Control method of concrete mixer

Abstract

The invention relates to the technical field of concrete mixers, and discloses a control method of a concrete mixer, which comprises the following steps: S1, preparation work; s2, data confirmation; s3, data acquisition; s4, alarm work is carried out; and S5, cleaning work is conducted, all parts comprise a data collection module, a processing module and an execution mechanism, and the data collection module is composed of a working condition data sensor and a load capacity sensor and used for collecting real-time working condition data, target working condition data, real-time load capacity and target load capacity of the mixing drum. According to the control method of the concrete mixer, various real-time data during working can be accurately obtained, in the working condition of rapid change, a response can be rapidly made through a module with accurate precision to improve the operation efficiency of equipment, and the situation that due to aging or dull of part of modules of the equipment, the efficiency of a mixing drum motor system is adjusted too slow, and the service life of the mixing drum motor system is prolonged is avoided. And the energy use is optimized, the operation cost is reduced, and the service life of the equipment is prolonged.

Description

Technical Field

[0001] The invention relates to the technical field of concrete mixer trucks, and in particular to a control method for a concrete mixer truck. Background Art

[0002] With the development of information technology and the Internet of Things, intelligent construction machinery has become an industry trend. By integrating advanced sensor technology and data analysis capabilities, modern construction machinery can achieve efficient operation in complex construction environments. Especially in the field of concrete mixer trucks, intelligent control systems can not only improve production efficiency, but also reduce energy consumption and maintenance costs. However, most concrete mixer trucks on the market still rely on manual judgment and manual adjustment, and cannot achieve real-time and precise control.

[0003] At present, there are two main ways to control concrete mixer trucks: one is manual control based on experience, that is, the driver manually adjusts the speed and torque of the mixer drum according to the on-site conditions and personal experience; the other is semi-automatic control based on simple sensor feedback. Although this type of system introduces speed sensors and load sensors, the control logic is relatively simple and usually only adjusts a specific parameter, lacking the ability to comprehensively consider changes in multiple factors. These two methods have their own advantages and disadvantages. The former is highly flexible but has poor stability, while the latter is relatively stable but difficult to adapt to complex and changing working conditions.

[0004] Although the existing control system has improved the operating convenience and safety of concrete mixer trucks to a certain extent, it still appears to be slow to respond and lacks precision when faced with rapidly changing working conditions, resulting in low equipment operation efficiency and serious energy waste. It also increases the risk of equipment failure. Therefore, a control method for concrete mixer trucks is urgently needed. Summary of the invention

[0005] The object of the present invention is to provide a control method for a concrete mixer truck to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a control method for a concrete mixer truck, comprising the following steps: S1. Preparation: Turn on the power, initialize the mixing drum motor system, and check whether each component is operating normally, including hardware self-check, software loading and other steps to ensure that each component is in normal working condition; S2. Data confirmation: input or confirm the preset target operating condition data and target load through the touch screen or remote terminal. The system stores this information in non-volatile memory for use or viewing in subsequent control processes; S3 data collection: Start the sensor group and enter the data collection mode to collect the working data and load information of the mixing drum in real time. The sensor data is transmitted to the processing module through the high-speed communication interface; S4 alarm operation: monitor system output and conduct manual intervention when necessary. The system provides real-time data monitoring function, and displays the working data and load information of the mixing drum through the touch screen or remote terminal. The data refresh frequency and alarm threshold can be set by the user to detect abnormal situations in time. S5 Cleaning work: After completing the work, turn off the power, clean and maintain the equipment, calibrate the sensor regularly to ensure measurement accuracy, avoid long-term overload operation, and prevent damage to the motor.

[0007] Preferably, in the S1 preparation work, each component includes a data acquisition module, a processing module and an actuator. The data acquisition module is composed of an operating data sensor and a load sensor, which is used to collect real-time operating data and target operating data of the mixing drum, as well as real-time load and target load.

[0008] Preferably, the processing module is responsible for receiving data from the data acquisition module, comparing it with a preset target value, and sending instructions to the actuator when a deviation is detected that exceeds a set threshold, and the actuator adjusts the output speed or torque of the mixing drum motor system according to the received instruction.

[0009] When the processing module detects that the deviation between the actual operating data or load information and the preset target value exceeds the set threshold, it will decide how to adjust the output speed or torque of the mixer drum motor system according to a certain control algorithm or strategy. Through the proportional-integral-differential (PID) control algorithm, the control signal is generated by calculating the proportion, integration and differentiation of the deviation, thereby achieving precise adjustment of the output speed or torque. The five variables of speed, torque, temperature in the operating data and weight and volume in the load information jointly determine the operating status of the mixer truck and the formulation of the control strategy. When multiple control instructions conflict, if an instruction is directly related to safety (for example, preventing the motor from overloading or overheating), the instruction will be executed first, and then the current operating conditions will be used to determine which instruction is more important.

[0010] Preferably, the sensor of the data acquisition module uses an industrial-grade Hall effect sensor or a piezoelectric sensor, which has the characteristics of high precision and low latency, ensuring the accuracy and real-time performance of data acquisition. The core of the processing module uses a high-performance microprocessor ARM Cortex-M series chip, and the actuator uses a brushless DC motor.

[0011] Among them, the Hall effect sensor used in the operating condition data sensor is the H43F switch-type Hall sensor, which is widely used due to its non-contact measurement, high precision and stability.

[0012] Preferably, the operating condition data includes but is not limited to the rotation speed, torque and temperature of the mixing drum, and the load information refers to the weight and volume of the concrete in the mixing drum, and the adjustment is assisted by various data.

[0013] Preferably, during the S4 alarm operation, the real-time operating condition data is compared with the target operating condition data, and the real-time load is compared with the target load. When the absolute value of the difference between the target operating condition data and the real-time operating condition data is greater than a preset first threshold, or when the absolute value of the difference between the real-time load and the target load is greater than a preset second threshold, the output speed of the mixing drum motor system or the output torque of the mixing drum motor system is adjusted.

[0014] Preferably, the step of adjusting the output speed of the mixing drum motor system or the output torque of the mixing drum motor system adopts a closed-loop control mechanism, namely feedback control: the operator inputs control information to the controlled object through system operation, and feeds back the state information of the controlled object to the input to correct the operation process so that the output of the system meets the expected requirements.

[0015] Preferably, after the S5 cleaning work, a learning module is used to enhance the robustness and adaptability of the system. The system is allowed to gradually optimize the control strategy through a machine learning algorithm. The control parameters can be automatically adjusted according to historical data and current working conditions to better match various working conditions and assist manual work.

[0016] Preferably, the learning module uses an adaptive learning rate optimization algorithm. By calling the operating data and load collected by the data acquisition module in the processing module, it can assign different learning rates to each parameter according to the requirements of different parameters and training stages, thereby improving the efficiency and effectiveness of training. Through the Adam optimization algorithm, the historical gradient square sum of each parameter is accumulated to adjust the learning rate, making its learning ability stronger and its applicability wider.

[0017] Compared with the prior art, the beneficial effects achieved by the present invention are: First, the present invention takes into account the differences in requirements of different types of concrete mixer trucks. Some core components, such as the microprocessor of the processing module, can be flexibly replaced according to actual conditions, as long as the same interface standards and communication protocols are met. The implementation of multiple steps can accurately obtain various real-time data during operation, and can quickly respond through accurate multi-modules in rapidly changing working conditions to improve the operating efficiency of the equipment, avoid the aging or sluggishness of some modules of the equipment, resulting in slow adjustment of the efficiency of the mixing drum motor system, leading to equipment failure, optimizing energy use, reducing operating costs, and extending the life of the equipment.

[0018] Second, in the present invention, during the startup phase, all sensors begin to monitor and transmit data to the processing module, which first loads the pre-stored target operating condition data and target load as a benchmark. Subsequently, during normal operation, the difference between the actual value and the target value is continuously monitored. Once a threshold value is exceeded, the motor output parameters are immediately adjusted according to a predetermined strategy. This closed-loop control mechanism can quickly respond to changes in the external environment, maintain the optimal operating state of the system, and dynamically adjust the output characteristics of the mixing drum motor system to effectively cope with complex and changeable actual operating conditions.

[0019] Third, after the work is completed, the present invention uses a learning module to call and learn the information stored in the non-volatile memory, such as historical data and the actual parameters of the current working conditions. By learning these data, the algorithm module can identify the optimal operating state of the mixer truck under different working conditions, and automatically optimize to obtain better control parameters and solutions. In subsequent work, these optimized control parameters and solutions can be used to provide suggestions to users, thereby reducing the possibility of human error and improving the reliability and safety of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the implementation process of the present invention; DETAILED DESCRIPTION The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Embodiment 1 See also Figure 1 The present invention provides a technical solution: a control method for a concrete mixer truck, comprising the following steps: S1. Preparation: Turn on the power, initialize the mixing drum motor system, and check whether each component is operating normally, including hardware self-check, software loading and other steps to ensure that each component is in normal working condition; S2. Data confirmation: input or confirm the preset target operating condition data and target load through the touch screen or remote terminal. The system stores this information in non-volatile memory for use or viewing in subsequent control processes; S3 data collection: Start the sensor group and enter the data collection mode to collect the working data and load information of the mixing drum in real time. The sensor data is transmitted to the processing module through the high-speed communication interface; S4 alarm operation: monitor system output and conduct manual intervention when necessary. The system provides real-time data monitoring function, and displays the working data and load information of the mixing drum through the touch screen or remote terminal. The data refresh frequency and alarm threshold can be set by the user to detect abnormal situations in time. S5 Cleaning work: After completing the work, turn off the power, clean and maintain the equipment, calibrate the sensor regularly to ensure measurement accuracy, avoid long-term overload operation, and prevent damage to the motor.

[0022] During the S1 preparation work, the components include a data acquisition module, a processing module and an actuator. The data acquisition module is composed of an operating data sensor and a load sensor, which are used to collect the real-time operating data and target operating data of the mixing drum, as well as the real-time load and target load.

[0023] The processing module is responsible for receiving data from the data acquisition module and comparing it with the preset target value. When it is detected that the deviation exceeds the set threshold, it sends an instruction to the actuator, and the actuator adjusts the output speed or torque of the mixing drum motor system according to the received instruction.

[0024] The sensors of the data acquisition module use industrial-grade Hall effect sensors or piezoelectric sensors, which have the characteristics of high precision and low latency, ensuring the accuracy and real-time performance of data acquisition. The core of the processing module uses a high-performance microprocessor ARM Cortex-M series chip, and the actuator uses a brushless DC motor.

[0025] The operating condition data includes but is not limited to the speed, torque and temperature of the mixing drum. The load information refers to the weight and volume of the concrete in the mixing drum. Adjustment is assisted by a variety of data.

[0026] Through the above technical solution, taking into account the differences in requirements of different types of concrete mixer trucks, some core components such as the microprocessor of the processing module can be flexibly replaced according to actual conditions, as long as the same interface standards and communication protocols are met. The implementation of multiple steps can accurately obtain various real-time data during operation, and can quickly respond through accurate multi-modules in rapidly changing working conditions to improve equipment operation efficiency, avoid aging or sluggishness of some modules of the equipment, resulting in slow adjustment of the efficiency of the mixing drum motor system, leading to equipment failure, optimizing energy use, reducing operating costs, and extending equipment life.

[0027] Embodiment 2 See also Figure 1The present invention provides a technical solution: a control method for a concrete mixer truck, in which, in S4 alarm operation, real-time operating condition data is compared with target operating condition data, and real-time load is compared with target load. When the absolute value of the difference between the target operating condition data and the real-time operating condition data is greater than a preset first threshold, or when the absolute value of the difference between the real-time load and the target load is greater than a preset second threshold, the output speed of the mixing drum motor system or the output torque of the mixing drum motor system is adjusted.

[0028] The step of adjusting the output speed of the mixer drum motor system or the output torque of the mixer drum motor system adopts a closed-loop control mechanism, namely feedback control: the operator inputs control information to the controlled object through system operation, and feeds back the state information of the controlled object to the input to correct the operation process so that the output of the system meets the expected requirements.

[0029] Through the above technical solution, during the startup phase, all sensors begin to monitor and transmit data to the processing module, which first loads the pre-stored target operating condition data and target load as a benchmark. Subsequently, during normal operation, the difference between the actual value and the target value is continuously monitored. Once a threshold value is exceeded, the motor output parameters are immediately adjusted according to the predetermined strategy. This closed-loop control mechanism can quickly respond to changes in the external environment, maintain the optimal operating state of the system, and dynamically adjust the output characteristics of the mixing drum motor system to effectively cope with complex and changeable actual working conditions.

[0030] Embodiment 3 See also Figure 1 ,The present invention provides a technical solution: a control method for a concrete mixer truck, after the S5 cleaning work, a learning module is used to enhance the robustness and adaptability of the system, and a machine learning algorithm is used to gradually optimize the control strategy, and the control parameters can be automatically adjusted according to historical data and current working conditions, so as to better match various working conditions and assist manual work.

[0031] The learning module uses an adaptive learning rate optimization algorithm. By calling the operating data and load collected by the data acquisition module in the processing module, it can assign different learning rates to each parameter according to the requirements of different parameters and training stages, thereby improving the efficiency and effectiveness of training. Through the Adam optimization algorithm, the historical gradient square sum of each parameter is accumulated to adjust the learning rate, making its learning ability stronger and its applicability wider.

[0032] Through the above technical solution, after the work is completed, the learning module is used to call and learn the information stored in the non-volatile memory, such as historical data and the actual parameters of the current working conditions. By learning these data, the algorithm module can identify the optimal operating state of the mixer truck under different working conditions, and automatically optimize to obtain better control parameters and solutions. In subsequent work, these optimized control parameters and solutions can be used to provide suggestions to users, thereby reducing the possibility of human error and improving the reliability and safety of the system.

[0033] When in use, considering the differences in the needs of different types of mixer trucks, some core components such as the microprocessor of the processing module can be flexibly replaced according to the actual situation, as long as the same interface standards and communication protocols are met. The implementation of multiple steps can accurately obtain various real-time data during work, and can quickly respond to the rapidly changing working conditions through accurate multi-modules to improve the operating efficiency of the equipment, avoid the aging or sluggishness of some modules of the equipment, resulting in slow adjustment of the efficiency of the mixing drum motor system, leading to equipment failure, optimizing energy use, reducing operating costs, and extending the life of the equipment. In the startup phase, all sensors begin to monitor and transmit data to the processing module. The processing module first loads the pre-stored target working condition data and target load as a benchmark. Subsequently, during normal operation, the difference between the actual value and the target value is continuously monitored. Once the threshold is exceeded, the motor output parameters are adjusted immediately according to the predetermined strategy. This closed-loop control mechanism can quickly respond to changes in the external environment, maintain the optimal operating state of the system, dynamically adjust the output characteristics of the mixing drum motor system, and effectively respond to complex and changeable actual working conditions. After the work is completed, the learning module is used to call and learn the information stored in the non-volatile memory, such as historical data and the actual parameters of the current working conditions. By learning these data, the algorithm module can identify the optimal operating state of the mixer truck under different working conditions, and automatically optimize to obtain better control parameters and solutions. In subsequent work, these optimized control parameters and solutions can be used to provide suggestions to users, reducing the possibility of human error and improving the reliability and safety of the system.

[0034] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit thereof, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A control method for a concrete mixer truck, characterized in that: The following steps are involved: S1. Preparation: Turn on the power, initialize the mixing drum motor system, and check whether each component is operating normally, including hardware self-check, software loading and other steps to ensure that each component is in normal working condition; S2. Data confirmation: input or confirm the preset target operating condition data and target load through the touch screen or remote terminal. The system stores this information in non-volatile memory for use or viewing in subsequent control processes; S3 data collection: Start the sensor group and enter the data collection mode to collect the working data and load information of the mixing drum in real time. The sensor data is transmitted to the processing module through the high-speed communication interface; S4 alarm operation: monitor system output and conduct manual intervention when necessary. The system provides real-time data monitoring function, and displays the working data and load information of the mixing drum through the touch screen or remote terminal. The data refresh frequency and alarm threshold can be set by the user to detect abnormal situations in time. S5 Cleaning work: After completing the work, turn off the power, clean and maintain the equipment, calibrate the sensor regularly to ensure measurement accuracy, avoid long-term overload operation, and prevent damage to the motor.

2. The control method of a concrete mixer truck according to claim 1, characterized in that: During the S1 preparation work, the components include a data acquisition module, a processing module and an actuator. The data acquisition module is composed of an operating data sensor and a load sensor, which are used to collect the real-time operating data and target operating data of the mixing drum, as well as the real-time load and target load.

3. A control method for a concrete mixer truck according to claim 2, characterized in that: The processing module is responsible for receiving data from the data acquisition module and comparing it with the preset target value. When it is detected that the deviation exceeds the set threshold, it sends an instruction to the actuator, and the actuator adjusts the output speed or torque of the mixing drum motor system according to the received instruction.

4. The control method of a concrete mixer truck according to claim 2, characterized in that: The sensors of the data acquisition module use industrial-grade Hall effect sensors or piezoelectric sensors, which have the characteristics of high precision and low latency, ensuring the accuracy and real-time performance of data acquisition. The core of the processing module uses a high-performance microprocessor ARM Cortex-M series chip, and the actuator uses a brushless DC motor.

5. The control method of a concrete mixer truck according to claim 2, characterized in that: The operating condition data includes but is not limited to the speed, torque and temperature of the mixing drum. The load information refers to the weight and volume of the concrete in the mixing drum. Adjustment is assisted by a variety of data.

6. The control method of a concrete mixer truck according to claim 1, characterized in that: During the S4 alarm operation, the real-time operating condition data is compared with the target operating condition data, and the real-time load is compared with the target load. When the absolute value of the difference between the target operating condition data and the real-time operating condition data is greater than the preset first threshold, or when the absolute value of the difference between the real-time load and the target load is greater than the preset second threshold, the output speed of the mixer drum motor system or the output torque of the mixer drum motor system is adjusted.

7. A control method for a concrete mixer truck according to claim 6, characterized in that: The step of adjusting the output speed of the mixer drum motor system or the output torque of the mixer drum motor system adopts a closed-loop control mechanism, namely feedback control: the operator inputs control information to the controlled object through system operation, and feeds back the state information of the controlled object to the input to correct the operation process so that the output of the system meets the expected requirements.

8. The control method of a concrete mixer truck according to claim 1, characterized in that: After the S5 cleaning work, the learning module is used to enhance the robustness and adaptability of the system. The system gradually optimizes the control strategy through the machine learning algorithm. It can automatically adjust the control parameters according to historical data and current working conditions to better match various working conditions and assist manual work.

9. A control method for a concrete mixer truck according to claim 8, characterized in that: The learning module uses an adaptive learning rate optimization algorithm. By calling the operating data and load collected by the data acquisition module in the processing module, it can assign different learning rates to each parameter according to the requirements of different parameters and training stages, thereby improving the efficiency and effectiveness of training. Through the Adam optimization algorithm, the historical gradient square sum of each parameter is accumulated to adjust the learning rate, making its learning ability stronger and its applicability wider.

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