency and avoids accidental connection to other WellBUS inverter slave stations.

[0079] After completing the BLE connection, the main control MCU deployed inside the WellBUS inverter slave station collects current operating status data in real time through the analog-to-digital sampling interface, drive feedback interface, and status detection interface. Because the load of the ore conveying system varies significantly, the system focuses on monitoring changes in output current and load fluctuation rate.

[0080] Simultaneously, the system configures the app to access historical parameter databases to read historical operating status data and constructs an adaptive parameter matching mechanism. The historical database records operating parameters, fault records, and operational stability data under different ore conveying conditions. For example, under light-load conveying conditions, it records shorter acceleration times and higher output frequency configurations; while under heavy-load conveying conditions, it records longer acceleration times and lower output frequency configurations. The coupling relationship between the current operating status vector and historical operating states is further analyzed, and historical configuration parameters closest to the current operating condition are selected. For example, when the system detects a high fluctuation rate in the current conveyor belt load, it automatically recommends extending the acceleration time and reducing the PI proportional gain, thereby reducing the risk of current surges during startup. Finally, target recommended parameters are generated.

[0081] After generating the target recommended parameters, the system allows users to view these parameters through the configuration app's graphical interface and confirm or modify them according to on-site needs. For example, technicians can adjust the maximum output frequency appropriately based on the ore conveying cycle time. The configuration app performs static range verification and dynamic operating condition verification on the recommended configuration parameters. During static range verification, the system compares the recommended parameters with preset allowable threshold ranges. For example, whether the maximum output frequency exceeds 50Hz; whether the acceleration time is less than 1s; and whether the PI proportional gain exceeds the stable range. If a parameter exceeds the allowable range, an abnormal prompt message is immediately generated. Simultaneously, dynamic operating condition verification is performed. For example, if the current motor temperature rise is detected to be close to the temperature rise protection threshold, and the recommended output frequency is still too high, it is determined that the current parameters do not match the operating conditions, and a message is displayed: "The current equipment temperature rise is high; it is recommended to reduce the maximum output frequency." For normal parameters that pass both verifications, a further encapsulation operation is performed to generate the target parameter configuration file.

[0082] A dual-scenario parameter synchronization mechanism is implemented for each WellBUS inverter slave station. When the target inverter is already connected to the WellBUS bus network, the broadcast synchronization mechanism is used first. Specifically, the configuration APP sends synchronization commands to the bridge inverter, and the WellBUS bus master station broadcasts the parameter configuration file to the target synchronization node. For example, in the ore conveying area, the parameters of more than twenty conveying inverters can be synchronized at one time, thereby significantly improving commissioning efficiency.

[0083] For new or maintained equipment not connected to the WellBUS bus network, the NFC+BLE node-by-node synchronization mechanism is automatically adopted. For example, when the frequency converter corresponding to a hoisting winch has just been replaced, technicians only need to bring their mobile terminals close to the equipment to quickly establish a BLE connection via NFC and write the target parameter configuration file into the corresponding frequency converter.

[0084] After parameter synchronization is complete, an operational stability assessment is performed based on the target parameter configuration file. For example, the WellBUS bus master station monitors the real-time changes in the operating status and configuration parameters of each slave station and calculates the corresponding operational stability coefficient. When the operational stability coefficient of a certain inverter slave station exceeds the stability threshold, the system automatically triggers a parameter rollback mechanism or a resynchronization mechanism to ensure the operational stability of the entire WellBUS distributed network.

[0085] The mobile configuration terminal and WellBUS bus master station upload each configuration record, operating data, and fault log to the cloud platform. Through the cloud platform, back-end maintenance personnel can remotely analyze the operating status of different WellBUS inverter slave stations and further optimize the historical parameter database and parameter recommendation strategies.

[0086] The embodiments of the present invention significantly improve parameter configuration efficiency and shorten equipment maintenance and recovery time. At the same time, because it can realize adaptive parameter recommendation and operational stability analysis, the operational consistency, security and stability of the entire WellBUS distributed network are significantly improved.

[0087] Example 3: A parameter configuration system based on a WellBUS distributed frequency converter, comprising: a distributed frequency converter parameter configuration network, an NFC dynamic authentication and Bluetooth communication module, a parameter adaptive matching module, a parameter verification and identification module, and an operational stability evaluation module; the distributed frequency converter parameter configuration network is connected to the NFC dynamic authentication and Bluetooth communication module, the parameter adaptive matching module, the parameter verification and identification module, and the operational stability evaluation module, respectively; the NFC dynamic authentication and Bluetooth communication module is connected to the parameter adaptive matching module; the parameter adaptive matching module is connected to the parameter verification and identification module; and the parameter verification and identification module is connected to the operational stability evaluation module. The distributed inverter parameter configuration network is used to connect several WellBUS inverter slave stations to the WellBUS bus network, establish node communication relationships based on the WellBUS bus master station, and install a parameter configuration APP on the mobile configuration terminal. The NFC dynamic authentication and Bluetooth communication module is used to perform dynamic authentication and Bluetooth quick connection operations based on NFC touch. The parameter adaptive matching module is used to collect the operating status data of the WellBUS inverter slave station in real time through the main control MCU, configure the APP to construct the operating status vector based on the operating status data, and combine it with the historical parameter database to construct the parameter adaptive matching mechanism, analyze the coupling relationship between the parameters, and generate the target recommended parameters; The parameter verification and identification module is used to configure the APP to perform static range verification and dynamic working condition verification on the recommended configuration parameters after the recommended configuration parameters are input through the graphical interface, identify abnormal configuration parameters, and generate target parameter configuration files. The operational stability assessment module is used to perform a dual scenario parameter synchronization mechanism for each WellBUS inverter slave station, and to conduct operational stability assessment in conjunction with the target parameter configuration file, thereby evaluating the operational stability of the WellBUS bus network.

[0088] Furthermore, the distributed inverter parameter configuration network includes a mobile configuration terminal, a WellBUS inverter slave station, and a WellBUS bus master station module; the WellBUS inverter slave station includes an MCU master control module, a drive isolation module, a rectifier-inverter module, a WellBUS bus interface module, an NFC tag module, and a Bluetooth communication module.

[0089] like Figure 2 The diagram shown is a system block diagram of a parameter configuration system based on a WellBUS distributed frequency converter according to an embodiment of the present invention, which can be used to execute... Figure 1 The steps in the method embodiments shown are implemented in a similar manner and have similar technical effects, and will not be repeated here.

[0090] Through the above embodiments, the present invention, by working collaboratively with a mobile configuration terminal via a WellBUS bus network, can significantly improve the efficiency of distributed frequency converter parameter configuration, avoiding the problems of long configuration time, poor parameter consistency, and high risk of misoperation caused by traditional manual commissioning of each unit; through NFC dynamic authentication and BLE fast connection mechanism, it can achieve scan-free and input-free fast connection, which not only improves on-site commissioning efficiency, but also enhances device connection security through dynamic session tokens to prevent unauthorized terminal access; through the operation status data analysis and historical parameter database matching mechanism, it can automatically recommend the most suitable target parameters for the current operating conditions based on the current load status, thereby reducing the risks of current surges, abnormal temperature rises, and equipment oscillations.

[0091] This invention combines static range verification with dynamic operating condition verification to further avoid parameter overruns and parameter mismatches with operating conditions, thereby improving parameter configuration security. The dual-scenario parameter synchronization mechanism can accommodate both WellBUS online network batch synchronization and offline device individual configuration needs, enhancing adaptability to complex industrial environments. Furthermore, the operational stability assessment and automatic parameter rollback mechanism can identify abnormal slave stations in real time and automatically restore abnormal parameters, thus improving the operational stability and reliability of the entire WellBUS distributed network.

[0092] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

[0093] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A parameter configuration method based on WellBUS distributed frequency converter, characterized in that, Includes the following steps: By constructing a distributed inverter parameter configuration network, several WellBUS inverter slave stations are connected to the WellBUS bus network, node communication relationships are established based on the WellBUS bus master station, and a parameter configuration APP is installed on the mobile configuration terminal. Perform dynamic authentication and quick Bluetooth connection operations based on NFC touch through the mobile configuration terminal; The main control MCU collects the operating status data of the WellBUS inverter slave station in real time, configures the APP to construct the operating status vector based on the operating status data, and constructs a parameter adaptive matching mechanism in combination with the historical parameter database to analyze the coupling relationship between the parameters and generate target recommended parameters. After the recommended configuration parameters are entered through the graphical interface, the configuration APP performs static range verification and dynamic operating condition verification on the recommended configuration parameters, identifies abnormal configuration parameters, and generates a target parameter configuration file. For each WellBUS inverter slave station, a dual scenario parameter synchronization mechanism is implemented, and an operational stability assessment is conducted in conjunction with the target parameter configuration file to evaluate the operational stability of the WellBUS bus network. The mobile configuration terminal and WellBUS bus master station upload each configuration record, running data and fault log to the cloud platform.

2. The parameter configuration method based on WellBUS distributed frequency converter according to claim 1, characterized in that, The mobile configuration terminal performs dynamic authentication based on NFC touch and quick Bluetooth connection operations, specifically as follows: After logging into the configuration APP via a mobile configuration terminal, a user permission identifier is generated based on the user's identity information. When the mobile configuration terminal approaches the target WellBUS inverter slave station, the NFC tag module inside the WellBUS inverter slave station is activated and generates a one-time dynamic session token based on the device's unique identifier, current timestamp, and security key. At the same time, it reads the Bluetooth device address, pairing code, and device status information, and encapsulates the above information into an NDEF data packet and sends it to the mobile configuration terminal. The mobile configuration terminal verifies the validity of the dynamic session token. Once the verification is successful, it automatically calls the Bluetooth interface to initiate a BLE connection request and completes the Bluetooth connection.

3. The parameter configuration method based on WellBUS distributed frequency converter according to claim 1, characterized in that, The main control MCU collects real-time operating status data from the WellBUS inverter slave station. The APP is configured to construct an operating status vector based on the operating status data, and combines it with a historical parameter database to build a parameter adaptive matching mechanism. The coupling relationship between various parameters is analyzed to generate target recommended parameters. The specific steps are as follows: Based on the main control MCU deployed inside the WellBUS inverter slave station, the operating status data of the WellBUS inverter slave station is collected in real time through analog-to-digital sampling interface, drive feedback interface and status detection interface, as a type of operating status data; The main control MCU performs preprocessing operations on the acquired type of operating status data to form standardized operating status data; By configuring the APP to receive standardized operational status data, a type of operational status vector is constructed according to the preset parameter order. The APP is configured to call the historical parameter database to read historical running status data, which is used as a second-class running status vector. Based on the import of one type of running state vector and two types of running state vector into the parameter adaptive matching mechanism, the running state coupling factor is output. Based on the operating status coupling factor, historical operating statuses that match the current operating conditions are selected, and the corresponding historical configuration parameters are determined as target recommended parameters.

4. The parameter configuration method based on WellBUS distributed frequency converter according to claim 1, characterized in that, The static range check is performed by comparing the recommended configuration parameters with the preset allowable threshold range. If the recommended configuration parameters are within the preset allowable threshold range, the recommended configuration parameters are normal; if the recommended configuration parameters exceed the preset allowable threshold range, the recommended configuration parameters are abnormal. The dynamic operating condition verification is as follows: Configure the APP to read the operating status vector corresponding to the current WellBUS inverter slave station, extract a type of operating status data and compare it with the preset operating status data allowable threshold range. If a type of operating status data is within the preset operating status data allowable threshold range, then the type of operating status data is normal. If a certain type of operational status data exceeds the preset allowable threshold range for operational status data, then that type of operational status data is considered abnormal.

5. The parameter configuration method based on WellBUS distributed frequency converter according to claim 1, characterized in that, For each WellBUS inverter slave station, a dual scenario parameter synchronization mechanism is implemented. The dual scenario parameter synchronization mechanism includes a broadcast synchronization mechanism based on the WellBUS bus and a node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication.

6. The parameter configuration method based on WellBUS distributed frequency converter according to claim 5, characterized in that, The broadcast synchronization mechanism based on the WellBUS bus works as follows: When the target WellBUS inverter slave station has been connected to the WellBUS bus network, the configuration APP sends a synchronization command to the currently configured bridge inverter; after receiving the synchronization command, the bridge inverter sends a parameter broadcast synchronization request to the WellBUS bus master station through the WellBUS interface; the WellBUS bus master station reads the synchronization control information in the target parameter configuration file and generates a target synchronization node set according to the synchronization group number, node address range, and device type.

7. The parameter configuration method based on WellBUS distributed frequency converter according to claim 5, characterized in that, The node-by-node synchronization mechanism based on NFC triggering and Bluetooth communication works as follows: when some WellBUS inverter slave stations are not connected to the bus network or require individual configuration, the operator carries a mobile configuration terminal and approaches each target inverter in turn; a BLE connection is quickly established through NFC triggering, and the target parameter configuration file is automatically read; subsequently, the configuration APP writes the target parameter configuration file to the corresponding WellBUS inverter slave station through the Bluetooth link. After each slave station completes the parameter update, it will send the configuration status result back to the configuration APP and record the current node configuration progress.

8. The parameter configuration method based on WellBUS distributed frequency converter according to claim 1, characterized in that, The operational stability of the WellBUS bus network is evaluated by combining the target parameter configuration file. The specific steps are as follows: The mobile configuration terminal obtains the target parameter configuration file of the current WellBUS inverter slave station, monitors the real-time configuration parameters and operating status data of the remaining WellBUS inverter slave stations in real time, and extracts the changing parameters to form a set of differential parameters. A stability assessment model is built based on the set of differential parameters, and the stability coefficient is output. The WellBUS bus master station identifies abnormal slave stations based on the stability coefficient. If the operating stability coefficient of the WellBUS inverter slave station is found to exceed the preset stability threshold, the parameter rollback mechanism or resynchronization mechanism will be automatically triggered to ensure the consistency of parameters and the stability of operation of the entire distributed network.

9. A parameter configuration system based on a WellBUS distributed frequency converter, applied to the parameter configuration method based on a WellBUS distributed frequency converter as described in any one of claims 1-8, characterized in that, include: Distributed frequency converter parameter configuration network, NFC dynamic authentication and Bluetooth communication module, parameter adaptive matching module, parameter verification and identification module, and operation stability evaluation module; The distributed inverter parameter configuration network is used to connect several WellBUS inverter slave stations to the WellBUS bus network, establish node communication relationships based on the WellBUS bus master station, and install a parameter configuration APP on the mobile configuration terminal. The NFC dynamic authentication and Bluetooth communication module is used to perform dynamic authentication and Bluetooth quick connection operations based on NFC touch. The parameter adaptive matching module is used to collect the operating status data of the WellBUS inverter slave station in real time through the main control MCU, configure the APP to construct the operating status vector based on the operating status data, and combine it with the historical parameter database to construct the parameter adaptive matching mechanism, analyze the coupling relationship between the parameters, and generate the target recommended parameters; The parameter verification and identification module is used to configure the APP to perform static range verification and dynamic working condition verification on the recommended configuration parameters after the recommended configuration parameters are input through the graphical interface, identify abnormal configuration parameters, and generate target parameter configuration files. The operational stability assessment module is used to perform a dual scenario parameter synchronization mechanism for each WellBUS inverter slave station, and to conduct operational stability assessment in conjunction with the target parameter configuration file, thereby evaluating the operational stability of the WellBUS bus network.

10. The parameter configuration system based on WellBUS distributed frequency converter according to claim 9, characterized in that, The distributed inverter parameter configuration network includes a mobile configuration terminal, a WellBUS inverter slave station, and a WellBUS bus master station module; the WellBUS inverter slave station includes an MCU master control module, a drive isolation module, a rectifier-inverter module, a WellBUS bus interface module, an NFC tag module, and a Bluetooth communication module.

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