A control system for a plant mixer

Abstract

The application discloses a kind of control systems of mixing station loader, belong to engineering machinery intelligent control technical field, including cloud management platform module, multidimensional data monitoring module, abnormal monitoring and early warning module, power-supply-drive collaborative control module, data storage and traceability module mobile terminal interaction module and security encryption module, the integrated control system including cloud management platform module, multidimensional data monitoring module, abnormal monitoring and early warning module, power-supply-drive collaborative control module, data storage and traceability module, mobile terminal interaction module and security encryption module is built in the application, seamless collaboration of each component is realized, equipment state is comprehensively controlled, abnormal risk is quickly responded, running efficiency is accurately optimized, data security is traceable and management is convenient and efficient, reduce the equipment energy consumption, prolong the service life of equipment, improve the operation safety and management efficiency.

Description

Technical Field

[0001] This invention belongs to the field of intelligent control technology for construction machinery, specifically referring to a control system for a loader in a concrete mixing plant. Background Technology

[0002] With the transformation of energy structure and increasingly stringent environmental protection requirements, the construction machinery industry is accelerating its upgrade towards new energy and intelligentization. As the core equipment for aggregate transfer and batching supply in mixing plants, the loaders of mixing plants have fixed operating locations, regular operating processes, and relatively stable load fluctuations, giving them a natural advantage in new energy transformation. Upgrading existing old machines to new energy has become an important path for the industry to reduce costs, increase efficiency, and achieve green development. However, the current control systems of mixing plant loaders are generally difficult to adapt to the operational needs after the shift to new energy, and many technical shortcomings have been exposed under traditional operating modes, which seriously restricts the equipment's operating efficiency and intelligent management level.

[0003] However, existing control systems for concrete mixing plant loaders have certain shortcomings. Existing technologies suffer from poor protocol compatibility, significant communication barriers between inverters, PLCs, and management platforms leading to data transmission delays or interruptions; data acquisition dimensions are limited and lack effective calibration mechanisms, making it difficult to comprehensively and accurately reflect equipment operating status and energy consumption, thus affecting the scientific nature of management decisions; anomaly monitoring has a narrow scope and vague judgment standards, with single and delayed handling methods, failing to achieve differentiated early warning and timely protection, and resulting in poor balancing of operational safety and continuity; the power supply system and drive system operate independently, with fixed drive parameters unable to dynamically adapt to different power supply conditions, leading to low operating efficiency and high energy consumption; data storage is scattered, lacks security, and is inconvenient for traceability and querying, making it difficult to support long-term fault diagnosis and status optimization; management relies on on-site operation or fixed terminals, with weak remote interaction capabilities and a lack of coordination with the overall production management system of the concrete mixing plant, resulting in low efficiency in centralized management of multiple devices; furthermore, data transmission and storage are susceptible to theft and tampering, and security is insufficient, severely restricting equipment operating efficiency, energy consumption control, and the level of intelligent management. Therefore, a control system for concrete mixing plant loaders is proposed. Summary of the Invention

[0004] The purpose of this invention is to provide a control system for a loader in a concrete mixing plant, so as to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a control system for a mixing plant loader, comprising a cloud management platform module, a multi-dimensional data monitoring module, an anomaly monitoring and early warning module, a power supply-drive coordinated control module, a data storage and traceability module, a mobile terminal interaction module, and a security encryption module;

[0006] The cloud management platform module is used to build a symbiotic protocol system with frequency converters and PLCs and to achieve overall system management.

[0007] The multi-dimensional data monitoring module is used to collect data related to the operation, energy consumption, and usage time of the loader equipment in real time.

[0008] The anomaly monitoring and early warning module is used to identify various equipment anomalies and activate a graded early warning and protection mechanism;

[0009] The power supply-drive coordinated control module is used to coordinate the parameters of the power supply system and the drive system to achieve safe and efficient operation.

[0010] The data storage and traceability module is used to store the operation and abnormal data of cloud storage devices and supports multi-condition query and traceability.

[0011] The mobile interaction module is used to push information to the administrator and provide a remote operation entry point;

[0012] The security encryption module is used to ensure the security and authenticity of data transmission and storage.

[0013] Preferably, the cloud management platform module has a built-in protocol adaptation unit and an operation status evaluation unit;

[0014] The protocol adaptation unit pre-stores the inverter communication protocol, PLC communication protocol and cloud platform communication protocol, and performs bidirectional real-time synchronization of the three through protocol conversion;

[0015] The operation status assessment unit, based on the preset normal operation parameter threshold range of the equipment and combined with the real-time data collected by the multi-dimensional data monitoring module, comprehensively assesses the operation status of the loader through weighted scoring and generates a multi-level operation status score report. When the score result reaches the preset unqualified standard, the abnormal monitoring and early warning module is automatically triggered to start the early warning process, and the score report and the corresponding abnormal data are associated and stored in the data storage and traceability module.

[0016] The cloud management platform module also has a hierarchical permission management function, which can set different levels of access permissions, with different permissions corresponding to different operation ranges.

[0017] Preferably, the multi-dimensional data monitoring module includes a device status acquisition unit, a power consumption acquisition unit, a usage time statistics unit, and a data calibration unit;

[0018] The equipment status acquisition unit collects core equipment operating parameters in real time, such as motor operating parameters, gearbox operating status parameters, torque converter operating parameters, and power supply interface connection status, through sensors deployed on key components such as the loader motor, gearbox, torque converter, and power supply interface.

[0019] The power consumption acquisition unit is connected to the relevant components of the power supply system and the optional power battery to collect instantaneous power consumption and cumulative power consumption in real time, and supports statistical analysis of power consumption data and generation of trend curves according to a preset time period.

[0020] The usage time statistics unit accurately records the loader's start-up time, downtime, and standby time, and calculates the effective working time, cumulative running time, and standby time percentage, clearly reflecting the equipment's usage efficiency.

[0021] The data calibration unit periodically acquires standard calibration data from sensors and power consumption metering devices, compares the deviation between real-time acquired data and standard data, and if the deviation exceeds the preset deviation range, it automatically starts the calibration algorithm to correct the acquired data and records the calibration-related information to the data storage and traceability module. If the deviation still exceeds the threshold after multiple consecutive calibrations, it determines that the corresponding acquisition device is faulty and triggers the anomaly monitoring and early warning module to send fault warning information.

[0022] Preferably, the anomaly monitoring and early warning module presets four types of anomalies: abnormal equipment parameters, abnormal power supply, abnormal communication, and abnormal safety overtravel, along with corresponding judgment conditions.

[0023] The abnormal device parameter determination condition is that the collected device operating parameters exceed the preset threshold range and the duration reaches the preset duration.

[0024] The communication anomaly determination condition is that the communication interruption time between the cloud management platform and the PLC, frequency converter or mobile terminal reaches the preset communication interruption duration; the safety overtravel anomaly determination condition is that the loader's operating range exceeds the preset operating radius.

[0025] Preferably, after the anomaly monitoring and early warning module identifies an anomaly, it immediately generates anomaly information including the time of occurrence of the anomaly, the type of anomaly, information related to the anomaly parameters, and the current work location, and activates a graded early warning mechanism.

[0026] Preferably, the power supply-drive coordinated control module includes a power supply status monitoring unit, a drive parameter adjustment unit, and a coordinated control strategy unit;

[0027] The power supply status monitoring unit collects the voltage, current, power and power supply mode of the power supply system in real time, and transmits the data to the collaborative control strategy unit in real time.

[0028] The drive parameter adjustment unit is directly connected to the loader's motor controller;

[0029] The collaborative control strategy unit dynamically formulates an adaptive collaborative control strategy based on power supply status data and real-time equipment operating requirements: when line power is used and the grid load is within a suitable range, the motor is controlled to start at an appropriate starting speed, and a reasonable acceleration time is set to reach the maximum speed, minimizing the impact on the grid during the starting process; when battery power is used, the drive parameters are intelligently adjusted according to the remaining battery power. When the remaining power is lower than a preset remaining power threshold, the maximum motor speed is limited, and the power output is reduced to save power and extend the operating range; when the power supply system malfunctions, the drive parameter adjustment unit immediately reduces the motor power output. If the malfunction persists for a preset duration, the motor is controlled to stop and automatically restart after the power supply is restored to normal.

[0030] Preferably, the data storage and traceability module adopts a cloud-based distributed storage architecture, which is divided into a real-time data storage unit, a historical data storage unit, and an abnormal data storage unit. The real-time data storage unit is used to store recent real-time data of device operation.

[0031] The historical data storage unit is used to store operational data that is beyond the recent range;

[0032] The abnormal data storage unit is used to store the complete data chain when an abnormality occurs, and the abnormal data is stored for a long time.

[0033] Preferably, the mobile interaction module includes an APP client and an information push unit;

[0034] The APP client has comprehensive functions: real-time display of key data; after receiving abnormal alarm information, the administrator can send confirmation commands through the APP to view the abnormal details and the system's recommended handling suggestions, and can also remotely issue control commands such as device shutdown and restart;

[0035] The information push unit supports administrators to customize push settings.

[0036] Preferably, the security encryption module employs high-strength encryption to encrypt all communication data between the cloud management platform and the PLC, frequency converter, and mobile terminal throughout the entire process; it encrypts and stores various types of data in the cloud, sets exclusive data access keys, which are updated regularly by the administrator, and supports a secure retrieval mechanism in case of key loss; the security encryption module has a data anti-tampering function, by adding a unique identifier to the stored data, when the data is illegally tampered with, the identifier verification fails, the system immediately triggers a communication anomaly warning, and marks the tampered data record.

[0037] Preferably, the cloud management platform module can also be connected to the overall production management system of the mixing plant to synchronize the loader's operating data and energy consumption data to the production management system, so as to realize the coordinated linkage between the loader's operation and the mixing plant's batching and production scheduling. When the loader's energy consumption increases abnormally or its operating efficiency decreases, the production management system can adjust the batching rhythm or scheduling plan to optimize the overall production process.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] 1. This invention constructs an integrated control system comprising a cloud management platform module, a multi-dimensional data monitoring module, an anomaly monitoring and early warning module, a power supply-drive collaborative control module, a data storage and traceability module, a mobile terminal interaction module, and a security encryption module. Based on a comprehensive design encompassing protocol adaptation, multi-dimensional data acquisition, hierarchical early warning, dynamic collaborative control, secure cloud storage, remote interaction, and cross-system integration, it achieves seamless collaboration among components, comprehensive control over equipment status, rapid response to anomalies and risks, precise optimization of operational efficiency, traceable and secure data, and convenient and efficient management. This reduces equipment energy consumption, extends equipment lifespan, and improves operational safety and management efficiency.

[0040] 2. This invention uses a protocol adaptation unit to preset multiple communication protocols and achieve bidirectional real-time synchronization; the operation status assessment unit generates multi-level scoring reports based on real-time data to achieve accurate quantitative assessment of equipment status, promptly triggering early warnings and associating stored data to provide a reliable basis for fault diagnosis; hierarchical permission management clarifies the operation scope of different levels, standardizes the system usage process, and enables the control system to have the core capabilities of intelligent overall planning, accurate assessment and standardized management, significantly improving the efficiency and security of equipment operation management;

[0041] 3. This invention uses a power supply status monitoring unit to capture key data such as power supply mode, voltage, and power in real time, and a drive parameter adjustment unit to precisely control core parameters such as motor starting speed and torque output. The collaborative control strategy unit dynamically formulates adaptation schemes according to different working conditions: when powered by the line, the starting parameters are optimized to reduce the impact on the power grid; when powered by the battery, the power output is adjusted according to the remaining power to extend the driving range; and when the power supply is abnormal, the power is reduced or the machine is shut down for protection. This not only ensures the stable operation of the equipment in complex power supply environments, but also significantly reduces energy consumption and equipment wear, and significantly improves the operating efficiency of the new energy loader. Attached Figure Description

[0042] Figure 1 The present invention describes the operation flow of a control system for a mixing plant loader. Figure 1 ;

[0043] Figure 2 The present invention describes the operation flow of a control system for a mixing plant loader. Figure 2;

[0044] Figure 3 The present invention describes the operation flow of a control system for a mixing plant loader. Figure 3 . Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Example

[0047] Please see Figures 1-3 As shown, the present invention provides a technical solution including a cloud management platform module, a multi-dimensional data monitoring module, an anomaly monitoring and early warning module, a power supply-drive collaborative control module, a data storage and traceability module, a mobile terminal interaction module, and a security encryption module;

[0048] The cloud management platform module is used to build a symbiotic protocol system with frequency converters and PLCs and to achieve overall system management.

[0049] The multi-dimensional data monitoring module is used to collect data related to the operation, energy consumption, and usage time of the loader equipment in real time.

[0050] The anomaly monitoring and early warning module is used to identify various equipment anomalies and activate a graded early warning and protection mechanism;

[0051] The power supply-drive coordinated control module is used to coordinate the parameters of the power supply system and the drive system to achieve safe and efficient operation.

[0052] The data storage and traceability module is used to store the operation and abnormal data of cloud storage devices and supports multi-condition query and traceability.

[0053] The mobile interaction module is used to push information to the administrator and provide a remote operation entry point;

[0054] The security encryption module is used to ensure the security and authenticity of data transmission and storage.

[0055] In this embodiment, the cloud management platform module has a built-in protocol adaptation unit and a running status evaluation unit;

[0056] The protocol adaptation unit pre-stores the inverter communication protocol, PLC communication protocol and cloud platform communication protocol, and performs bidirectional real-time synchronization of the three through protocol conversion to ensure that inverter frequency adjustment data, PLC logic control data and cloud platform management commands can interact without delay.

[0057] The operation status assessment unit, based on the preset normal operation parameter threshold range of the equipment and combined with the real-time data collected by the multi-dimensional data monitoring module, comprehensively assesses the operation status of the loader through weighted scoring and generates a multi-level operation status score report. When the score result reaches the preset unqualified standard, the abnormal monitoring and early warning module is automatically triggered to start the early warning process, and the score report and the corresponding abnormal data are associated and stored in the data storage and traceability module.

[0058] The cloud management platform module also has a hierarchical permission management function, which can set different levels of access permissions. Different permissions correspond to different operation scopes. Administrator permissions can perform operations such as configuring core system parameters, allocating permissions, and issuing device control commands, while operator permissions can only view device operation data and receive early warning information, ensuring the standardization and security of system operation.

[0059] In this embodiment, the multi-dimensional data monitoring module includes a device status acquisition unit, a power consumption acquisition unit, a usage time statistics unit, and a data calibration unit;

[0060] The equipment status acquisition unit collects core equipment operating parameters in real time, such as motor operating parameters, gearbox operating status parameters, torque converter operating parameters, and power supply interface connection status, through sensors deployed on key components of the loader, including the motor, gearbox, torque converter, and power supply interface. This ensures the real-time and comprehensiveness of parameter acquisition.

[0061] The power consumption acquisition unit is connected to the relevant components of the power supply system and the optional power battery to collect instantaneous power consumption and cumulative power consumption in real time. It also supports the statistical analysis of power consumption data and the generation of trend curves according to preset time periods, providing data support for energy consumption analysis.

[0062] The usage time statistics unit accurately records the loader's start-up time, shutdown time, and standby time, and calculates the effective working time (defined as the running time when the motor load current reaches or exceeds the preset load current threshold), cumulative running time, and the percentage of standby time, clearly reflecting the equipment's usage efficiency.

[0063] The data calibration unit periodically acquires standard calibration data from sensors and power consumption metering devices, compares the deviation between real-time acquired data and standard data, and if the deviation exceeds the preset deviation range, it automatically starts the calibration algorithm to correct the acquired data and records the calibration-related information to the data storage and traceability module. If the deviation still exceeds the threshold after multiple consecutive calibrations, it determines that the corresponding acquisition device is faulty and triggers the anomaly monitoring and early warning module to send fault warning information.

[0064] In this embodiment, the anomaly monitoring and early warning module presets four types of anomalies: abnormal equipment parameters, abnormal power supply, abnormal communication, and abnormal safety overtravel, along with corresponding judgment conditions.

[0065] The abnormal equipment parameter determination condition is that the collected equipment operating parameters exceed the preset threshold range and the duration reaches the preset duration; power supply abnormality covers a variety of specific situations such as overvoltage, undervoltage, overcurrent, leakage, short circuit and overheating, and each situation corresponds to a preset judgment standard;

[0066] The communication anomaly determination condition is that the communication interruption time between the cloud management platform and the PLC, frequency converter or mobile terminal reaches the preset communication interruption duration; the safety overtravel anomaly determination condition is that the loader's operating range exceeds the preset operating radius.

[0067] In this embodiment, after the anomaly is detected, the anomaly monitoring and early warning module immediately generates anomaly information including the time of occurrence of the anomaly, the type of anomaly, information related to the anomaly parameters, and the current work location, and activates the hierarchical early warning mechanism.

[0068] In this embodiment, the power supply-drive coordinated control module includes a power supply status monitoring unit, a drive parameter adjustment unit, and a coordinated control strategy unit;

[0069] The power supply status monitoring unit collects the voltage, current, power and power supply mode of the power supply system in real time, such as line power supply or battery power supply, and transmits the data to the collaborative control strategy unit in real time.

[0070] The drive parameter adjustment unit is directly connected to the loader's motor controller and can precisely adjust core drive parameters such as motor starting speed, rated speed, torque output, and acceleration time.

[0071] The collaborative control strategy unit dynamically formulates adaptive collaborative control strategies based on power supply status data and real-time equipment operating requirements: when line power is used and the grid load is within a suitable range, the motor is controlled to start at an appropriate starting speed, and a reasonable acceleration time is set to reach the maximum speed, minimizing the impact on the grid during the starting process; when battery power is used, the drive parameters are intelligently adjusted according to the remaining battery power. When the remaining power is lower than a preset remaining power threshold, the maximum speed of the motor is limited, and the power output is reduced to save power and extend the operating range; when the power supply system is abnormal, the drive parameter adjustment unit immediately reduces the motor power output. If the abnormality continues for a preset abnormality duration, the motor is controlled to stop and automatically restart after the power supply is restored to normal, achieving seamless coordination between the power supply and drive systems.

[0072] In this embodiment, the data storage and traceability module adopts a cloud-based distributed storage architecture, which is divided into a real-time data storage unit, a historical data storage unit, and an abnormal data storage unit. The real-time data storage unit is used to store recent real-time data of device operation, maintain the original storage at a reasonable collection frequency, and meet the real-time retrieval requirements.

[0073] The historical data storage unit is used to store operational data that is beyond the recent range. It adopts an efficient compression storage algorithm, aggregates data according to a preset time period, and stores it. The storage period meets the actual application requirements, while taking into account storage costs and data integrity.

[0074] The abnormal data storage unit is used to store the complete data chain when an abnormality occurs, including equipment operating parameters, power supply data, communication data and early warning information for a preset time before and after the abnormality occurs. The abnormal data is stored for a long time, providing a complete basis for fault diagnosis and responsibility tracing. It supports multi-condition combined queries by time range, equipment number, data type and abnormality type. The query results can be exported to common data formats. It also provides a variety of data visualization display functions to facilitate users to intuitively analyze the equipment operation status.

[0075] In this embodiment, the mobile terminal interaction module includes an APP client and an information push unit;

[0076] The APP client has comprehensive functions: real-time display of key data such as the loader's current operating status, instantaneous and cumulative power consumption, cumulative running time, standby time percentage, and core motor operating parameters; it supports viewing historical data statistical reports according to preset time periods; after receiving abnormal alarm information, the administrator can send confirmation commands through the APP to view the abnormal details and system-recommended handling suggestions, and can also remotely issue control commands such as equipment shutdown and restart to realize remote emergency handling;

[0077] The information push unit supports administrators to customize push settings, allowing them to choose the types of warnings to be received and the push frequency. It supports multiple push methods, with the backup push method only triggered when the main push method fails or a level 1 warning is issued, ensuring that no warning information is missed.

[0078] In this embodiment, the security encryption module employs high-strength encryption to encrypt all communication data between the cloud management platform and the PLC, inverter, and mobile terminal throughout the entire process, preventing theft or tampering during data transmission. It also encrypts various types of data stored in the cloud, sets exclusive data access keys, and updates these keys periodically by the administrator. Furthermore, it supports a secure retrieval mechanism for lost keys to ensure data accessibility. The security encryption module also features data anti-tampering functionality. By adding a unique identifier to the stored data, when data is illegally tampered with, the identifier verification fails, the system immediately triggers a communication anomaly warning, and marks the tampered data record, ensuring the security, authenticity, and integrity of equipment operation data and anomaly information.

[0079] In this embodiment, the cloud management platform module can also interface with the overall production management system of the mixing plant, synchronizing loader operation data and energy consumption data to the production management system. This enables coordinated operation between the loader and the mixing plant's batching and production scheduling. When the loader's energy consumption increases abnormally or its operating efficiency decreases, the production management system can adjust the batching rhythm or scheduling plan to optimize the overall production process. At the same time, the cloud management platform module supports centralized management of multiple loaders, allowing simultaneous access to loader equipment from multiple mixing plants. It can classify and manage these loaders by equipment identifier and mixing plant name, generating comprehensive operation reports for multiple devices.

[0080] Working Principle: The cloud management platform module acts as the core hub, establishing a symbiotic protocol system with the frequency converter and PLC to coordinate the operation of each module; the multi-dimensional data monitoring module collects real-time data on equipment operation, energy consumption, and usage time; the anomaly monitoring and early warning module continuously identifies various abnormal situations and activates tiered early warning and protection mechanisms; the power supply-drive collaborative control module dynamically matches the parameters of the power supply system and drive system to ensure safe and efficient operation; the data storage and traceability module stores various types of data in the cloud, supporting multi-condition query and traceability; the mobile interaction module provides administrators with information push and remote operation channels; and the security encryption module ensures the security and authenticity of data transmission and storage throughout the entire process.

[0081] The cloud management platform module achieves overall system management through the collaborative work of its built-in functional units; the protocol adaptation unit pre-stores multiple communication protocols and uses protocol conversion technology to achieve bidirectional real-time data synchronization between the inverter, PLC, and cloud platform; the operation status evaluation unit uses preset equipment normal operation parameter threshold ranges as standards, combined with real-time data collected by the multi-dimensional data monitoring module, to comprehensively evaluate the loader's operation status through weighted scoring, generating multi-level scoring reports. When the score reaches the unqualified standard, the anomaly monitoring and early warning module is automatically triggered, and the relevant reports are stored in association with the anomaly data; the hierarchical permission management function standardizes the system operation process by setting different levels of access permissions and corresponding operation scopes. Administrators can perform operations such as core parameter configuration and permission allocation, while operators can only view data and receive early warnings, ensuring the standardization and security of system operation;

[0082] The multi-dimensional data monitoring module achieves comprehensive and accurate data collection and processing through the coordinated operation of four functional units. The equipment status acquisition unit utilizes sensors deployed on key components of the loader to capture in real time the operating parameters of core components such as motors, gearboxes, and torque converters, as well as the connection status of power supply interfaces. The power consumption acquisition unit is connected to relevant components of the power supply system and the power battery, collecting instantaneous and cumulative power consumption in real time, and generating trend curves based on statistical data according to preset time periods. The usage time statistics unit accurately records the loader's start-up, shutdown, and standby times, distinguishing between effective working time, cumulative running time, and the proportion of standby time, clearly presenting the equipment's usage efficiency. The data calibration unit periodically acquires standard calibration data, compares the deviation between real-time collected data and standard data, and automatically starts the calibration algorithm to correct the data and records it if it exceeds the preset range. If multiple calibrations still fail to meet the standard, the acquisition device is judged to be faulty and an early warning is triggered.

[0083] The anomaly monitoring and early warning module achieves accurate identification through preset anomaly types and judgment conditions. The module pre-defines four core anomaly types: equipment parameter anomalies, power supply anomalies, communication anomalies, and safety overtravel anomalies, and sets corresponding judgment conditions for each type of anomaly. Among them, equipment parameter anomalies are judged based on the collected parameters exceeding the preset threshold and lasting for a preset duration; power supply anomalies cover various situations such as overvoltage and undervoltage, and each situation has its own preset judgment criteria; communication anomalies are judged based on the communication interruption duration between the cloud management platform and related components or mobile terminals reaching a preset value; and safety overtravel anomalies are judged based on the loader's operating range exceeding the preset operating radius, through clear classification and judgment logic.

[0084] Upon detecting an anomaly, the anomaly monitoring and early warning module immediately initiates a standardized processing procedure; it quickly integrates anomaly-related information to generate complete anomaly information, including the time of occurrence, type of anomaly, anomaly parameter information, and current work location; subsequently, it activates a tiered early warning mechanism, classifying different early warning levels according to the severity of the anomaly, and taking differentiated handling measures for anomalies of different levels.

[0085] The power supply-drive coordinated control module achieves coordinated optimization of the power supply and drive systems through the dynamic linkage of three functional units. The power supply status monitoring unit collects data such as voltage, current, power and power supply mode of the power supply system in real time and transmits the data to the coordinated control strategy unit in real time. The drive parameter adjustment unit is directly connected to the loader motor controller and can accurately adjust core drive parameters such as motor starting speed and rated speed. Based on the received power supply status data and the real-time operating requirements of the equipment, the coordinated control strategy unit dynamically formulates an appropriate control strategy and adjusts the drive parameters for different operating conditions such as line power supply, battery power supply and power supply abnormality. This minimizes the impact of motor starting on the power grid, maximizes battery range, and protects the equipment in case of power supply abnormality, ensuring seamless coordinated operation of the power supply and drive systems.

[0086] The data storage and traceability module adopts a cloud-based distributed storage architecture to achieve classified storage and efficient utilization of data. The real-time data storage unit is dedicated to storing recent real-time equipment operation data, maintaining a reasonable collection frequency for raw storage and meeting users' real-time retrieval needs. The historical data storage unit stores operation data that exceeds the recent range, aggregating data according to a preset time period through efficient compression storage, ensuring data integrity while controlling storage costs. The abnormal data storage unit is dedicated to storing the complete data chain when an abnormality occurs, including relevant operation, power supply, communication data and early warning information before and after the abnormality, and is stored long-term. The module supports multi-condition combined queries, and the query results can be exported to common data formats and provide various data visualization display functions to facilitate users' intuitive analysis of equipment operation.

[0087] The mobile interaction module achieves convenient management through the collaborative operation of the APP client and the information push unit. The APP client has comprehensive functions, which can display key information such as the loader's operating status, energy consumption data, and running time in real time, and supports viewing historical data statistical reports according to preset time periods. When receiving abnormal alarm information, the administrator can send a confirmation command through the APP to view the abnormal details and the system's recommended handling suggestions. At the same time, the administrator can remotely issue control commands such as equipment shutdown and restart to realize remote emergency handling. The information push unit supports the administrator to customize the push settings, and can independently select the types of warnings to be received and the push frequency. It provides multiple push methods, among which the backup push method is triggered only when the main push method fails or a level 1 warning occurs, ensuring that the warning information is delivered in a timely manner without omission.

[0088] The security encryption module ensures data security and authenticity through multiple encryption protection mechanisms. It employs high-strength encryption technology to encrypt all communication data between the cloud management platform and PLCs, frequency converters, and mobile terminals throughout the entire process, preventing data theft or tampering during transmission. Various types of data stored in the cloud are encrypted and stored with dedicated data access keys. These keys are updated regularly by the administrator, and a secure retrieval mechanism is provided in case of key loss, preventing data inaccessibility due to key issues. The module also features data anti-tampering functionality. By adding a unique identifier to stored data, when data is illegally tampered with, the identifier verification fails, the system immediately triggers a communication anomaly warning, and marks the tampered data record, comprehensively ensuring the security, authenticity, and integrity of equipment operation data and abnormal information.

[0089] The cloud management platform module achieves overall optimization through cross-system integration and multi-device management functions. It can interface with the overall production management system of the mixing plant, synchronizing loader operation data and energy consumption data to the management system in real time. This enables coordinated operation between the loader and the mixing plant's batching and production scheduling. When the loader experiences abnormally high energy consumption or decreased operating efficiency, the production management system can adjust the batching rhythm or scheduling plan accordingly, optimizing the overall production process. Simultaneously, the module supports centralized management of multiple loaders, allowing simultaneous access to loader equipment from multiple mixing plants. It categorizes and manages these loaders by equipment identifier and mixing plant name, generating comprehensive multi-device operation reports. This provides data support for enterprise-wide management and energy consumption optimization, improving overall management efficiency.

[0090] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their likenesses.

[0091] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A control system for a loader in a concrete mixing plant, characterized in that: It includes a cloud management platform module, a multi-dimensional data monitoring module, an anomaly monitoring and early warning module, a power supply-drive collaborative control module, a data storage and traceability module, a mobile terminal interaction module, and a security encryption module; The cloud management platform module is used to build a symbiotic protocol system with frequency converters and PLCs; The multi-dimensional data monitoring module is used to collect data related to the operation, energy consumption, and usage time of the loader equipment in real time. The anomaly monitoring and early warning module is used to identify various equipment anomalies and activate a graded early warning and protection mechanism; The power supply-drive coordinated control module is used to coordinate the parameters of the power supply system and the drive system to achieve safe and efficient operation. The data storage and traceability module is used to store the operation and abnormal data of cloud storage devices and supports multi-condition query and traceability. The mobile interaction module is used to push information to the administrator and provide a remote operation entry point; The security encryption module is used to ensure the security and authenticity of data transmission and storage.

2. The control system for a mixing plant loader according to claim 1, characterized in that: The cloud management platform module has a built-in protocol adaptation unit and an operation status evaluation unit. The protocol adaptation unit pre-stores the inverter communication protocol, PLC communication protocol and cloud platform communication protocol, and performs bidirectional real-time synchronization of the three through protocol conversion; The operation status assessment unit, based on the preset normal operation parameter threshold range of the equipment and combined with the real-time data collected by the multi-dimensional data monitoring module, comprehensively assesses the operation status of the loader through weighted scoring and generates a multi-level operation status score report. When the score result reaches the preset unqualified standard, the abnormal monitoring and early warning module is automatically triggered to start the early warning process, and the score report and the corresponding abnormal data are associated and stored in the data storage and traceability module. The cloud management platform module also has a hierarchical permission management function, which can set different levels of access permissions, with different permissions corresponding to different operation ranges.

3. The control system for a mixing plant loader according to claim 1, characterized in that: The multi-dimensional data monitoring module includes a device status acquisition unit, a power consumption acquisition unit, a usage time statistics unit, and a data calibration unit. The equipment status acquisition unit collects core equipment operating parameters in real time through sensors deployed on key components; The power consumption acquisition unit is connected to the relevant components of the power supply system and the optional power battery to collect instantaneous power consumption and cumulative power consumption in real time, and supports statistical analysis of power consumption data and generation of trend curves according to a preset time period. The usage time statistics unit accurately records the loader's start-up time, downtime, and standby time, and calculates the effective working time, cumulative running time, and standby time percentage, clearly reflecting the equipment's usage efficiency. The data calibration unit periodically acquires standard calibration data from sensors and power consumption metering devices, compares the deviation between real-time acquired data and standard data, and if the deviation exceeds the preset deviation range, it automatically starts the calibration algorithm to correct the acquired data and records the calibration-related information to the data storage and traceability module. If the deviation still exceeds the threshold after multiple consecutive calibrations, it determines that the corresponding acquisition device is faulty and triggers the anomaly monitoring and early warning module to send fault warning information.

4. The control system for a mixing plant loader according to claim 1, characterized in that: The anomaly monitoring and early warning module is preset with four types of anomalies: abnormal equipment parameters, abnormal power supply, abnormal communication, and abnormal safety overtravel, as well as corresponding judgment conditions. The abnormal device parameter determination condition is that the collected device operating parameters exceed the preset threshold range and the duration reaches the preset duration. The communication anomaly determination condition is that the communication interruption time between the cloud management platform and the PLC and mobile terminal reaches the preset communication interruption duration. The condition for determining a safety overtravel anomaly is that the loader's operating range exceeds the preset operating radius.

5. The control system for a mixing plant loader according to claim 1, characterized in that: Once the anomaly monitoring and early warning module identifies an anomaly, it immediately generates anomaly information including the time of occurrence, type of anomaly, relevant information on anomaly parameters, and the current work location, and activates a tiered early warning mechanism.

6. The control system for a mixing plant loader according to claim 1, characterized in that: The power supply-drive coordinated control module includes a power supply status monitoring unit, a drive parameter adjustment unit, and a coordinated control strategy unit. The power supply status monitoring unit collects the voltage, current, power and power supply mode of the power supply system in real time, and transmits the data to the collaborative control strategy unit in real time. The drive parameter adjustment unit is directly connected to the loader's motor controller; The collaborative control strategy unit dynamically formulates an adaptive collaborative control strategy based on power supply status data and real-time equipment operating requirements: when line power is used and the grid load is within a suitable range, the motor is controlled to start at an appropriate starting speed, and a reasonable acceleration time is set to reach the maximum speed, minimizing the impact on the grid during the starting process; when battery power is used, the drive parameters are intelligently adjusted according to the remaining battery power. When the remaining power is lower than a preset remaining power threshold, the maximum motor speed is limited, and the power output is reduced to save power and extend the operating range; when the power supply system malfunctions, the drive parameter adjustment unit immediately reduces the motor power output. If the malfunction persists for a preset duration, the motor is controlled to stop and automatically restart after the power supply is restored to normal.

7. The control system for a mixing plant loader according to claim 1, characterized in that: The data storage and traceability module adopts a cloud-based distributed storage architecture, which is divided into a real-time data storage unit, a historical data storage unit, and an abnormal data storage unit. The real-time data storage unit is used to store recent real-time data of device operation. The historical data storage unit is used to store operational data that is beyond the recent range; The abnormal data storage unit is used to store the complete data chain when an abnormality occurs, and the abnormal data is stored for a long time.

8. The control system for a mixing plant loader according to claim 1, characterized in that: The mobile interaction module includes an APP client and an information push unit; The APP client has comprehensive functions: real-time display of key data; after receiving abnormal alarm information, the administrator can send confirmation commands through the APP, view the abnormal details and the system's recommended handling suggestions, and remotely issue equipment shutdown and restart control commands; The information push unit supports administrators to customize push settings.

9. The control system for a mixing plant loader according to claim 1, characterized in that: The security encryption module employs high-strength encryption to encrypt all communication data between the cloud management platform and the PLC, inverter, and mobile terminal. It also encrypts various types of data stored in the cloud, assigning dedicated data access keys that are periodically updated by the administrator and supporting a secure retrieval mechanism in case of key loss. Furthermore, the security encryption module has anti-tampering capabilities. By adding a unique identifier to the stored data, if the data is illegally tampered with, the identifier verification fails, the system immediately triggers a communication anomaly warning, and marks the tampered data record.

10. The control system for a mixing plant loader according to claim 1, characterized in that: The cloud management platform module can also be connected to the overall production management system of the mixing plant, synchronizing the loader's operating data and energy consumption data to the production management system, realizing the coordinated linkage between the loader's operation and the mixing plant's batching and production scheduling. When the loader's energy consumption increases abnormally or its operating efficiency decreases, the production management system can adjust the batching rhythm or scheduling plan to optimize the overall production process.

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