A machine tool electrical energy efficiency dynamic optimization management system and method

Abstract

The application discloses a machine tool electrical energy efficiency dynamic optimization management system and method, and relates to the technical field of management systems, and comprises a shaping module, a constrained active shaping action is selected from machine tool adjustable electrical control quantities aiming at a boundary uncertain area, and event attribution is distinguished according to electrical response before and after execution to obtain an event visualization result; a tracking module takes the event visualization result as a starting point, tracks response changes of a subsequent candidate electrical event relative to the active shaping action, establishes a control influence chain and tracks to an influence termination event to form a control effect domain; a reconstruction module corrects candidate electrical event boundaries in a candidate energy efficiency event chain or splits and combines the same according to the control effect domain to form a reconstructed energy efficiency event chain and determine a releasable control object; and the application reduces invalid electrical energy consumption and realizes effective reduction of machine tool electrical energy consumption.

Description

Technical Field

[0001] This invention relates to the field of management system technology, and in particular to a dynamic optimization management system and method for machine tool electrical energy efficiency. Background Technology

[0002] As CNC machine tools develop towards higher speeds, greater complexity, and greater intelligence, machine tool electrical energy efficiency management is gradually evolving from simple energy consumption metering to machining status identification, electrical load analysis, and online adjustment. Existing technologies typically correlate the machining program execution status with parameters such as current and power of the spindle, feed, and auxiliary loads in a time-series manner. Combined with operational phase division, energy consumption modeling, and dynamic control, this approach analyzes and optimizes electrical energy consumption under different machining conditions to improve equipment operating efficiency and energy utilization.

[0003] Existing machine tool electrical energy efficiency optimization technologies typically determine the energy efficiency control object based on pre-defined machining states or electrical events during dynamic adjustment, and implement energy-saving adjustments for the corresponding loads. However, during machine tool operation, electrical loads exhibit cross-event continuity and linkage changes, which means that load changes generated by a single energy efficiency adjustment may continuously affect subsequent machining events. This leads to a deviation between the local energy-saving effect and the energy consumption linked to subsequent loads, making it difficult to continuously adjust the energy efficiency control object and control range according to the actual operating state of the machine tool. Consequently, this affects the machine tool's energy-saving effect and dynamic optimization management of electrical energy efficiency. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a dynamic optimization management system for machine tool electrical energy efficiency to solve the problem that the energy efficiency control object and control range are difficult to dynamically adjust due to the continuity and linkage changes of electrical load across events.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a dynamic optimization management system for machine tool electrical energy efficiency, comprising: The module is constructed to obtain the machine tool processing status and corresponding electrical load changes, forming candidate electrical events. Based on the cross-boundary residual state between adjacent events, the boundary uncertainty region is divided, and a candidate energy efficiency event chain is constructed. The shaping module selects constrained active shaping actions from the adjustable electrical control quantities of the machine tool for the boundary uncertainty area, and distinguishes the event attribution based on the electrical response before and after execution to obtain the event display result; The tracking module starts with the event manifestation result, tracks the response changes of subsequent candidate electrical events relative to the active shaping action, establishes a control influence chain and tracks it to the influence termination event to form a control effect domain; The reconstructed module corrects the boundaries of candidate electrical events in the candidate energy efficiency event chain based on the control effect domain, or splits and merges them to form a reconstructed energy efficiency event chain and determines the releasable control objects. The adjustment module performs energy efficiency adjustment on the releasable control object, marks electrical changes that exceed the control effect domain as new boundary uncertainty areas, updates and reconstructs the energy efficiency event chain, and re-executes the active shaping action.

[0007] Preferably, the method for forming candidate electrical events includes: The machine tool's machining program execution position, spindle start / stop and speed changes, motion status of each feed axis, tool changing and retraction status, and cooling, lubrication and chip removal status are obtained to form the machine tool's machining status. Synchronously acquire the current, power, start / stop time and duration of the spindle drive, each feed drive and auxiliary electrical load corresponding to the machine tool processing state, and form the electrical load change; The machine tool processing state changes and electrical load changes with time correspondence are arranged in chronological order of occurrence to form candidate processing event sequences and candidate electrical event sequences. The correlation between the machine tool processing state changes and electrical load changes within the same time interval is established to obtain candidate electrical events.

[0008] Preferably, the method for constructing the candidate energy efficiency event chain includes: For each candidate electrical event, the power drop, load recovery, and continuous changes in auxiliary load after the end of its corresponding processing state are continuously tracked, and the part that has not yet recovered to the corresponding steady state is identified as the cross-boundary residual state of the candidate electrical event. Based on whether there is a continuation of cross-boundary residual state between adjacent candidate electrical events, candidate electrical events are divided into a definite event region and a boundary uncertain region; Candidate electrical events are arranged in chronological order of occurrence. Initial inheritance relationships are marked between adjacent candidate electrical events, and each candidate electrical event is marked with its own definite event region or boundary uncertain region, forming a candidate energy efficiency event chain.

[0009] Preferably, the method for obtaining the event manifestation result includes: Based on the order of candidate electrical events on both sides of the boundary uncertainty region, the direction of propagation of the cross-boundary residual state from the previous candidate electrical event to the next candidate electrical event is taken as the event attribution direction. Select active shaping actions that are reversible, short-term, and whose adjustment range is within the allowable operating range of the current machine tool processing state from the adjustable electrical control quantities of the machine tool, and apply them to the relevant electrical loads within the boundary uncertainty region; The response trajectories before and after the active shaping action are obtained respectively. The response trajectories are aligned and subtracted according to the same time base to obtain the difference response trajectory. Based on the response start time, response direction, and duration of the differential response trajectories, response changes that start from the previous candidate electrical event, have the same response direction as the event attribution direction, and whose response duration crosses the boundary of adjacent candidate electrical events are classified as the cross-boundary residual state continuation of the previous candidate electrical event; response changes that start from the subsequent candidate electrical event and whose response duration does not cross the boundary of adjacent candidate electrical events are classified as the emergence of the subsequent candidate electrical event; and response changes where the response start times of the load corresponding to the previous candidate electrical event and the load corresponding to the subsequent candidate electrical event overlap are classified as the joint coupling of the two candidate electrical events, forming an event manifestation result that includes the response direction and initial propagation relationship.

[0010] Preferably, the method for tracking the response changes of subsequent candidate electrical events relative to the active shaping action includes: Using the response direction and initial propagation relationship in the event manifestation results as the tracing path, starting from the actual occurrence time of the active shaping action, the electrical response changes of relevant electrical loads and subsequent candidate electrical events are continuously acquired along the response direction; By comparing the electrical response changes of subsequent candidate electrical events after the active shaping action with the original response trajectories of the corresponding electrical loads in the candidate energy efficiency event chain before the active shaping action, and excluding natural changes in the processing state, the new responses of subsequent candidate electrical events relative to the active shaping action are obtained. For subsequent candidate electrical events that generate new responses and can continue to propagate electrical changes along the initial propagation relationship, establish a control influence chain according to the order in which the new responses appear.

[0011] Preferably, the method for forming the control effect domain includes: The candidate electrical event at the moment when the active shaping action is applied is identified as the initial controlled event; Candidate electrical events that directly receive new responses in the control influence chain are identified as directly controlled events, while candidate electrical events that receive new responses after being passed through a previous event are identified as indirectly controlled events. The subsequent candidate electrical events are continuously tracked along the control influence chain, and the first subsequent candidate electrical event that no longer exhibits attributable electrical changes induced by active shaping actions is identified as the influence termination event. Based on the control influence relationships among the initiating controlled event, directly controlled event, indirectly controlled event, and event that affects termination, a control effect domain is formed.

[0012] Preferably, the method of forming the reconfigurable energy efficiency event chain and determining the releasable control object includes: For a candidate electrical event that is confirmed by the event manifestation results to be formed by the coupling of two consecutive candidate electrical events, its event boundary is corrected to the position in the corresponding control effect domain where the termination event is located, and the candidate electrical event with the boundary correction is obtained. Candidate electrical events with multiple response directions are split into sub-events with independent inheritance relationships according to the different response directions in the event manifestation results. Adjacent sub-events with the same continuous control influence path confirmed by the control influence chain are merged again. The reconstructed energy efficiency event chain is formed by the candidate electrical events after boundary correction and the merged sub-events. Based on the reconstructed energy efficiency event chain, the effective electrical energy consumption contribution of each candidate electrical event is recalculated, and the instantaneous energy consumption change of each candidate electrical event in its control effect domain is compared with the linkage change of subsequent candidate electrical events. Candidate electrical events that can generate a local energy consumption reduction within the control effect domain and do not propagate electrical load changes to subsequent candidate electrical events are identified as releasable control objects.

[0013] Preferably, the method of marking electrical changes that exceed the control effect domain as new boundary uncertainty regions includes: The control sequence of energy efficiency adjustment is determined according to the event position of the releasable control object in the reconfigurable energy efficiency event chain, and energy efficiency adjustment is implemented on the operating control quantity of the spindle drive, feed drive or auxiliary electrical load corresponding to the releasable control object. During the energy efficiency regulation process, the regulated processing state and electrical response are continuously acquired. The regulated electrical changes are compared with the control effect domain to determine whether the regulated electrical changes exceed the control effect domain and whether new subsequent candidate electrical events are generated. Electrical changes that exceed the control effect domain are marked as new boundary uncertainty regions.

[0014] Preferably, the method of updating and reconstructing the energy efficiency event chain and re-executing the active shaping action includes: For adjustment results that do not exceed the control effect domain and do not generate new subsequent candidate electrical events, the adjusted reconstructed energy efficiency event chain state is used as the inherited state for the next processing period. For adjustment results that exceed the control effect domain or generate new subsequent candidate electrical events, the reconstructed energy efficiency event chain containing the new boundary uncertainty region is used as the new candidate energy efficiency event chain. The active shaping action is re-executed, and the control effect domain and reconstructed energy efficiency event chain are re-formed.

[0015] Secondly, the present invention provides a method for dynamic optimization management of machine tool electrical energy efficiency, comprising: The machine tool processing status and corresponding electrical load changes are obtained to form candidate electrical events. The boundary uncertainty region is divided according to the cross-boundary residual state between adjacent events, and a candidate energy efficiency event chain is constructed. For the boundary uncertainty region of the candidate energy efficiency event chain, constrained active shaping actions are selected from the adjustable electrical control quantities of the machine tool, and the event attribution is distinguished according to the electrical response before and after execution to obtain the event manifestation results; Starting with the event manifestation result, the response changes of subsequent candidate electrical events relative to the active shaping action are tracked to establish a control influence chain and tracked to the influence termination event, forming a control effect domain; Based on the control effect domain, the candidate energy efficiency event chain is reconstructed in reverse, the event boundaries of the candidate electrical events are corrected or they are split and merged to form a reconstructed energy efficiency event chain and determine the releasable control objects; Energy efficiency regulation is applied to releasable controllable objects, electrical changes that exceed the control effect domain are marked as new boundary uncertainty regions, and the energy efficiency event chain is updated and reconstructed to re-execute active shaping actions.

[0016] The beneficial effects of this invention are as follows: by implementing constrained active shaping actions for the boundary uncertainty region, forming a difference response trajectory based on the electrical response before and after execution and revealing the actual attribution of adjacent candidate electrical events, energy efficiency regulation can be implemented for electrical loads that need to be optimized in reality, avoiding ineffective regulation of loads that do not have energy-saving space, thereby reducing ineffective power consumption and achieving effective reduction of machine tool electrical energy consumption. By tracking the response propagation of the active shaping action in subsequent candidate electrical events to form a control effect domain, and reconstructing the energy efficiency event chain and determining the releasable control objects based on the control effect domain, the energy efficiency regulation can avoid control relationships that cause additional energy consumption of subsequent loads. Furthermore, the control range is continuously adjusted based on the actual response after formal regulation, thereby achieving continuous correction and optimization of energy-saving effects and realizing the goal of dynamic optimization management of machine tool electrical energy efficiency. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a dynamic optimization management system for machine tool electrical energy efficiency according to the present invention; Figure 2 This is a schematic diagram of a dynamic optimization management method for machine tool electrical energy efficiency according to the present invention; Figure 3 This is a flowchart illustrating the formation of the control effect domain in this invention; Figure 4 This is a flowchart of the process of re-executing the active shaping action in this invention. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0020] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0021] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0022] Reference Figure 1 , Figure 2 , Figure 3 and Figure 4 As one embodiment of the present invention, this embodiment provides a dynamic optimization management system for machine tool electrical energy efficiency, comprising the following steps: The ways in which candidate electrical events are formed include: When a machine tool executes a machining program, it reads the current program segment number and the execution progress within the program segment from the machine tool's CNC device. The execution progress within the program segment is expressed as the percentage of the completed program segment content relative to the total content of the program segment. For example, when a certain machining program segment reaches the midpoint of its travel, the execution progress within the program segment is typically set to 50%. The execution position of the machining program is represented by both the program segment number and the execution progress within the program segment. The spindle start-up, shutdown and speed change are obtained by the actual spindle speed fed back by the spindle encoder. For example, when the spindle speed starts to decrease from 8000 r / min, it is recorded as a spindle speed change; when the spindle speed rises from zero, it is recorded as a spindle start; and when the spindle speed falls back to zero, it is recorded as a spindle stop. The motion state of each feed axis is obtained through the feed axis position signal and feed axis speed signal fed back by each feed drive. The motion state of the feed axis includes the direction of movement of the feed axis, the speed of movement, and the time when the feed axis starts to move and stops moving. Tool changing and retraction status are acquired through the completion signals of the tool changing and retraction actions of the machine tool; cooling, lubrication, and chip removal status are acquired through the operation feedback signals of the cooling pump, lubrication pump, and chip conveyor; the machining program execution position, spindle start / stop and speed changes, motion status of each feed axis, tool changing and retraction status, and cooling, lubrication, and chip removal status are summarized and recorded at 2ms intervals based on the same time base of the machine tool CNC device master clock to form the machine tool machining status.

[0023] Under the same time reference used to form the machine tool processing state, the spindle drive current is obtained by a current sensor installed at the spindle drive input end, and the spindle drive power is obtained by a power sensor installed at the spindle drive input end. For example, the spindle drive power in the constant speed cutting stage is 12kW and the spindle drive current is 28A. The current and power of each feed drive are obtained by current sensors and power sensors installed at each feed drive input terminal. For example, the feed drive power of a certain feed axis during the rapid movement phase is 3kW. Auxiliary electrical loads include cooling pumps, lubrication pumps, and chip conveyors. The current and power of the auxiliary electrical loads are obtained through current sensors and power sensors corresponding to the auxiliary electrical loads. The start and stop times of the spindle drive, each feed drive and auxiliary electrical load are determined according to the change of current. The moment when the current rises from zero and maintains a stable operation is recorded as the start time, and the moment when the current falls back to zero from a stable operation is recorded as the stop time. The time length between the start time and the stop time is recorded as the duration. For example, the duration of the cooling pump from the start time to the stop time is 120s. The current, power, start and stop times, and durations of the spindle drive, each feed drive, and auxiliary electrical loads are summarized and recorded according to the same time base to form electrical load changes. The electrical load changes and the machine tool processing status share the same time base, so that the electrical load changes and the machine tool processing status form a time correspondence.

[0024] The moment when the machine tool processing state changes is taken as the processing state change point. The machine tool processing state change includes the change of spindle speed, the start of feed axis movement, the stop of feed axis movement, the start of tool change action, the start of tool retraction action, the start of coolant pump, and the stop of coolant pump. For example, the processing state change point when the spindle speed starts to decrease from 8000 r / min is located at the 10th and 200th second of a certain processing cycle. The moment when the current or power changes continuously during the change of electrical load is taken as the point of electrical load change. For example, the point of electrical load change when the spindle drive power starts to decrease from 12kW is located at the 10.204s of a certain machining cycle. Arrange the processing status change points in chronological order of occurrence to form a candidate processing event sequence; arrange the electrical load change points in chronological order of occurrence to form a candidate electrical event sequence. For the machining state change points in the candidate machining event sequence and the electrical load change points in the candidate electrical event sequence, calculate the time difference between the occurrence time of the machining state change point and the occurrence time of the electrical load change point. Establish a correlation between machining state change points and electrical load change points whose time difference does not exceed 20ms (example value) and whose change content corresponds to each other. For example, the time difference between the machining state change point where the spindle speed starts to decrease from 8000r / min and the electrical load change point where the spindle drive power starts to decrease from 12kW is 4ms (example value). Establish a correlation between the two. The machining state change points and electrical load change points that have established a correlation are used together as candidate electrical events.

[0025] Methods for constructing candidate energy efficiency event chains include: For each candidate electrical event, after the processing state change corresponding to the candidate electrical event ends, the power drop, load recovery and continuous change of auxiliary load of the electrical load corresponding to the candidate electrical event are continuously tracked. The steady state of the electrical load corresponding to the candidate electrical event is determined by the current and power values ​​of the corresponding electrical load when it is running smoothly before the candidate electrical event occurs. For example, if the spindle drive power is 12kW when it is running smoothly during the constant speed cutting stage, then 12kW is the steady state of the spindle drive. Power drop refers to the process of the power of the corresponding electrical load decreasing from its steady state value. Load recovery refers to the process of the power of the corresponding electrical load rising back to its steady state value. Continuous change of auxiliary load refers to the changes in current and power of the cooling pump, lubrication pump, or chip conveyor that continue to run after the corresponding processing state has ended. The system continuously tracks power decline, load recovery, and continuous changes in auxiliary load at 2ms intervals, as shown in the example. If the current and power of the corresponding electrical load have recovered to a stable state during the tracking process, the tracking ends. If the current or power of the corresponding electrical load has not yet recovered to a steady state, the portion of the current or power that has not yet recovered to a steady state is identified as the cross-boundary residual state of the candidate electrical event. For example, if the spindle drive power drops from 12kW in a steady state to 8kW and then only recovers to 11.6kW and remains stable, the 0.4kW power portion that has not yet recovered to the 12kW steady state is identified as the cross-boundary residual state of the candidate electrical event.

[0026] Two candidate electrical events that occur at adjacent times in a candidate electrical event sequence are referred to as the preceding candidate electrical event and the following candidate electrical event, respectively. If the cross-boundary residual state of the previous candidate electrical event continues after the start time of the next candidate electrical event, that is, the current part or power part of the electrical load corresponding to the previous candidate electrical event that has not yet recovered to a stable state still exists after the start of the next candidate electrical event, then there is a continuation of the cross-boundary residual state between the previous candidate electrical event and the next candidate electrical event, and the previous candidate electrical event and the next candidate electrical event are jointly divided into the boundary uncertainty region. If the cross-boundary residual state of the previous candidate electrical event has recovered to a stable state before the start time of the next candidate electrical event, then there is no continuation of the cross-boundary residual state between the previous and next candidate electrical events, and the previous and next candidate electrical events are jointly classified as a definite event region; for example, if the spindle drive power of the spindle braking candidate electrical event has not recovered to a stable state of 12kW after the start time of the cooling pump start candidate electrical event, then the spindle braking candidate electrical event and the cooling pump start candidate electrical event are jointly classified as a boundary uncertain region.

[0027] Arrange the candidate electrical events in the order of their occurrence in the candidate electrical event sequence; if there is a continuation of the cross-boundary residual state between the previous candidate electrical event and the next candidate electrical event, then mark the initial inheritance relationship between the previous candidate electrical event and the next candidate electrical event (the initial inheritance relationship indicates that the cross-boundary residual state of the previous candidate electrical event is continued to the next candidate electrical event). Mark the definite event region or boundary uncertainty region to which each candidate electrical event belongs on each candidate electrical event; summarize and record the arranged candidate electrical events, the initial inheritance relationship between adjacent candidate electrical events, and the definite event region or boundary uncertainty region to which each candidate electrical event belongs to form a candidate energy efficiency event chain.

[0028] In existing machine tool electrical energy efficiency optimization processes, electrical events are typically divided based on machining status, and energy efficiency adjustment targets are directly determined according to preset event boundaries. However, residual loads and response coupling may exist between adjacent candidate electrical events, making it difficult to clearly attribute electrical changes within the boundary region to either the preceding or following candidate electrical event, thus hindering the accurate determination of energy efficiency adjustment targets. Therefore, this invention implements constrained active shaping actions for the boundary uncertainty region and utilizes the electrical responses before and after execution to reveal event attribution. The specific steps are as follows: The ways to obtain event manifestation results include: Candidate electrical events on both sides of the boundary uncertainty region, namely the preceding and following candidate electrical events in the candidate energy efficiency event chain that are jointly divided into the boundary uncertainty region, are determined in order of occurrence according to the order in which they occur in the candidate electrical event sequence. The electrical event that occurs earlier is considered the preceding candidate electrical event, and the electrical event that occurs later is considered the following candidate electrical event. Since the cross-boundary residual state of the previous candidate electrical event continues until after the start time of the next candidate electrical event, the continuation of the cross-boundary residual state can only be from the previous candidate electrical event to the next candidate electrical event. The propagation direction from the previous candidate electrical event to the next candidate electrical event is taken as the event attribution direction. The event attribution direction indicates which candidate electrical event the cross-boundary residual state was issued from and which candidate electrical event it continues to.

[0029] Adjustable electrical control quantities of machine tools refer to the operating control quantities that the CNC device of a machine tool can adjust online during the machining process, including spindle speed, feed rate, and the duty cycle of the cooling pump, lubrication pump, and chip conveyor. Reversibility refers to the ability to restore the machine tool's adjustable electrical control quantity to its value before execution after the active shaping action is completed. Short-term refers to the execution time of the active shaping action being shorter than the duration of the cross-boundary residual state of the previous candidate electrical event within the boundary uncertainty zone. Adjustment range within the allowable operating range of the current machine tool processing state means that the adjusted value of the machine tool's adjustable electrical control quantity does not exceed the allowable speed range, feed rate range, and auxiliary electrical load operating range of the current machining program segment in the machine tool's CNC device. When selecting, first determine the control quantity corresponding to the relevant electrical load in the boundary uncertainty region from the adjustable electrical control quantities of the machine tool. For example, when the boundary uncertainty region is composed of spindle braking candidate electrical event and coolant pump start candidate electrical event, the relevant electrical load is spindle drive and coolant pump, and the corresponding adjustable electrical control quantities of the machine tool are spindle speed and coolant pump operating duty cycle. Then, the form and magnitude of the active shaping action are determined according to the three conditions of reversibility, short duration, and adjustment range. For example, for the spindle drive, an active shaping action is selected to reduce the spindle speed by 5% for example and continue for 200ms before restoring the original speed. For the coolant pump, an active shaping action is selected to reduce the coolant pump duty cycle by 10% for example and continue for 200ms before restoring the original duty cycle. For the feed drive, an active shaping action is selected to adjust the feed ratio by 3% for example. Even after the spindle speed is reduced by 5%, the speed is still within the allowable speed range of the current machining program segment. The 200ms is shorter than the duration of the cross-boundary residual state. After the execution is completed, the spindle speed is restored to 8000r / min, which satisfies the three conditions of reversibility, short duration and adjustment range. Finally, during the period when the cross-boundary residual state of the previous candidate electrical event still exists, the machine tool CNC device will apply the selected active shaping action to the relevant electrical load in the boundary uncertainty region, that is, send a spindle speed adjustment command to the spindle drive and a duty cycle adjustment command to the coolant pump.

[0030] The response trajectory refers to the record of the current and power of the relevant electrical loads changing over time within the boundary uncertainty region. It is continuously acquired by the current and power sensors corresponding to the spindle drive input, each feed drive input, and the auxiliary electrical loads at 2ms intervals. The response trajectory before the active shaping action is taken as a current and power record of a period of time equal to the duration of the active shaping action before the active shaping action is applied. The response trajectory after the active shaping action is taken as a current and power record of a period of time after the active shaping action is applied, covering the duration of the active shaping action and the start time of the next candidate electrical event. Alignment based on the same time reference means taking the main clock of the machine tool CNC device as the reference and aligning the starting point of the response trajectory before the active shaping action and the starting point of the response trajectory after the active shaping action to the time when the active shaping action is applied, so that the current value and power value at the same relative time in the two response trajectories correspond one-to-one. Subtraction refers to subtracting the current and power values ​​in the response trajectory before the active shaping action from the current and power values ​​in the response trajectory after the active shaping action is executed at each relative moment. The differences between the relative moments are then arranged in chronological order to obtain the difference response trajectory.

[0031] For each differential response trajectory, the response start time, response direction, and duration are determined for each relevant electrical load: the response start time is the moment when the current difference or power difference in the differential response trajectory starts to change continuously from zero; the response direction is the direction of power decrease when the power difference in the differential response trajectory is negative and the direction of power increase when the power difference is positive; the duration is the time length between the response start time and the return of the current difference and power difference in the differential response trajectory to zero; the boundary between adjacent candidate electrical events is the start time of the next candidate electrical event. The response change that begins within the duration of the preceding candidate electrical event, has the same direction as the event attribution direction (i.e., the response change is emitted by the load corresponding to the preceding candidate electrical event and appears on the load corresponding to the following candidate electrical event along the event attribution direction), and whose start time plus duration exceeds the start time of the following candidate electrical event, is classified as a cross-boundary residual state continuation of the preceding candidate electrical event. For example, if the spindle drive power difference response begins within the duration of the spindle braking candidate electrical event and continues until after the start time of the cooling pump start candidate electrical event, it is classified as a cross-boundary residual state continuation of the spindle braking candidate electrical event. A response change whose start time is after the start time of the next candidate electrical event and whose start time plus duration does not exceed the start time of the next adjacent candidate electrical event is classified as the new generation of the next candidate electrical event. For example, if the cooling pump power difference response starts after the start time of the cooling pump start candidate electrical event and returns to zero within the duration of the cooling pump start candidate electrical event, it is classified as the new generation of the cooling pump start candidate electrical event. The response changes of the load corresponding to the previous candidate electrical event are classified as two coupled candidate electrical events if the difference between the response start time of the load corresponding to the previous candidate electrical event and the response start time of the load corresponding to the next candidate electrical event does not exceed the sample value of 2ms sampling interval (i.e., both events change continuously at the same sampling time). For example, if the spindle drive power difference response and the coolant pump power difference response start to change at the same sampling time, they are classified as a coupled candidate electrical event of spindle braking and a candidate electrical event of coolant pump start. The above classification results, together with the response direction of each response change and the order in which the response changes appear among the relevant electrical loads (the electrical load with the response change first points to the electrical load with the response change later, as the initial propagation relationship), are summarized and recorded to form an event manifestation result that includes the response direction and the initial propagation relationship.

[0032] By actively shaping the response trajectory, different response trajectories are formed. Based on the response start time, response direction, and duration, the continuation of cross-boundary residuals, the emergence of subsequent candidate electrical events, and the joint coupling relationship between preceding and subsequent candidate electrical events are distinguished. This allows adjacent candidate electrical events that were originally difficult to distinguish to obtain clear actual attribution and propagation relationships. As a result, the energy efficiency control object corresponding to the change in electrical load is accurately determined, ineffective energy efficiency regulation is reduced, and energy-saving control can be implemented for electrical loads that need to be optimized in accordance with actual needs. This provides an accurate control basis for subsequent dynamic optimization management of machine tool electrical energy efficiency.

[0033] Methods for tracking changes in the response of subsequent candidate electrical events relative to active shaping actions include: Subsequent candidate electrical events refer to each candidate electrical event in the candidate energy efficiency event chain that occurs after the active shaping action is applied. The tracing path is given by the response direction and initial propagation relationship in the event manifestation results. The response direction indicates the direction of power decrease or power increase, and the initial propagation relationship indicates the order in which the electrical load with the first response change points to the electrical load with the subsequent response change. The actual moment when the active shaping action occurs is the moment when the current sensor and power sensor of the relevant electrical load first record a continuous change in current or power after the CNC device of the machine tool issues the adjustment command. For example, the moment when the spindle drive power starts to decrease from 11.6kW after the command to reduce the spindle speed by 5% is issued. Starting from the actual moment the active shaping action occurs, along the electrical load sequence pointed to by the initial propagation relationship, the current and power of the relevant electrical loads and the electrical loads corresponding to each subsequent candidate electrical event are continuously acquired through the corresponding current and power sensors at 2ms intervals. Changes consistent with the response direction are retained as electrical response changes. For example, if the initial propagation relationship is that the spindle drive points to the cooling pump, the change in the power decrease direction of the spindle drive is acquired first, and then the current and power changes of the electrical loads corresponding to the cooling pump start-up candidate electrical event and each subsequent candidate electrical event are acquired continuously.

[0034] The original response trajectory refers to the record of the current and power changes over time of the electrical load corresponding to each subsequent candidate electrical event in the candidate energy efficiency event chain before the active shaping action occurs, with the example value taken at 2ms intervals. It is taken from the electrical load changes that have been summarized and recorded when the candidate energy efficiency event chain is formed. Natural changes in processing state refer to the changes in current and power that will occur in the electrical load corresponding to the subsequent candidate electrical events when no active shaping action is applied, due to the changes in its own processing state. For example, the change in current of a cooling pump from zero to stable operation at startup. During the comparison, the main clock of the machine tool CNC device is used as the same time reference. The changes in the electrical response after the active shaping action and the original response trajectory are aligned with the start time of the subsequent candidate electrical events. At each relative moment, the current and power values ​​after the active shaping action are subtracted from the current and power values ​​at the corresponding relative moment in the original response trajectory. The part with a zero difference is the natural change in the processing state and is excluded. The part with a non-zero difference that continues to exist over time is the new response of the subsequent candidate electrical event relative to the active shaping action. For example, if the power of the coolant pump after the active shaping action is 0.1kW lower than the original response trajectory at the same relative moment, then the 0.1kW power difference is the new response of the coolant pump start-up candidate electrical event relative to the active shaping action.

[0035] For each subsequent candidate electrical event, first determine whether a new response will be generated; Next, determine whether the electrical change can continue to be transmitted along the initial propagation relationship. That is, on the electrical load that is located after the electrical load corresponding to the subsequent candidate electrical event in the initial propagation relationship, whether a new response also appears after the new response of the subsequent candidate electrical event appears. If it appears, the transmission can continue; if it does not appear, the transmission cannot continue. Successor candidate electrical events that simultaneously satisfy the conditions for generating new responses and can continue to propagate electrical changes along the initial propagation relationship are arranged in order of their respective response start times. The propagation relationship between two adjacent successor candidate electrical events is marked in the direction from the first responder to the second responder. The arranged successor candidate electrical events and the propagation relationships between adjacent successor candidate electrical events are summarized and recorded to establish a control influence chain.

[0036] In existing machine tool electrical energy efficiency optimization processes, energy consumption changes for each machining event are typically evaluated separately based on predetermined event boundaries. However, the energy-saving effect of a single event may be transmitted to subsequent candidate electrical events through electrical load linkages, making it difficult to reconcile the reduction in local energy consumption with subsequent linkage energy consumption, thus affecting the determination of releasable control objects. Therefore, this invention reconstructs the candidate energy efficiency event chain based on the control effect domain and determines releasable control objects by combining instantaneous energy consumption changes with subsequent linkage changes. The specific steps are as follows: The ways to form a control effect domain include: The moment when the active shaping action is applied is the moment when the machine tool CNC device sends a spindle speed adjustment command or a duty cycle adjustment command to the relevant electrical loads within the boundary uncertainty area; In the candidate energy efficiency event chain, the active shaping action is applied after the start time of the candidate electrical event and within the period when the corresponding electrical load has not yet recovered to a stable state, based on the start time and duration of each candidate electrical event. The found candidate electrical event is identified as the starting controlled event, which represents the candidate electrical event directly affected by the active shaping action. For example, if the active shaping action is applied to the spindle drive during the period when the cross-boundary residual state of the spindle braking candidate electrical event still exists, then the spindle braking candidate electrical event is determined as the initiation controlled event.

[0037] In the control effect chain, determine the source of new responses for each candidate electrical event according to the marked transmission relationships: If the electrical load corresponding to a candidate electrical event is directly located after the electrical load corresponding to the initial controlled event in the initial propagation relationship, and its new response appears directly after the change in the electrical response of the initial controlled event, without passing through other candidate electrical events, then it is determined as a directly controlled event. If a new response to a candidate electrical event occurs after a new response to a candidate electrical event preceding it in the control influence chain, i.e., there is a preceding candidate electrical event in the transitive relationship that points to it, and the preceding candidate electrical event is not the initial controlled event, then it is determined to be an indirect controlled event.

[0038] Attributable electrical change refers to the electrical response change of the electrical load corresponding to the subsequent candidate electrical event after the active shaping action. The difference between the change and the original response trajectory is not zero, the response direction is consistent with the response direction in the event manifestation result, and the occurrence time is located after the new response of the previous candidate electrical event in the control influence chain. In other words, it is a new response that can be attributed to the active shaping action along the transmission relationship. Starting from the initial controlled event along the control influence chain, the current and power of the directly controlled event, the indirectly controlled event, and the subsequent candidate electrical events are continuously acquired through the corresponding current and power sensors at intervals of 2ms (example value). The data are then subtracted from their original response trajectories to determine whether there is an attributable electrical change. Subsequent candidate electrical events whose difference is zero after the first control along the control influence chain, or whose difference is not zero but whose response direction is inconsistent with the response direction in the event manifestation result, are identified as influence termination events. Once an influence termination event is identified, tracking is stopped.

[0039] The starting controlled event is taken as the starting point of the control effect domain, and the ending event is taken as the ending point of the control effect domain. The directly controlled events and indirectly controlled events located between the starting point and the ending point are arranged in order of control influence relationship. The electrical load corresponding to each candidate electrical event, the response start time and response direction of each newly added response are recorded. The starting point, the ending point, the intermediate candidate electrical events and the control influence relationship between them are summarized and recorded to form the control effect domain. The control effect domain represents the range of candidate electrical events that can produce attributable electrical changes in the candidate energy efficiency event chain in a single active shaping action.

[0040] The methods for forming a reconfigurable energy efficiency event chain and identifying releasable control objects include: For candidate electrical events that are confirmed to be continuously affected by active shaping actions, the start time of the influencing termination event is searched in the corresponding control effect domain. The end time of the candidate electrical event in the candidate energy efficiency event chain is rewritten from the original time determined by the recovery of current and power to a steady state to the start time of the influencing termination event, so that all candidate electrical events involved in the attributable electrical changes caused by active shaping actions are included within the corrected event boundary. For example, the end time of the spindle braking candidate electrical event was originally located at the moment when the spindle drive power rose to 11.6kW and remained stable. After correction, it was rewritten as the start time of the feed axis rapid movement candidate electrical event that affects the termination event, thus obtaining the candidate electrical event after boundary correction.

[0041] In the event visualization results, find candidate electrical events with both power decrease and power increase directions in the differential response trajectory of the electrical load corresponding to the same candidate electrical event. For example, the candidate electrical event of cooling pump start-up first shows a power decrease direction change after the cooling pump start-up moment, which is followed by the power increase direction change when the cooling pump itself reaches stable operation. The candidate electrical event is divided into sub-events arranged in chronological order, with the moment when the response direction changes as the boundary. Each sub-event contains only one response direction. For example, the candidate electrical event of cooling pump start-up is divided into a first sub-event in the direction of power decrease and a second sub-event in the direction of power increase. Each sub-event is individually labeled with its inheritance relationship with the previous candidate electrical event or the previous sub-event. For example, the first sub-event in the power decrease direction inherits the cross-boundary residual state of the spindle braking candidate electrical event, while the second sub-event in the power increase direction does not inherit the cross-boundary residual state of the spindle braking candidate electrical event. Next, check whether the new responses of adjacent sub-events all come from the same previous candidate electrical event and have the same response direction according to the transmission relationship marked in the control influence chain. If they are the same, merge the adjacent sub-events back into one sub-event; otherwise, keep them separated. The candidate electrical events after boundary correction, the merged sub-events, and the remaining candidate electrical events that did not participate in the correction and splitting are rearranged according to their order of occurrence. The inheritance relationship between adjacent candidate electrical events or sub-events is re-marked, and the records are summarized to form a reconstructed energy efficiency event chain.

[0042] For each candidate electrical event in the reconstructed energy efficiency event chain, the power of the corresponding electrical load is accumulated point by point according to the example value of 2ms sampling interval, with the corrected start time to end time as the accumulation interval, to obtain the effective electrical energy consumption contribution. For example, the effective electrical energy consumption contribution of the spindle braking candidate electrical event is obtained by accumulating the spindle drive power point by point from its start time to the start time of the feed axis rapid traverse candidate electrical event; then for each candidate electrical event, the power difference obtained by subtracting the original response trajectory from the active shaping action is accumulated point by point within the event boundary of the candidate electrical event itself to obtain the instantaneous energy consumption change; For example, the difference in spindle drive power during a 5% spindle speed reduction lasting 200ms is denoted as -0.6kW, and the energy reduction is obtained by accumulating the values ​​point by point. The new responses of directly controlled events and indirectly controlled events within the control effect domain are accumulated point by point within their respective event boundaries to obtain the linkage change affected by subsequent candidate electrical events. For example, the new response of the cooling pump start-up candidate electrical event is denoted as 0.1kW, and the energy change is obtained by accumulating the values ​​point by point. For each candidate electrical event, the sign and magnitude of the instantaneous energy consumption change are compared and recorded with the sign and magnitude of the linkage change of its subsequent candidate electrical events.

[0043] For each candidate electrical event in the reconstructed energy efficiency event chain, first check whether the instantaneous energy consumption change is negative. If it is negative, a local energy consumption decrease is formed within the control effect domain. Then check whether the linkage change of the subsequent candidate electrical events is zero, or both are negative and the absolute value is not greater than the absolute value of the instantaneous energy consumption change. If this condition is met, the electrical load change has not spread to the subsequent candidate electrical events. Candidate electrical events that satisfy both conditions are identified as releasable control objects; candidate electrical events that do not satisfy either condition are not identified as releasable control objects. For example, if the instantaneous energy consumption change of the spindle brake candidate electrical event is negative, the linkage change of the coolant pump start candidate electrical event is a negative value obtained by accumulating the power reduction example value of 0.1kW and the absolute value is less than the absolute value of the instantaneous energy consumption change of the spindle brake candidate electrical event, and the chip conveyor start candidate electrical event does not show an increase in electrical energy, then the spindle brake candidate electrical event is determined to be a releaseable control object. If the instantaneous energy consumption change of a candidate electrical event for a feed axis is negative, but the linkage change of its subsequent candidate electrical events is positive, then it is uncertain whether it is a releasable controllable object.

[0044] By modifying the boundaries of candidate electrical events based on the control effect domain and splitting and merging candidate electrical events, the reconstructed energy efficiency event chain can reflect the actual impact range of the active shaping action. Then, by comparing the instantaneous energy consumption changes of each candidate electrical event with the linkage changes of subsequent candidate electrical events, releaseable control objects that reduce local energy consumption without causing adverse load spread are selected. This avoids simply pursuing local energy saving and causing subsequent event energy consumption to increase. It enables energy efficiency regulation to select control objects around the actual energy saving effect, reduces ineffective or adverse energy efficiency regulation, and achieves continuous reduction of machine tool electrical energy consumption.

[0045] Methods for marking electrical changes that fall outside the control effect domain as new boundary uncertainty areas include: The control order is determined according to the order of occurrence in the reconstructed energy efficiency event chain. The releaseable control objects that are earlier in the order are adjusted first, and the releaseable control objects that are later in the order are adjusted later. When there are multiple releaseable control objects in the same control effect domain, the releaseable control object corresponding to the initial controlled event is adjusted first, and the releaseable control object corresponding to the subsequent candidate electrical event is adjusted after its electrical change is stable. Energy efficiency adjustment is achieved by the machine tool CNC device sending adjustment commands for spindle speed, feed rate, or operating duty cycle to the spindle drive, feed drive, or auxiliary electrical load corresponding to the release control object. The adjustment direction follows the direction that has been confirmed to form a local energy consumption reduction in the active shaping action, and the adjustment range does not exceed the speed range, feed rate range, and auxiliary electrical load operating range allowed by the current machining program segment. For example, after a spindle braking candidate electrical event is determined to be a releasable control object, an adjustment command of 5% spindle speed reduction is issued to the spindle drive during the period when the cross-boundary residual state of the spindle braking candidate electrical event exists. This adjustment is maintained within the event boundary after the spindle braking candidate electrical event is corrected, instead of restoring the original speed after 200ms as in the active shaping action.

[0046] During the energy efficiency regulation process, the machine tool processing status after regulation, as well as the current and power of the spindle drive, each feed drive and auxiliary electrical load, are continuously acquired at 2ms intervals, with the example value as the interval. The adjusted current and power are subtracted from the original response trajectory by aligning them with the same time base. The portion of the difference that is not zero and persists over time is the adjusted electrical change. Compare each candidate electrical event that exhibits the adjusted electrical change with the range from the initial controlled event to the event that affects the termination of the control effect domain. If all of them are within the range of the control effect domain, they are judged to be within the control effect domain. If the event that affects the termination of the control effect domain or the candidate electrical event arranged after the event that affects the termination of the control effect domain exhibits the adjusted electrical change, they are judged to be outside the control effect domain. At the same time, check whether new successive responses have appeared among the candidate electrical events that were not originally marked with a transit relationship within the control effect domain. If a new response appears, it is determined that a new subsequent candidate electrical event has been generated and propagated. For electrical changes that are determined to be outside the control effect range after adjustment, the candidate electrical event that shows the adjusted electrical change and its previous candidate electrical event are jointly marked as a new boundary uncertainty region. For example, if the feed drive power of the candidate electrical event that affects the termination event of rapid traverse of the feed axis no longer maintains 3kW and shows a continuous difference during the 5% reduction in spindle speed, then the candidate electrical event of chip conveyor start and the candidate electrical event of rapid traverse of the feed axis are jointly marked as a new boundary uncertainty region.

[0047] The methods for updating and reconstructing the energy efficiency event chain and re-executing proactive shaping actions include: For adjustment results that are determined to be within the control effect domain and without generating new subsequent candidate electrical events, the event boundaries, inheritance relationships, and control effect domains of each candidate electrical event in the reconstructed energy efficiency event chain do not need to be modified. The start and end times of each candidate electrical event, the inheritance relationship between adjacent candidate electrical events, each control effect domain, the releasable control object, and the adjustment range of its operating control quantity in the reconstructed energy efficiency event chain during the energy efficiency adjustment period are summarized and recorded as the inheritance state for the next processing period. The next processing period refers to the period when the same processing program is executed again to the same program segment number. When the same program segment number is executed, the energy efficiency adjustment is directly implemented according to the releaseable control object and the adjustment range of the running control quantity recorded in the inherited state. The active shaping action is no longer re-executed for the confirmed boundary uncertainty area. For example, when the spindle speed starts to brake from 8000 r / min in the next processing period, an adjustment command of 5% spindle speed reduction is directly issued to the spindle drive.

[0048] For adjustment results that are judged to be outside the control effect domain or to generate new subsequent candidate electrical events, the operating control quantity of this energy efficiency adjustment is first restored to the value before adjustment. Then, the reconstructed energy efficiency event chain with the new boundary uncertainty region marked is used as the new candidate energy efficiency event chain. The new candidate energy efficiency event chain retains the event boundaries and inheritance relationships of the original candidate electrical events after correction. The candidate electrical event before and after the new boundary uncertainty region is marked as the boundary uncertainty region. For the new boundary uncertainty region, the event attribution direction is redefined, active shaping action is reselected and applied, the difference response trajectory is obtained to obtain the event manifestation result, the control influence chain is re-established and the control effect domain is formed, the reconstructed energy efficiency event chain is re-formed and the releasable control object is determined, and then energy efficiency adjustment is implemented again and the comparison is judged; for example, taking the new boundary uncertainty region formed by the chip conveyor start candidate electrical event and the feed axis rapid movement candidate electrical event as the object, the active shaping action of reducing the operating duty cycle of the chip conveyor by 10% and continuing for 200ms before recovery is selected, and the control effect domain and reconstructed energy efficiency event chain are re-formed with the chip conveyor start candidate electrical event as the starting controlled event.

[0049] This embodiment also provides a method for dynamic optimization management of machine tool electrical energy efficiency, including: The machine tool processing status and corresponding electrical load changes are obtained to form candidate electrical events. The boundary uncertainty region is divided according to the cross-boundary residual state between adjacent events, and a candidate energy efficiency event chain is constructed. For the boundary uncertainty region of the candidate energy efficiency event chain, constrained active shaping actions are selected from the adjustable electrical control quantities of the machine tool, and the event attribution is distinguished according to the electrical response before and after execution to obtain the event manifestation results; Starting with the event manifestation result, the response changes of subsequent candidate electrical events relative to the active shaping action are tracked to establish a control influence chain and tracked to the influence termination event, forming a control effect domain; Based on the control effect domain, the candidate energy efficiency event chain is reconstructed in reverse, the event boundaries of the candidate electrical events are corrected or they are split and merged to form a reconstructed energy efficiency event chain and determine the releasable control objects; Energy efficiency regulation is applied to releasable controllable objects, electrical changes that exceed the control effect domain are marked as new boundary uncertainty regions, and the energy efficiency event chain is updated and reconstructed to re-execute active shaping actions.

[0050] This embodiment also provides a computer device applicable to a dynamic optimization management system for machine tool electrical energy efficiency, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize a dynamic optimization management system for machine tool electrical energy efficiency as proposed in the above embodiment.

[0051] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0052] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements a dynamic optimization management system for machine tool electrical energy efficiency as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the present invention.

Claims

1. A dynamic optimization management system for machine tool electrical energy efficiency, characterized in that, include: The module is constructed, the machine tool processing status and corresponding electrical load changes are obtained, candidate electrical events are formed, and the boundary uncertainty region is divided according to the cross-boundary residual state between adjacent events to construct the candidate energy efficiency event chain. The shaping module selects constrained active shaping actions from the adjustable electrical control quantities of the machine tool for the boundary uncertainty area, and distinguishes the event attribution based on the electrical response before and after execution to obtain the event display result; The tracking module starts with the event manifestation result, tracks the response changes of subsequent candidate electrical events relative to the active shaping action, establishes a control influence chain and tracks it to the influence termination event to form a control effect domain; The reconstructed module corrects the boundaries of candidate electrical events in the candidate energy efficiency event chain based on the control effect domain, or splits and merges them to form a reconstructed energy efficiency event chain and determines the releasable control objects. The adjustment module performs energy efficiency adjustment on the releasable control object, marks electrical changes that exceed the control effect domain as new boundary uncertainty areas, updates and reconstructs the energy efficiency event chain, and re-executes the active shaping action.

2. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 1, characterized in that, The methods for forming candidate electrical events include: The machine tool's machining program execution position, spindle start / stop and speed changes, motion status of each feed axis, tool changing and retraction status, and cooling, lubrication and chip removal status are obtained to form the machine tool's machining status. Synchronously acquire the current, power, start / stop time and duration of the spindle drive, each feed drive and auxiliary electrical load corresponding to the machine tool processing state, and form the electrical load change; The machine tool processing state changes and electrical load changes with time correspondence are arranged in chronological order of occurrence to form candidate processing event sequences and candidate electrical event sequences. The correlation between the machine tool processing state changes and electrical load changes within the same time interval is established to obtain candidate electrical events.

3. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 2, characterized in that, The methods for constructing candidate energy efficiency event chains include: For each candidate electrical event, the power drop, load recovery, and continuous changes in auxiliary load after the end of its corresponding processing state are continuously tracked, and the part that has not yet recovered to the corresponding steady state is identified as the cross-boundary residual state of the candidate electrical event. Based on whether there is a continuation of cross-boundary residual state between adjacent candidate electrical events, candidate electrical events are divided into a definite event region and a boundary uncertain region; Candidate electrical events are arranged in chronological order of occurrence. Initial inheritance relationships are marked between adjacent candidate electrical events, and each candidate electrical event is marked with its own definite event region or boundary uncertain region, forming a candidate energy efficiency event chain.

4. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 3, characterized in that, The methods for obtaining the event visualization results include: Based on the order of candidate electrical events on both sides of the boundary uncertainty region, the direction of propagation of the cross-boundary residual state from the previous candidate electrical event to the next candidate electrical event is taken as the event attribution direction. Select active shaping actions that are reversible, short-term, and whose adjustment range is within the allowable operating range of the current machine tool processing state from the adjustable electrical control quantities of the machine tool, and apply them to the relevant electrical loads within the boundary uncertainty region; The response trajectories before and after the active shaping action are obtained respectively. The response trajectories are aligned and subtracted according to the same time base to obtain the difference response trajectory. Based on the response start time, response direction, and duration of the differential response trajectories, response changes that start from the previous candidate electrical event, have the same response direction as the event attribution direction, and whose response duration crosses the boundary of adjacent candidate electrical events are classified as the cross-boundary residual state continuation of the previous candidate electrical event; response changes that start from the subsequent candidate electrical event and whose response duration does not cross the boundary of adjacent candidate electrical events are classified as the emergence of the subsequent candidate electrical event; and response changes where the response start times of the load corresponding to the previous candidate electrical event and the load corresponding to the subsequent candidate electrical event overlap are classified as the joint coupling of the two candidate electrical events, forming an event manifestation result that includes the response direction and initial propagation relationship.

5. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 4, characterized in that, The methods for tracking the response changes of subsequent candidate electrical events relative to the active shaping action include: Using the response direction and initial propagation relationship in the event manifestation results as the tracing path, starting from the actual occurrence time of the active shaping action, the electrical response changes of relevant electrical loads and subsequent candidate electrical events are continuously acquired along the response direction; By comparing the electrical response changes of subsequent candidate electrical events after the active shaping action with the original response trajectories of the corresponding electrical loads in the candidate energy efficiency event chain before the active shaping action, and excluding natural changes in the processing state, the new responses of subsequent candidate electrical events relative to the active shaping action are obtained. For subsequent candidate electrical events that generate new responses and can continue to propagate electrical changes along the initial propagation relationship, establish a control influence chain according to the order in which the new responses appear.

6. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 5, characterized in that, The methods for forming the control effect domain include: The candidate electrical event at the moment when the active shaping action is applied is identified as the initial controlled event; Candidate electrical events that directly receive new responses in the control influence chain are identified as directly controlled events, while candidate electrical events that receive new responses after being passed through a previous event are identified as indirectly controlled events. The subsequent candidate electrical events are continuously tracked along the control influence chain, and the first subsequent candidate electrical event that no longer exhibits attributable electrical changes induced by active shaping actions is identified as the influence termination event. Based on the control influence relationships among the initiating controlled event, directly controlled event, indirectly controlled event, and event that affects termination, a control effect domain is formed.

7. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 6, characterized in that, The methods for forming the reconfigurable energy efficiency event chain and determining the releasable control objects include: For a candidate electrical event that is confirmed by the event manifestation results to be formed by the coupling of two consecutive candidate electrical events, its event boundary is corrected to the position in the corresponding control effect domain where the termination event is located, and the candidate electrical event with the boundary correction is obtained. Candidate electrical events with multiple response directions are split into sub-events with independent inheritance relationships according to the different response directions in the event manifestation results. Adjacent sub-events with the same continuous control influence path confirmed by the control influence chain are merged again. The reconstructed energy efficiency event chain is formed by the candidate electrical events after boundary correction and the merged sub-events. Based on the reconstructed energy efficiency event chain, the effective electrical energy consumption contribution of each candidate electrical event is recalculated, and the instantaneous energy consumption change of each candidate electrical event in its control effect domain is compared with the linkage change of subsequent candidate electrical events. Candidate electrical events that can generate a local energy consumption reduction within the control effect domain and do not propagate electrical load changes to subsequent candidate electrical events are identified as releasable control objects.

8. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 7, characterized in that, The methods for marking electrical changes that exceed the control effect domain as new boundary uncertainty regions include: The control sequence of energy efficiency adjustment is determined according to the event position of the releasable control object in the reconfigurable energy efficiency event chain, and energy efficiency adjustment is implemented on the operating control quantity of the spindle drive, feed drive or auxiliary electrical load corresponding to the releasable control object. During the energy efficiency regulation process, the regulated processing state and electrical response are continuously acquired. The regulated electrical changes are compared with the control effect domain to determine whether the regulated electrical changes exceed the control effect domain and whether new subsequent candidate electrical events are generated. Electrical changes that exceed the control effect domain are marked as new boundary uncertainty regions.

9. The machine tool electrical energy efficiency dynamic optimization management system as described in claim 8, characterized in that, The methods for updating and reconstructing the energy efficiency event chain and re-executing the proactive shaping action include: For adjustment results that do not exceed the control effect domain and do not generate new subsequent candidate electrical events, the adjusted reconstructed energy efficiency event chain state is used as the inherited state for the next processing period. For adjustment results that exceed the control effect domain or generate new subsequent candidate electrical events, the reconstructed energy efficiency event chain containing the new boundary uncertainty region is used as the new candidate energy efficiency event chain. The active shaping action is re-executed, and the control effect domain and reconstructed energy efficiency event chain are re-formed.

10. A method for dynamic optimization management of machine tool electrical energy efficiency, used to implement the dynamic optimization management system for machine tool electrical energy efficiency as described in any one of claims 1-9, characterized in that, include: The machine tool processing status and corresponding electrical load changes are obtained to form candidate electrical events. The boundary uncertainty region is divided according to the cross-boundary residual state between adjacent events, and a candidate energy efficiency event chain is constructed. For the boundary uncertainty region of the candidate energy efficiency event chain, constrained active shaping actions are selected from the adjustable electrical control quantities of the machine tool, and the event attribution is distinguished according to the electrical response before and after execution to obtain the event manifestation results; Starting with the event manifestation result, the response changes of subsequent candidate electrical events relative to the active shaping action are tracked to establish a control influence chain and tracked to the influence termination event to form a control effect domain; Based on the control effect domain, the candidate energy efficiency event chain is reconstructed in reverse, the event boundaries of the candidate electrical events are corrected or they are split and merged to form a reconstructed energy efficiency event chain and determine the releasable control objects; Energy efficiency regulation is applied to releasable controllable objects, electrical changes that exceed the control effect domain are marked as new boundary uncertainty regions, and the energy efficiency event chain is updated and reconstructed to re-execute active shaping actions.

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