A method, medium and equipment for controlling energy saving and consumption reduction of a roadheader

Abstract

The present invention discloses a method, medium and equipment for controlling energy conservation and consumption reduction of a tunnel boring machine, and relates to the technical field of energy consumption control. The method comprises: performing working face surrounding rock state detection and tunneling state scene monitoring; performing mechanical drive analysis according to the working face surrounding rock state and determining a first control strategy; dividing the tunnel boring machine into system modules and exploring the multi-module coupling law under the drive of the whole machine, taking any system module as the basis for judgment, performing energy consumption over-limit analysis on the tunneling state scene, determining the module consumption reduction amplitude, combining the multi-module coupling law to adjust the whole machine in the same amplitude and determine the second control strategy; coupling the first control strategy with the second control strategy to perform low-energy operation regulation on the tunnel boring machine. The method solves the technical problems of high energy consumption and poor energy-saving effect of tunnel boring machines in the prior art, and achieves the technical effect of realizing precise energy consumption control through multi-level control strategy and system module coupling regulation, reducing the energy consumption of the tunnel boring machine and improving operation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption control, and in particular to a method, medium and equipment for controlling energy saving and consumption reduction of a roadheader. Background Art

[0002] As indispensable construction equipment in tunnels, underground mines, and other projects, tunnel boring machines (TBMs) are widely used in various underground engineering projects. Due to their high-power drive, large mechanical structure, and complex working environment, TBMs consume a high level of energy during operation, which in turn affects the overall cost and efficiency of the project. Existing energy control technologies have certain limitations and are unable to accurately regulate energy consumption based on changes in the surrounding rock conditions of the working face and real-time monitoring of tunneling conditions. Therefore, existing energy control methods are unable to effectively reduce the energy consumption of TBMs, resulting in TBMs failing to achieve the expected operating efficiency and energy-saving effects. Summary of the Invention

[0003] The present application provides a method, medium and equipment for controlling energy conservation and consumption reduction of a tunnel boring machine, which solves the technical problems of high energy consumption and poor energy conservation effect of tunnel boring machines in the prior art.

[0004] A first aspect of the present application provides a method for controlling energy conservation and consumption reduction of a roadheader, the method comprising:

[0005] Detection equipment is installed at the tunneling head to detect the surrounding rock status of the working face, and multiple types of sensors are installed on the whole machine to monitor the tunneling status scene. A difference frequency cutting unit is developed in the control center of the tunneling machine. According to the surrounding rock status of the working face, a mechanical drive analysis of multiple rollers is performed to determine the first control strategy. The tunneling machine is divided into system modules, and the multi-module coupling law under the drive of the whole machine is explored. Based on any system module, the energy consumption limit analysis of the tunneling status scene is performed to determine the module consumption reduction range. Combined with the multi-module coupling law, the whole machine is adjusted in the same amplitude to determine the second control strategy, where the segmentation granularity includes at least drive-hydraulic-variable control-auxiliary. According to the timestamp constraint, the first control strategy and the second control strategy are coupled to perform low-energy operation regulation of the tunneling machine.

[0006] Furthermore, the surrounding rock state of the working face includes the surrounding rock state in the forward direction of each cutter position; according to the difference frequency cutting unit, the cutting drive control analysis based on the surrounding rock state is performed on each cutter to determine multiple sets of cutting parameters; the multiple sets of cutting parameters are integrated, and the timestamp constraints under the unit period are executed as the first control strategy.

[0007] Furthermore, the excavation big data is retrieved, the rock quality state is divided into N levels, the excavation big data is clustered, and N groups of excavation data are determined; the N groups of excavation data are traversed, statistical analysis within the group is performed, and N roller cutter cutting parameters are mined; a mapping between the N levels of rock quality state and the N roller cutter cutting parameters is established, a linear curve conversion is performed and trained until convergence to determine the cutting decision block; the cutting decision block is mirrored, and the difference frequency cutting unit is determined by integration.

[0008] Furthermore, based on the excavation big data, clustering is performed based on the excavation scenarios to determine M groups of scenario data; the M groups of scenario data are traversed to mine M groups of whole-machine driving standards that meet the excavation scenario requirements, wherein the M groups of whole-machine driving standards meet the low energy consumption baseline; according to the segmentation granularity, the M groups of whole-machine driving standards are decoupled to determine M coupling sequences; with the scenario as the independent variable, any system module as the decision variable, and the multi-module coupling law as the dependent variable, a multi-module coupling curve is constructed as the multi-module coupling law.

[0009] Furthermore, the excavation status scenario is received, scenario matching based on the independent variable is performed, and the scenario coupling sequence in the multi-module coupling curve is determined; any one system module is selected as the target decision variable; the excavation status scenario is identified, and the real-time variable state based on the target decision variable is located; based on the scenario coupling sequence, the sequence node state based on the target decision variable is located, and energy consumption over-limit judgment and coupling decision are performed on the real-time variable state to determine the second control strategy.

[0010] Furthermore, the real-time variable state and the sequence node state are checked. If the real-time variable state is greater than the sequence node state, an energy-saving and consumption-reducing instruction is generated. According to the energy-saving and consumption-reducing instruction, the state out-of-limit part is located as a pre-adjustment amplitude. According to the pre-adjustment amplitude, a coupling decision is made to determine the second control strategy.

[0011] Furthermore, taking the pre-adjusted amplitude as a standard, the remaining system modules are subjected to same-frequency adjustment based on the coupling relationship to determine multi-module amplitude modulation; and parameter control conversion is performed on the multi-module amplitude modulation to determine the second control strategy.

[0012] Furthermore, the first control strategy and the second control strategy are coupled to determine a pre-control strategy; a control transition is determined for the pre-control strategy; if a control transition exists, a multi-step conversion is performed on the pre-control strategy, and control adjustment is performed in response to the control center of the tunnel boring machine, wherein the adjustment transition threshold is limited by tunneling stability.

[0013] The second aspect of the present application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a method for controlling energy conservation and consumption reduction of a tunnel boring machine provided in the present application.

[0014] The third aspect of the present application provides an electronic device, comprising: a memory for storing executable instructions; and a processor for executing the executable instructions stored in the memory to implement a tunnel boring machine energy-saving and consumption-reduction control method provided in the present application.

[0015] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0016] Detection equipment was installed at the tunneling head to monitor the working face surrounding rock conditions, and multiple sensors were added to the entire machine to monitor the tunneling status scenario. A differential frequency cutting unit was developed in the tunneling machine's control center. Based on the working face surrounding rock conditions, it performed a mechanical drive analysis of multiple cutters to determine the first control strategy. The tunneling machine was then segmented into system modules, and the multi-module coupling patterns under the machine's drive were explored. Based on any system module, energy consumption overrun analysis was performed for tunneling scenarios to determine the extent of module energy reduction. Based on the multi-module coupling patterns, the entire machine was synchronized to determine the second control strategy. The segmentation granularity included at least drive-hydraulic-variable control-auxiliary. Finally, the first and second control strategies were coupled based on timestamp constraints to achieve low-energy operation control for the tunneling machine. This approach addresses the technical issues of high energy consumption and poor energy-saving performance of tunneling machines in the prior art. Through multi-level control strategies and system module coupling, precise energy control was achieved, reducing tunneling machine energy consumption and improving operational efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 A schematic flow chart of a method for controlling energy saving and consumption reduction of a roadheader provided in an embodiment of the present application;

[0019] Figure 2 A schematic flow chart of the multi-module coupling rule under the driving of the entire excavator in a method for controlling energy conservation and consumption reduction of a roadheader provided in an embodiment of the present application;

[0020] Figure 3 This is a schematic diagram of the structure of an exemplary electronic device of this application.

[0021] Description of reference numerals: processor 21 , memory 22 , input device 23 , output device 24 . DETAILED DESCRIPTION

[0022] The present application solves the technical problems of high energy consumption and poor energy-saving effect of tunnel boring machines in the prior art by providing a tunnel boring machine energy-saving and consumption-reduction control method, medium and equipment.

[0023] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0024] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0025] Example 1, as Figure 1 As shown, an embodiment of the present application provides a method for controlling energy saving and consumption reduction of a roadheader, wherein the method includes:

[0026] Detection equipment is installed on the tunneling head to detect the surrounding rock status of the working face, and multiple types of sensors are installed on the entire machine to monitor the tunneling status scene.

[0027] In the embodiment of the present application, detection equipment is added to the head of the tunnel boring machine and multiple types of sensors are equipped on the entire machine to enable real-time detection of the surrounding rock conditions of the working face and comprehensive monitoring of the tunneling status.

[0028] The detection equipment installed on the head of the tunnel boring machine includes lidar, geological sensors, acoustic sensors, etc. Through the combined use of these sensors, the hardness, strength, density, porosity, crack distribution and other parameters of the surrounding rock can be comprehensively collected, and then the changes in the surrounding rock of the working face can be evaluated to ensure the safety of the surrounding rock during the tunneling operation and avoid operation interruption due to unstable surrounding rock.

[0029] In addition to the surrounding rock detection equipment at the tunneling head, multiple types of sensors are installed on other key components of the TBM to comprehensively monitor its operating status. These sensors include load sensors, pressure sensors, temperature sensors, displacement sensors, and vibration sensors. Load sensors monitor parameters such as tool load and thrust, ensuring the TBM operates at optimal loads and avoiding overload or inefficient operation. Pressure sensors monitor the hydraulic system's operating pressure, enabling real-time adjustments to the oil supply and pressure to improve system efficiency. Temperature sensors monitor the operating temperature of key TBM components (such as the motor and hydraulic pump) to prevent damage from overheating. Displacement sensors monitor the TBM's displacement and thrust distance in real time, ensuring accuracy and stability during the tunneling process. Vibration sensors detect TBM vibration to prevent mechanical damage or increased energy consumption caused by excessive vibration.

[0030] A difference frequency cutting unit is developed in the control center of the tunnel boring machine. According to the surrounding rock state of the working face, a mechanical drive analysis of multiple cutters is performed to determine the first control strategy.

[0031] In an embodiment of the present application, a difference frequency cutting unit is developed in the tunnel boring machine control center. The difference frequency cutting unit is used to receive feedback data from the working face surrounding rock detection equipment in real time and analyze parameters such as the hardness, strength, and stability of the surrounding rock.

[0032] Based on the surrounding rock conditions of the working face, the differential frequency cutting unit conducts a mechanical drive analysis of the multiple rollers of the tunnel boring machine. Through the mechanical model, it analyzes the stress conditions, speed requirements, and contact status between the cutters and the surrounding rock under different working face conditions of the multiple rollers. Based on the results of the mechanical drive analysis of the multiple rollers, the differential frequency cutting unit formulates a first control strategy. The first control strategy intelligently adjusts the cutter speed, propulsion force, and hydraulic system output of the tunnel boring machine according to the changes in the surrounding rock conditions of different working faces to achieve optimal tunneling efficiency and lowest energy consumption.

[0033] Furthermore, the surrounding rock state of the working face includes the surrounding rock state in the forward direction of each cutter position; according to the difference frequency cutting unit, the cutting drive control analysis based on the surrounding rock state is performed on each cutter to determine multiple sets of cutting parameters; the multiple sets of cutting parameters are integrated, and the timestamp constraints under the unit period are executed as the first control strategy.

[0034] The working face's surrounding rock conditions encompass not only the overall physical and mechanical properties of the surrounding rock but also the specific conditions along the cutting path of each cutter. By performing detailed detection of the surrounding rock properties at each cutter location, the differential frequency cutting unit can assess the rock hardness, stability, and geological conditions of each cutter's area in real time, providing tailored operating parameters for each cutter.

[0035] Based on the surrounding rock conditions at the working face, the differential frequency cutting unit analyzes the cutting drive control for each cutter. Specifically, at each cutter position, the unit performs a mechanical drive analysis based on the surrounding rock characteristics at that location. This includes analyzing parameters such as the load on each cutter, the contact force between the cutter and the surrounding rock, and changes in propulsion force. By optimizing the drive parameters for each cutter, the unit ensures that each cutter on the roadheader operates optimally under varying geological conditions, avoiding excessive wear and inefficient energy consumption.

[0036] Based on the analysis results of the cutting drive control performed on each cutter, the difference frequency cutting unit determines multiple sets of cutting parameters. These parameters include the rotational speed, propulsion force, hydraulic output pressure, etc. of each cutter, and each set of cutting parameters is dynamically adjusted according to the specific surrounding rock conditions at the location of each cutter, so that each cutter can obtain the optimal working parameters under different surrounding rock conditions, thereby improving tunneling efficiency and reducing unnecessary energy consumption. The multiple sets of cutting parameters determined are integrated and synchronously scheduled according to timestamp constraints within a unit cycle to obtain the first control strategy. The first control strategy can accurately adjust the operating parameters of each cutter according to the real-time changes in the surrounding rock conditions, ensuring that the tunneling machine can maintain an efficient and low-energy working state under different surrounding rock conditions.

[0037] Furthermore, the construction of the difference frequency cutting unit includes:

[0038] Retrieve excavation big data, divide the rock quality into N levels, cluster the excavation big data, and determine N groups of excavation data; traverse the N groups of excavation data, perform intra-group statistical analysis, and mine N roller cutter cutting parameters; establish a mapping between the N levels of rock quality and the N roller cutter cutting parameters, perform linear curve conversion and train until convergence to determine the cutting decision block; mirror the cutting decision block, and integrate to determine the difference frequency cutting unit.

[0039] In this embodiment, a difference frequency cutting unit is constructed to conduct in-depth analysis and processing of various data during the tunneling process, formulating strategies suitable for different rock conditions. Specifically, the tunneling big data accumulated during the tunneling operation is retrieved. This big data includes real-time data from various sensors (such as load cells, pressure sensors, displacement sensors, etc.) and surrounding rock detection equipment. Through comprehensive analysis of tunneling data, clustering algorithms (such as K-Means and hierarchical clustering) are used to divide the rock quality into N levels (N-level rock quality states). Each level corresponds to a specific surrounding rock characteristic, such as hardness, stability, and crack distribution. The tunneling big data is divided into N groups of tunneling data according to the N-level rock quality states. The N groups of tunneling data are traversed, and statistical analysis is performed within the group for each group of tunneling data, including the calculation of parameters such as mean, standard deviation, and deviation. Through these statistical analyses, the main influencing factors of the disc cutter cutting process under each rock quality state can be discovered, including key cutting parameters such as disc cutter load, propulsion force, and rotational speed. Then, N disc cutter cutting parameters are determined to ensure that each group of rock quality states corresponds to a set of optimized disc cutter working parameters. Based on the statistical analysis results, a mapping relationship is established between N rock quality states and N roller cutter cutting parameters. This mapping relationship is established through a linear curve conversion method, mapping the changes in rock quality state to the adjustment range of the cutting parameters. Through continuous training and optimization of this mapping relationship until the model converges, the roller cutter cutting parameters are optimally configured for each rock quality state. After establishing the mapping relationship between rock quality state and roller cutter cutting parameters, a cutting decision block is generated, which contains the optimal roller cutter cutting parameter combinations obtained through mapping for different rock quality states.

[0040] By mirroring the cutting decision blocks—that is, symmetrically or inversely mapping them—we ensure optimal performance across a wide range of operating conditions. This mirroring process integrates multiple decision blocks to form the final difference-frequency cutting unit. This unit automatically selects appropriate cutting parameters based on real-time surrounding rock data and adjusts the cutter's operating state in real time, achieving precise energy consumption control under varying rock conditions.

[0041] The tunnel boring machine is divided into system modules, and the multi-module coupling law under the whole machine drive is explored. Based on any system module, the energy consumption limit analysis of the tunneling state scenario is performed to determine the module consumption reduction range. The whole machine is adjusted in the same amplitude based on the multi-module coupling law to determine the second control strategy, where the segmentation granularity includes at least drive-hydraulic-variable control-auxiliary.

[0042] By segmenting the TBM into its system modules, multiple functional modules are derived, including a drive module, a hydraulic module, a variable control module, and an auxiliary module. The drive module provides power to the TBM, including the motor drive system and propulsion system. The hydraulic module controls the flow and pressure of hydraulic oil, supporting various TBM operations. The variable control module adjusts various control strategies based on operational requirements, including power output and speed regulation. The auxiliary module includes lighting, ventilation, and cooling systems, supporting auxiliary functions of the TBM. This modularization allows the performance and energy consumption of each module to be individually monitored and adjusted, laying the foundation for subsequent energy efficiency control.

[0043] Through in-depth analysis of the coupling relationships between modules, we identify which modules' operations affect the energy efficiency of other modules. For example, an increased workload on the hydraulic module may lead to increased energy consumption in the drive module. Based on the principles of module segmentation and coupling, we analyze the energy consumption levels of each module under different operating conditions, identify which modules' energy consumption exceeds predetermined limits, and optimize the energy efficiency of these excess modules. By adjusting the entire machine's amplitude, we synchronize the energy reduction requirements of each module, and develop a secondary control strategy to ensure coordinated optimization of the modules' operating conditions, achieving efficient and low-energy operation.

[0044] Furthermore, if Figure 2 As shown in the figure, the multi-module coupling rules under the mining machine drive include:

[0045] According to the excavation big data, clustering is performed based on the excavation scenarios to determine M groups of scenario data; the M groups of scenario data are traversed to mine M groups of whole-machine driving standards that meet the excavation scenario requirements, wherein the M groups of whole-machine driving standards meet the low-energy consumption baseline; according to the segmentation granularity, the M groups of whole-machine driving standards are decoupled to determine M coupling sequences; with the scenario as the independent variable, any system module as the decision variable, and the multi-module coupling law as the dependent variable, a multi-module coupling curve is constructed as the multi-module coupling law.

[0046] Preferably, based on the excavation big data, the data is clustered according to different excavation scenarios to determine M groups of scenario data, each group of scenario data represents a specific operating environment and conditions, such as surrounding rock type, operating load and operating depth, etc.; through the analysis of these excavation scenario data, the whole machine drive standards that match the requirements of each scenario are excavated. These standards can not only meet the needs of various excavation operations, but also ensure that a low energy consumption baseline is always maintained in different operating scenarios.

[0047] After determining M sets of whole-machine drive standards, these whole-machine drive standards are further decoupled based on the granularity of the system modules, converting each set of whole-machine drive standards into M independent coupling sequences. Each coupling sequence corresponds to the energy efficiency relationship and interaction between modules in a specific operating scenario. Finally, a multi-module coupling curve is constructed, using the excavation scenario as the independent variable, the working status of any system module as the decision variable, and the multi-module coupling law as the dependent variable. The module coupling curve reflects the energy efficiency transfer and adjustment rules between modules in different operating scenarios. Through the module coupling curve, the synergy between modules can be accurately identified, and the working status of the modules can be dynamically adjusted according to changes in the scenario, thereby achieving optimal energy efficiency adjustment for the entire machine.

[0048] Furthermore, based on any system module as the basis for judgment, the energy consumption limit analysis is performed on the tunneling state scenario to determine the module consumption reduction range. The whole machine is adjusted in the same range in combination with the multi-module coupling rule to determine the second control strategy, including:

[0049] Receive the excavation status scenario, perform scenario matching based on the independent variable, and determine the scenario coupling sequence in the multi-module coupling curve; select any one system module as the target decision variable; identify the excavation status scenario, and locate the real-time variable state based on the target decision variable; based on the scenario coupling sequence, locate the sequence node state based on the target decision variable, and perform energy consumption over-limit judgment and coupling decision on the real-time variable state to determine the second control strategy.

[0050] In the embodiment of the present application, any system module is used as the basis for judgment, and an energy consumption limit analysis is performed on the excavation state scenario to determine the module's consumption reduction range, and the whole machine is adjusted in the same range in combination with the multi-module coupling law, and finally a second control strategy is formulated.

[0051] Specifically, the excavation status scenario is received, and the real-time data of the excavation status scenario is compared to select a scenario coupling sequence suitable for the current operating conditions; any system module is selected as the target decision variable, and then the excavation status scenario is identified, and the real-time variable status based on the target decision variable is located, that is, the selected system module is monitored in real time, and the parameters related to the module's operation are obtained. These data reflect the working status of the module in the current operating environment.

[0052] Based on the previously selected scenario coupling sequence, the sequence node states of the target decision variables are located, and an energy consumption over-limit determination is performed on the real-time variable states. By analyzing the gap between the real-time state of the selected system module and the set energy efficiency benchmark, it is determined whether its energy consumption exceeds the predetermined limit. If the energy consumption of the selected system module exceeds the set threshold, a coupling decision is made based on the multi-module coupling rules, coordinating the operating states of other related modules to achieve overall energy efficiency optimization. Finally, based on the results of the energy consumption over-limit determination and the coupling decision, a second control strategy is determined. This control strategy achieves low-energy and high-efficiency operation of the tunnel boring machine under different operating conditions by precisely adjusting the operating state and parameters of the target module and its related modules.

[0053] Furthermore, the real-time variable state and the sequence node state are checked. If the real-time variable state is greater than the sequence node state, an energy-saving and consumption-reducing instruction is generated. According to the energy-saving and consumption-reducing instruction, the state exceeding the limit is located as a pre-adjustment amplitude. According to the pre-adjustment amplitude, a coupling decision is made to determine the second control strategy.

[0054] By comparing the real-time variable state with the preset sequence node state, the system determines whether the current energy consumption level of the selected system module exceeds the predetermined energy efficiency range. If the real-time variable state is greater than the sequence node state, indicating that the module's energy consumption exceeds the predetermined efficiency standard, energy-saving and consumption-reduction instructions are generated to guide subsequent adjustment operations.

[0055] After generating energy-saving and consumption-reduction instructions, the system locates the out-of-limit components—specifically, the modules with excessive energy consumption—and uses this as a pre-adjustment range. This range sets a reduction value based on the specific performance of the out-of-limit component, reflecting the adjusted energy efficiency level. Based on this pre-adjustment range, a coupling decision is made to determine the second control strategy. During this coupling decision, the pre-adjustment range is coordinated with the operating conditions of other modules according to the multi-module coupling rules, ensuring optimal energy efficiency for the entire roadheader system.

[0056] Furthermore, performing a coupling decision to determine the second control strategy includes:

[0057] Taking the pre-adjusted amplitude as a standard, the remaining system modules are subjected to same-frequency adjustment based on the coupling relationship to determine the multi-module amplitude modulation; and the multi-module amplitude modulation is subjected to parameter control conversion to determine the second control strategy.

[0058] Specifically, using the pre-adjusted amplitude as a standard, a coupling-based co-frequency adjustment is performed for the remaining system modules of the tunnel boring machine. This adjustment process is based on the mutual influence between modules and the law of energy efficiency transfer, ensuring that when the energy efficiency of the target module is adjusted, the operating status and energy consumption of other related modules are coordinated and adjusted. The determined multi-module amplitude modulation is subjected to parameter control conversion, that is, each adjustment amount of the amplitude modulation is effectively converted and adjusted to adapt to the operating characteristics and actual needs of the different modules of the system. Based on the parameter control conversion results, the second control strategy is determined. This strategy comprehensively optimizes the energy efficiency of the tunnel boring machine according to the adjusted operating parameters of each module, ensuring that the tunnel boring machine can operate efficiently and with low energy consumption in different operating environments.

[0059] According to the timestamp constraint, the first control strategy and the second control strategy are coupled to perform low-energy operation control on the roadheader.

[0060] During the operation of the tunnel boring machine, the first control strategy is dynamically combined with the second control strategy based on real-time data and preset timestamp constraints to ensure that appropriate energy efficiency adjustment measures are taken at different time points.

[0061] In practice, timestamp constraints coordinate the execution timing of different strategies, ensuring smooth transitions and dynamic adjustments between the primary and secondary control strategies during operation. For example, when the roadheader is operating at high load, the primary control strategy primarily reduces energy consumption by adjusting the state of the tunneling head and cutter in real time, while the secondary control strategy coordinates the overall system modules. In this case, timestamp constraints ensure that the primary and secondary control strategies do not conflict with each other and achieve optimal energy efficiency.

[0062] Furthermore, after coupling the first control strategy and the second control strategy, the method includes:

[0063] The first control strategy and the second control strategy are coupled to determine a pre-control strategy; a control transition is determined for the pre-control strategy; if a control transition exists, a multi-step conversion is performed on the pre-control strategy, and control and adjustment are performed in response to the control center of the roadheader, wherein the adjustment transition threshold is limited by the tunneling stability.

[0064] After coupling the first and second control strategies, a pre-control strategy is generated. This strategy integrates the regulatory characteristics of both strategies, encompassing both energy-efficient control of the tunneling head and cutter (derived from the first control strategy) and coordinated regulation between system modules and overall machine optimization (derived from the second control strategy). Through this coupling, the pre-control strategy ensures optimal energy efficiency for the tunneling machine under various operating conditions.

[0065] The determined pre-control strategy is subjected to a control transition judgment. A control transition refers to a sudden change or large adjustment of the control strategy due to changes in the external environment or fluctuations in the equipment status during the operation of the tunnel boring machine. If a control transition is determined to exist, that is, when the state of the tunnel boring machine suddenly changes or there is a drastic load change, a multi-step conversion will be performed on the pre-control strategy. A multi-step conversion means that when a large change occurs, the control strategy of the tunnel boring machine is gradually adjusted through multiple small-step adjustments, thereby avoiding large control fluctuations and ensuring a smooth transition of the operation.

[0066] When executing multi-step transitions, the TBM control center responds and makes corresponding adjustments. By setting tunneling stability as the adjustment transition threshold, this ensures that the TBM operation does not become unstable during the adjustment process. Using tunneling stability as a transition threshold ensures that the TBM control adjustments remain within a safe range under various operating conditions, avoiding unnecessary equipment damage or energy loss due to excessive or rapid control adjustments.

[0067] In summary, the embodiments of the present application have at least the following technical effects:

[0068] Detection equipment was installed at the tunneling head to monitor the working face surrounding rock conditions, and multiple sensors were added to the entire machine to monitor the tunneling status scenario. A differential frequency cutting unit was developed in the tunneling machine's control center. Based on the working face surrounding rock conditions, it performed a mechanical drive analysis of multiple cutters to determine the first control strategy. The tunneling machine was then segmented into system modules, and the multi-module coupling patterns under the machine's drive were explored. Based on any system module, energy consumption overrun analysis was performed for tunneling scenarios to determine the extent of module energy reduction. Based on the multi-module coupling patterns, the entire machine was synchronized to determine the second control strategy. The segmentation granularity included at least drive-hydraulic-variable control-auxiliary. Finally, the first and second control strategies were coupled based on timestamp constraints to achieve low-energy operation control for the tunneling machine. This approach addresses the technical issues of high energy consumption and poor energy-saving performance of tunneling machines in the prior art. Through multi-level control strategies and system module coupling, precise energy control was achieved, reducing tunneling machine energy consumption and improving operational efficiency.

[0069] Example 2: Figure 3 This is a structural diagram of an electronic device provided in accordance with the second embodiment of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiment of the present invention. Figure 3 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention. Figure 3 As shown, the electronic device includes a processor 21, a memory 22, an input device 23 and an output device 24; the number of processors 21 in the electronic device can be one or more. Figure 3Taking a processor 21 as an example, the processor 21, memory 22, input device 23 and output device 24 in the electronic device can be connected through a bus or other means. Figure 3 The bus connection is taken as an example.

[0070] In Example 3, based on the same inventive concept as the method for controlling energy conservation and consumption reduction for a roadheader described in Example 1, this embodiment provides a computer-readable storage medium capable of storing software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the method for controlling energy conservation and consumption reduction for a roadheader described in this embodiment. The processor executes the software programs, instructions, and modules stored in the memory to execute various functional applications and data processing functions of the computer device, thereby implementing the method for controlling energy conservation and consumption reduction for a roadheader described above.

[0071] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0073] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A method for controlling energy saving and consumption reduction of a roadheader, characterized in that: The method comprises: Detection equipment is installed on the tunneling head to detect the surrounding rock conditions at the working face, and multiple types of sensors are installed on the entire machine to monitor the tunneling status scene. A differential frequency cutting unit is developed in the control center of the roadheader. Based on the surrounding rock conditions at the working face, the unit performs a mechanical drive analysis of the multiple cutters and determines a first control strategy. The differential frequency cutting unit is configured to receive real-time feedback data from surrounding rock detection equipment at the working face and analyze the hardness, strength, and stability parameters of the surrounding rock. The roadheader is segmented into system modules, and the multi-module coupling rules under the whole machine drive are explored. Based on any system module, an energy consumption limit analysis is performed on the tunneling state scenario to determine the module consumption reduction range. The whole machine is adjusted in the same amplitude based on the multi-module coupling rules to determine the second control strategy. The segmentation granularity includes at least drive-hydraulic-variable control-auxiliary. According to the timestamp constraint, coupling the first control strategy and the second control strategy to control the roadheader to perform low-energy operation; The surrounding rock state of the working face includes the surrounding rock state in the forward direction of each cutter position; According to the difference frequency cutting unit, cutting drive control analysis based on surrounding rock state is performed on each cutter to determine multiple groups of cutting parameters; Integrating the multiple sets of cutting parameters and executing the timestamp constraint under the unit period as the first control strategy; Exploring the multi-module coupling rules under the whole machine drive, including: Based on the excavation big data, clustering is performed based on the excavation scenarios to determine M groups of scenario data; Traversing the M sets of scenario data, mining M sets of whole-machine driving standards that meet the requirements of the tunneling scenario, wherein the M sets of whole-machine driving standards meet a low energy consumption baseline; Decoupling the M groups of whole-machine drive standards according to the segmentation granularity to determine M coupling sequences; Taking the scenario as the independent variable, any system module as the decision variable, and the multi-module coupling law as the dependent variable, a multi-module coupling curve is constructed as the multi-module coupling law; Based on any system module, the energy consumption limit analysis is performed on the tunneling state scenario to determine the module consumption reduction range. The whole machine is adjusted in the same range according to the multi-module coupling rule to determine the second control strategy, including: receiving the excavation state scenario, performing scenario matching based on independent variables, and determining a scenario coupling sequence in the multi-module coupling curve; Select any system module as the target decision variable; Identifying the tunneling state scenario and locating the real-time variable state based on the target decision variable; Based on the scenario coupling sequence, the sequence node state based on the target decision variable is located, and energy consumption over-limit judgment and coupling decision are performed on the real-time variable state to determine the second control strategy.

2. The method for controlling energy saving and consumption reduction of a roadheader according to claim 1, wherein: The construction of the difference frequency cutting unit includes: Retrieving excavation big data, classifying rock quality into N levels, clustering the excavation big data, and determining N groups of excavation data; Traversing the N groups of tunneling data, performing intra-group statistical analysis, and mining N disc cutter cutting parameters; Establishing a mapping between the N levels of rock quality and the N disc cutter cutting parameters, performing linear curve conversion and training until convergence to determine a cutting decision block; Mirror processing is performed on the cutting decision block to integrate and determine the difference frequency cutting unit.

3. The method for controlling energy saving and consumption reduction of a roadheader according to claim 1, wherein: Verifying the real-time variable state and the sequence node state, and generating an energy-saving and consumption-reducing instruction if the real-time variable state is greater than the sequence node state; According to the energy-saving and consumption-reducing instruction, the portion of the positioning state exceeding the limit is used as the pre-adjustment amplitude; According to the pre-adjustment amplitude, a coupling decision is made to determine the second control strategy.

4. A method for controlling energy saving and consumption reduction of a roadheader according to claim 3, characterized in that: Performing a coupling decision to determine the second control strategy includes: Taking the pre-adjusted amplitude as a standard, the remaining system modules are subjected to same-frequency adjustment based on the coupling relationship to determine the multi-module amplitude modulation; Perform parameter control conversion on the multi-module amplitude modulation to determine the second control strategy.

5. The method for controlling energy saving and consumption reduction of a roadheader according to claim 1, characterized in that: After coupling the first control strategy and the second control strategy, the method includes: coupling the first control strategy and the second control strategy to determine a pre-control strategy; A control transition is determined for the pre-control strategy. If a control transition exists, a multi-step conversion is performed on the pre-control strategy, and control adjustment is performed in response to the control center of the tunnel boring machine, wherein the control transition threshold is limited by tunneling stability.

6. An electronic device, characterized in that: The electronic device comprises: a memory for storing executable instructions; The processor is configured to implement a method for controlling energy saving and consumption reduction of a roadheader according to any one of claims 1 to 5 when executing the executable instructions stored in the memory.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a method for controlling energy saving and consumption reduction of a roadheader according to any one of claims 1 to 5 is implemented.

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